The Registry of Open Data on AWS is now available on AWS Data Exchange
All datasets on the Registry of Open Data are now discoverable on AWS Data Exchange alongside 3,000+ existing data products from category-leading data providers across industries. Explore the catalog to find open, free, and commercial data sets. Learn more about AWS Data Exchange

About

This registry exists to help people discover and share datasets that are available via AWS resources. See recent additions and learn more about sharing data on AWS.

See all usage examples for datasets listed in this registry tagged with cog.


Search datasets (currently 13 matching datasets)

You are currently viewing a subset of data tagged with cog.


Add to this registry

If you want to add a dataset or example of how to use a dataset to this registry, please follow the instructions on the Registry of Open Data on AWS GitHub repository.

Unless specifically stated in the applicable dataset documentation, datasets available through the Registry of Open Data on AWS are not provided and maintained by AWS. Datasets are provided and maintained by a variety of third parties under a variety of licenses. Please check dataset licenses and related documentation to determine if a dataset may be used for your application.


Tell us about your project

If you have a project using a listed dataset, please tell us about it. We may work with you to feature your project in a blog post.

USGS Landsat

agriculturecogdisaster responseearth observationgeospatialnatural resourcesatellite imagerystac

This joint NASA/USGS program provides the longest continuous space-based record of Earth’s land in existence. Every day, Landsat satellites provide essential information to help land managers and policy makers make wise decisions about our resources and our environment. Data is provided for Landsats 1, 2, 3, 4, 5, 7, 8, and 9 (excludes Landsat 6).As of June 28, 2023 (announcement), the previous single SNS topic arn:aws:sns:us-west-2:673253540267:public-c2-notify was replaced with three new SNS topics for different types of scenes.

Details →

Usage examples

See 23 usage examples →

Sentinel-2 Cloud-Optimized GeoTIFFs

agriculturecogdisaster responseearth observationgeospatialnatural resourcesatellite imagerystac

The Sentinel-2 mission is a land monitoring constellation of two satellites that provide high resolution optical imagery and provide continuity for the current SPOT and Landsat missions. The mission provides a global coverage of the Earth's land surface every 5 days, making the data of great use in ongoing studies. This dataset is the same as the Sentinel-2 dataset, except the JP2K files were converted into Cloud-Optimized GeoTIFFs (COGs). Additionally, SpatioTemporal Asset Catalog metadata has were in a JSON file alongside the data, and a STAC API called Earth-search is freely available t...

Details →

Usage examples

See 17 usage examples →

Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE)

cogearth observationgeophysicsgeospatialglobalicenetcdfsatellite imagerystaczarr

The Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project has a singular mission: to accelerate ice sheet and glacier research by producing globally comprehensive, high resolution, low latency, temporally dense, multi-sensor records of land ice and ice shelf change while minimizing barriers between the data and the user. ITS_LIVE data currently consists of NetCDF Level 2 scene-pair ice flow products posted to a standard 120 m grid derived from Landsat 4/5/7/8/9, Sentinel-2 optical scenes, and Sentinel-1 SAR scenes. We have processed all land-ice intersecting image pai...

Details →

Usage examples

See 16 usage examples →

ESA WorldCover

agriculturecogdisaster responseearth observationgeospatialland coverland usemachine learningmappingnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

The European Space Agency (ESA) WorldCover product provides global land cover maps for 2020 & 2021 at 10 m resolution based on Copernicus Sentinel-1 and Sentinel-2 data. The WorldCover product comes with 11 land cover classes and has been generated in the framework of the ESA WorldCover project, part of the 5th Earth Observation Envelope Programme (EOEP-5) of the European Space Agency. A first version of the product (v100), containing the 2020 map was released in October 2021. The 2021 map was released in October 2022 using an improved algorithm (v200). The WorldCover 2020 and 2021 maps we...

Details →

Usage examples

See 15 usage examples →

Digital Earth Africa Global Mangrove Watch

coastalcogdeafricaearth observationgeospatialland covernatural resourcesatellite imagerystacsustainability

The Global Mangrove Watch (GMW) dataset is a result of the collaboration between Aberystwyth University (U.K.), solo Earth Observation (soloEO; Japan), Wetlands International the World Conservation Monitoring Centre (UNEP-WCMC) and the Japan Aerospace Exploration Agency (JAXA). The primary objective of producing this dataset is to provide countries lacking a national mangrove monitoring system with first cut mangrove extent and change maps, to help safeguard against further mangrove forest loss and degradation. The Global Mangrove Watch dataset (version 2) consists of a global baseline map of ...

Details →

Usage examples

See 13 usage examples →

Digital Earth Africa Landsat Collection 2 Level 2

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystac

Digital Earth Africa (DE Africa) provides free and open access to a copy of Landsat Collection 2 Level-2 products over Africa. These products are produced and provided by the United States Geological Survey (USGS). The Landsat series of Earth Observation satellites, jointly led by USGS and NASA, have been continuously acquiring images of the Earth’s land surface since 1972. DE Africa provides data from Landsat 5, 7 and 8 satellites, including historical observations dating back to late 1980s and regularly updated new acquisitions. New Level-2 Landsat 7 and Landsat 8 data are available after 15...

