Planetary-computer

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2023.1.26

Changelog

This is the changelog for the Planetary Computer January 2023 release. See <a href="https://planetarycomputer.microsoft.com/docs/changelogs/history">previous changelogs</a> for notes about previous releases.

This release brings a new datasets and features, including:

- [Vector rendering](vector-rendering)
- [New datasets](new-datasets)
- [Dataset updates](dataset-updates)
- [Updates to our Terms of Use](updates-to-our-terms-of-use)
- [Notices for upcoming release](notices-for-upcoming-release)

<!-- (vector-tile-rendering)= -->
Vector Rendering

The Planetary Computer Data Catalog contains assets in a variety of common
geospatial formats, but until now the Explorer has only supported visualizing
raster data. With this release, we're introducing support for vector rendering
for collections with GeoParquet data assets. We're showcasing this feature with
the [MS Buildings](https://planetarycomputer.microsoft.com/dataset/ms-buildings)
dataset, which contains over 1 billion building footprints across the world.

For this, and future, GeoParquet vector datasets you'll find a new
[collection-level asset](https://github.com/radiantearth/stac-spec/blob/master/collection-spec/collection-spec.md#asset-object)
with a role of `tilejson` that contains a [TileJSON](https://github.com/mapbox/tilejson-spec) endpoint that can be used to render the data as [Mapbox Vector Tiles](https://docs.mapbox.com/data/tilesets/guides/vector-tiles-standards/).

[Use the Explorer](https://planetarycomputer.microsoft.com/explore?c=-77.7333%2C39.4660&z=5.05&v=2&d=ms-buildings&m=Global&r=Default&s=true%3A%3A100%3A%3Atrue&sr=desc&ae=0)
to quickly visualize the geographic coverage of the dataset:

<img src="https://planetarycomputer.microsoft.com/_images/docs-explorer-vector-buildings-us-extent.png" height=500/>

Or overlay it with other layers to see how it fits into the broader context of the world. For example, to see villages in southern Nigeria that have very low nighttime light intensity:

<img src="https://planetarycomputer.microsoft.com/_images/docs-explorer-vector-buildings-at-light.png" height=500/>

<!-- (new-datasets-jan-23)= -->
New datasets

This release includes several new datasets:

ESA Climate Change Initiative Land Cover

The <a href="https://planetarycomputer.microsoft.com/dataset/esa-cci-lc">ESA Climate Change Initiative Land Cover</a> datasets consistent global annual land cover maps at 300m spatial resolution from 1992 to 2020. There are collections containing <a href="https://planetarycomputer.microsoft.com/dataset/esa-cci-lc">Cloud Optimized GeoTIFFs</a> and <a href="https://planetarycomputer.microsoft.com/dataset/esa-cci-lc-netcdf">NetCDF</a> files.

This is a timelapse from 1992-2020 over <a href="https://planetarycomputer.microsoft.com/explore?c=-55.0498%2C-12.5996&z=5.29&v=2&d=esa-cci-lc&s=true%3A%3A100%3A%3Atrue&sr=desc&m=Most+recent+%282020%29&r=Classification&ae=0">the Amazon Rainforest in Brazil and Bolivia</a>:

<img style="width: 600px;" src="https://ai4edatasetspublicassets.azureedge.net/assets/pc_video/docs-esa-cci-lc-1992-2020-brazil.gif" alt="Timelapse ESA CCI LC 1992-2020 over Brazil"/>

NOAA Climate Normals

The <a href="https://planetarycomputer.microsoft.com/dataset/group/noaa-climate-normals">NOAA US Climate Normals</a> datasets provide information about typical climate conditions for thousands of weather station locations across the United States.

The individual weather station data is contained in the <a href="https://planetarycomputer.microsoft.com/dataset/noaa-climate-normals-tabular">noaa-climate-normals-tabular</a> colleciton, which contains tabular data in GeoParquet format.

Additionally, there is gridded data provided in the collections <a href="https://planetarycomputer.microsoft.com/dataset/noaa-climate-normals-gridded">noaa-climate-normals-gridded</a>, which contains Cloud Optimized GeoTIFFs, and <a href="https://planetarycomputer.microsoft.com/dataset/noaa-climate-normals-netcdf">noaa-climate-normals-netcdf</a> which contains NetCDF files.

