This basemap, included in the ArcGIS Living Atlas of the World, uses the World Street Map (Night) vector tile layer.
This work is licensed under the Esri Master License Agreement.The map is designed to be used as a basemap by marine GIS professionals and as a reference map by anyone interested in ocean data. The basemap focuses on bathymetry. It also includes inland waters and roads, overlaid on land cover and shaded relief imagery.
This work is licensed under the Esri Master License Agreement.The existence, sources, distribution, circulation, and physicochemical nature of macroscale oceanic water bodies have long been a focus of oceanographic inquiry. Building on that work, this paper describes an objectively derived and globally comprehensive set of 37 distinct volumetric region units, called ecological marine units (EMUs). They are constructed on a regularly spaced ocean point-mesh grid, from sea surface to seafloor, and attributed with data from the 2018 World Ocean Atlas.
The point attribute data are the means of the decadal averages from a 57-year climatology of six physical and chemical environment parameters (temperature, salinity, dissolved oxygen, nitrate, phosphate, and silicate). The database includes over 52 million points that depict the global ocean in x, y, and z dimensions. The point data were statistically clustered to define the 37 EMUs, which represent physically and chemically distinct water volumes based on spatial variation in the six marine environmental characteristics used. The aspatial clustering to produce the 37 EMUs did not include point location or depth as a determinant, yet strong geographic and vertical separation was observed. Twenty-two of the 37 EMUs are globally or regionally extensive, and account for 99% of the ocean volume, while the remaining 15 are smaller and shallower, and occur around coastal features. We assessed the vertical distribution of EMUs in the water column and placed them into classical depth zones representing epipelagic (0 m to 200 m), mesopelagic (200 m to 1,000 m), bathypelagic (1,000 m to 4,000 m) and abyssopelagic (>4,000 m) layers. The mapping and characterization of the EMUs represent a new spatial framework for organizing and understanding the physical, chemical, and ultimately biological properties and processes of oceanic water bodies.
The EMUs are an initial objective partitioning of the ocean using longterm historical average data, and could be extended in the future by adding new classification variables and by introducing functionality to develop time-specific EMU distribution maps. The EMUs are an open-access resource, and as both a standardized geographic framework and a baseline physicochemical characterization of the oceanic environment, they are intended to be useful for disturbance assessments, ecosystem accounting exercises, conservation priority setting, and marine protected area network design, along with other research and management applications.
", "keyword": [ "open science", "emu", "ecological marine units", "ocean", "marine", "ecosystem", "ExU" ], "issued": "2016-09-13T20:29:05.000Z", "modified": "2026-02-19T22:46:27.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_oceans", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-71.3458,180.0000,83.7386", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/esri::ecological-marine-unit-emu-explorer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livingatlas.arcgis.com/emu" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=3e20c8ae23b44ca7b99af621fdc129de", "landingPage": "https://www.amerigeo.org/datasets/esri::seafloor-bathymetry-meters", "title": "Seafloor Bathymetry (meters)", "description": " This work is licensed under the Esri Master License Agreement.
If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
Geographic Information Systems (GIS) can help in solving some of the biggest challenges when it come to disasters by:
This work is licensed under the Esri Master License Agreement. This work is licensed under the Esri Master License Agreement.
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov
Worldview uses NASA's Global Imagery Browse Services (GIBS) to rapidly retrieve its imagery for an interactive browsing experience. While Worldview uses OpenLayers as its mapping library, GIBS imagery can also be accessed from Google Earth, NASA WorldWind, and several other clients. We encourage interested developers to build their own clients or integrate NASA imagery into their existing ones using these services.
Comments/suggestions/problem reports are welcome via Earthdata Support. View frequently asked questions (FAQ) about Worldview.
Source Information Obtained Oct 18, 2018 from https://earthdata.nasa.gov/worldview
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
October 15, 2021
News from: Other news from our GEOBON network
The Climate-influenced Nutrient Flows and Threats to the Biodiversity of the Belize Barrier Reef Reserve System (BZ-SDG) project, supported by NASA’s Biological Diversity and Ecological Forecasting Program, focuses on studying the impacts of current and future riverine discharge on the health of the Belize Barrier Reef Reserve System (BBRRS). While the BBRRS is a UNESCO-designated World Heritage Site that is a cornerstone of Belize’s Blue Economy, threats from land use change and climate change could significantly impact the health and biodiversity of this significant assemblage of ecosystems. The project has recently completed a third year of joint fieldwork between US- and Belize-based researchers at Wildlife Conservation Society (WCS) in Belize City. In-situ water sample collection for sediments and key nutrients in the barrier reef lagoon is being used to calibrate and validate a remote sensing-based model of water quality. This represents just one use of satellite remote sensing, which will also form a key part of the Belize’s revised Integrated Coastal Zone Management Plan, the country’s guiding document for managing coastal development. Over the past 3 years, the team has conducted multiple in-person and virtual stakeholder workshops with partners in Belize and has published early results in Frontiers in Marine Science, Marine Pollution Bulletin, and Remote Sensing of Environment.
GEO BON is a project by the Quebec Centre for Biodiversity Science.
Address:
GEO BON Secretariate
Quebec Centre for Biodiversity Science
1205 Docteur Penfield
Montreal, Quebec,
Canada H3A 1B1
contact: info@geobon.org
web: https://www.geobon.org
Liability for contents and links:
GEO BON shall not be liable for the accuracy of the contents, for editorial and technical errors, for completeness, for omissions, for updating or for any similar aspects of its website. The use of the available information shall be at the user’s own risk. Although we carefully check their contents, we cannot assume any liability for the contents of external links to third-party websites. Such websites and their contents shall be subject to the liability of their owners. Please inform us of any errors in terms of contents or technology using the special e-mail address for this purpose: info[at]geobon.org
Data protection provisions:
GEO BON shall protect the privacy of all people using its website. Any personal data provided shall be treated as confidential and not passed on to third parties.
Use of images:
Unless otherwise stated, GEO BON has the rights to the images on the pages of the GEO BON website. The transfer of image usage rights is available upon request. The images may not be used for other purposes, e.g. commercial purposes. Please contact us by e-mail: info[at]geobon.org
EBV Logo Design by César Fernando Gutierrez Montoya, cgutierrez[at]humboldt.org.co
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News from: Other news from our GEOBON network
The Climate-influenced Nutrient Flows and Threats to the Biodiversity of the Belize Barrier Reef Reserve System (BZ-SDG) project, supported by NASA’s Biological Diversity and Ecological Forecasting Program, focuses on studying the impacts of current and future riverine discharge on the health of the Belize Barrier Reef Reserve System (BBRRS). While the BBRRS is a UNESCO-designated World Heritage Site that is a cornerstone of Belize’s Blue Economy, threats from land use change and climate change could significantly impact the health and biodiversity of this significant assemblage of ecosystems. The project has recently completed a third year of joint fieldwork between US- and Belize-based researchers at Wildlife Conservation Society (WCS) in Belize City. In-situ water sample collection for sediments and key nutrients in the barrier reef lagoon is being used to calibrate and validate a remote sensing-based model of water quality. This represents just one use of satellite remote sensing, which will also form a key part of the Belize’s revised Integrated Coastal Zone Management Plan, the country’s guiding document for managing coastal development. Over the past 3 years, the team has conducted multiple in-person and virtual stakeholder workshops with partners in Belize and has published early results in Frontiers in Marine Science, Marine Pollution Bulletin, and Remote Sensing of Environment.
GEO BON is a project by the Quebec Centre for Biodiversity Science.
Address:
GEO BON Secretariate
Quebec Centre for Biodiversity Science
1205 Docteur Penfield
Montreal, Quebec,
Canada H3A 1B1
contact: info@geobon.org
web: https://www.geobon.org
Liability for contents and links:
GEO BON shall not be liable for the accuracy of the contents, for editorial and technical errors, for completeness, for omissions, for updating or for any similar aspects of its website. The use of the available information shall be at the user’s own risk. Although we carefully check their contents, we cannot assume any liability for the contents of external links to third-party websites. Such websites and their contents shall be subject to the liability of their owners. Please inform us of any errors in terms of contents or technology using the special e-mail address for this purpose: info[at]geobon.org
Data protection provisions:
GEO BON shall protect the privacy of all people using its website. Any personal data provided shall be treated as confidential and not passed on to third parties.
Use of images:
Unless otherwise stated, GEO BON has the rights to the images on the pages of the GEO BON website. The transfer of image usage rights is available upon request. The images may not be used for other purposes, e.g. commercial purposes. Please contact us by e-mail: info[at]geobon.org
EBV Logo Design by César Fernando Gutierrez Montoya, cgutierrez[at]humboldt.org.co
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Esta imagen fue tomada el 20 de junio y el mismo día entregada al Ministerio de Agricultura y Riego y al Centro de Operaciones de Emergencia Nacional para la evaluación del desastre y toma de acciones correspondientes, en atención a lo solicitado por las autoridades del Ministerio de Agricultura y Riego.
Una vez ocurrido el deslizamiento de tierra, CONIDA realizó la programación para la adquisición de imágenes del satélite PerúSAT-1 y coordinaciones con otras agencias espaciales para la toma de imágenes necesarias de la zona afectada.
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is an online map-based user interface which allows users to discover and access Earth observation data and resources from different providers from all over the world.
The portal is implemented and operated by the European Space Agency and provides a single internet discovery and access point to the ever-growing quantities of heterogeneous collections of Earth observations from satellites, airplanes, drones and in-situ sensors at global, regional and local scales through the Global Earth Observation System of Systems (GEOSS).
The GEOSS is a social and software ecosystem connecting a large array of observing systems, data systems and processing services to strengthen monitoring of the state of the Earth. It facilitates data and information accessibility and interoperability to support the Sustainable Development Goals (SDG) agenda and the Disaster Risk Reduction.
The GEOSS Platform is the cornerstone around which the GEOSS software ecosystem is implemented. The GEOSS Platform is the “glueware” that enables the connection and coordination of the many autonomous and multi-organizational systems and services contributing to GEOSS.
The figure above provides an overview of the GEOSS Platform and its main components:
The GEOSS Portal.
The GEO Discovery and Access Broker (GEO DAB) is the primary mechanism by which all data and information is discovered and accessed. The GEO DAB implements the necessary mediation and harmonization services through Application Program Interfaces (APIs). These APIs allow data providers to share resources without having to make major changes to their technology or standards.
The GEOSS Yellow pages service implements the simplified registration process for new Data Providers.
The GEOSS Service Status Checker is the component, developed by USGS/FGDC and integrated into the GEO DAB, which aims at improving user experience by providing information on Reliability of Services. The Status Checker is an automatic mechanism to monitor, diagnose and alert data providers and users on the Health status of the web services provided by the GEOSS Platform.
In addition to the above described main components of the Platform, GEOSS offers the so-called Reuse Components to serve the specificities of the various user communities. This means that user communities, which might have their own data, portals and corresponding specific needs, can reuse some of the GEOSS Platform components customized and tailored to their specific requirements.
The Reuse Components are:
The GEOSS Portal and the GEOS DAB evolved thanks to ESA-EC collaboration and have become more user-centric. Different developments are already available from the Operational Portal which is basically focused on discovery and access to data, others are provided as proof of concept in a development portal which is moving towards handling information and services to provide users with the possibility to acquire knowledge and take well-informed decisions.
Follow this link https://prezi.com/view/Z68hB3z0c2d95hdKLSGh/ to have a number of scenarios at your fingertips.
Send an email to GEOSS Portal Team for any further clarification or feedback.
The GEOSS Portal has been updated for a more intuitive and fluid user experience.
The main updates and functionalities are listed below:
GEO at the United Nations Climate Change Conference COP26
Blog / November 6, 2021
The 2021 United Nations Climate Change Conference, also known as COP26, is the 26th Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC). It will take place in Glasgow, Scotland, from 31 October to 12 November 2021, under the presidency of the United Kingdom.
While the Blue Zone at the Scottish Event Campus (SEC) will host the official negotiations and side events restricted to country delegates and admitted observers, a Green Zone has been set up at the Glasgow Science Centre, which will be open to the public via a ticketing system.
The Group on Earth Observations (GEO) community will be present through the negotiations, side events and engagements outside the official COP26 events over the two weeks to promote the role of Earth observations in providing actionable information for climate adaptation and mitigation.
In addition to the in-person meetings, a Space & Geospatial Virtual Pavilion organised by the Knowledge Transfer Network (KTN) in collaboration with more than 30 other partners, will explore the role of innovation, inclusive growth, and collaboration in supporting the climate emergency and meeting Net Zero targets using the power of place.
A selection of the key EO-related events at COP26 can be found below. This list will be continuously updated as more information becomes available, including livestream links to follow the events remotely whenever possible.
The GEO Secretariat will be represented during the two weeks by Sara Venturini (Climate Coordinator), Diana Mastracci (GEO Indigenous Alliance) and Steven Ramage (Chief Engagement Officer). We will be working closely with UK GEO, GEO Associates and Participating Organisations, as well with as the UNFCCC Secretariat and other COP26 organisers.
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The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
https://wiki.earthdata.nasa.gov/display/GIBS/GIBS+Available+Imagery+Products#expand-AerosolOpticalDepth29Products
NASA GIS API for Developers https://wiki.earthdata.nasa.gov/display/GIBS/GIBS+API+for+Developers
The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.
The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.
https://wiki.earthdata.nasa.gov/display/GIBS/GIBS+Available+Imagery+Products#expand-AerosolOpticalDepth29Products
NASA GIS API for Developers https://wiki.earthdata.nasa.gov/display/GIBS/GIBS+API+for+Developers
Climate change is one of the biggest challenges facing the world. It is also recognized as one of the challenges where use of Earth observations (EO) can make the most difference, as EO has the capability to capture environmental and socio-economic data over a range of spatial, spectral and temporal resolutions.
The impacts of climate change are faced by all, but poor and vulnerable communities and groups are the most affected. Supporting sustainable development agendas while tackling the effects of climate change illustrates the inter-linkages between GEO’s Engagement Priorities.
GEO is well positioned to support its Members and the broader community with the requisite Earth observations to support: effective assessment and monitoring of climate and related socio-economic variables; assessment and evaluation of different policy responses and actions; and tracking of the implementation of those actions and responses.
GEO uses its unique convening power to connect Members and key partners such as the UN Framework Convention on Climate Change (UNFCCC), the Intergovernmental Panel on Climate Change (IPCC), the World Meteorological Organization (WMO), the United Nations Environment Programme (UN Environment), and the Committee on Earth Observation Satellites (CEOS) to lead national, regional and global climate action efforts.