Details →

Usage examples

See 13 usage examples →

Digital Earth Africa CHIRPS Rainfall

agricultureclimatecogdeafricaearth observationfood securitygeospatialmeteorologicalsatellite imagerystacsustainability

Digital Earth Africa (DE Africa) provides free and open access to a copy of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) monthly and daily products over Africa. The CHIRPS rainfall maps are produced and provided by the Climate Hazards Center in collaboration with the US Geological Survey, and use both rain gauge and satellite observations. The CHIRPS-2.0 Africa Monthly dataset is regularly indexed to DE Africa from the CHIRPS monthly data. The CHIRPS-2.0 Africa Daily dataset is likewise indexed from the CHIRPS daily data. Both products have been converted to clou...

Details →

Usage examples

See 11 usage examples →

Digital Earth Africa GeoMAD

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystac

GeoMAD is the Digital Earth Africa (DE Africa) surface reflectance geomedian and triple Median Absolute Deviation data service. It is a cloud-free composite of satellite data compiled over specific timeframes. The geomedian component combines measurements collected over the specified timeframe to produce one representative, multispectral measurement for every pixel unit of the African continent. The end result is a comprehensive dataset that can be used to generate true-colour images for visual inspection of anthropogenic or natural landmarks. The full spectral dataset can be used to develop m...

Details →

Usage examples

See 11 usage examples →

Digital Earth Africa Water Observations from Space

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacwater

Water Observations from Space (WOfS) is a service that draws on satellite imagery to provide historical surface water observations of the whole African continent. WOfS allows users to understand the location and movement of inland and coastal water present in the African landscape. It shows where water is usually present; where it is seldom observed; and where inundation of the surface has been observed by satellite. They are generated using the WOfS classification algorithm on Landsat satellite data. There are several WOfS products available for the African continent including scene-level dat...

Details →

Usage examples

See 11 usage examples →

RADARSAT-1

agriculturecogdisaster responseearth observationgeospatialglobalicesatellite imagerysynthetic aperture radar

Developed and operated by the Canadian Space Agency, it is Canada's first commercial Earth observation satellite.

Details →

Usage examples

See 11 usage examples →

CBERS on AWS

agriculturecogdisaster responseearth observationgeospatialimagingsatellite imagerystac

Imagery acquired by the China-Brazil Earth Resources Satellite (CBERS), 4 and 4A. The image files are recorded and processed by Instituto Nacional de Pesquisas Espaciais (INPE) and are converted to Cloud Optimized Geotiff format in order to optimize its use for cloud based applications. Contains all CBERS-4 MUX, AWFI, PAN5M and PAN10M scenes acquired since the start of the satellite mission and is daily updated with new scenes. CBERS-4A MUX Level 4 (Orthorectified) scenes are being ingested starting from 04-13-2021. CBERS-4A WFI Level 4 (Orthorectified) scenes are being ingested starting from ...

Details →

Usage examples

See 10 usage examples →

Digital Earth Africa Sentinel-1 Radiometrically Terrain Corrected

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsynthetic aperture radar

DE Africa’s Sentinel-1 backscatter product is developed to be compliant with the CEOS Analysis Ready Data for Land (CARD4L) specifications. The Sentinel-1 mission, composed of a constellation of two C-band Synthetic Aperture Radar (SAR) satellites, are operated by European Space Agency (ESA) as part of the Copernicus Programme. The mission currently collects data every 12 days over Africa at a spatial resolution of approximately 20 m. Radar backscatter measures the amount of microwave radiation reflected back to the sensor from the ground surface. This measurement is sensitive to surface rough...

Details →

Usage examples

See 10 usage examples →

Digital Earth Africa Sentinel-2 Level-2A

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystac

The Sentinel-2 mission is part of the European Union Copernicus programme for Earth observations. Sentinel-2 consists of twin satellites, Sentinel-2A (launched 23 June 2015) and Sentinel-2B (launched 7 March 2017). The two satellites have the same orbit, but 180° apart for optimal coverage and data delivery. Their combined data is used in the Digital Earth Africa Sentinel-2 product. Together, they cover all Earth’s land surfaces, large islands, inland and coastal waters every 3-5 days. Sentinel-2 data is tiered by level of pre-processing. Level-0, Level-1A and Level-1B data contain raw data fr...

Details →

Usage examples

See 10 usage examples →

Maxar Open Data Program

cogdisaster responseearth observationgeospatialsatellite imagerystac

Pre and post event high-resolution satellite imagery in support of emergency planning, risk assessment, monitoring of staging areas and emergency response, damage assessment, and recovery. These images are generated using the Maxar ARD pipeline, tiled on an organized grid in analysis-ready cloud-optimized formats.