Note that this dataset resides in the East US Azure region.


<img src="https://ai4edatasetspublicassets.blob.core.windows.net/assets/pc_thumbnails/noaa-climate-normals-gridded-thumb.png" width=700/>

Cropland Data Layer

The [USDA Cropland Data Layer](https://planetarycomputer.microsoft.com/dataset/usda-cdl) is a crop-specific land cover classification product of more than 100 crop categories grown in the United States.

<img src="https://planetarycomputer.microsoft.com/_images/changelog-usda-cdl.png" width=558/>

USGS Land Change Monitoring, Assessment, and Projection

The <a href="https://planetarycomputer.microsoft.com/dataset/group/usgs-lcmap">USGS Land Change Monitoring, Assessment, and Projection (LCMAP)</a> datasets provide land cover mapping and change monitoring from the U.S.

There are two datasets; one containing "Collection 1.3" data for the Conterminous United States (<a href="https://planetarycomputer.microsoft.com/dataset/usgs-lcmap-conus-v13">usgs-lcmap-conus-v13</a>) and another containing "Collection 1.0" data for Hawaii (<a href="https://planetarycomputer.microsoft.com/dataset/usgs-lcmap-hawaii-v10">usgs-lcmap-hawaii-v10</a>)

This is a timelapse from 1985-2021 over <a href="https://planetarycomputer.microsoft.com/explore?c=-121.2561%2C39.7589&z=8.36&v=2&d=usgs-lcmap-conus-v13%7C%7Cusgs-lcmap-conus-v13&s=false%3A%3A100%3A%3Atrue%7C%7Ctrue%3A%3A100%3A%3Atrue&sr=desc%7C%7Cdesc&m=1985%7C%7CMost+recent+%282021%29&r=Land+Cover%7C%7CLand+Cover&ae=0">California's Plumas National Forest</a>:

<img style="width: 600px;" src="https://ai4edatasetspublicassets.blob.core.windows.net/assets/pc_video/docs-usgs-lcmap-cali-1985-2021.gif" alt="Timelapse ESA CCI LC 1992-2020 over Brazil"/>

National Wetlands Inventory

The <a href="https://planetarycomputer.microsoft.com/dataset/fws-nwi">FWS National Wetlands Inventory</a> collection contains more than 35 million wetland and deepwater features. This dataset covers the conterminous United States, Hawaii, Puerto Rico, the Virgin Islands, Guam, the major Northern Mariana Islands and Alaska.

<img src="https://planetarycomputer.microsoft.com/_images/changelog-fws-nwi.png" height=400/>

<!-- (dataset-updates-jan-23)= -->
Dataset updates

NOAA GOES updates
- GOES-18 data is now available in the <a href="https://planetarycomputer.microsoft.com/dataset/goes-cmi">Cloud Moisture Index (goes-cmi)</a> collection.
- Additional data products for GOES that are not yet in the API are documented in the catalog: <a href="https://planetarycomputer.microsoft.com/dataset/storage/goes-fdc">Fire Detection and Characterization (FDC)</a>, <a href="https://planetarycomputer.microsoft.com/dataset/storage/goes-lst">Land Surface Temperature (LST)</a>, <a href="https://planetarycomputer.microsoft.com/dataset/storage/goes-rrqpe">Rainfall Rate and Quantitative Precipitation Estimation (RRQPE)</a>, and <a href="https://planetarycomputer.microsoft.com/dataset/storage/goes-sst">Sea Surface Temperature (SST)</a>
- The goes-cmi collection now has a render configuration that utilizes infrared data to better visualize night-time scenes. See <a href="https://planetarycomputer.microsoft.com/explore?c=-92.2446%2C37.2474&z=3.64&v=2&d=goes-cmi&s=false%3A%3A100%3A%3Atrue&ae=0&sr=desc&m=cql%3A6ded4476e6da6a428e449b19bd25ab17&r=Infrared">this example</a> in the Explorer.