GEO and the UN Framework Convention on Climate Change (UNFCCC)
The Earth observations community can play a crucial role in global efforts to address climate change and implement the UNFCCC and the 2015 Paris Agreement. The data and knowledge derived from Earth observations helps governments and other stakeholders at regional, national and sub-national levels to respond in many areas, including mitigation, adaptation and other specific provisions of the Paris Agreement, as well as provide input to the process including through the global stocktake.
Earth observations contribute near real-time data on greenhouse gas (GHG) concentrations and emissions for carbon accounting in relation to mitigation responses. When Earth observation data is combined with other critical socio-economic information at the local scale and over extended timescales, efforts to monitor progress on adaptation responses can all be enhanced in addition to impact, vulnerability and risk assessments and the development of measures to increase resilience.
GEO, through the first GEO Climate Workshop in June 2018, has engaged with the UNFCCC Secretariat to identify key areas where coordinated Earth observations through GEO could support climate action including: mitigation; activities relating to reducing emissions from deforestation and forest degradation (REDD+); adaptation; loss and damage; technology development and transfer; capacity building; and the global stocktake. The Paris Agreement has also highlighted the need to strengthen scientific knowledge on climate, including research, systematic observation of the climate system and early warning systems, in a manner that informs climate services and supports decision-making. These are all areas where GEO is active through the 2020-2022 Work Programme activities and can provide support.
GEO and the Intergovernmental Panel on Climate Change (IPCC)
Earth observations are important for the work of the IPCC. The IPCC provides scientific input to inform the Conference of the Parties (COP) of the UNFCCC and the Convention bodies, in particular the Subsidiary Body for Scientific and Technological Advice (SBSTA). The SBSTA has been increasingly emphasizing the value of systematic observations - a term that encompasses Earth observations in the UNFCCC context. Earth observations, and in particular satellite data, provide benchmark measurements on variables which contribute to the accuracy of climate models and projections that inform policy decisions.
The refined IPCC Guidelines for National Greenhouse Gas Inventories include information on the potential contributions of space-based Earth observations for comparison with GHG emission estimates. Parties to the UNFCCC have agreed to use the IPCC Guidelines in reporting to the Convention. GEO could further support Parties in using Earth observations for their reporting.
The findings of the latest IPCC special reports have already benefited from the enhanced use of Earth observation data and there is scope for improvement. For instance, satellite observations were used to monitor the frequency of marine heatwaves over several decades, and other variables including ice flows. Satellite data was also used to monitor vegetation greening/browning. Increased availability of open Earth observation datasets can increase the quality of monitoring and help address the gaps identified by the IPCC.
Current IPCC analyses do not include urban ecosystem dynamics in detail. Urban areas, urban expansion, and other urban processes and their relation to land-related processes are considered “extensive, dynamic, and complex”. The provision of Earth observation information in support of urban resilience is an area of potential GEO support.
IPCC analyses have identified “a lack of knowledge of adaptation limits and potential maladaptation to combined effects of climate change and desertification.” A similar issue was identified for limits to adaptation in relation to sea level rise and ice loss. Earth observations can provide an understanding of real-time physical risk exposure, notably where other sources of data are sparse, to support decision analysis and the development of adaptation solutions.
Furthermore, the recent IPCC special reports have pointed out that the expanded use of new Information and Communication Technologies (ICTs), climate services and remote-sensing is critical for near-term actions for capacity-building, as well as technology transfer and deployment to strengthen adaptation and mitigation. GEO is working to address the challenges around big data involving the community to use new ICTs for the development of new ways to monitor climate and non-climate variables. Investments in human, technical and institutional capacities on the expanded use of digital technologies are crucial and are expected to bring high returns.
Group on Earth Observations
7 bis, avenue de la Paix
Case postale 2300
CH-1211 Geneva, Switzerland
Tel. +41 22 730 8505
Fax +41 22 730 8520
secretariat@geosec.org
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The 2021 State of Climate Services Report - GEO’s contribution
Blog / October 12, 2021
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On 5 October 2021, the World Meteorological Organization (WMO) published the 2021 State of Climate Services Report with contributions from more than 20 international organizations, including the Group on Earth Observations (GEO). This 2021 edition focuses on water, an indispensable resource at the heart of the global agenda for sustainable development, disaster risk reduction and climate adaptation that affects all communities and economic sectors. Since 2019, WMO and its partners have published annual State of Climate Services reports to provide input to the UN Framework Convention on Climate Change (UNFCCC) process, thus supporting climate adaptation with science-based information.
The report finds that for the 101 WMO Member countries for which data is available:
Significant additional financial commitments are needed to meet adaptation targets, but there are several constraints that limit what countries can do. These include low capacity to develop and implement projects and difficulties in raising funds within the public financial systems of low-income countries.
The report draws lessons from 16 case studies from around the world to improve water resource management and reduce the impact of water-related disasters. In collaboration with the Group on Earth Observations Global Water Sustainability (GEOGloWS) Initiative, AmeriGEO, and ENEE-Honduras, GEO contributed the case study on "Reliable and Actionable Information for Water Management Ahead of Hurricanes Eta and Iota in Honduras."
The GEOGloWS Streamflow Forecast Service is a worldwide application of the global runoff forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) that translates runoff into river discharge forecasts for all rivers in the world. The GEOGLoWS-ECMWF Streamflow Forecast Service was used by the state-owned power company of Honduras, Empresa Nacional de Energía Eléctrica (ENEE), to establish a series of low flow releases through the massive hydroelectric dam “El Cajón” between hurricanes Eta and Iota that hit the country in November 2020, following discharge protocols that dictate that the maximum discharge of 1000 m3/sec must not be exceeded. Following the first hurricane Eta, the information from the regional flash flood guidance and short-term forecast models was insufficient to determine a long-term management strategy and estimate the volume of runoff that Iota was bringing thirteen days later. Through collaboration with AmeriGEO, ENEE became aware of the 15-day discharge forecast from the GEOGLoWS ECMWF Streamflow Forecast Service provided directly from the web. Based on that information, prior to the arrival of Iota, a total of 185.95 million m3 was discharged, providing the reservoir with sufficient storage for the runoff that Iota brought from the upper basin. The timely application of the information provided by the GEOGloWS-ECMWF Streamflow Forecast Service enabled national authorities to efficiently manage the reservoir during the storms and helped to prevent potentially huge losses and damages in the Sula Valley, one of the most populated and productive areas in Honduras. This case study demonstrates the importance of climate services and early warning systems in protecting livelihoods by helping communities prepare for and respond to climate related challenges.
The 2021 State of the Climate Services report concludes with 6 strategic recommendations, including the need to:
To support these recommendations in the face of increasing water-related threats and stresses, GEO is promoting Earth observation data and tools for improved water management, monitoring, and early warning, and facilitating collaboration between data providers, developing countries, and underrepresented communities.
", "keyword": [ "Climate", "Climate Change", "Climate Indicators", "News", "Americas", "AmeriGEO", "AmeriGEOSS", "Climate Initiatives", "GEO", "GeoPathways", "GeoPathways 2021-2022", "Inter-American", "NASA", "NOAA", "Open Science", "Science", "USGS" ], "issued": "2021-11-16T20:52:51.000Z", "modified": "2021-11-18T00:41:52.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "akremer_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::the-2021-state-of-climate-services-report-geos-contribution" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=4efa7ff176aa4f43b08e9a4afaad7538", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::geo-at-the-united-nations-climate-change-conference-cop26-", "title": "GEO at the United Nations Climate Change Conference COP26 ", "description": "Blog / November 6, 2021
The 2021 United Nations Climate Change Conference, also known as COP26, is the 26th Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC). It will take place in Glasgow, Scotland, from 31 October to 12 November 2021, under the presidency of the United Kingdom.
While the Blue Zone at the Scottish Event Campus (SEC) will host the official negotiations and side events restricted to country delegates and admitted observers, a Green Zone has been set up at the Glasgow Science Centre, which will be open to the public via a ticketing system.
The Group on Earth Observations (GEO) community will be present through the negotiations, side events and engagements outside the official COP26 events over the two weeks to promote the role of Earth observations in providing actionable information for climate adaptation and mitigation.
In addition to the in-person meetings, a Space & Geospatial Virtual Pavilion organised by the Knowledge Transfer Network (KTN) in collaboration with more than 30 other partners, will explore the role of innovation, inclusive growth, and collaboration in supporting the climate emergency and meeting Net Zero targets using the power of place.
A selection of the key EO-related events at COP26 can be found below. This list will be continuously updated as more information becomes available, including livestream links to follow the events remotely whenever possible.
The GEO Secretariat will be represented during the two weeks by Sara Venturini (Climate Coordinator), Diana Mastracci (GEO Indigenous Alliance) and Steven Ramage (Chief Engagement Officer). We will be working closely with UK GEO, GEO Associates and Participating Organisations, as well with as the UNFCCC Secretariat and other COP26 organisers.
The vision of GEO is to realize a future\nwhere decisions and actions, for the benefit of humankind, are informed by\ncoordinated, comprehensive and sustained Earth Observation information and\nservices.
\n\nWith this in mind, the GEO Global Water\nSustainability Initiative (GEOGLOWS) is working to provide relevant, actionable\ninformation about water that promotes the use of earth observations while\nstrengthening observational networks in local operational frameworks.
\n\n", "keyword": [ "hydrological forecasting", "Flood", "Stream flow forecasting", "Water", "agua", "Inundación", "Sistemas de pronóstico hidrológico global", "Sequía", "GEOGLOWS", "GEO", "GEOSS", "Hydrology", "Hidrología", "Americas", "AmeriGEO", "AmeriGEOSS", "Climate", "Climate Change", "Climate Indicators", "Climate Initiatives", "GeoPathways", "GeoPathways 2021-2022", "Inter-American", "NASA", "NOAA", "Open Science", "Science", "USGS" ], "issued": "2018-12-03T22:07:37.000Z", "modified": "2021-11-18T00:41:52.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AngelicaGutierrez_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::global-stream-flood-forecasting-kyotoplenary-final" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8c531fbd318e487b9c844b434b799073", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::landsat-collection-1-surface-reflectance", "title": "Landsat Collection 1 Surface Reflectance", "description": "Landsat 8 Operational Land Imager (OLI)Landsat 8 OLI Collection 1 Surface Reflectance are generated using the Land Surface Reflectance Code (LaSRC) (version 1.4.1), which makes use of the coastal aerosol band to perform aerosol inversion tests, uses auxiliary climate data from MODIS, and uses a unique radiative transfer model. (Vermote et al., 2016).
LaSRC hardcodes the view zenith angle to “0”, and the solar zenith and view zenith angles are used for calculations as part of the atmospheric correction.
The Landsat 8 Collection 1 Land Surface Reflectance Code (LaSRC) Product Guide contains details about the LaSRC algorithm and the Landsat 8 Surface Reflectance data products created from it.
Landsat 4-5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+)Landsat 4-5 TM and Landsat 7 ETM+ Collection 1 Surface Reflectance are generated using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) algorithm (version 3.4.0), a specialized software originally developed through a National Aeronautics and Space Administration (NASA) Making Earth System Data Records for Use in Research Environments (MEaSUREs) grant by NASA Goddard Space Flight Center (GSFC) and the University of Maryland (Masek et al., 2006).
The software applies Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric correction routines to Level-1 data products. Water vapor, ozone, atmospheric pressure, aerosol optical thickness, and digital elevation are input with Landsat data to the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) radiative transfer models to generate top of atmosphere (TOA) reflectance, surface reflectance, TOA brightness temperature, and masks for clouds, cloud shadows, adjacent clouds, land, and water.
The Landsat 4-7 Collection 1 Surface Reflectance Product Guide contains details about the LEDAPS algorithm and the Surface Reflectance data products created from it.
The USGS Global Visualization Viewer (GloVis) is an online search and order tool for selected satellite data. Through a graphic map display, the user can select any area of interest and immediately view all available browse images for the specified location. From the browse image viewer page, the user may either navigate to view adjacent scene locations or select a new area of interest. GloVis also offers additional features such as cloud cover limits, date limits, user-specified map layer displays, scene list curation, and access to metadata. The viewer provides access to Thermal Infrared (TIR) and Visible and Near Infrared (VNIR) data from the LP DAAC’s ASTER L1T data product. A selection of data collected by Landsat satellites and other remote sensing instruments are also available. A full listing of available data products can be found in the GloVis FAQ’s.
The International Production Assessment Division (IPAD) is part of the Office of Global Analysis (OGA) within the Foreign Agricultural Service (FAS), an agency within the US Department of Agriculture (USDA). FAS-IPAD uses satellite imagery and remote sensing data to assist in its agricultural estimates of global crop conditions. The division provides monthly estimates of area, yield and production for 17 distinct commodities in over 160 countries around the world, including post-disaster assessments. GADAS is a powerful visualization tool based on an ArcGIS platform that enables FAS-IPAD analysts, and other users, to rapidly assess real-time crop conditions using a wide variety of data layers from a multitude of sources.
GADAS integrates a vast array of highly detailed data streams to include daily precipitation data, vegetation index, crop masks, land cover data, irrigation and water data, elevation and infrastructure, political data, and much more. In addition, FAS-IPAD has partnered with the Pacific Disaster Center (PDC) in Hawaii to incorporate real-time data streams into GADAS for worldwide monitoring, tracking, and pre- and post-disaster agricultural assessments resulting from hurricanes, typhoons, tsunamis, floods, droughts, earthquakes and volcanic eruptions.
You may want to begin exploring GADAS for the many things it can be used for, such as:
We welcome your feedback on how GADAS has worked or is working for you, and are enthusiastic about expanding the data layers, utilization, and future development of this very powerful GIS tool. Please contact us at OGA.IPAD@fas.usda.gov to provide your valued comments…we look forward to hearing from you!
Here’s a screenshot centered over the northern Atlantic Ocean:
", "keyword": [ "Disaster", "Agriculture", "Elevation", "Volcano", "volcanic", "droughts", "typhoon", "hurricane", "eruption", "irrigation", "water", "infrastructure", "land cover", "crop", "vegetation", "AmeriGEOSS", "GEOSS", "GEO", "UNGGIM-Americas", "Americas", "AmeriGEO", "Climate", "Climate Change", "Climate Indicators", "Climate Initiatives", "GeoPathways", "GeoPathways 2021-2022", "Inter-American", "NASA", "NOAA", "Open Science", "Science", "USGS" ], "issued": "2018-10-23T12:36:36.000Z", "modified": "2021-11-18T00:41:51.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AmeriGEOSS", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::global-agriculture-and-disaster-assessment-system-gadas" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://geo.fas.usda.gov/GADAS/index.html" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=3dc822981ab1440ea1ef58ef07559c8e", "landingPage": "https://www.amerigeo.org/maps/amerigeoss::global-stream-flow-web-map", "title": "Global Stream Flow Web Map", "description": "Historically, much of the data acquired internationally was retained solely in the archive of the IC that originally acquired the data. There was no requirement to provide a copy of the data to the USGS; so much of the international data was not duplicated in the USGS archive.