Details →

Usage examples

See 10 usage examples →

Digital Earth Africa ALOS PALSAR, ALOS-2 PALSAR-2 and JERS-1

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsynthetic aperture radar

The ALOS/PALSAR annual mosaic is a global 25 m resolution dataset that combines data from many images captured by JAXA’s PALSAR and PALSAR-2 sensors on ALOS-1 and ALOS-2 satellites respectively. This product contains radar measurement in L-band and in HH and HV polarizations. It has a spatial resolution of 25 m and is available annually for 2007 to 2010 (ALOS/PALSAR) and 2015 to 2020 (ALOS-2/PALSAR-2). The JERS annual mosaic is generated from images acquired by the SAR sensor on the Japanese Earth Resources Satellite-1 (JERS-1) satellite. This product contains radar measurement in L-band and H...

Details →

Usage examples

See 9 usage examples →

Digital Earth Africa Cropland Extent Map (2019)

agriculturecogdeafricaearth observationfood securitygeospatialsatellite imagerystacsustainability

Digital Earth Africa's cropland extent map (2019) shows the estimated location of croplands in Africa for the period January to December 2019. Cropland is defined as: "a piece of land of minimum 0.01 ha (a single 10m x 10m pixel) that is sowed/planted and harvest-able at least once within the 12 months after the sowing/planting date." This definition will exclude non-planted grazing lands and perennial crops which can be difficult for satellite imagery to differentiate from natural vegetation. This provisional cropland extent map has a resolution of 10m, and was built using Cope...

Details →

Usage examples

See 9 usage examples →

Digital Earth Africa Fractional Cover

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainability

Fractional cover (FC) describes the landscape in terms of coverage by green vegetation, non-green vegetation (including deciduous trees during autumn, dry grass, etc.) and bare soil. It provides insight into how areas of dry vegetation and/or bare soil and green vegetation are changing over time. The product is derived from Landsat satellite data, using an algorithm developed by the Joint Remote Sensing Research Program. Digital Earth Africa's FC service has two components. Fractional Cover is estimated from each Landsat scene, providing measurements from individual days. Fractional Cover...

Details →

Usage examples

See 9 usage examples →

New Zealand Imagery

aerial imagerycogearth observationgeospatialsatellite imagerystac

The New Zealand Imagery dataset consists of New Zealand's publicly owned aerial and satellite imagery, which is freely available to use under an open licence. The dataset ranges from the latest high-resolution aerial imagery down to 5cm in some urban areas to lower resolution satellite imagery that provides full coverage of mainland New Zealand, Chathams and other offshore islands. It also includes historical imagery that has been scanned from film, orthorectified (removing distortions) and georeferenced (correctly positioned) to create a unique and crucial record of changes to the New Zea...

Details →

Usage examples

See 9 usage examples →

New Zealand Elevation

cogearth observationelevationgeospatialstac

The New Zealand Elevation dataset consists of New Zealand's publicly owned digital elevation models and digital surface models, which are freely available to use under an open licence. The dataset contains 1m resolution grids derived from LiDAR data. Point clouds are not included in the initial release.All of the elevation files are Cloud Optimised GeoTIFFs using LERC compression for the main grid and LERC compression with lower max_z_error for the overviews. These elevation files are accompanied by

Details →

Usage examples

See 8 usage examples →

Radiant MLHub

cogearth observationenvironmentalgeospatiallabeledmachine learningsatellite imagerystac

Radiant MLHub is an open library for geospatial training data that hosts datasets generated by Radiant Earth Foundation's team as well as other training data catalogs contributed by Radiant Earth’s partners. Radiant MLHub is open to anyone to access, store, register and/or share their training datasets for high-quality Earth observations. All of the training datasets are stored using a SpatioTemporal Asset Catalog (STAC) compliant catalog and exposed through a common API. Training datasets include pairs of imagery and labels for different types of machine learning problems including image ...

Details →

Usage examples

See 8 usage examples →

World Bank - Light Every Night

cogdisaster responseearth observationsatellite imagerystac

Light Every Night - World Bank Nighttime Light Data – provides open access to all nightly imagery and data from the Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS DNB) from 2012-2020 and the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) from 1992-2013. The underlying data are sourced from the NOAA National Centers for Environmental Information (NCEI) archive. Additional processing by the University of Michigan enables access in Cloud Optimized GeoTIFF format (COG) and search using the Spatial Temporal Asset Catalog (STAC) standard. The data is...

Details →

Usage examples

See 8 usage examples →

ASTER L1T Cloud-Optimized GeoTIFFs

cogearth observationgeospatialminingnatural resourcesatellite imagerysustainability

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1 Precision Terrain Corrected Registered At-Sensor Radiance (AST_L1T) data contains calibrated at-sensor radiance, which corresponds with the ASTER Level 1B (AST_L1B), that has been geometrically corrected, and rotated to a north-up UTM projection. The AST_L1T is created from a single resampling of the corresponding ASTER L1A (AST_L1A) product.The precision terrain correction process incorporates GLS2000 digital elevation data with derived ground control points (GCPs) to achieve topographic accuracy for all daytim...