Other dataset updates

- [TerraClimate](https://planetarycomputer.microsoft.com/dataset/terraclimate) was updated to include the latest data from the producer, the [Climatology Lab](https://www.climatologylab.org/terraclimate.html). The dataset now covers 1958 - 2021. Note that some variables, such as the station influence variables, are no longer provided. The Zarr store linked from the STAC collection is at a new URL. The data at the old URL will be deleted sometime in the future. In addition, the STAC metadata now includes the latest updates from the [`xarray-assets`](https://github.com/stac-extensions/xarray-assets) STAC extension.
- The <a href="https://planetarycomputer.microsoft.com/dataset/storage/noaa-nws">NOAA National Water Model</a> data products, which are hosted but not yet fully integrated into the API, are now documented in the data catalog.
- Using [new functionality in stactools](https://github.com/stac-utils/stactools/pull/307), the footprints in the <a href="https://planetarycomputer.microsoft.com/dataset/aster">ASTER collection</a> have been update to better match the actual image data, rather than the full raster extent.
- Collections now have an `msft:region` property, which indicates the Azure Region in which the data is hosted.
- The <a href="https://planetarycomputer.microsoft.com/dataset/ms-buildings">Microsoft Building Footprints</a> dataset can now be visualized in the Explorer, using the vector rendering feature described above.

<!-- (future-release-notice-jan-23)= -->

Documentation Improvements

- Added a new [Sentinel-2 notebook](https://planetarycomputer.microsoft.com/dataset/sentinel-2-l2a#Baseline-Change) demonstrating the Sentinel-2 L2A Baseline Change, and how to harmonize data across it.
- Expanded the Data Catalog documentation to include a <a href="https://planetarycomputer.microsoft.com/docs/concepts/data-catalog/#data-providers">new section</a> on how the Planetary Computer relates to data providers like the [NOAA Open Data Dissemination](https://www.noaa.gov/information-technology/open-data-dissemination) program.

<!-- (terms-of-use-update-jan-23)= -->
Updates to our Terms of Use

Our <a href="https://planetarycomputer.microsoft.com/terms">Terms of Use</a> has been updated to clarify terms about the data access tokens issued by the Planetary Computer for data access. No change in behavior or permissions has occurred. Please read the Terms of Use to get more information about the permitted utilization of data tokens for the Planetary Computer.

Notices for upcoming release


Please be advised that in the next release, approximately in the April/May 2023 time frame, we will be upgrading the version of our raster tiling engine, TiTiler. This will result in some changes to the way rendering parameters are specified when generating image tiles. These changes will affect both the [Item Tile endpoints](https://planetarycomputer.microsoft.com/api/data/v1/docs#/Item%20tile%20endpoints) and the [Mosaic Tile endpoints](https://planetarycomputer.microsoft.com/api/data/v1/docs#/PgSTAC%20Mosaic%20endpoints).

These changes will **not** affect how you use the Explorer or any links you've saved or shared via the Explorer. It will only affect certain query string parameters you may have generated that hit `/api/data/` endpoints directly.

Please see the upstream changes for more information:

- [pgstac-titiler changelog](https://github.com/stac-utils/titiler-pgstac/blob/master/CHANGES.md?plain=1#L55-L63)
- [rio-tiler changelog](https://github.com/cogeotiff/rio-tiler/blob/main/docs/src/v4_migration.md#band-names)

If you have any questions, please reach out to us on our [GitHub Discussions page](https://github.com/microsoft/planetarycomputer/discussions).

2022.10.28

We're pleased to announce our June 2022 release! This release includes improvements to the data catalog and Explorer user interface, support for bulk queries with GeoParquet, and several new datasets. Feel free to post comments and questions in the thread below.