In an attempt to consolidate the Landsat historical record, the Landsat Global Archive Consolidation (LGAC) initiative was established. The goal is to consolidate the Landsat archives of all stations worldwide and make all Landsat scenes available to users.
*Note: Some stations shown are still active. Stations that have solely collected data as part of the USGS Landsat Ground Network (LGN) are not shown.
", "keyword": [ "USGS", "Geopathways", "AmeriGEO", "Remote sensing", "Satellite platform", "FGDC", "Ground stations", "Landsat" ], "issued": "2021-07-09T01:53:20.000Z", "modified": "2021-07-13T21:41:44.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::landsat-historical-international-ground-stations" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat.usgs.gov/historical-international-ground-stations" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e1ab27eab7f142dd8099e93981856842", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::satélite-perúsat-1-monitorea-situación-de-cuarentena", "title": "Satélite PerúSAT-1 monitorea situación de cuarentena", "description": "{{description}}", "keyword": [ "" ], "issued": "2021-07-13T20:48:04.000Z", "modified": "2021-07-13T21:03:28.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "rich_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::satélite-perúsat-1-monitorea-situación-de-cuarentena" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/e1ab27eab7f142dd8099e93981856842" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=3edb35089b73437dba6df9505fe44d6c", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::usgs-circ1455-2019-joint-agency-commercial-imagery-evaluation-land-remote-sensing-satellite-compendium-eng", "title": "USGS CIRC1455 2019 Joint Agency Commercial Imagery Evaluation— Land Remote Sensing Satellite Compendium ENG", "description": "{{description}}", "keyword": [ "Remote Sensing", "FGDC", "USGS", "AmeriGEO", "GEO", "UN-GGIM-Americas", "CONIDA", "Landsat", "PeruSAT-1", "PeruSAT" ], "issued": "2021-07-13T20:07:22.000Z", "modified": "2021-07-13T20:13:36.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "akremer_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::usgs-circ1455-2019-joint-agency-commercial-imagery-evaluation-land-remote-sensing-satellite-compendium-eng" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=09ab8a6c52344c84a29920b44e213505", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::radarsat-antarctic-mapping-project-digital-elevation-model-version-2", "title": "Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2", "description": "The National Snow and Ice Data Center (NSIDC) supports research into our world’s frozen realms: the snow, ice, glaciers, frozen ground, and climate interactions that make up Earth’s cryosphere. NSIDC manages and distributes scientific data, creates tools for data access, supports data users, performs scientific research, and educates the public about the cryosphere.
NSIDC is a CoreTrustSeal certified Regular Member of the World Data System, an Interdisciplinary Body of the International Science Council (ISC; formerly ICSU).Data management: Our data management professionals and scientists work with data providers and users to create or publish data products, tools, and resources. We work to ensure that past, present, and future science data remain accessible for studying the Earth and its climate.
Scientific research: Scientists at NSIDC specialize in remote sensing of snow and ice, Arctic climate, frozen ground, ice sheets, glaciers, and more. Our researchers use the data products we offer, helping us better serve our research communities.
Experience: NSIDC began in 1976 as an analog archive and information center, the World Data Center for Glaciology. Since then, NSIDC has evolved to manage cryosphere-related data ranging from the smallest text file to terabytes of remote sensing data from NASA’s Earth Observing System satellite program. Read more about NSIDC history.
", "keyword": [ "USGS", "FGDC", "Geopathways", "Remote Sensing", "DEM", "NASA", "Digital Elevation Model", "Radarsat", "mapping", "Bakal" ], "issued": "2021-07-09T03:27:01.000Z", "modified": "2021-07-09T04:04:40.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::radarsat-antarctic-mapping-project-digital-elevation-model-version-2" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://nsidc.org/data/nsidc-0082" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6b3c0d0c4d1d412d968cdb2334c85fda", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::landsat-8-l8-calibration-parameter-file-cpf-data-format-control-book-dfcb", "title": "LANDSAT 8 (L8) CALIBRATION PARAMETER FILE (CPF) DATA FORMAT CONTROL BOOK (DFCB)", "description": "This document describes the contents of the Calibration Parameter File (CPF)\ngenerated by the Image Assessment System (IAS) for the Operational Land Imager\n(OLI) and the Thermal Infrared Sensor (TIRS). The IAS periodically updates the CPF.\nThis file is stamped with applicability dates and is published, allowing systems or\nindividuals who require the file to access it. The CPF is also available to International\nGround Stations (IGSs) and customers via the Landsat Mission Web Site (LMWS). The\nCPF supplies the radiometric and geometric correction parameters and other pertinent\nparameters required during Level 0 (L0) and Level 1 (L1) processing to create products\nof uniform consistency.\nThis document also describes the Response Linearization Look Up Table (RLUT). The\nvalues contained in the table are a product of the Non-Linear Response\nCharacterization used to correct the non-linear relationship between the input signal and\nthe Digital Number (DN) value at the output of the OLI and TIRS instruments.", "keyword": [ "USGS", "Geopathways", "FGDC", "Remote Sensing", "LandSat8", "Satellite platform", "Data Format", "Control Book", "Bakal" ], "issued": "2021-07-09T03:48:13.000Z", "modified": "2021-07-09T04:00:41.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::landsat-8-l8-calibration-parameter-file-cpf-data-format-control-book-dfcb" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8a60e0e7787a431a89b07e75174a24b8", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::ceos-analysis-ready-data-strategy-october-2019", "title": "CEOS Analysis Ready Data Strategy (October 2019)", "description": "CEOS Analysis Ready Data Strategy\nCEOS ensures international coordination of civil space-based Earth observation programs and\npromotes exchange of data to optimize societal benefit and inform decision making for securing\na prosperous and sustainable future for humankind.\nThe rapidly evolving domain of information technology has led to greatly enhanced\ncomputational capability and much increased expectations of a broadened user community\nfamiliar with Big Data systems and the benefits of cloud storage and computing, machine\nlearning, and artificial intelligence. Satellite data is now just one of many sources of information\navailable to results-driven users and data hungry, automated systems.\nAdditionally, Earth observation missions are no longer the sole domain of government programs\nand space agencies. Miniaturization, standardization and innovation have led to significant new\nEarth observation and data access capabilities in the commercial ‘Space 2.0’ sector. This new\npresence poses a challenge for CEOS agencies to identify and communicate the distinct role for\ngovernment funded missions and to strategically shape the EO landscape to include and\nleverage the rapidly emerging capabilities of the commercial sector.The Landsat Data Users Handbooks are prepared by the U.S. Geological Survey (USGS) Landsat Project Science Office at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, SD, and the National Aeronautics and Space Administration (NASA) Landsat Project Science
The purpose of this handbook is to provide a basic understanding and associated reference material for the Landsat 8 (L8) observatory and its science data products. In doing so, this document does not include a detailed description of all technical details of the L8 mission, but instead focuses on the information that the users need to gain an understanding of the science data products.
This handbook includes various sections that provide an overview of reference material and a more detailed description of applicable data user and product information.
Office at NASA's Goddard Space Flight Center (GSFC) in Greenbelt, Maryland.
Access Landsat 7 Data User HandbookThe Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (DEM) version 1 (NASADEM_HGT) dataset, which provides global elevation data at 1 arc second spacing.
NASADEM data products were derived from original telemetry data from the Shuttle Radar Topography Mission (SRTM), a collaboration between NASA and the National Geospatial-Intelligence Agency (NGA), as well as participation from the German and Italian space agencies. SRTM’s primary focus was to generate a near-global DEM of the Earth using radar interferometry. It was a primary component of the payload on space shuttle Endeavour during its STS-99 mission, which was launched on February 11, 2000, and flew for 11 days.
In addition to Terra Advanced Spaceborne Thermal and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 2 data, NASADEM also relied on Ice, Cloud, and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) ground control points of its lidar shots to improve surface elevation measurements that led to improved geolocation accuracy. Other reprocessing improvements include the conversion to geoid reference and the use of GDEMs and Advanced Land Observing Satellite Panchromatic Remote-sensing instrument for Stereo Mapping (PRISM) AW3D30 DEM, and interpolation for void filling.
NASADEM are distributed in 1° by 1° tiles and consist of all land between 60° N and 56° S latitude. This accounts for about 80% of Earth’s total landmass.
NASADEM_HGT data product layers include DEM, number of scenes (NUM), and an updated SRTM water body dataset (water mask). The NUM layer indicates the number of scenes that were processed for each pixel and the source of the data. A low-resolution browse image showing elevation is also available for each NASADEM_HGT granule.
The global 1 arc second NASADEM product is also available in NetCDF4 format as the NASADEM_NC dataset with the source of each elevation pixel in the corresponding NASADEM_NUMNC product.
", "keyword": [ "USGS", "FGDC", "Geopathways", "DEM", "3D", "Topography", "NASA", "Remote Sensing" ], "issued": "2021-07-09T03:21:56.000Z", "modified": "2021-07-09T03:23:01.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::nasa-shuttle-radar-topography-mission-reprocessed" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://lpdaac.usgs.gov/products/nasadem_hgtv001" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ef87dafed19d4725b18c669a4e5f1b20", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::usgs-eros-archive-digital-elevation-global-multi-resolution-terrain-elevation-data-2010", "title": "USGS EROS Archive - Digital Elevation - Global Multi-resolution Terrain Elevation Data 2010", "description": "The Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) provides a new level of detail in global topographic data. The GMTED2010 product suite contains seven new raster elevation products for each of the 30-, 15-, and 7.5-arc-second spatial resolutions and incorporates the current best available global elevation data.", "keyword": [ "USGS", "AmeriGEO", "Geopathways", "DEM", "Remote Sensing", "Terrain Elevation", "Digital Elevation", "FGDC" ], "issued": "2021-07-09T03:16:45.000Z", "modified": "2021-07-09T03:18:41.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::usgs-eros-archive-digital-elevation-global-multi-resolution-terrain-elevation-data-2010" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-global-multi-resolution-terrain-elevation?qt-science_center_objects=0#qt-science_center_objects" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=5b98f01b15e24f08a24b56a0e591f705", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::landsat-collection-1-level-1-product-definition", "title": "Landsat Collection 1 Level 1 Product Definition", "description": "Executive StatementThe LidarExplorer was originally created to enable identification of lidar projects having 3D visualization enabled (via Entwine) and having Amazon AWS cloud access. Now that all of the USGS Lidar products are available in the Cloud and 3D visualization is being enabled for all projects, these original requirements have been satisfied.
Moving forward this application will bring together the necessary information for discovering and understanding the underlying 3DEP elevation data and provide avenues for efficiently processing the data within the cloud to avoid the need to download and process data locally. Users will be able to define their area of interest, select and filter products based on needs, create processing pipelines for transforming the data into derived products or results and execute the processing using within-cloud processing capabilities.
", "keyword": [ "USGS", "Geopathways", "FGDC", "Remote sensing", "Lidar", "3D" ], "issued": "2021-07-09T03:12:08.000Z", "modified": "2021-07-09T03:13:15.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::3dep-lidarexplorer" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://prd-tnm.s3.amazonaws.com/LidarExplorer/index.html#" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=07d742b3c81444e2808bd8a683c2a2b8", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::landsat-collection-1-vs-landsat-collection-2", "title": "Landsat Collection 1 vs Landsat Collection 2", "description": "{{description}}", "keyword": [ "Landsat", "Remote Sensing", "Dieasters", "Imagery", "Landsat Collection", "Landsat Collection 2", "Landsat Collection1" ], "issued": "2021-07-09T01:11:33.000Z", "modified": "2021-07-09T02:53:00.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "mfung_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::landsat-collection-1-vs-landsat-collection-2" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=46a77937db574f899c4fde69b8573e1a", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::-landsat-burned-area-ba-algorithm-description-document-add-v1", "title": " LANDSAT BURNED AREA (BA) ALGORITHM DESCRIPTION DOCUMENT (ADD) V1", "description": "This Landsat Burned Area (BA) Algorithm Description Document (ADD) defines the\nalgorithm used for the generation of Burn Probability and Burn Classification bands,\nwhich are contained within the Landsat Level 3 BA Science Product created at the U.S.\nGeological Survey (USGS) Earth Resource Observation and Science (EROS) Center.\nThis document is under Land Satellites Data System (LSDS) Configuration Control\nBoard (CCB) control. Please submit changes to this document, as well as supportive\nmaterial justifying the proposed changes, via Change Request (CR) to the Process and\nChange Management Tool.", "keyword": [ "USGS", "AmeriGEO", "Geopathways", "LandSat", "Burned Area", "Remote Sensing", "Satellite platform", "product guide" ], "issued": "2021-07-09T02:50:42.000Z", "modified": "2021-07-09T02:52:08.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::-landsat-burned-area-ba-algorithm-description-document-add-v1" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=480645253076494ca001a35b870970ed", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::landsat-collection-2-surface-reflectance", "title": "Landsat Collection 2 Surface Reflectance", "description": "Landsat Collection 2 Surface Reflectance measures the fraction of incoming solar radiation that is reflected from Earth's surface to the Landsat sensor.
Surface reflectance improves comparison between multiple images over the same region by accounting for atmospheric effects such as aerosol scattering and thin clouds, which can help in the detection and characterization of Earth surface change. Surface reflectance is generated from Level-1 inputs that meet the <76 degrees Solar Zenith Angle constraint and include the required auxiliary data inputs to generate a scientifically viable product
Please note that Level-2 Multispectral Scanner (MSS) surface reflectance products will only become available upon the maturity of an operational atmospheric compensation algorithm which satisfies the USGS Landsat program requirements.
The map shows the locations of all active ground stations operated by our US and International Cooperator (IC) ground station network for the direct downlink and distribution of Landsat 7 and/or Landsat 8 data. The circles show the approximate area over which each station has the capability for direct reception of Landsat data.
In addition to the ground stations displayed on this page, many stations have received Landsat data in the past. The Historical International Ground Stations page displays these ground stations, and lists the approximate date ranges of the Landsat data collected.
Organizations interested in pursuing direct access to L7 and/or L8 via data downlink should visit the Benefits of Becoming an IC page for more information.
