SpatioTemporal Asset Catalog (STAC) Item - 20210101_184738_ssc13_u0002 in san-francisco

Roscosmos open datasets catalog STAC Item

SpatioTemporal Asset Catalog (STAC) Item - 20201214_180159_ssc12_u0001 in sp-crater

SpatioTemporal Asset Catalog (STAC) Item - veg.plot_18880101_20151231 in veg.plot

SpatioTemporal Asset Catalog (STAC) Item - 20201214_180159_ssc12_u0002 in sp-crater

SpatioTemporal Asset Catalog (STAC) Item - 20201214_032156_ssc3_u0002 in angkor-wat

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 to search the archive. This dataset contains all of the scenes in the original Sentinel-2 Public Dataset and will grow as that does. L2A data are available from April 2017 over wider Europe region and globally since December 2018.

Contains polygon boundaries for each HEC-RAS model used to develop pluvial flood risk data. Attributes described below, contain links to the model metadata.

Metadata is stored in SpatioTemporal Asset Catalog (STAC) Items that include information for the HEC-RAS model files and associated data which can be downloaded and run on any Windows machine that has HEC-RAS 6.X installed.

Field definitions are: id: Unique ID for the pluvial model; datetime: Time the model data was created; huc12: Hydrologic Unit Code (HUC) 12 containing the model; tidal: Indicates if the model has a tidal boundary (1) or not (0); mhw2020: (Mean High Water 2020) Link to model metadata and input files if the simulation included a tidal simulation; mhw2040: (Mean High Water 2040) Link to model metadata and input files if the simulation included a tidal simulation; mhw2060: (Mean High Water 2060) Link to model metadata and input files if the simulation included a tidal simulation; mhw2080: (Mean High Water 2080) Link to model metadata and input files if the simulation included a tidal simulation; mhw2100: (Mean High Water 2100) Link to model metadata and input files if the simulation included a tidal simulation; nt: (not-tidal) Link to model metadata and input files if there is no tidal boundary condition applied.

SpatioTemporal Asset Catalog (STAC) Item - 20201230_151832_ssc13_u0001 in cocabamba-peru

ArcticDEM - 2m GSD Digital Elevation Models (DEMs) and mosaics from 2007 to the present. The ArcticDEM 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-resolution (~0.5 meter) imagery acquired by the Maxar constellation of optical imaging satellites.

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 published and openly available under the terms of the World Bank’s open data license.

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 on-going studies. L1C data are available from June 2015 globally. L2A data are available from November 2016 over Europe region and globally since January 2017.

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 the Sentinel-2 annual scene collections from the Mircosoft Planetary Computer. Each of the maps has an assessed average accuracy of over 75%. These maps have been improved from Impact Observatory’s previous release and provide a relative reduction in the amount of anomalous change between classes, particularly between “Bare” and any of the vegetative classes “Trees,” “Crops,” “Flooded Vegetation,” and “Rangeland”. This updated time series of annual global maps is also re-aligned to match the ESA UTM tiling grid for Sentinel-2 imagery. Data can be accessed directly from the Registry of Open Data on AWS, from the STAC 1.0.0 endpoint, or from the IO Store for a specific Area of Interest (AOI).

SpatioTemporal Asset Catalog (STAC) Item - 20201213_045438_ss01_u0001 in planet-stac-skysat

Digital Surface Model (DSM) of SP Crater, Arizona, created from stereo images captured by a Planet SkySat satellite. It is distributed as a single band Cloud-optimized GeoTiff, with each pixel representing the height at that location.

A 'True Ortho' image of SP Crater, Arizona, meaning it's been geometrically corrected to remove distortions from perspective, tilt, and object height, offering a perfectly overhead view of terrain. It is done by combining many level 1a stereo captures from a Planet SkySat satellite, and then uses that to pansharpen colors from a Planetscope basemap from the coincident month. It is distributed as a 3 band Cloud-Optimized GeoTiff.