This release brings a number of new features to the Explorer app, including:

- [Item preview mode](https://planetarycomputer.microsoft.com/docs/overview/changelog/#item-preview-mode)
- [Generate a timelapse GIF for a dataset mosaic](https://planetarycomputer.microsoft.com/docs/overview/changelog/#generate-a-timelapse-gif-for-a-dataset-mosaic)
- [Generate a static image of a dataset mosaic](https://planetarycomputer.microsoft.com/docs/overview/changelog/#generate-a-static-image-of-a-dataset-mosaic)
- [Advanced filter allows settings time in ranges](https://planetarycomputer.microsoft.com/docs/overview/changelog/#advanced-filter-allows-settings-time-in-ranges)
- [Ability to change sort order of search results](https://planetarycomputer.microsoft.com/docs/overview/changelog/#ability-to-change-sort-order-of-search-results)

This release also includes several new datasets:

New datasets

This release includes several new datasets:

GOES-R Lightning Detection

[GOES-R Lightning Detection](https://planetarycomputer.microsoft.com/dataset/goes-glm):
Continuous lightning detection over the Western Hemisphere from the Geostationary Lightning Mapper (GLM) instrument.

![GOES-R lightning image](https://planetarycomputer.microsoft.com/_images/docs-data-glm_c.jpg)

NOAA MRMS QPE

- [NOAA MRMS QPE 1-Hour Pass 1](https://planetarycomputer.microsoft.com/dataset/noaa-mrms-qpe-1h-pass1): Integrated multi-sensor cumulative precipitation estimate for the past hour with a 1-hour latency.
- [NOAA MRMS QPE 1-Hour Pass 2](https://planetarycomputer.microsoft.com/dataset/noaa-mrms-qpe-1h-pass2): Integrated multi-sensor cumulative precipitation estimate for the past hour with a 2-hour latency.
- [NOAA MRMS QPE 24-Hour Pass 2](https://planetarycomputer.microsoft.com/dataset/noaa-mrms-qpe-24h-pass2): Integrated multi-sensor cumulative precipitation estimate for the past 24 hours with a 2-hour latency.

![NOAA-MRMS-QPE-image](https://planetarycomputer.microsoft.com/_images/docs-data-noaa-mrms-qpe_c.jpg)

NOAA Monthly NClimGrid

[NOAA Monthly NClimGrid](https://planetarycomputer.microsoft.com/dataset/noaa-nclimgrid-monthly): Monthly Climate Gridded dataset with data on temperature and precipitation.

<img style="height: 300px;" src="https://ai4edatasetspublicassets.azureedge.net/assets/pc_video/docs-data-noaa-nclimgrid-monthly.gif" alt="Timelapse avg temp nclimgrid"/>

Denver Regional Council of Governments Land Use Land Cover

[Denver Regional Council of Governments Land Use Land Cover](https://planetarycomputer.microsoft.com/dataset/drcog-lulc): 1-ft resolution land use / land cover dataset around Denver, Colorado.

![DR COG image](https://planetarycomputer.microsoft.com/_images/docs-data-denver-regional_c.jpg)

Chesapeake Land Cover/Land Use

[Chesapeake Land Cover (7-class)](https://planetarycomputer.microsoft.com/dataset/chesapeake-lc-7): 1-meter land cover data product for the entire Chesapeake Bay watershed with a uniform set of 7 land cover classes.

![](https://planetarycomputer.microsoft.com/_images/docs-data-chesapeake-7_c.jpg)

[Chesapeake Land Cover (13-class)](https://planetarycomputer.microsoft.com/dataset/chesapeake-lc-13): 1-meter land cover data product for the entire Chesapeake Bay watershed with 13 varying land cover classes.

![](https://planetarycomputer.microsoft.com/_images/docs-data-chesapeake-13_c.jpg)

[Chesapeake Land Use](https://planetarycomputer.microsoft.com/dataset/chesapeake-lu): 1-meter land use data product for the entire Chesapeake Bay watershed.

![](https://planetarycomputer.microsoft.com/_images/docs-data-chesapeake-lu_c.jpg)

2022.6.30

We're pleased to announce our June 2022 release! This release includes improvements to the data catalog and Explorer user interface, support for bulk queries with GeoParquet, and several new datasets. Feel free to post comments and questions in the thread below.