", "keyword": [ "USGS", "FGDC", "AmeriGEO", "Remote sensing", "Ground stations", "Geopathways", "Landsat" ], "issued": "2021-07-09T01:48:22.000Z", "modified": "2021-07-09T02:45:25.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::landsat-international-ground-station-igs-network" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsat.usgs.gov/igs-network" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8ac2d400820f4a16ab84c4f308d9d08a", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::landsat-8-collection-1-land-surface-reflectance-code-lasrc-product-guide-v3", "title": "Landsat 8 Collection 1 Land Surface Reflectance Code (LaSRC) Product Guide V3", "description": "This document describes relevant characteristics of the Collection 1 (C1) Landsat 8 (L8)\nLevel 2 (L2) Surface Reflectance (SR), Top of Atmosphere (TOA) Reflectance, and\nTOA Brightness Temperature (BT) products to facilitate their use in the land remote\nsensing community.The Landsat Analysis Ready Data (ARD) Tile Conversion Tool converts latitude/longitude coordinates or a single Landsat WRS-2 path/row into the corresponding Landsat ARD tiles, displays them on the map, and lists them all on the right side of the map.
U.S. Landsat ARD is available for the conterminous United States (CONUS), Alaska, and Hawaii, for Landsat Collection 1 and Landsat Collection 2. NOTE: The tiles for CONUS and Hawaii are the same for Landsat Collection 1 and Landsat Collection 2. For Alaska, additional tiles were added to the Collection 2 grid. Select Collection 2 to view the new Alaska tiles.
GloVIS
Since 2001, the USGS Global Visualization Viewer (GloVis) has been available to users for accessing remote sensing data. In 2017, it was redesigned to address changing internet technologies. With easy-to- use navigation tools, users can instantly view and download scenes.
This viewer allows you to:
Quality Assessment (QA) bands are helpful for evaluating the overall usefulness of a Landsat pixel. Each pixel in the QA band contains an integer value that represents bit packed combinations of surface, atmospheric, and sensor conditions that can affect the individual pixel quality.
QA bands are currently provided with Landsat Level-1 and Landsat Level-2 Surface Reflectance data products.
", "keyword": [ "USGS", "AmeriGEO", "FGDC", "LandSat", "Remote sensing", "Satellite platform", "Geopathways" ], "issued": "2021-07-09T02:34:23.000Z", "modified": "2021-07-09T02:35:25.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "BakalDagnachew_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/documents/amerigeoss::landsat-missions-landsat-quality-assessment-tools" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://www.usgs.gov/core-science-systems/nli/landsat/landsat-quality-assessment-tools?qt-science_support_page_related_con=0#qt-science_support_page_related_con" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=efb48718f27c43979e7aaaf22e3e278f", "landingPage": "https://www.amerigeo.org/documents/amerigeoss::landsat-acquisition-tool-convert-path-row-and-lat-long", "title": "Landsat Acquisition Tool Convert Path/Row and Lat/Long", "description": "Use the tools on this page to determine when the Landsat 7 and Landsat 8 satellites acquire data over your area of interest, and to view the paths that were acquired on any given day.The Landsat-related metadata files listed below each contain the entire dataset, and due to the size of each file, may take several minutes to download depending on your internet connection.
The Center for Spatial Information Science and Systems (CSISS) is an interdisciplinary research center chartered by the provost and affiliated with the College of Science at George Mason University, Fairfax VA, 22030, U.S.A.
CSISS currently operates Laboratory for Advanced Information Technology and Standards (LAITS)
CSISS is a member of the National Committee on Information Technology Standards Technical Committee L1 and a member of Open GIS Consortium (OGC).
CSISS Misson:
* To conduct world-class research in spatial information science and system.
* To provide state-of-art research training to post-doctoral fellows, Ph.D. and Master students in the field.
CSISS Research Focus:
* Theory and methodology of spatial information science;
* Standards and Interoperability of spatial data, information, knowledge, and systems;
* Architecture and prototype of widely distributed large spatial information systems, such as NSDI, GSDI, and GEOSS, as well as service-based spatial knowledge and decision-making systems;
* Exploration of new information technologies that have potential applications in Spatial Information Science (SIS);
* The applications of SIS in the social sectors having either national interests or major commercial values, such as renewable energy, location-based mobile services, intelligent transportation, and homeland security.
Landsat 7 and Landsat 8 Level-1 Real-Time scenes are available for download within 4-6 hours after acquisition.
For Landsat 7 Level-1 scenes, the timeframe from acquisition (Real-Time) to Tier 1 or Tier 2 takes approximately 24-26 days to allow for application of the refined bumper mode parameters to the Real-Time scene. For Landsat 8 Level-1 scenes it takes approximately 14-16 days to process to a Tier 1 or Tier 2 product while refined Thermal Infrared Sensor (TIRS) instrument line of sight model parameters are applied to the Real-Time scene. Visit the Collection 1 Tiers section on this page for more information about the Landsat Collections Tier structure: https://www.usgs.gov/land-resources/nli/landsat/landsat-collection-1.
Collection 2 Level-2 Surface Reflectance and Surface Temperature products are typically available within 24 hours after a scene has been processed into Tier 1 or Tier 2. Landsat 7 and Landsat 8 both utilize NASA's Goddard Earth Observing System Model Version 5 Forward Processing for Instrument Teams (GEOS-5 FP-IT) Atmospheric Assimilation Products for Level-2 product generation.
Upon launch and on-orbit checkout, Landsat 9 will deliver Collection 2 Level-1 Tier 1 or Tier 2 scenes within 4-6 hours of acquisition, and a Level-2 Surface Reflectance and Surface Temperature product within 3 days. Landsat 9 will also utilize the GEOS-5 FP-IT atmospheric auxiliary data product for Level-2 product generation.
Return to Landsat Science Products Overview
Left: Landsat Surface Reflectance image (Landsat 7 bands 5,4,3) and Right: Derived Burned Area product for an area within Landsat CONUS ARD tile h006v010 acquired on July 7, 2003.
Accurate and complete data on fire locations and burned areas (e.g. fire occurrence) are needed to quantify trends and patterns of fire occurrence, characterize drivers of fire occurrence, projections of future fire pattern behavior, and help with assessments of fire impacts on both natural and social systems.
The Landsat Burned Area product is designed to identify burned areas across all ecosystems (e.g. forests, shrublands, and grasslands) for Landsat 4-8 data.
The Landsat Burned Area product contains two acquisition-based raster data products that represent burn classification and burn probability. Landsat Burned Area is generated from U.S. Landsat Analysis Ready Data (ARD) Surface Reflectance and Top of Atmosphere Brightness Temperature data.
The Landsat Burned Area product is processed to 30-meter spatial resolution in Albers Equal Area (AEA) projection using the World Geodetic System 1984 (WGS84) datum and gridded to a common tiling scheme.
Product AvailabilityThe Landsat Burned Area product is available for the conterminous U.S for the following date ranges:
Landsat 4 TM: March 1984 to December 1993
The Burned Area product includes two acquisition-based raster data products that represent burn classification and burn probability. Additional product specifications can be found in the Landsat Burned Area Product Guide. The Burned Area package includes a metadata file in Extensible Markup Language (.xml) format.
The list below describes the products and filenames that are delivered with the Landsat Burned Area package.
Burn Probability (BP): Provides the maximum per-pixel BP; generated by comparing the current individual acquisition against composites created from seasonal average and the previous year of acquisition.
Delivered file name: *_BP.tif
Approximate file size: 8.3 MB
Burned Classification (BC): Indicates if an area was burned by applying a threshold to the BP product.
Delivered file name: *_BC.tif
Approximate file size: 200 KB
The product metadata file (.xml) lists the band information for both the burn classification and burn probability. The units for the pixel size is “m” and should be “meters” to be compliant with the schema.
| Landsat Burned Area User Communities | |
|---|---|
| Community | Potential Use |
| Carbon cycling research (e.g., Group on Earth Observations (GEO) Forest Carbon Tracking, USGS Carbon Sequestration) | Tracking carbon from living and dead vegetation and coal/humus states into atmospheric states |
| Wildland resource management agencies and groups (including US Forest Service, Bureau of Land Management, BLM Alaska Fire Service, National Park Service, Bureau of Indian Affairs, and Fish and Wildlife Service) | Planning and management of fire occurrence on managed lands |
| Monitoring Trends in Burn Severity (MTBS) | Locations of burned areas for additional severity analysis |
| LANDFIRE | Fire hazard evaluation, disturbance characterization, change tracking |
| Fire research (e.g., National Interagency Fire Center, Office of Wildland Fire) | 30 meter product of history and extent of fire locations |
| Agricultural, grasslands, and prairie research (including GEO Agriculture, US Forest Service, Agricultural Research Service, some Long Term Ecological Research Network (LTER) sites) | Grasslands and prairie research, cropland and prairie burning extent, history, and use |
| Committee on Earth Observations from Space (CEOS) Land Product Validation Working Group for Burned Area Validation Protocols | Validation and/or verification of alternative burned area products |
| Climate research | Tracking of greenhouse gas generation, and fire activity as an indicator or symptom of changes in climate |
| Global Observation of Forest Cover and Land Dynamics (GOFC-GOLD) | Fire management, emissions estimation and smoke trace gas monitoring, the role of fire in the carbon budget, and burned area product validation of other systems |
Landsat Burned Area products are available for download from EarthExplorer. The data are located under the Landsat category, Landsat Collection 1 Level-3 subcategory, and listed as Burned Area.
Visit the Landsat Data Access webpage for information about bulk download options.
DocumentationLandsat Burned Area Product Guide
Landsat Burned Area Algorithm Description Document (ADD)
Landsat Burned Area Digital Object Identifier (DOI): doi.org/10.5066/F77W6BDJ
Citation InformationThere are no restrictions on the use of Landsat Level-3 Science Products. It is not a requirement of data use, but the following citations may be used in publication or presentation materials to acknowledge the USGS as a data source and to credit the original research.
Landsat Level 3 Burned Area Science Product courtesy of the U.S. Geological Survey.
Hawbaker, T.J., Vanderhoof, M.K., Schmidt, G.L., Beal, Y.-J., Picotte, J.J., Takacs, J.D., Falgout, J.T., Dwyer, J.L., 2020. The Landsat Burned Area algorithm and products for the United States. Remote Sensing of the Environment 244. https://doi.org/10.1016/j.rse.2020.111801
Hawbaker, T.J., Vanderhoof, M.K., Beal, Y.-J., Takacs, J.D., Schmidt, G.L., Falgout, J.T., Williams, B., Brunner, N.M., Caldwell, M.K., Picotte, J.J., Howard, S.M., Stitt, S., Dwyer, J.L., 2017a. Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 -2015). U.S. Geological Survey Data Release. https://doi.org/10.5066/F73B5X76
Hawbaker, T.J., Vanderhoof, M.K., Beal, Y.-J., Takacs, J.D., Schmidt, G.L., Falgout, J.T., Williams, B., Fairaux, N.M., Caldwell, M.K., Picotte, J.J., Howard, S.M., Stitt, S., Dwyer, J.L., 2017b. Mapping burned areas using dense time-series of Landsat data. Remote Sensing of Environment 198, 504–522. https://doi.org/10.1016/j.rse.2017.06.027
References
Hawbaker, T.J., Vanderhoof, M.K., Schmidt, G.L., Beal, Y.-J., Picotte, J.J., Takacs, J.D., Falgout, J.T., Dwyer, J.L., 2020. The Landsat Burned Area algorithm and products for the United States. Remote Sensing of the Environment 244. https://doi.org/10.1016/j.rse.2020.111801
Hawbaker, T.J., Vanderhoof, M.K., Beal, Y.-J., Takacs, J.D., Schmidt, G.L., Falgout, J.T., Williams, B., Brunner, N.M., Caldwell, M.K., Picotte, J.J., Howard, S.M., Stitt, S., Dwyer, J.L., 2017a. Landsat Burned Area Essential Climate Variable products for the conterminous United States (1984 -2015). U.S. Geological Survey Data Release. https://doi.org/10.5066/F73B5X76
Hawbaker, T.J., Vanderhoof, M.K., Beal, Y.-J., Takacs, J.D., Schmidt, G.L., Falgout, J.T., Williams, B., Fairaux, N.M., Caldwell, M.K., Picotte, J.J., Howard, S.M., Stitt, S., Dwyer, J.L., 2017b. Mapping burned areas using dense time-series of Landsat data. Remote Sensing of Environment 198, 504–522. https://doi.org/10.1016/j.rse.2017.06.027
Vanderhoof, K.M., Brunner, N., Beal, G.Y.-J., Hawbaker, J.T., 2017. Evaluation of the U.S. Geological Survey Landsat Burned Area Essential Climate Variable across the Conterminous U.S. Using Commercial High-Resolution Imagery. Remote Sensing 9. https://doi.org/10.3390/rs9070743
Vanderhoof, M.K., Fairaux, N., Beal, Y.-J.G., Hawbaker, T.J., 2017a. Validation of the USGS Landsat Burned Area Essential Climate Variable (BAECV) across the conterminous United States. Remote Sensing of Environment 198, 393–406. https://doi.org/10.1016/j.rse.2017.06.025
Vanderhoof, M.K., Fairaux, N.M., Beal, Y.-J., Hawbaker, T.J., 2017b. Data Release for the Validation of the USGS Landsat Burned Area Essential Climate Variable (BAECV) across the conterminous U.S. U.S. Geological Survey Data Release. https://doi.org/10.5066/F7T151VX
Data Source: This map includes image services compiled from the following Global Land Survey (GLS) datasets: GLS 2005, GLS 2000, GLS 1990, and GLS 1975. GLS datasets are created by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) using Landsat images. These global minimal-cloud cover, orthorectified Landsat data products support global assessments of land-cover, land cover-change, and ecosystem dynamics such as disturbance and vegetation health.
This work is licensed under the Web Services and API Terms of Use.
View Summary | View Terms of Use
Landsat Analysis Ready Data (ARD) products are consistently processed to the highest scientific standards and level of processing required for direct use in monitoring and assessing landscape change. Landsat ARD significantly reduces the magnitude of data processing, removing the need to download and prepare large amounts of data for time-series investigative analysis.
The Landsat-7 satellite is part of NASA's ESE (Earth Science Enterprise) program, a joint venture of NASA and USGS (United States Geological Survey). The overall mission objective is to extend and improve upon the long-term record of medium-resolution multispectral imagery of the Earth's continental surfaces provided by the earlier Landsat satellites.