Details →

Usage examples

See 7 usage examples →

ArcticDEM

cogearth observationelevationgeospatialmappingopen source softwaresatellite imagerystac

ArcticDEM - 2m GSD Digital Elevation Models (DEMs) and mosaics from 2007 to the present. The ArticDEM project seeks to fill the need for high-resolution time-series elevation data in the Arctic. The time-dependent nature of the strip DEM files allows users to perform change detection analysis and to compare observations of topography data acquired in different seasons or years. The mosaic DEM tiles are assembled from multiple strip DEMs with the intention of providing a more consistent and comprehensive product over large areas. ArcticDEM data is constructed from in-track and cross-track high-...

Details →

Usage examples

See 7 usage examples →

Earth Observation Data Cubes for Brazil

cogearth observationgeosciencegeospatialimage processingopen source softwaresatellite imagerystac

Earth observation (EO) data cubes produced from analysis-ready data (ARD) of CBERS-4, Sentinel-2 A/B and Landsat-8 satellite images for Brazil. The datacubes are regular in time and use a hierarchical tiling system. Further details are described in Ferreira et al. (2020).

Details →

Usage examples

See 7 usage examples →

Reference Elevation Model of Antarctica (REMA)

cogearth observationelevationgeospatialmappingopen source softwaresatellite imagerystac

The Reference Elevation Model of Antarctica - 2m GSD Digital Elevation Models (DEMs) and mosaics from 2009 to the present. The REMA project seeks to fill the need for high-resolution time-series elevation data in the Antarctic. The time-dependent nature of the strip DEM files allows users to perform change detection analysis and to compare observations of topography data acquired in different seasons or years. The mosaic DEM tiles are assembled from multiple strip DEMs with the intention of providing a more consistent and comprehensive product over large areas. REMA data is constructed from in...

Details →

Usage examples

See 7 usage examples →

Scottish Public Sector LiDAR Dataset

citiescoastalcogelevationenvironmentallidarurban

This dataset is Lidar data that has been collected by the Scottish public sector and made available under the Open Government Licence. The data are available as point cloud (LAS format or in LAZ compressed format), along with the derived Digital Terrain Model (DTM) and Digital Surface Model (DSM) products as Cloud optimized GeoTIFFs (COG) or standard GeoTIFF. The dataset contains multiple subsets of data which were each commissioned and flown in response to different organisational requirements. The details of each can be found at https://remotesensingdata.gov.scot/data#/list

Details →

Usage examples

See 7 usage examples →

10m Annual Land Use Land Cover (9-class)

cogearth observationenvironmentalgeospatialland coverland usemachine learningmappingplanetarysatellite imagerystacsustainability

This dataset, produced by Impact Observatory, Microsoft, and Esri, displays a global map of land use and land cover (LULC) derived from ESA Sentinel-2 imagery at 10 meter resolution for the years 2017 - 2023. Each map is a composite of LULC predictions for 9 classes throughout the year in order to generate a representative snapshot of each year. This dataset was generated by Impact Observatory, which used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. Each global map was produced by applying this model to ...

Details →

Usage examples

See 6 usage examples →

Capella Space Synthetic Aperture Radar (SAR) Open Dataset

cogcomputer visionearth observationgeospatialimage processingsatellite imagerystacsynthetic aperture radar

Open Synthetic Aperture Radar (SAR) data from Capella Space. Capella Space is an information services company that provides on-demand, industry-leading, high-resolution synthetic aperture radar (SAR) Earth observation imagery. Through a constellation of small satellites, Capella provides easy access to frequent, timely, and flexible information affecting dozens of industries worldwide. Capella's high-resolution SAR satellites are matched with unparalleled infrastructure to deliver reliable global insights that sharpen our understanding of the changing world – improving decisions ...

Details →

Usage examples

See 6 usage examples →

Amazonia EO satellite on AWS

agriculturecogdisaster responseearth observationgeospatialimagingsatellite imagerystacsustainability

Imagery acquired by Amazonia-1 satellite. The image files are recorded and processed by Instituto Nacional de Pesquisas Espaciais (INPE) and are converted to Cloud Optimized Geotiff format in order to optimize its use for cloud based applications. WFI Level 4 (Orthorectified) scenes are being ingested daily starting from 08-29-2022, the complete Level 4 archive will be ingested by the end of October 2022.

Details →

Usage examples

See 5 usage examples →

ESA WorldCover Sentinel-1 and Sentinel-2 10m Annual Composites

agriculturecogdisaster responseearth observationgeospatialland coverland usemachine learningmappingnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

The WorldCover 10m Annual Composites were produced, as part of the European Space Agency (ESA) WorldCover project, from the yearly Copernicus Sentinel-1 and Sentinel-2 archives for both years 2020 and 2021. These global mosaics consists of four products composites. A Sentinel-2 RGBNIR yearly median composite for bands B02, B03, B04, B08. A Sentinel-2 SWIR yearly median composite for bands B11 and B12. A Sentinel-2 NDVI yearly percentiles composite (NDVI 90th, NDVI 50th NDVI 10th percentiles). A Sentinel-1 GAMMA0 yearly median composite for bands VV, VH and VH/VV (power scaled). Each product is...