Highlights

- The Catalog and Explorer interfaces have been redesigned to accommodate the increased number of datasets available in the Planetary Computer.
- The entire website, including the Explorer, Catalog, and Documentation pages, have all been updated to work well on most mobile devices.
- We now provide snapshots of our STAC items for most of our collections as [GeoParquet](https://github.com/opengeospatial/geoparquet) datasets to support bulk STAC queries.

Bulk STAC queries with GeoParquet

Many of our collections now include a `geoparquet-items` collection-level asset that links to a [GeoParquet](https://github.com/opengeospatial/geoparquet) dataset in Azure Blob Storage. Each row in these Parquet datasets is a STAC item. While most users should continue to use the normal STAC API, these Parquet datasets are a nice complement for workloads that need to return very many STAC items.

See [Bulk STAC item queries with GeoParquet](../quickstarts/stac-geoparquet) for more. Discuss this on the [GeoParquet board](https://github.com/opengeospatial/geoparquet/discussions/114).

New datasets

This release includes several new datasets in our STAC API. Each of these links to the dataset details page, which includes an example notebook.

- [Deltares Floods](https://planetarycomputer.microsoft.com/dataset/deltares-floods)
- [Deltares Water Availability](https://planetarycomputer.microsoft.com/dataset/deltares-water-availability)
- [Microsoft Building Footprints](https://planetarycomputer.microsoft.com/dataset/ms-buildings)
- [Kwando & Upper Zambezi Rivers HydroForecast](https://planetarycomputer.microsoft.com/dataset/kaza-hydroforecast)


Discuss this in the [release thread](https://github.com/microsoft/PlanetaryComputer/discussions/79).

2022.5.20

We're pleased to announce our May 2022 release! This release includes several performance improvements, API enhancements, and *many* new datasets.

Highlights

- **Improved performance and scalability of our STAC API**. Requests to our STAC API, including searches, will return faster and scale to larger concurrent loads. See the pgstac [0.5](https://github.com/stac-utils/pgstac/blob/main/CHANGELOG.md#v050) and [0.6](https://github.com/stac-utils/pgstac/releases/tag/v0.6.0) release notes for more.
- The [Explorer](https://planetarycomputer.microsoft.com/explore) now includes the ability to pin layers, allowing you to compare multiple queries. See [working with multiple layers](https://planetarycomputer.microsoft.com/docs/overview/explorer/#working-with-multiple-layers) for more.
- Many new datasets are available through our [catalog](https://planetarycomputer.microsoft.com/catalog). See the datasets section below for more.

New datasets

This release includes many new datasets. Each of these links to the dataset details page, which includes an example notebook.