Following the loss of Landsat-6 during launch in 1993, Landsat-7 was placed on a fast track for launch in 1998, but was ultimately launched on 15 April 1999 (a one-year delay resulted from having to replace some faulty electronics inside the ETM+ sensor).
USGS Landsat Product Information
| Band Number | µm | Resolution |
|---|---|---|
| 1 | 0.45-0.515 | 30 m |
| 2 | 0.525-0.605 | 30 m |
| 3 | 0.63-0.69 | 30 m |
| 4 | 0.775-0.90 | 30 m |
| 5 | 1.55-1.75 | 30 m |
| 6 | 10.4-12.5 | 60 m |
| 7 | 2.08-2.35 | 30 m |
| 8 | 0.52-0.9 | 15 m |
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Absolutely no accuracy or completeness guarantee is implied or intended.
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The Oregon Department of Geology and Mineral Industries (DOGAMI) has been identifying and mapping the tsunami inundation hazard along the Oregon coast since 1994. In Oregon, DOGAMI manages the National Tsunami Hazard Mitigation Program, which has been administered by the National Oceanic and Atmospheric Administration (NOAA) since 1995. DOGAMI’s work is designed to help cities, counties, and other sites in coastal areas reduce the potential for disastrous tsunami-related consequences by understanding and mitigating this geologic hazard. Using federal funding awarded by NOAA, DOGAMI has developed a new generation of tsunami inundation maps to help residents and visitors along the entire Oregon coast prepare for the next Cascadia Subduction Zone (CSZ) earthquake and tsunami.
TIM series inundation maps incorporate all the best tsunami science that is available today, including recent publications by colleagues studying the Cascadia Subduction Zone, updated computer simulation models using high-resolution lidar topographic data, and knowledge gained from the 2004 Sumatra, 2010 Chile, and 2011 Tōhoku earthquakes and tsunamis.
", "keyword": [ "AmeriGEO", "AmeriGEOSS", "AmeriGEOSS-Disaster", "Natural Hazards", "Tsunami", "earthquake" ], "issued": "2019-02-18T16:20:17.000Z", "modified": "2019-02-18T16:23:26.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AmeriGEOSS", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::tsunami-inundation-map-tim-series" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://www.oregongeology.org/pubs/tim/p-TIM-overview.htm" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=8a4ffc7b7ab3404a8cd4e4576fae7c1d", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::surging-seas-risk-zone-map", "title": "Surging Seas: Risk Zone Map", "description": "IntroductionClimate Central’s Surging Seas: Risk Zone map shows areas vulnerable to near-term flooding from different combinations of sea level rise, storm surge, tides, and tsunamis, or to permanent submersion by long-term sea level rise. Within the U.S., it incorporates the latest, high-resolution, high-accuracy lidar elevation data supplied by NOAA (exceptions: see Sources), displays points of interest, and contains layers displaying social vulnerability, population density, and property value. Outside the U.S., it utilizes satellite-based elevation data from NASA in some locations, and Climate Central’s more accurate CoastalDEM in others (see Methods and Qualifiers). It provides the ability to search by location name or postal code.
The accompanying Risk Finder is an interactive data toolkit available for some countries that provides local projections and assessments of exposure to sea level rise and coastal flooding tabulated for many sub-national districts, down to cities and postal codes in the U.S. Exposure assessments always include land and population, and in the U.S. extend to over 100 demographic, economic, infrastructure and environmental variables using data drawn mainly from federal sources, including NOAA, USGS, FEMA, DOT, DOE, DOI, EPA, FCC and the Census.
This web tool was highlighted at the launch of The White House's Climate Data Initiative in March 2014. Climate Central's original Surging Seas was featured on NBC, CBS, and PBS U.S. national news, the cover of The New York Times, in hundreds of other stories, and in testimony for the U.S. Senate. The Atlantic Cities named it the most important map of 2012. Both the Risk Zone map and the Risk Finder are grounded in peer-reviewed science.
This map is based on analysis of digital elevation models mosaicked together for near-total coverage of the global coast. Details and sources for U.S. and international data are below. Elevations are transformed so they are expressed relative to local high tide lines (Mean Higher High Water, or MHHW). A simple elevation threshold-based “bathtub method” is then applied to determine areas below different water levels, relative to MHHW. Within the U.S., areas below the selected water level but apparently not connected to the ocean at that level are shown in a stippled green (as opposed to solid blue) on the map. Outside the U.S., due to data quality issues and data limitations, all areas below the selected level are shown as solid blue, unless separated from the ocean by a ridge at least 20 meters (66 feet) above MHHW, in which case they are shown as not affected (no blue).
Areas using lidar-based elevation data: U.S. coastal states except Alaska
Elevation data used for parts of this map within the U.S. come almost entirely from ~5-meter horizontal resolution digital elevation models curated and distributed by NOAA in its Coastal Lidar collection, derived from high-accuracy laser-rangefinding measurements. The same data are used in NOAA’s Sea Level Rise Viewer. (High-resolution elevation data for Louisiana, southeast Virginia, and limited other areas comes from the U.S. Geological Survey (USGS)).
Areas using CoastalDEM™ elevation data: Antigua and Barbuda, Barbados, Corn Island (Nicaragua), Dominica, Dominican Republic, Grenada, Guyana, Haiti, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, San Blas (Panama), Suriname, The Bahamas, Trinidad and Tobago.
CoastalDEM™ is a proprietary high-accuracy bare earth elevation dataset developed especially for low-lying coastal areas by Climate Central. Use our contact form to request more information.
Warning for areas using other elevation data (all other areas)
Areas of this map not listed above use elevation data on a roughly 90-meter horizontal resolution grid derived from NASA’s Shuttle Radar Topography Mission (SRTM). SRTM provides surface elevations, not bare earth elevations, causing it to commonly overestimate elevations, especially in areas with dense and tall buildings or vegetation. Therefore, the map under-portrays areas that could be submerged at each water level, and exposure is greater than shown (Kulp and Strauss, 2016). However, SRTM includes error in both directions, so some areas showing exposure may not be at risk.
SRTM data do not cover latitudes farther north than 60 degrees or farther south than 56 degrees, meaning that sparsely populated parts of Arctic Circle nations are not mapped here, and may show visual artifacts.
Areas of this map in Alaska use elevation data on a roughly 60-meter horizontal resolution grid supplied by the U.S. Geological Survey (USGS). This data is referenced to a vertical reference frame from 1929, based on historic sea levels, and with no established conversion to modern reference frames. The data also do not take into account subsequent land uplift and subsidence, widespread in the state. As a consequence, low confidence should be placed in Alaska map portions.
Flood control structures (U.S.)
Levees, walls, dams or other features may protect some areas, especially at lower elevations. Levees and other flood control structures are included in this map within but not outside of the U.S., due to poor and missing data. Within the U.S., data limitations, such as an incomplete inventory of levees, and a lack of levee height data, still make assessing protection difficult. For this map, levees are assumed high and strong enough for flood protection. However, it is important to note that only 8% of monitored levees in the U.S. are rated in “Acceptable” condition (ASCE). Also note that the map implicitly includes unmapped levees and their heights, if broad enough to be effectively captured directly by the elevation data.
For more information on how Surging Seas incorporates levees and elevation data in Louisiana, view our Louisiana levees and DEMs methods PDF. For more information on how Surging Seas incorporates dams in Massachusetts, view the Surging Seas column of the web tools comparison matrix for Massachusetts.
Error
Errors or omissions in elevation or levee data may lead to areas being misclassified. Furthermore, this analysis does not account for future erosion, marsh migration, or construction. As is general best practice, local detail should be verified with a site visit. Sites located in zones below a given water level may or may not be subject to flooding at that level, and sites shown as isolated may or may not be be so. Areas may be connected to water via porous bedrock geology, and also may also be connected via channels, holes, or passages for drainage that the elevation data fails to or cannot pick up. In addition, sea level rise may cause problems even in isolated low zones during rainstorms by inhibiting drainage.
Connectivity
At any water height, there will be isolated, low-lying areas whose elevation falls below the water level, but are protected from coastal flooding by either man-made flood control structures (such as levees), or the natural topography of the surrounding land. In areas using lidar-based elevation data or CoastalDEM (see above), elevation data is accurate enough that non-connected areas can be clearly identified and treated separately in analysis (these areas are colored green on the map). In the U.S., levee data are complete enough to factor levees into determining connectivity as well.
However, in other areas, elevation data is much less accurate, and noisy error often produces “speckled” artifacts in the flood maps, commonly in areas that should show complete inundation. Removing non-connected areas in these places could greatly underestimate the potential for flood exposure. For this reason, in these regions, the only areas removed from the map and excluded from analysis are separated from the ocean by a ridge of at least 20 meters (66 feet) above the local high tide line, according to the data, so coastal flooding would almost certainly be impossible (e.g., the Caspian Sea region).
Water level means feet or meters above the local high tide line (“Mean Higher High Water”) instead of standard elevation. Methods described above explain how each map is generated based on a selected water level. Water can reach different levels in different time frames through combinations of sea level rise, tide and storm surge. Tide gauges shown on the map show related projections (see just below).
The highest water levels on this map (10, 20 and 30 meters) provide reference points for possible flood risk from tsunamis, in regions prone to them.
", "keyword": [ "AmeriGEO", "AmeriGEOSS", "AmeriGEOSS-Disaster", "Natural Hazards", "flood", "Tsunami" ], "issued": "2019-02-18T16:05:47.000Z", "modified": "2019-02-18T16:08:41.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AmeriGEOSS", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::surging-seas-risk-zone-map" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://ss2.climatecentral.org/#6/10.066/-87.100?show=satellite&projections=0-K14_RCP85-SLR&level=5&unit=feet&pois=hide" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=448c603f85a64aeaa45ca7e6f69556f5", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::pacific-tsunami-warning-center", "title": "Pacific Tsunami Warning Center", "description": "PTWC ResponsibilitiesNOAA's two Tsunami Warning Centers (PTWC and WC/ATWC) have separate areas of responsibility, which are the geographical areas within which each Center has the responsibility for the dissemination of messages and the provision of interpretive information to emergency managers and other officials, news media, and the public.
As the primarly operational headquarters for the Pacific Tsunami Warning System, PTWC provides warnings for Pacific basin teletsunamis (tsunamis that can cause damage far away from their source) to almost every country around the Pacific rim and to most of the Pacific island states. This function is carried out under the auspices of the UNESCO/IOCInternational Coordination Group for the Pacific Tsunami Warning System. A few destructive teletsunamis are generated each century by great earthquakes around the Pacific rim. Such tsunamis can propagate across the entire Pacific in less than 24 hours, and cause widespread destruction along shorelines located thousands of miles from the source. With ever-increasing population and development along most coastlines, there is a corresponding increase in risk. The last destructive teletsunami occurred in 1964 following the great Alaska earthquake.
Pacific - U.S. InterestsAs a U.S. National Tsunami Warning Center, PTWC provides warnings for teletsunamis to Hawaiʻi, Guam, American Samoa, Wake Island, Johnston Island, the Commonwealth of the Northern Marianas, the Federated States of Micronesia, the Republic of the Marshall Islands, and all other U.S. interests in the Pacific located outside WC/ATWC's area of responsibility (Alaska, British Columbia, Washington, Oregon, and California). PTWC serves as a backup to WC/ATWC.
South China SeaPTWC is the interim warning center to nations bordering the South China Sea (China, Macao, Hong Kong, Taiwan, Philippines, Malaysia, Brunei, Indonesia, Singapore, Thailand, Cambodia, Vietnam).
As the Hawaiʻi Regional Tsunami Warning Center, PTWC provides a more rapid warning for local tsunamis generated in Hawaiian waters. Two significant local tsunamis have been generated in Hawaiʻi in historical times, one in 1868 and one in 1975. Both were caused by major earthquakes that displaced the sea bottom along the southeast flank of the island of Hawaiʻi. Although these tsunamis caused damage and casualties only on that island, a future local tsunami could have adverse effects further up the island chain. Local tsunamis strike nearby shores almost immediately after being generated by the earthquake. Consequently, the earliest warning for a local tsunami is the strong shaking of the ground, and persons near the shoreline that feel strong shaking should evacuate immediately without waiting for an official warning.
PTWC is the interim warning center to countries in the Coastal Hazards Warning System for the Caribbean and Adjacent Regions (CARIBE).
Caribbean Sea - U.S. InterestsFrom 2005-2007, PTWC was the interim warning center to U.S. Interests (Puerto Rico, Virgin Islands) in the Caribbean Sea. The WC/ATWC now provides this service to U.S. interets in the Caribbean.
From 2005-2013, PTWC provided an interim tsunami warning service to the Indian Ocean Tsunami Warning and Mitigation System (IOTWS). Service is now being provided by Regional Tsunami Service Providers in Australia, India, and Indonesia.
The WC/ATWC is the authoritative tsunami warning center for the western and eastern coasts of the United States mainland and Canada.
", "keyword": [ "AmeriGEO", "AmeriGEOSS", "AmeriGEOSS-Disaster", "Tsunami", "natural hazards" ], "issued": "2019-02-18T15:53:28.000Z", "modified": "2019-02-18T15:57:44.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AmeriGEOSS", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::pacific-tsunami-warning-center" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://ptwc.weather.gov/?region=0" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a88e37a33f8548319d653ef4d3b7bdcf", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::earth-alerts", "title": "Earth Alerts", "description": "AcknowledgementsThe Portal can be complex, so we've made several single-topic maps to simplify things.
| Seismic Scenarios Catalog | ||
| Interactive map provides loss estimates for a suite of earthquake scenarios on various faults. Each of the twenty scenarios has additional Hazus and Summary reports for viewing or download. | ||
 | Layers generally include:
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| Natural Hazards | ||
| Natural hazards interactive map showing information relating to faults, landslides, earthquakes, tsunamis, and volcanoes. Ideal for homeowners. | ||
 | Layers include:
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| Tsunami Evacuation Map | ||
| Tsunami evacuation information for areas along the Pacific Coast, Strait of Juan de Fuca, and northern Puget Sound communities. Data was developed from tsunami evacuation brochures developed with the cooperation of coastal communities, counties, and the Department of Emergency Management | ||
 | Layers include:
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| Geothermal Resources | ||
| Geothermal resource interactive map, with temperature, chemistry, geophysical, and fault data along with statewide geothermal favorability modeling. | ||
 | Layers include:
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| Subsurface Data | ||
| Digital inventory and interactive map of subsurface data, including geotechnical boring logs, test pit logs, and water well records, with lithology information and links to original source documentation. | ||
 | Layers include:
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| Earth Resources | ||
| Interactive map of active surface mines permitted by DNR and oil and gas exploration wells, with links to scanned geophysical logs and other well permit documents. | ||
 | Layers include:
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| Coal Mine Maps | ||
| Collection of historic coal mine locations, including links to scanned mine maps. The map collection includes both georeferenced and un-georeferenced maps. | ||
 | Layers include:
| |
Coastal storms and other meteorological phenomenon can have a significant impact on how high water levels rise and how often. The inundation analysis program is extremely beneficial in determining the frequency (or the occurrence of high waters for different elevations above a specified threshold) and duration (or the amount of time that the specified location is inundated by water) of observed high waters (tides). Statistical output from these analyses can be useful in planning marsh restoration activities. Additionally, the analyses have broader applications for the coastal engineering and mapping community, such as, ecosystem management and regional climate change. Since these statistical outputs are station specific, use for evaluating surrounding areas may be limited.