Details →

Usage examples

See 5 usage examples →

Global 30m Height Above Nearest Drainage (HAND)

agriculturecogdisaster responseelevationgeospatialhydrologysatellite imagerystac

Height Above Nearest Drainage (HAND) is a terrain model that normalizes topography to the relative heights along the drainage network and is used to describe the relative soil gravitational potentials or the local drainage potentials. Each pixel value represents the vertical distance to the nearest drainage. The HAND data provides near-worldwide land coverage at 30 meters and was produced from the 2021 release of the Copernicus GLO-30 Public DEM as distributed in the Registry of Open Data on AWS.

Details →

Usage examples

See 5 usage examples →

Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Data Set

agriculturecogearth observationearthquakesecosystemsenvironmentalgeologygeophysicsgeospatialglobalinfrastructuremappingnatural resourcesatellite imagerysynthetic aperture radarurban

This data set is the first-of-its-kind spatial representation of multi-seasonal, global SAR repeat-pass interferometric coherence and backscatter signatures. Global coverage comprises all land masses and ice sheets from 82 degrees northern to 79 degrees southern latitude. The data set is derived from high-resolution multi-temporal repeat-pass interferometric processing of about 205,000 Sentinel-1 Single-Look-Complex data acquired in Interferometric Wide-Swath mode (Sentinel-1 IW mode) from 1-Dec-2019 to 30-Nov-2020. The data set was developed by Earth Big Data LLC and Gamma Remote Sensing AG, under contract for NASA's Jet Propulsion Laboratory. ...

Details →

Usage examples

See 5 usage examples →

Indiana Statewide Digital Aerial Imagery Catalog

aerial imageryagriculturecogearth observationgeospatialimagingmappingnatural resourcesustainability

The State of Indiana Geographic Information Office and IOT Office of Technology manage a series of digital orthophotography dating back to 2005. Every year's worth of imagery is available as Cloud Optimized GeoTIFF (COG) files, original GeoTIFF, and other compressed deliverables such as ECW and MrSID. Additionally, each imagery year is organized into a tile grid scheme covering the entire geography of Indiana. All years of imagery are tiled from a 5,000 ft grid or sub tiles depending upon the resolution of the imagery. The naming of the tiles reflects the lower left coordinate from the...

Details →

Usage examples

See 4 usage examples →

JAXA / USGS / NASA Kaguya/SELENE Terrain Camera Observations

cogplanetarysatellite imagerystac

The Japan Aerospace EXploration Agency (JAXA) SELenological and ENgineering Explorer (SELENE) mission’s Kaguya spacecraft was launched on September 14, 2007 and science operations around the Moon started October 20, 2007. The primary mission in a circular polar orbit 100-km above the surface lasted from October 20, 2007 until October 31, 2008. An extended mission was then conducted in lower orbits (averaging 50km above the surface) from November 1, 2008 until the SELENE mission ended with Kaguya impacting the Moon on June 10, 2009. These data were collected in monoscopic observing mode. To cre...

Details →

Usage examples

See 4 usage examples →

NAIP on AWS

aerial imageryagriculturecogearth observationgeospatialnatural resourceregulatory

The National Agriculture Imagery Program (NAIP) acquires aerial imagery during the agricultural growing seasons in the continental U.S. This "leaf-on" imagery andtypically ranges from 30 centimeters to 100 centimeters in resolution and is available from the naip-analytic Amazon S3 bucket as 4-band (RGB + NIR) imagery in MRF format, on naip-source Amazon S3 bucket as 4-band (RGB + NIR) in uncompressed Raw GeoTiff format and naip-visualization as 3-band (RGB) Cloud Optimized GeoTiff format. More details on NAIP

Details →

Usage examples

See 4 usage examples →

NASA / USGS Controlled Europa DTMs

cogplanetarysatellite imagerystac

Knowledge of a planetary surface’s topography is necessary to understand its geology and enable landed mission operations. The Solid State Imager (SSI) on board NASA’s Galileo spacecraft acquired more than 700 images of Jupiter’s moon Europa. Although moderate- and high-resolution coverage is extremely limited, repeat coverage of a small number of sites enables the creation of digital terrain models (DTMs) via stereophotogrammetry. Here we provide stereo-derived DTMs of five sites on Europa. The sites are the bright band Agenor Linea, the crater Cilix, the crater Pwyll, pits and chaos adjacent...

Details →

Usage examples

See 4 usage examples →

NASA / USGS Controlled THEMIS Mosaics

cogplanetarysatellite imagerystac

These data are infrared image mosaics, tiled to the Mars quadrangle, generated using Thermal Emission Imaging System (THEMIS) images from the 2001 Mars Odyssey orbiter mission. The mosaic is generated at the full resolution of the THEMIS infrared dataset, which is approximately 100 meters/pixel. The mosaic was absolutely photogrammetrically controlled to an improved Viking MDIM network that was develop by the USGS Astrogeology processing group using the Integrated Software for Imagers and Spectrometers. Image-to-image alignment precision is subpixel (i.e., <100m). These 8-bit, qualitative d...