* [Sentinel-1](https://planetarycomputer.microsoft.com/dataset/group/sentinel-1): Synthetic Aperture Radar raster products, including the world's first openly licensed (_CC-BY-4.0_), globally available radiometrically terrain corrected Sentinel 1 product.
* [Sentinel-1 RTC](https://planetarycomputer.microsoft.com/dataset/sentinel-1-rtc): Global radiometrically terrain corrected SAR imagery derived from the Sentinel 1 Level 1 GRD product.
* [Sentinel-1 GRD](https://planetarycomputer.microsoft.com/dataset/sentinel-1-grd): Focused SAR data that has been detected, multi-looked and projected to ground range using an Earth ellipsoid model.
* [Landsat](https://planetarycomputer.microsoft.com/dataset/group/landsat): Imagery from Landsat 1-9, starting from 1972.
* [Landsat Collection 2 Level-1](https://planetarycomputer.microsoft.com/dataset/landsat-c2-l1): Landsat Collection 2 Level-1 data from the Multispectral Scanner System (MSS) onboard Landsat 1 through Landsat 5.
* [Landsat Collection 2 Level-2](https://planetarycomputer.microsoft.com/dataset/landsat-c2-l2): Landsat Collection 2 Level-2 data from the Thematic Mapper (TM) onboard Landsat 4 and 5, the Enhanced Thematic Mapper Plus (ETM+) onboard Landsat 7, and the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) onboard Landsat 8 and 9.
* [MODIS](https://planetarycomputer.microsoft.com/dataset/group/modis) imagery and derived products, starting from 2000.
* [MODIS Burned Area Monthly](https://planetarycomputer.microsoft.com/dataset/modis-64A1-061): MODIS Burned Area Monthly
* [MODIS Gross Primary Productivity 8-Day Gap-Filled](https://planetarycomputer.microsoft.com/dataset/modis-17A2HGF-061): MODIS Gross Primary Productivity 8-Day Gap-Filled
* [MODIS Gross Primary Productivity 8-Day](https://planetarycomputer.microsoft.com/dataset/modis-17A2H-061): MODIS Gross Primary Productivity 8-Day
* [MODIS Land Surface Temperature/3-Band Emissivity 8-Day](https://planetarycomputer.microsoft.com/dataset/modis-21A2-061): MODIS Land Surface Temperature/3-Band Emissivity 8-Day
* [MODIS Land Surface Temperature/Emissivity 8-Day](https://planetarycomputer.microsoft.com/dataset/modis-11A2-061): MODIS Land Surface Temperature/Emissivity 8-Day
* [MODIS Land Surface Temperature/Emissivity Daily](https://planetarycomputer.microsoft.com/dataset/modis-11A1-061): MODIS Land Surface Temperature/Emissivity Daily
* [MODIS Leaf Area Index/FPAR 4-Day](https://planetarycomputer.microsoft.com/dataset/modis-15A3H-061): MODIS Leaf Area Index/FPAR 4-Day
* [MODIS Leaf Area Index/FPAR 8-Day](https://planetarycomputer.microsoft.com/dataset/modis-15A2H-061): MODIS Leaf Area Index/FPAR 8-Day
* [MODIS Nadir BRDF-Adjusted Reflectance (NBAR) Daily](https://planetarycomputer.microsoft.com/dataset/modis-43A4-061): MODIS Nadir BRDF-Adjusted Reflectance (NBAR) Daily
* [MODIS Net Evapotranspiration Yearly Gap-Filled](https://planetarycomputer.microsoft.com/dataset/modis-16A3GF-061): MODIS Net Evapotranspiration Yearly Gap-Filled
* [MODIS Net Primary Production Yearly Gap-Filled](https://planetarycomputer.microsoft.com/dataset/modis-17A3HGF-061): MODIS Net Primary Production Yearly Gap-Filled
* [MODIS Snow Cover 8-day](https://planetarycomputer.microsoft.com/dataset/modis-10A2-061): MODIS Snow Cover 8-day
* [MODIS Snow Cover Daily](https://planetarycomputer.microsoft.com/dataset/modis-10A1-061): MODIS Snow Cover Daily
* [MODIS Surface Reflectance 8-Day (250m)](https://planetarycomputer.microsoft.com/dataset/modis-09Q1-061): MODIS Surface Reflectance 8-Day (250m)
* [MODIS Surface Reflectance 8-Day (500m)](https://planetarycomputer.microsoft.com/dataset/modis-09A1-061): MODIS Surface Reflectance 8-Day (500m)
* [MODIS Thermal Anomalies/Fire 8-Day](https://planetarycomputer.microsoft.com/dataset/modis-14A2-061): MODIS Thermal Anomalies/Fire 8-Day
* [MODIS Thermal Anomalies/Fire Daily](https://planetarycomputer.microsoft.com/dataset/modis-14A1-061): MODIS Thermal Anomalies/Fire Daily
* [MODIS Vegetation Indices 16-Day (250m)](https://planetarycomputer.microsoft.com/dataset/modis-13Q1-061): MODIS Vegetation Indices 16-Day (250m)
* [MODIS Vegetation Indices 16-Day (500m)](https://planetarycomputer.microsoft.com/dataset/modis-13A1-061): MODIS Vegetation Indices 16-Day (500m)