The data input for this tool is 6-minute water level data time series and the tabulated times and heights of the high tides over a user specified time period, relative to a desired tidal datum or user-specified datum. The data output of this tool provides summary statistics, which includes the number of occurrences of inundation above the threshold (events) and length of duration of inundation of each events above the threshold elevation for a specified time period. In addition to summary statistics, graphical outputs are provided using three plots. The first plot is a histogram of frequency of occurrence relative to the threshold elevation, the second plot is a histogram of the frequency of duration of inundation, and the third plot is an X-Y plot of frequency of elevation versus duration of inundation for each event. Input data time series are presently limited to the verified data from a set of operating and historical tide stations in the NOAA CO-OPS data base.
Overview
Download here the 2018-2019 update on the GEO Global Water Sustainability.
This Initiative consolidates the positive elements of the water activities in the first phase of GEO and ensures that strong coordination and commitment is in place for links between data, information, knowledge, and applications and policy. There are many contributions being made to these goals by various GEO Member countries but these contributions are unlikely to be included in planning or in synthesis or to be linked with policy at the global scale unless they are part of a larger framework for coordinating water within and beyond GEO. Thus, when mature, GEOGLOWS could provide a coordination framework for all water initiatives under the GEO programme.
This Initiative is intended to facilitate the use of Earth observation assets to contribute to mitigating water shortages, excesses and degraded quality arising from population growth, climate change and industrial development. The Initiative is relevant to GEO Strategic Objectives and follows the model of GEO projects. It will achieve its objectives by facilitating collaborations, enabling projects, and encouraging conversations that will strengthen these programmes, increasing awareness of related activities, and promoting the leverage of existing or planned activities.
The Initiative will develop knowledge based on an analysis of Essential Water Variables (EWVs) and use the knowledge to inform applications related to minimizing Basin and Regional Risk, policies related to enhancing global water sustainability and capacity building through regional programs and alliances such as AmeriGEOSS. To achieve this objective it strives to enhance observational programs, innovate on ways to make more effective use of data, adhere to GEO principles of good data management, and implement the policy of free and open data exchange.
Activities for the period
This Initiative will involve the collection, processing, and analysis of data to produce a better understanding of water processes, improved predictions, and insights into strategies for more effective water management; models and tools that will be applied in the provision of monitoring and prediction services for water management; and general evidence and support for policy development. The scope of this work will initially cover the responsibility areas of the member nations involved and will provide the global overviews needed to make the connections between data and policy. The scientific approaches are supported by the enhancement of data collection and processing, the improvement of data services, and the expansion of capabilities to use the data by all segments of society and in all parts of the world.
The GEOGLOWS framework includes activities focusing on:
User engagement
End users will be engaged in the definition of needs for data, products and services. Emerging applications such as water quality applications and extreme event monitoring should lead to new services. Once user requirements are further clarified, an evaluation of global data centers’ current holdings should be carried out to determine where new initiatives and services are required. They will assist in the conduct of gap analysis to clarify the adequacy of existing products and services and the need for new services.
AmeriGEOSS functions as a User Engagement element through the surveys it undertakes at its meetings and training sessions to address this need. Other user engagement will be achieved through continuous active participation in the Integrated Global Water Cycle Observations (IGWCO) Community of Practice (CoP) where emphasis will be placed on engagements with users around the world. In addition GEOGLOWS will organize side events at the GEO Work Planning Symposium and Plenary meetings to inform experts in other SBAs of their activities and to stimulate cross-SBA activities. GEOLGLOWS members will be encouraged to organize scientific sessions and town halls at international science meetings to expand their activities.
Future plans
In addition to suggesting a strategy for coordination, this Initiative will also provide a set of recommendations for implementation including preliminary proposals for new activities. Part of this will involve expanding the geographical scope of GEOGLOWS by bringing more GEO Members into the Initiative.
Resources
Leadership
Contributors
Members: Brazil, Canada, Colombia, Costa Rica, EC, Germany, Mexico, the Netherlands, USA.
Participating Organizations: CODATA, WMO.
Others: Barbados, El Salvador, International Association of Hydrological Sciences (IAHS).
Linkages across the Work Programme
Initiatives: AmeriGEOSS; Earth Observations in Service of the 2030 Agenda for Sustainable Development.
Leadership & Contributors (this list is being populated)
Role | Name | Member/PO | Implementing Entity | |
|---|---|---|---|---|
Lead | Rose Alabaster | n/a | rose.alabaster@gmail.com | |
Lead | Angelica Gutierrez | United States | NOAA | angelica.gutierrez@noaa.gov |
Contributor | Stephan Dietrich | Germany | BfG | dietrich@bafg.de |
Google Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities and makes it available for scientists, researchers, and developers to detect changes, map trends, and quantify differences on the Earth's surface.
SATELLITE IMAGERY+
YOUR ALGORITHMS+
REAL WORLD APPLICATIONSExplore our interactive timelapse viewer to travel back in time and see how the world has changed over the past twenty-nine years. Timelapse is one example of how Earth Engine can help gain insight into petabyte-scale datasets.
EXPLORE TIMELAPSEThe public data archive includes more than thirty years of historical imagery and scientific datasets, updated and expanded daily. It contains over twenty petabytes of geospatial data instantly available for analysis.
EXPLORE DATASETSThe Earth Engine API is available in Python and JavaScript, making it easy to harness the power of Google’s cloud for your own geospatial analysis.
EXPLORE THE APIUse our web-based code editor for fast, interactive algorithm development with instant access to petabytes of data.
LEARN ABOUT THE CODE EDITORScientists and non-profits use Earth Engine for remote sensing research, predicting disease outbreaks, natural resource management, and more.
SEE CASE STUDIES
The Smithsonian's "Eruptions, Earthquakes, & Emissions" web application (or "E3") is a time-lapse animation of volcanic eruptions and earthquakes since 1960. It also shows volcanic gas emissions (sulfur dioxide, SO2) since 1978 — the first year satellites were available to provide global monitoring of SO2. The eruption data are drawn from the Volcanoes of the World (VOTW) database maintained by the Smithsonian's Global Volcanism Program (GVP). The earthquake data are pulled from the United States Geological Survey (USGS) Earthquake Catalog. Sulfur-dioxide emissions data incorporated into the VOTW for use here originate in NASA's Multi-Satellite Volcanic Sulfur Dioxide L4 Long-Term Global Database. Please properly credit and cite any use of GVP eruption and volcano data, which are available via a download button within the app, through webservices, or through options under the Database tab above. A citation for the E3 app is given below.
Clicking the image will open this web application in a new tab.
Global Volcanism Program, 2016. Eruptions, Earthquakes & Emissions, v. 1.0 (internet application). Smithsonian Institution. Accessed 19 Oct 2018 (https://volcano.si.edu/E3/).
VEI is the "Richter Scale" of volcanic eruptions. Assigning a VEI is not an automated process, but involves assessing factors such as the volume of tephra (volcanic ash or other ejected material) erupted, the height the ash plume reaches above the summit or altitude into the atmosphere, and the type of eruption (Newhall and Self, 1982). VEIs range from 1 (small eruption) to 8 (the largest eruptions in Earth's entire history).
For information about volcanic eruptions before 1960, explore the GVP website, where we catalog eruption information going back more than 10,000 years. This E3 app only displays eruptions starting in 1960 because the catalog is much more complete after that date. For most eruptions before the 20th century we rely on the geologic record more than historical first-hand accounts — and the geologic record is inherently incomplete (due to erosion) and not fully documented.
The E3 app displays emissions of sulfur dioxide gas (SO2) from erupting volcanoes, including the mass in kilotons. Even though water vapor (steam) and carbon dioxide gas (see more about CO2 below) are much more abundant volcanic gases, SO2is the easiest to detect using satellite-based instruments, allowing us to obtain a global view. There is no universally accepted "magnitude" scale for emissions; the groupings presented here were chosen to best graphically present the relative volumes based on available data.
You are seeing a time-lapse movie of satellite measurements of SO2 associated with a particular emission event. These SO2 clouds, or plumes, are blown by winds and can circle the globe in about a week. As plumes travel, they mix with the air, becoming more dilute until eventually the concentration of SO2 falls below the detection limit of satellites. Earth's entire atmosphere derives from outgassing of the planet — in fact, the air you breathe was once volcanic gas, and some of it might have erupted very recently!
E3 shows volcanic gas emissions captured from satellite-based instruments, which were first deployed in 1978. NASA launched the Total Ozone Mapping Spectrometer (TOMS) in 1978, which provided the first space-borne observations of volcanic gas emissions. Numerous satellites capable of measuring volcanic gases are now in orbit.
The most abundant gases expelled during a volcanic eruption are water vapor (H2O in the form of steam) and carbon dioxide (CO2). Sulfur dioxide (SO2) is typically the third most abundant gas. Hydrogen gas, carbon monoxide and other carbon species, hydrogen halides, and noble gases typically comprise a very small percentage of volcanic gas emissions. So why can't we show H2O and CO2 in the E3 app? Earth's atmosphere has such high background concentrations of H2O and CO2 that satellites cannot easily detect a volcano's signal over this background "noise." Atmospheric SO2 concentrations, however, are very low. Therefore volcanic emissions of SO2 stand out and are more easily detected by satellites. Scientists are just beginning to have reliable measurements of volcanic carbon dioxide emissions because new satellites dedicated to monitoring CO2 have either recently been launched or have launches planned for the coming decade.
We don't really know. CO2, carbon dioxide, is the dominant form of carbon in most volcanic eruptions, and can be the dominant gas emitted from volcanoes. Humans release more than 100 times more CO2 to the atmosphere than volcanoes (Gerlach, 2011) through activities like burning fossil fuels. Because of this, the background levels of CO2 in the atmosphere have risen to levels that are so high (greater than 400 parts per million, or 0.04%) that satellites cannot easily detect the CO2 from volcanic eruptions. Scientists are able to estimate the amount of carbon flowing from Earth's interior to exterior (the flux) by measuring carbon emissions directly at volcanic vents and by measuring the carbon dissolved in volcanic rocks. Scientific teams in the Deep Carbon Observatory (one of the supporters of E3) are working to quantify the flux of carbon from Earth's interior to exterior.
No, not in modern times. The dominant effect of volcanic eruptions is to cool the planet in the short term. This is because sulfur emissions create aerosols that block the sun's incoming rays temporarily. While volcanoes do emit powerful greenhouse gases like carbon dioxide, they do so at a rate that is likely 100 times less than humans (Gerlach, 2011). Prior to human activity in the Holocene (approximately the last 10,000 years), volcanic gas emissions did play a large role in modulating Earth's climate.
Eruptions and earthquakes occur at Earth's plate boundaries — places where Earth's tectonic plates converge, diverge, or slip past one another. The forces operating at these plate boundaries cause both earthquakes and eruptions. For example, the Pacific "Ring of Fire" describes the plate boundaries that surround the Pacific basin. Around most of the Pacific Rim, the seafloor (Earth's oceanic crust) is "subducting" beneath the continents. This means that the seafloor is being dragged down into Earth's interior. You might think of this as Earth's way of recycling! In this process, ocean water is released to Earth's solid rocky mantle, melting the mantle rock and generating magma that erupts through volcanoes on the continents where the plates converge. In contrast, mid-ocean ridges, chains of seafloor volcanoes, define divergent plate boundaries. The Mid-Atlantic Ridge that runs from Iceland to the Antarctic in the middle of the Atlantic Ocean is one example of a divergent plate boundary. Earth's crust is torn apart at the ridge, as North and South America move away from Europe and Africa. New lava erupts to fill the gap. This lava cools, creating new ocean crust. All these episodes where solid rock collides or is torn apart generate earthquakes. And boom! You have co-located eruptions and earthquakes. To learn more about plate margins using E3, watch this video.
E3 is a successor to the program Seismic/Eruption developed by Alan Jones (Binghamton University). That program was one of the first to show the global occurrence of earthquakes (USGS data) and eruptions (GVP data) through space and time with animations and sound. The program ran in the Smithsonian's Geology, Gems, and Minerals Hall from 1997 to 2016, and was also available on the "Earthquakes and Eruptions" CD-ROM. E3 builds upon Seismic/Eruption with the addition of emissions data and automated data updates.
The application is currently showing 2,065 eruptions from 334 volcanoes. It is also showing 360 emission activity periods from 118 different volcanoes. In addition, there are 67 animations available showing the movement of SO2 clouds from 44 volcanoes.
The application checks for updates once a week. Earthquake data, being instrumentally recorded, is typically very current. Eruption data, which relies on observational reports and analysis by GVP staff, is generally updated every few months; however, known ongoing eruptions will continue through the most recent update check. Emissions data is collected by satellite instruments and also must be processed by scientists, so updates will be provided as soon as they are available following an event, on the schedule with eruption updates.
To run the map, your computer and browser must support WebGL. For more information on WebGL, please visit https://get.webgl.org to test if it should work.