Details →

Usage examples

See 4 usage examples →

NASA / USGS Europa Controlled Observation Mosaics

cogplanetarysatellite imagerystac

The Solid State Imager (SSI) on NASA's Galileo spacecraft acquired more than 500 images of Jupiter's moon, Europa. These images vary from relatively low-resolution hemispherical imaging, to high-resolution targeted images that cover a small portion of the surface. Here we provide a set of 92 image mosaics generated from minimally processed, projected Galileo images with photogrammetrically improved locations on Europa's surface.

These images provide users with nearly the entire Galileo Europa imaging dataset at its native resolution and with improved relative image locations. The S
...

Details →

Usage examples

See 4 usage examples →

NASA / USGS Europa Controlled Observations

cogplanetarysatellite imagerystac

The Solid State Imager (SSI) on NASA's Galileo spacecraft acquired more than 500 images of Jupiter's moon, Europa. These images vary from relatively low-resolution hemispherical imaging, to high-resolution targeted images that cover a small portion of the surface. Here we provide a set of 481 minimally processed, projected Galileo images with photogrammetrically improved locations on Europa's surface. These individual images were subsequently used as input into a set of 92 observation mosaics.

These images provide users with nearly the entire Galileo Europa imaging dataset at its native resolution and with improved relative image locations. The Solid State Imager on NASA's Galileo spacecraft provided the only moderate- to high-resolution images of Jupiter's moon, Europa. Unfortunately, uncertainty in the position and pointing of the spacecraft, as well as the position and orientation of Europa, when the images were acquired resulted in significant errors in image locations on the surface. The result of these errors is that images acquired during different Galileo orbits, or even at different times during the same orbit, are significantly misaligned (errors of up to 100 km on the surface).

The dataset provides a set of individual images that can be used for scientific analysis
...

Details →

Usage examples

See 4 usage examples →

NASA / USGS Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) Targeted DTMs

cogelevationplanetarysatellite imagerystac

As of March, 2023 the Mars Reconnaissance Orbiter (MRO) High Resolution Science Experiment (HiRISE) sensor has collected more than 5000 targeted stereopairs. During HiRISE acquisition, the Context Camera (CTX) also collects lower resolution, higher spatial extent context images. These CTX acquisitions are also targeted stereopairs. This data set contains targeted CTX DTMs and orthoimages, created using the NASA Ames Stereopipeline. These data have been created using relatively controlled CTX images that have been globally bundle adjusted using the USGS Integrated System for Imagers and Spectro...

Details →

Usage examples

See 4 usage examples →

NASA / USGS Released HiRISE Digital Terrain Models

cogplanetarysatellite imagerystac

These data are digital terrain models (DTMs) created by multiple different institutions and released to the Planetary Data System (PDS) by the University of Arizona. The data are processed from the Planetary Data System (PDS) stored JP2 files, map projected, and converted to Cloud Optimized GeoTiffs (COGs) for efficient remote data access. These data are controlled to the Mars Orbiter Laser Altimeter (MOLA). Therefore, they are a proxy for the geodetic coordinate reference frame. These data are not guaranteed to co-register with an uncontrolled products (e.g., the uncontrolled High Resolution ...

Details →

Usage examples

See 4 usage examples →

NASA / USGS Uncontrolled HiRISE RDRs

cogplanetarysatellite imagerystac

These data are red and color Reduced Data Record (RDR) observations collected and originally processed by the High Resolution Imaging Science Experiment (HiRISE) team. The mdata are processed from the Planetary Data System (PDS) stored RDRs, map projected, and converted to Cloud Optimized GeoTiffs (COGs) for efficient remote data access. These data are not photogrammetrically controlled and use a priori NAIF SPICE pointing. Therefore, these data will not co-register with controlled data products. Data are released using simple cylindrical (planetocentric positive East, center longitude 0, -180...

Details →

Usage examples

See 4 usage examples →

Sentinel-1

agriculturecogdisaster responseearth observationgeospatialsatellite imagerysynthetic aperture radar

Sentinel-1 is a pair of European radar imaging (SAR) satellites launched in 2014 and 2016. Its 6 days revisit cycle and ability to observe through clouds makes it perfect for sea and land monitoring, emergency response due to environmental disasters, and economic applications. This dataset represents the global Sentinel-1 GRD archive, from beginning to the present, converted to cloud-optimized GeoTIFF format.

Details →

Usage examples

See 4 usage examples →

Sentinel-2 L2A 120m Mosaic

agriculturecogearth observationgeospatialmachine learningnatural resourcesatellite imagery

Sentinel-2 L2A 120m mosaic is a derived product, which contains best pixel values for 10-daily periods, modelled by removing the cloudy pixels and then performing interpolation among remaining values. As there are some parts of the world, which have lengthy cloudy periods, clouds might be remaining in some parts. The actual modelling script is available here.