Source Obtained from http://volcano.si.edu/E3/
", "keyword": [ "Hazards", "Disasters", "Volcano", "Volcanic", "AmeriGEOSS", "GEOSS", "GEO", "Earthquakes", "Emissions", "Sulfur Dioxide", "UNGGIM-Americas", "Application", "disaster", "hazard", "EuroGEOSS" ], "issued": "2018-10-19T12:13:15.000Z", "modified": "2018-11-11T13:48:59.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AmeriGEOSS", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::eruptions-earthquakes-emissions" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://volcano.si.axismaps.io" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ca8444a524bc46aab234b96d4f99a8f0", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::global-data-explorer-gdex", "title": "Global Data Explorer (GDEx)", "description": "The Global Data Explorer (GDEx) tool allows users to browse and download ASTER GDEM data based on geographic areas of interest or predefined regions, including state, province, and county (for the United States). Data output from GDEx is available in GeoTIFF or ArcASCII format. GDEx is the result of collaboration between the LP DAAC and George Mason University's Center for Spatial Information Science and Systems.", "keyword": [ "AmeriGEOSS", "GEO", "GEOSS", "LPDACC", "USGS", "NASA", "SRTM", "ASTER", "DEM", "GDEx" ], "issued": "2018-11-09T17:30:30.000Z", "modified": "2018-11-09T17:35:24.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AmeriGEOSS", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::global-data-explorer-gdex" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://gdex.cr.usgs.gov/gdex/" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=3b27c4696d614d30a65f28474690d375", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::landsatlook-viewer-1", "title": "LandsatLook Viewer", "description": "{{description}}", "keyword": [ "Landsat" ], "issued": "2018-11-09T17:02:10.000Z", "modified": "2018-11-09T17:02:12.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AAlvarez_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://www.amerigeo.org/apps/amerigeoss::landsatlook-viewer-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landsatlook.usgs.gov/" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=61a7eb3f37344191914ecdde6db8a038", "landingPage": "https://www.amerigeo.org/apps/amerigeoss::landsatlook-viewer", "title": "LandsatLook Viewer", "description": "
The LandsatLook Viewer is a prototype tool that was developed to allow rapid online viewing and access to the USGS Landsat image archives. This viewer allows you to:
We welcome feedback and input for future versions of this Viewer! Please provide your comments or suggestions .
About the ImageryThis viewer provides visual and download access to the USGS LandsatLook "Natural Color" imageproduct archive.
BackgroundThe Landsat satellites have been collecting multispectral images of Earth from space since 1972. Each image contains multiple bands of spectral information which may require significant user time, system resources, and technical expertise to obtain a visual result. As a result, the use and access to Landsat data has been historically limited to the scientific and technical user communities.
The LandsatLook “Natural Color” image product option was created to provide Landsat imagery in a simple user-friendly and viewer-ready format, based on specific bands that have been selected and arranged to simulate natural color. This type of product allows easy visualization of the archived Landsat image without any need for specialized software or technical expertise.
LandsatLook ViewerThe LandsatLook Viewer displays the LandsatLook Natural Color image product for all Landsat 1-8 images in the USGS archive and was designed primarily for visualization purposes.
The imagery within this Viewer will be of value to anyone who wants to quickly see the full Landsat record for an area, along with major image features or obvious changes to Earth’s surface through time. An area of interest may be extracted and downloaded as a simple graphic file directly through the viewer, and the original full image tile is also available if needed. Any downloaded LandsatLook image product is a georeferenced file and will be compatible within most GIS and Web mapping applications.
If the user needs to perform detailed technical analysis, the full bands of Landsat source data may also be accessed through direct links provided on the LandsatLook Viewer.
Image ServicesThe imagery that is visible on this LandsatLook Viewer is based on Web-based ArcGIS image services. The underlying REST service endpoints for the LandsatLook imagery are available at https://landsatlook.usgs.gov/arcgis/rest/services/LandsatLook/ImageServer .
Useful linksLandsat- Landsat Mission (USGS)- Landsat Science (NASA)LandsatLook- Product Description- USGS Fact Sheet- LandsatLook image services (REST)Landsat Products- Landsat 8 OLI/TIRS- Landsat 7 ETM+- Landsat 4-5 TM- Landsat 1-5 MSS- Landsat Band DesignationsLandsatLook images are full-resolution files derived from Landsat Level-1 data products. The images are compressed and stretched to create an image optimized for image selection and visual interpretation. It is recommended that these images not be used in image analysis.
LandsatLook image files are included as options when downloading Landsat scenes from EarthExplorer, GloVis, or the LandsatLook Viewer (See Figure 1).
Figure 1. LandsatLook and Level-1 product download options
The LandsatLook Natural Color image is a .jpg composite of three bands to show a “natural” looking (false color) image. Reflectance values were calculated from the calibrated scaled digital number (DN) image data. The reflectance values were scaled to a 1-255 range using a gamma stretch with a gamma=2.0. This stretch was designed to emphasize vegetation without clipping the extreme values.
Landsat 1-3 MSS = Bands 7,5,4
The LandsatLook Thermal image is a one-band gray scale .jpg image that displays thermal properties of a Landsat scene. Image brightness temperature values were calculated from the calibrated scaled digital number (DN) image data. An image specific 2 percent clip and a linear stretch to 1-255 were applied to the brightness temperature values.
Landsat 1-5 MSS = not available
LandsatLook Quality images are 8-bit files generated from the Landsat Level-1 Quality band to provide a quick view of the quality of the pixels within the scene to determine if a particular scene would work best for the user's application. This file includes values representing bit-packed combinations of surface, atmosphere, and sensor conditions that can affect the overall usefulness of a given pixel. Color mapping assignments can be seen in the tables below.
For each Landsat scene, LandsatLook Quality images can be downloaded individually in .jpg format, or as a GeoTIFF format file (_QB.TIF) within the LandsatLook Images with Geographic Reference file.
| Landsat Collection 1 LandsatLook 8-bit Quality Images Designations | ||||||
| Landsat 8 OLI/TIRS | Landsat 7 ETM+, Landsat 4-5 TM | Landsat 1-5 MSS | Color | |||
| Bit | Description | Bit | Description | Bit | Description | |
| 0 | Designated Fill | 0 | Designated Fill | 0 | Designated Fill |
|
| 1 | Terrain Occlusion | 1 | Dropped Pixel | 1 | Dropped Pixel |
|
| 2 | Radiometric Saturation | 2 | Radiometric Saturation | 2 | Radiometric Saturation |
|
| 3 | Cloud | 3 | Cloud | 3 | Cloud |
|
| 4 | Cloud Shadow | 4 | Cloud Shadow | 4 | Unused |
|
| 5 | Snow/Ice | 5 | Snow/Ice | 5 | Unused |
|
| 6 | Cirrus | 6 | Unused | 6 | Unused |
|
| 7 | Unused | 7 | Unused | 7 | Unused | Unused |
Table 1. Landsat Collection 1 LandsatLook 8-bit Quality Images Designations
LandsatLook Images with Geographic ReferenceThe LandsatLook Image with Geographic Reference is a .zip file bundle that contains the Natural Color, Thermal, and the 8-bit Quality images in georeferenced GeoTiff (.TIF) file format.
Additional Information About LandsatLook Images
Many geographic information systems and image processing software packages easily support .jpg images. To create these files, Landsat data is mapped to a 1-255 range, with the fill area set to zero (if a no-data value is set to zero, the compression algorithm may introduce zero-value artifacts into the data area causing very dark data values to be displayed as no-data).
", "keyword": [ "AmeriGEOSS", "GEO", "GEOSS", "Imagery", "USGS", "Landsat", "Sentinel-2", "Landsat WRS-1", "Landsat 8", "Landsat 7", "Landsat 4", "Landsat 5" ], "issued": "2018-11-09T16:41:56.000Z", "modified": "2018-11-09T16:59:00.000Z", "publisher": { "name": "USGS" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AmeriGEOSS", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "", "license": "Use the USGS EarthExplorer (EE) to search, download, and order satellite images, aerial photographs, and cartographic products. In addition to data from the Landsat missions and a variety of other data providers, EE provides access to MODIS land data products from the NASA Terra and Aqua missions, and ASTER level-1B data products over the U.S. and Territories from the NASA ASTER mission. Registered users of EE have access to more features than guest users.
The EarthExplorer user interface is an online search, discovery, and ordering tool developed by the United States Geological Survey (USGS). EarthExplorer supports the searching of satellite, aircraft, and other remote sensing inventories through interactive and textual-based query capabilities. Through the interface, users can identify search areas, datasets, and display metadata, browse and integrated visual services within the interface.
The distributable version of EarthExplorer provides the basic software to provide this functionality. Users are responsible for verification of system recommendations for hosting the application on your own servers. By default, this version of our code is not hooked up to a data source so you will have to integrate the interface with your data. Integration options include service-based API's, databases, and anything else that stores data. To integrate with a data source simply replace the contents of the 'getDataset' and 'search' functions in the CWIC.php file.
Distribution is being provided due to users requests for the codebase. The EarthExplorer source code is provided "As Is", without a warranty or support of any kind. The software is in the public domain; it is available to any government or private institution.
The software code base is managed through the USGS Configuration Management Board. The software is managed through an automated configuration management tool that updates the code base when new major releases have been thoroughly reviewed and tested.
The concept for the Geohazard Supersites and Natural Laboratory was conceived during the 3rd International Geohazards workshop held in November 2007 at ESA-ESRIN. In 2010 it was established as an initiative within the Group on Earth Observation (GEO), and is organised as a voluntary international partnership which aims to improve geophysical scientific research and geohazard assessment, promoting rapid and effective uptake of scientific results for enhanced societal benefits in Disaster Risk Reduction (DRR). The focus of the initiative are areas with important scientific problems and high risk levels: the Supersites and the Natural Laboratories.
WHO ARE WE?
The space agencies under the Committee for Earth Observation Satellites (CEOS) support the initiative by contributing satellite imagery at no cost over the Supersite areas, within a specific quota agreed in advance.
In situ data providers, as geophysical monitoring institutes and research infrastructure consortiums, provide open access to data and research products, and contribute in kind resources for the management of the Supersites and their data infrastructures.
The international scientific community exploits the openly shared EO data to investigate the volcanic or tectonic processes ongoing at the Supersites. They in turn are expected to share the results of their research in a reusable format.
The end-users and decision makers involved in Disaster Risk Management receive updated scientific information which can greatly benefit their Prevention or Response activities at the Supersites.
Details on the composition of our Partnership are available here.
WHY GSNL
The incomplete knowledge of seismic and volcanic phenomena and the slow uptake of scientific results by decision makers often increase the consequences of eruptions and earthquakes, especially in less developed countries. The lack of knowledge may be caused by lack of observations, but can also be due to a difficult access to existing data and reusable scientific results. Other relevant causes could be the lack of local capacities, technologies, resources.
By establishing a Supersite, the local scientific community can increase the level of international collaboration and attention on important scientific questions. The advancements generated by the focused scientific investigations will be transferred to end-users and decision makers by the Supersite Coordinator, ensuring a smooth and rapid uptake of information.
HOW GSNL WORKS
Supersite proposals are first evaluated by the GSNL Scientific Advisory Committee and independent reviewers. The CEOS Data Coordination Team (DCT) collects the various space agencies' commitments to support the Supersite image requests (with archive data and new acquisitions). The space agencies then provide open access to satellite imagery for the Supersite scientific community. The in situ data providers (which in most cases are the Supersite Coordinators) commit to provide open access to ground-based data. The Supersite data and resources are open for the international scientific community (licensing may apply), and this stimulates collaboration, knowledge transfer, capacity building, and generation of new scientific results, which are shared within the community.
The research results which are relevant to geohazard assessment are then communicated by the Supersite Coordinator to the end-users and decision makers, using the national institutional channels.
GSNL OBJECTIVES
 |  |
The Global Wildfire Information System is a joint initiative of the GEO and the Copernicus Work Programs. TheGlobal Wildfire Information System (GWIS) aims at bringing together existing information sources at regional and national level in order to provide a comprehensive view and evaluation of fire regimes and fire effects at global level.
GWIS builds on the ongoing activities of the European Forest Fire Information System (EFFIS), the Global Terrestrial Observing System (GTOS) Global Observation of Forest Cover- Global Observation of Land Dynamics (GOFC-GOLD) Fire Implementation Team (GOFC Fire IT), and the associated Regional Networks, complementing existing activities that are on-going around the world with respect to wildfire information gathering. The development of GWIS is supported by the partner organizations and space agencies. Support to GWIS was just launched by NASA through its ROSES program
Access to worldwide information on wildfires is available through the GWIS viewer at http://gwis.jrc.ec.europa.eu/static/gwis_current_situation/public/index.html
Reference: http://gwis.jrc.ec.europa.eu/
This map contains a number of world-wide dynamic image services providing\naccess to various Landsat scenes covering the landmass of the World for\nvisual interpretation. Landsat 8 collects new scenes for each location on Earth every 16 days, assuming limited cloud coverage. Newest and near cloud-free scenes are displayed by default on top. Most scenes collected since 1st January 2015 are included. The service also includes scenes from the Global Land Survey* (circa 2010, 2005, 2000, 1990, 1975).
The service contains a range of different predefined renderers for Multispectral, Panchromatic as well as Pansharpened scenes. The layers in the service can be time-enabled\nso that the applications can restrict the displayed scenes to a specific date range.
This ArcGIS Server dynamic service can be used in Web Maps and ArcGIS Desktop, Web and Mobile applications using the REST based image services API. Users can also export images, but the exported area is limited to maximum of 2,000 columns x 2,000 rows per request.
Data Source: The imagery in these services is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). The data for these services reside on the Landsat Public Datasets hosted on the Amazon Web Service cloud. Users can access full scenes from https://github.com/landsat-pds/landsat_ingestor/wiki/Accessing-Landsat-on-AWS, or alternatively access http://landsatlook.usgs.gov to review and download full scenes from the complete USGS archive.
For more information on Landsat 8 images, see http://landsat.usgs.gov/landsat8.php.
*The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit http://landsat.usgs.gov/science_GLS.php.
For more information on each of the individual layers, see
http://www.arcgis.com/home/item.html?id=d9b466d6a9e647ce8d1dd5fe12eb434b ;
http://www.arcgis.com/home/item.html?id=6b003010cbe64d5d8fd3ce00332593bf ;
http://www.arcgis.com/home/item.html?id=a7412d0c33be4de698ad981c8ba471e6
", "keyword": [ "imagery", "temporal", "multispectral", "landsat", "landsat 8", "GLS", "panchromatic", "pansharpened", "AmeriGEOSS", "GEOSS", "GEO", "UNGGIM-Americas" ], "issued": "2018-04-24T17:26:36.000Z", "modified": "2018-11-09T01:30:39.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AAlvarez_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "-60.0919,-3.9131,-58.5127,-2.6421", "license": " This work is licensed under the Esri Master License Agreement.",
"distribution": [
{
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"title": "ArcGIS Hub Dataset",
"format": "Web Page",
"mediaType": "text/html",
"accessURL": "https://www.amerigeo.org/maps/amerigeoss::landsat-layers-doug"
}
],
"theme": [
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},
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"identifier": "https://www.arcgis.com/home/item.html?id=3b2e282a79664bed8a579f27de046a02",
"landingPage": "https://www.amerigeo.org/maps/amerigeoss::landsat-layers",
"title": "Landsat Layers",
"description": "This map contains a number of world-wide dynamic image services providing\naccess to various Landsat scenes covering the landmass of the World for\nvisual interpretation. Landsat 8 collects new scenes for each location on Earth every 16 days, assuming limited cloud coverage. Newest and near cloud-free scenes are displayed by default on top. Most scenes collected since 1st January 2015 are included. The service also includes scenes from the Global Land Survey* (circa 2010, 2005, 2000, 1990, 1975).
The service contains a range of different predefined renderers for Multispectral, Panchromatic as well as Pansharpened scenes. The layers in the service can be time-enabled\nso that the applications can restrict the displayed scenes to a specific date range.
This ArcGIS Server dynamic service can be used in Web Maps and ArcGIS Desktop, Web and Mobile applications using the REST based image services API. Users can also export images, but the exported area is limited to maximum of 2,000 columns x 2,000 rows per request.
Data Source: The imagery in these services is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). The data for these services reside on the Landsat Public Datasets hosted on the Amazon Web Service cloud. Users can access full scenes from https://github.com/landsat-pds/landsat_ingestor/wiki/Accessing-Landsat-on-AWS, or alternatively access http://landsatlook.usgs.gov to review and download full scenes from the complete USGS archive.
For more information on Landsat 8 images, see http://landsat.usgs.gov/landsat8.php.
*The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit http://landsat.usgs.gov/science_GLS.php.
For more information on each of the individual layers, see
http://www.arcgis.com/home/item.html?id=d9b466d6a9e647ce8d1dd5fe12eb434b ;
http://www.arcgis.com/home/item.html?id=6b003010cbe64d5d8fd3ce00332593bf ;
http://www.arcgis.com/home/item.html?id=a7412d0c33be4de698ad981c8ba471e6
", "keyword": [ "imagery", "temporal", "multispectral", "landsat", "landsat 8", "GLS", "panchromatic", "pansharpened", "AmeriGEOSS", "GEOSS", "GEO", "UNGGIM-Americas" ], "issued": "2017-12-15T12:50:51.000Z", "modified": "2018-11-09T01:30:39.000Z", "publisher": { "name": "AmeriGEO" }, "contactPoint": { "@type": "vcard:Contact", "fn": "AAlvarez_amerigeoss", "hasEmail": "mailto:support@amerigeo.org" }, "accessLevel": "public", "spatial": "-38.0767,-34.8320,91.3862,36.4388", "license": " This work is licensed under the Esri Master License Agreement.",
"distribution": [
{
"@type": "dcat:Distribution",
"title": "ArcGIS Hub Dataset",
"format": "Web Page",
"mediaType": "text/html",
"accessURL": "https://www.amerigeo.org/maps/amerigeoss::landsat-layers"
}
],
"theme": [
"geospatial"
]
},
{
"@type": "dcat:Dataset",
"identifier": "https://www.arcgis.com/home/item.html?id=3d500aac0b604cda9d20b2bdd2304ae3",
"landingPage": "https://www.amerigeo.org/datasets/amerigeoss::landsat8-views",
"title": "Landsat8 Views",
"description": "Multispectral Landsat 8 OLI Image Service covering the landmass of the World. This service includes 8-band multispectral scenes, at 30 meter resolution. It can be used for mapping and change detection of agriculture, soils, vegetation health, water-land features and boundary studies. Using on-the-fly processing, the raw DN values are transformed to scaled (5000 - 55000) apparent reflectance values and then different service based renderings for band combinations and indices are applied. The service is updated on a daily basis to include the latest best scenes from the USGS.",
"keyword": [
"landsat 8",
"AmeriGEOSS",
"GEOSS",
"GEO",
"UNGGIM-Americas"
],
"issued": "2018-03-23T15:12:51.000Z",
"modified": "2026-09-02T05:41:07.549Z",
"publisher": {
"name": "AmeriGEOSS"
},
"contactPoint": {
"@type": "vcard:Contact",
"fn": "AAlvarez_amerigeoss",
"hasEmail": "mailto:amerigeoss@gmail.com"
},
"accessLevel": "public",
"spatial": "-180.0000,-85.2379,180.0000,84.3916",
"license": "",
"distribution": [
{
"@type": "dcat:Distribution",
"title": "ArcGIS Hub Dataset",
"format": "Web Page",
"mediaType": "text/html",
"accessURL": "https://www.amerigeo.org/datasets/amerigeoss::landsat8-views"
},
{
"@type": "dcat:Distribution",
"title": "ArcGIS GeoService",
"format": "ArcGIS GeoServices REST API",
"mediaType": "application/json",
"accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/Landsat8_Views/ImageServer"
}
],
"theme": [
"geospatial"
]
},
{
"@type": "dcat:Dataset",
"identifier": "https://www.arcgis.com/home/item.html?id=48a9360abf8d415f9be2a92ed92bf070",
"landingPage": "https://www.amerigeo.org/datasets/amerigeoss::landsat-layer-2018-02-28-urban-index",
"title": "Landsat layer - 2018/02/28 - Urban Index",
"description": "Landsat layer with Urban Index applied on it.",
"keyword": [
"Landsat",
"AmeriGEOSS",
"GEOSS",
"GEO",
"UNGGIM-Americas"
],
"issued": "2018-02-28T17:26:12.000Z",
"modified": "2026-11-09T15:29:24.904Z",
"publisher": {
"name": "AmeriGEOSS"
},
"contactPoint": {
"@type": "vcard:Contact",
"fn": "AAlvarez_amerigeoss",
"hasEmail": "mailto:amerigeoss@gmail.com"
},
"accessLevel": "public",
"spatial": "-180.0000,-65.3235,180.0000,65.3126",
"license": "",
"distribution": [
{
"@type": "dcat:Distribution",
"title": "ArcGIS Hub Dataset",
"format": "Web Page",
"mediaType": "text/html",
"accessURL": "https://www.amerigeo.org/datasets/amerigeoss::landsat-layer-2018-02-28-urban-index"
},
{
"@type": "dcat:Distribution",
"title": "ArcGIS GeoService",
"format": "ArcGIS GeoServices REST API",
"mediaType": "application/json",
"accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/Landsat/MS/ImageServer"
}
],
"theme": [
"geospatial"
]
},
{
"@type": "dcat:Dataset",
"identifier": "https://www.arcgis.com/home/item.html?id=5588b5a87a914b70bf541d408236dc41",
"landingPage": "https://www.amerigeo.org/datasets/amerigeoss::imagery-landsat-multispectral-landsat-image-service",
"title": "Imagery - Landsat/Multispectral Landsat Image Service",
"description": "Multispectral Landsat image service covering the landmass of the World. This service includes scenes from Landsat 8 and Global Land Survey (GLS) data from epochs 1990, 2000, 2005 & 2010 at 30 meter resolution as well as GLS 1975 at 60 meter resolution. GLS datasets are created by the United States Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) using Landsat images. This service can be used for mapping and change detection of urban growth, change of natural resources and comparing Landsat 8 imagery with GLS data. Using on-the-fly processing, the raw DN values are transformed to scaled (5000 - 55000) apparent reflectance values and then different service based renderings for band combinations and indices are applied. The band names are in line with Landsat 8 bands; GLS data band names are mapped along the same lines.",
"keyword": [
"Landsat",
"Imagery",
"GeoPlatform.gov",
"AmeriGEOSS",
"Change Detection",
"Urban Growth",
"Natural Resources",
"30 Meter Resolution",
"60 Meter Resolution",
"GEOSS",
"GEO",
"UNGGIM-Americas"
],
"issued": "2018-03-23T14:37:41.000Z",
"modified": "2026-11-09T20:13:50.953Z",
"publisher": {
"name": "AmeriGEOSS"
},
"contactPoint": {
"@type": "vcard:Contact",
"fn": "AAlvarez_amerigeoss",
"hasEmail": "mailto:support@amerigeo.org"
},
"accessLevel": "public",
"spatial": "-180.0000,-65.3235,180.0000,65.3126",
"license": "",
"distribution": [
{
"@type": "dcat:Distribution",
"title": "ArcGIS Hub Dataset",
"format": "Web Page",
"mediaType": "text/html",
"accessURL": "https://www.amerigeo.org/datasets/amerigeoss::imagery-landsat-multispectral-landsat-image-service"
},
{
"@type": "dcat:Distribution",
"title": "ArcGIS GeoService",
"format": "ArcGIS GeoServices REST API",
"mediaType": "application/json",
"accessURL": "https://landsat2.arcgis.com/arcgis/rest/services/Landsat/MS/ImageServer"
}
],
"theme": [
"geospatial"
]
},
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"title": "Advanced Webinar: Radar Remote Sensing for Land, Water, & Disaster Applications",
"description": "Optical satellite remote sensing depends on cloudless, well-illuminated areas to produce quality data. This is especially problematic for collecting data during nighttime or when there is cloud cover. Radar is an ideal sensor because of its ability to “see” the surface through clouds or regardless of day or night conditions. In addition, the radar signal can penetrate through the vegetation canopy and provide information about conditions underneath, such as whether there is flooding. Also, techniques such as interferometry can track surface deformation on the order of centimeters, such as displacement caused by earthquakes.
This webinar series builds on ARSET's previous webinar: Introduction to Synthetic Aperture Radar. The training will focus on different techniques such as time-series, polarimetry, and interferometry for mapping and monitoring disasters, water and land cover applications such as deforestation, crops, flooding, and earthquakes.
La teledetección satelital óptica depende de áreas sin nubes y bien iluminadas para producir datos de calidad. Esto es especialmente problemático para la recolección de datos durante la noche o cuando hay cobertura nubosa. El radar es un sensor ideal debido a su habilidad de “ver” la superficie a través de las nubes o independientemente si es de día o de noche. Además, la señal de radar puede penetrar a través del dosel de vegetación y proporcionar información sobre las condiciones en la superficie, como por ejemplo si el área esta inundada. Las técnicas como la interferometría pueden detectar deformación en la superficie en escala de centímetros, como por ejemplo el desplazamiento causado por terremotos.
Esta serie en línea tiene como base la capacitación ARSET: Introducción al Radar de Apertura Sintética. Esta capacitación se enfocará en diferentes técnicas tales como series temporales, polarimetría e interferometría para el mapeo y monitoreo de aplicaciones relacionadas a desastres y cobertura terrestre como la deforestación, los cultivos, las inundaciones y los terremotos.
SOURCE: https://arset.gsfc.nasa.gov/disasters/webinars/advanced-SAR-18
By the end of this training, attendees will be able to:
Al concluir esta capacitación, los(las) participantes podrán:
Remote sensing users from local, regional, state, federal, and international organizations interested in using SAR for terrestrial applications such as inundation mapping, land cover land use change studies, and surface deformation for volcanic and earthquake activity.
ParticipantesUsuarios de la teledetección de organizaciones locales, regionales, estatales, federales e internacionales interesados en utilizar SAR para aplicaciones terrestres como el mapeo de inundaciones, estudios de cambios en la cobertura terrestre y el uso del suelo y deformación superficial para actividad volcánica y terremotos.
This session will cover synthetic aperture radar (SAR) applications for mapping land cover and land cover change, including deforestation. We will address the challenges encountered when mapping these types of applications, and how to best address them.
Primera Sesión: 7 de agosto
Esta sesión cubrirá aplicaciones de radar de apertura sintética (SAR por sus siglas en inglés) para el mapeo de la cobertura terrestre y sus cambios, incluyendo la deforestacion. Abordaremos los retos que enfrentamos al mapear este tipo de aplicaciones y la mejor manera de superarlos.
This session will cover using SAR for mapping flooded areas and flood dynamics in natural and urban environments.
Segunda Sesión: 9 de agosto
Esta sesión cubrirá el uso de SAR para el mapeo de áreas inundadas y la dinámica de inundaciones en ambientes naturales y urbanos.
This session will cover using cover using SAR for mapping crop growth.
Tercera Sesión: 14 de agosto
Esta sesión cubrirá el uso de SAR para el mapeo de el crecimiento de cultivos.
This session will cover using interferometric SAR to map surface deformation related to earthquakes.
Sesión Cuatro: Agosto 16
Esta sesión cubrirá el uso de SAR interferométrico para mapear deformación en la superficie terrestre relacionada con terremotos.
Hurricane Katrina of August, 2005, is remembered as one of the most destructive and influential storms in United States history. The densely populated city of New Orleans, one of many areas around the Gulf Coast to face catastrophic damage, endured extreme flooding and physical destruction when several levees and other flood prevention features guarding the city broke down. Many evacuated the city and fled to far corners of the country, and a large portion of these evacuees were unable to resettle in New Orleans after the storm. Dealing with the aftermath of Hurricane Katrina involved many immense challenges, but ten years later, one can see the effects of a decade of hard work in restoring this historic city. This series of maps tracks New Orleans through these ten years of change.
The story map uses the Esri Story Map Series app,
The story was produced by Esri in collaboration with the Smithsonian Institution. The story can also be found on the Smithsonian Website. Data for each map was taken from the following sources:
Katrina Diaspora: 2006 American Community Survey 1-year Estimates, State-to-State Migration Flows, NHC, NOAA, NWS.
Flooding: Terrestrial lidar datasets of New Orleans levee failures from Hurricane Katrina, August 29, 2005: U.S. Geological Survey Data Series, NASA Earth Observatory, NOAA National Geodetic Survey.
Population Shift: The Data Center analysis of data from U.S. Census 2000 Summary File 1 (SF1) and U.S. Census 2010 Summary File 1 (SF1)
Steady Restoration: The Data Center analysis of Valassis Residential and Business Database
Neighborhood Reference Map: City of New Orleans GIS Department
| Very High Human Development: | 0.736 and higher |
| High Human Development: | 0.615 to 0.735 |
| Medium Human Development: | 0.494 to 0.614 |
| Low Human Development: | 0.493 and lower |
| Very High Human Development: | 0.736 and higher |
| High Human Development: | 0.615 to 0.735 |
| Medium Human Development: | 0.494 to 0.614 |
| Low Human Development: | 0.493 and lower |
| Very High Human Development: | 0.736 and higher |
| High Human Development: | 0.615 to 0.735 |
| Medium Human Development: | 0.494 to 0.614 |
| Low Human Development: | 0.493 and lower |
This is the 20160330 situation report on the Ebola Response.
This interactive map journal shows the evolution of the outbreak and the global response. The report contains a review of the epidemiological situation based on official information reported by ministries of health, and an assessment of the response measured against the core Roadmap indicators where available. Substantial efforts are ongoing to improve the availability and accuracy of information about both the epidemiological situation and the implementation of response measures.
The html version of the latest situation report is available on the WHO website here.
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