Details →

Usage examples

See 4 usage examples →

Sentinel-3

cogearth observationenvironmentalgeospatiallandoceanssatellite imagerystac

This data set consists of observations from the Sentinel-3 satellite of the European Commission’s Copernicus Earth Observation Programme. Sentinel-3 is a polar orbiting satellite that completes 14 orbits of the Earth a day. It carries the Ocean and Land Colour Instrument (OLCI) for medium resolution marine and terrestrial optical measurements, the Sea and Land Surface Temperature Radiometer (SLSTR), the SAR Radar Altimeter (SRAL), the MicroWave Radiometer (MWR) and the Precise Orbit Determination (POD) instruments. The satellite was launched in 2016 and entered routine operational phase in 201...

Details →

Usage examples

See 4 usage examples →

Sentinel-5P Level 2

air qualityatmospherecogearth observationenvironmentalgeospatialsatellite imagerystac

This data set consists of observations from the Sentinel-5 Precursor (Sentinel-5P) satellite of the European Commission’s Copernicus Earth Observation Programme. Sentinel-5P is a polar orbiting satellite that completes 14 orbits of the Earth a day. It carries the TROPOspheric Monitoring Instrument (TROPOMI) which is a spectrometer that senses ultraviolet (UV), visible (VIS), near (NIR) and short wave infrared (SWIR) to monitor ozone, methane, formaldehyde, aerosol, carbon monoxide, nitrogen dioxide and sulphur dioxide in the atmosphere. The satellite was launched in October 2017 and entered ro...

Details →

Usage examples

See 4 usage examples →

ASF SAR Data Products for Disaster Events

cogdisaster responsegeospatialsatellite imagerystac

synthetic Aperture Radar (SAR) data is a powerful tool for monitoring and assessing disaster events and can provide valuable insights for researchers, scientists, and emergency response teams. The Alaska Satellite Facility (ASF) curates this collection of (primarily) SAR and SAR-derived satellite data products from a variety of data sources for disaster events.

Details →

Usage examples

See 3 usage examples →

NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6)

air temperatureclimateclimate modelclimate projectionsCMIP6cogearth observationenvironmentalglobalmodelNASA Center for Climate Simulation (NCCS)near-surface relative humiditynear-surface specific humiditynetcdfprecipitation

The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four "Tier 1" greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The CMIP6 GCM runs were developed in support of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). This dataset includes downscaled projections from ScenarioMIP model runs for which daily scenarios were produced and distributed...

Details →

Usage examples

See 3 usage examples →

Copernicus Digital Elevation Model (DEM)

agriculturecogdisaster responseearth observationelevationgeospatialsatellite imagery

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. We provide two instances of Copernicus DEM named GLO-30 Public and GLO-90. GLO-90 provides worldwide coverage at 90 meters. GLO-30 Public provides limited worldwide coverage at 30 meters because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. Note that in both cases ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized Ge...

Details →

Usage examples

See 2 usage examples →

High Resolution Canopy Height Maps by WRI and Meta

aerial imageryagricultureclimatecogearth observationgeospatialimage processingland covermachine learningsatellite imagery

Canopy Height maps for a selection of regions. Created using machine learning models on high-resolution worldwide Maxar satellite imagery.

Details →

Usage examples

See 2 usage examples →

NOAA Emergency Response Imagery

aerial imageryclimatecogdisaster responseweather

In order to support NOAA's homeland security and emergency response requirements, the National Geodetic Survey Remote Sensing Division (NGS/RSD) has the capability to acquire and rapidly disseminate a variety of spatially-referenced datasets to federal, state, and local government agencies, as well as the general public. Remote sensing technologies used for these projects have included lidar, high-resolution digital cameras, a film-based RC-30 aerial camera system, and hyperspectral imagers. Examples of rapid response initiatives include acquiring high resolution images with the Emerge/App...

Details →

Usage examples

See 2 usage examples →

PALSAR-2 ScanSAR Turkey & Syria Earthquake (L2.1 & L1.1)

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

JAXA has responded to the Earthquake events in Turkey and Syria by conducting emergency disaster observations and providing data as requested by the Disaster and Emergency Management Authority (AFAD), Ministry of Interior in Turkey, through Sentinel Asia and the International Disaster Charter. Additional information on the event and dataset can be found here. The 25 m PALSAR-2 ScanSAR is normalized backscatter data of PALSAR-2 broad area observation mode with observation width of 350 km. Polarization data are stored as 16-bit digital numbers (DN). The DN values can be converted to gamma naught...

Details →

Usage examples

See 2 usage examples →

Analysis Ready Sentinel-1 Backscatter Imagery

agriculturecogdisaster responseearth observationenvironmentalgeospatialsatellite imagerystacsynthetic aperture radar

The Sentinel-1 mission is a constellation of C-band Synthetic Aperature Radar (SAR) satellites from the European Space Agency launched since 2014. These satellites collect observations of radar backscatter intensity day or night, regardless of the weather conditions, making them enormously valuable for environmental monitoring. These radar data have been processed from original Ground Range Detected (GRD) scenes into a Radiometrically Terrain Corrected, tiled product suitable for analysis. This product is available over the Contiguous United States (CONUS) since 2017 when Sentinel-1 data becam...

Details →

Usage examples

See 1 usage example →

New Jersey Statewide Digital Aerial Imagery Catalog

aerial imagerycogearth observationgeospatialimagingmapping

The New Jersey Office of GIS, NJ Office of Information Technology manages a series of 11 digital orthophotography and scanned aerial photo maps collected at various years ranging from 1930 to 2017. Each year’s worth of imagery are available as Cloud Optimized GeoTIFF (COG) files and some years are available as compressed MrSID and/or JP2 files. Additionally, each year of imagery is organized into a tile grid scheme covering the entire geography of New Jersey. Many years share the same tiling grid while others have unique grids as defined by the project at the time.

Details →

Usage examples

See 1 usage example →

PALSAR-2 ScanSAR CARD4L (L2.2)

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

The 25 m PALSAR-2 ScanSAR is normalized backscatter data of PALSAR-2 broad area observation mode with observation width of 350 km. The SAR imagery was ortho-rectificatied and slope corrected using the ALOS World 3D - 30 m (AW3D30) Digital Surface Model. Polarization data are stored as 16-bit digital numbers (DN). The DN values can be converted to gamma naught values in decibel unit (dB) using the following equation: γ0 = 10*log10(DN2) - 83.0 dB CARD4L stands for CEOS Analysis Ready Data for Land (Level 2.2) data are ortho-rectified and radiometrically terrain-corrected. This datase...

Details →

Usage examples

See 1 usage example →

PALSAR-2 ScanSAR Flooding in Rwanda (L2.1)

agriculturecogdeafricadisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

Torrential rainfall triggered flooding and landslides in many parts of Rwanda. The hardest-hit districts were Ngororero, Rubavu, Nyabihu, Rutsiro and Karongi. According to reports, 14 people have died in Karongi, 26 in Rutsiro, 18 in Rubavu, 19 in Nyabihu and 18 in Ngororero.Rwanda National Police reported that the Mukamira-Ngororero and Rubavu-Rutsiro roads are impassable due to flooding and landslide debris. UNITAR on behalf of United Nations Office for the Coordination of Humanitarian Affairs (OCHA) / Regional Office for Southern & Eastern Africa in cooperation with Rwanda Space Agency ...

Details →

Usage examples

See 1 usage example →

PALSAR-2 ScanSAR Tropical Cycolne Mocha (L2.1)

agriculturecogdisaster responseearth observationgeospatialnatural resourcesatellite imagerystacsustainabilitysynthetic aperture radar

Tropical Cyclone Mocha began to form in the Bay of Bengal on 11 May 2023 and continues to intensify as it moves towards Myanmar and Bangladesh.Cyclone Mocha is the first storm to form in the Bay of Bengal this year and is expected to hit several coastal areas in Bangladesh on 14 May with wind speeds of up to 175 km/h.After made its landfall in the coast between Cox’s Bazar (Bangladesh) and Kyaukphyu (Myanmar) near Sittwe (Myanmar). At most, Catastrophic Damage-causing winds was possible especially in the areas of Rakhine State and Chin State, and Severe Damage-causing winds is possible in the ...

Details →

Usage examples

See 1 usage example →

Cloud to Street - Microsoft Flood and Clouds Dataset

cogcomputer visiondeep learningearth observationfloodsgeospatialmachine learningsatellite imagerysynthetic aperture radar

This dataset consists of chips of Sentinel-1 and Sentinel-2 satellite data. Each Sentinel-1 chip contains a corresponding label for water and each Sentinel-2 chip contains a corresponding label for water and clouds. Data is stored in folders by a unique event identifier as the folder name. Within each event folder there are subfolders for Sentinel-1 (s1) and Sentinel-2 (s2) data. Each chip is contained in its own sub-folder with the folder name being the source image id, followed by a unique chip identifier consisting of a hyphenated set of 5 numbers. All bands of the satellite data, as well a...

Details →

NOAA National Blend of Models (NBM)

agricultureclimatecogmeteorologicalweather

The National Blend of Models (NBM) is a nationally consistent and skillful suite of calibrated forecast guidance based on a blend of both NWS and non-NWS numerical weather prediction model data and post-processed model guidance. The goal of the NBM is to create a highly accurate, skillful and consistent starting point for the gridded forecast.

Details →

VENUS L2A Cloud-Optimized GeoTIFFs

activity detectionagriculturecogdisaster responseearth observationenvironmentalgeospatialimage processingland covernatural resourcesatellite imagerystac

The Venµs science mission is a joint research mission undertaken by CNES and ISA, the Israel Space Agency. It aims to demonstrate the effectiveness of high-resolution multi-temporal observation optimised through Copernicus, the global environmental and security monitoring programme. Venµs was launched from the Centre Spatial Guyanais by a VEGA rocket, during the night from 2017, August 1st to 2nd. Thanks to its multispectral camera (12 spectral bands in the visible and near-infrared ranges, with spectral characteristics provided here), it acquires imagery every 1-2 days over 100+ areas at...

Details →