* [USGS 3DEP](https://planetarycomputer.microsoft.com/dataset/group/3dep-lidar): Lidar elevation data as Cloud Optimized Point Cloud (COPC) and derived Cloud Optimized GeoTIFF (COG) data processed from the USGS 3D Elevation Program.
* [USGS 3DEP Lidar Point Cloud](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-copc)
* [USGS 3DEP Lidar Height Above Ground (HAG)](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-hag)
* [USGS 3DEP Lidar Classification](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-classification)
* [USGS 3DEP Lidar Digital Surfice Model (DSM)](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-dsm)
* [USGS 3DEP Digital Terrain Model (DTM)](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-dtm)
* [USGS 3DEP Digital Terrain Model (Native)](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-dtm-native)
* [USGS 3DEP Lidar Point Source](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-pointsourceid)
* [USGS 3DEP Lidar Intensity](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-intensity)
* [USGS 3DEP Lidar Returns](https://planetarycomputer.microsoft.com/dataset/3dep-lidar-returns)
* [NAIP](https://planetarycomputer.microsoft.com/dataset/naip): National Agriculture Imagery Program (NAIP) imagery updated for 2020
* [CIL Global Downscaled Projections for Climate Impacts Research Collection](https://planetarycomputer.microsoft.com/dataset/group/cil-gdpcir): Climate Impact Lab Global Downscaled Projections for Climate Impacts Research
* [ECMWF Open Data (real-time)](https://planetarycomputer.microsoft.com/dataset/ecmwf-forecast): ECMWF Open Data (Real Time) forecasts
* [ERA5 - PDS](https://planetarycomputer.microsoft.com/dataset/era5-pds): A comprehensive reanalysis, which assimilates as many observations as possible in the upper air and near surface.
* [ESA WorldCover 2020](https://planetarycomputer.microsoft.com/dataset/esa-worldcover): Global land cover product at 10 meter resolution for 2020 based on Sentinel-1 and Sentinel-2 data
* [ALOS Forest/Non-Forest Annual Mosaic](https://planetarycomputer.microsoft.com/dataset/alos-fnf-mosaic): Global 25-meter resolution map classifying "forest" and "non-forest" landcover.
* [ALOS PALSAR Annual Mosaic](https://planetarycomputer.microsoft.com/dataset/alos-palsar-mosaic): Global 25-meter resolution SAR image mosaic.
* [NOAA C-CAP Regional Land Cover and Change](https://planetarycomputer.microsoft.com/dataset/noaa-c-cap): Periodic coastal landcover classifications back to 1975
* [Urban Innovation Eclipse Sensor Data](https://planetarycomputer.microsoft.com/dataset/eclipse): A network of low-cost air quality sensing network for cities and led by the Urban Innovation Group at Microsoft Research
* [Planet NICFI](https://planetarycomputer.microsoft.com/dataset/group/planet-nicfi):
* [Planet-NICFI Basemaps (Analytic)](https://planetarycomputer.microsoft.com/dataset/planet-nicfi-analytic): Planet's high-resolution, analysis-ready mosaics of the world's tropics (Microsoft - GEO RFP winners only)
* [Planet-NICFI Basemaps (Visual)](https://planetarycomputer.microsoft.com/dataset/planet-nicfi-visual): Planet's high-resolution, analysis-ready mosaics of the world's tropics (Microsoft - GEO RFP winners only)

API updates

STAC API

- Updated the STAC API to [v1.0.0-rc.1](https://github.com/radiantearth/stac-api-spec/releases/tag/v1.0.0-rc.1)
- Initial support for [queryables](https://github.com/radiantearth/stac-api-spec/tree/master/fragments/filter#queryables) in the STAC API. See [Sentinel-2-l2a](https://planetarycomputer.microsoft.com/api/stac/v1/collections/sentinel-2-l2a/queryables) for an example. Additional queryables and more metadata description in coming releases.
- Scalability and performance improvements.

Data API

- Upgrades to pgstac-titiler [0.1.0a7](https://github.com/stac-utils/titiler-pgstac/blob/master/CHANGES.md#010a7-2022-04-05-pre-release)
- Scalability and performance improvements.

Documentation and Tutorials

In addition to the dataset examples, we have several new tutorials going in-depth on a specific topic.

* [Customizable radiometric terrain correction of Sentinel-1 products](https://planetarycomputer.microsoft.com/docs/tutorials/customizable-rtc-sentinel1/) using the open-source [sarsen](https://github.com/bopen/sarsen) package.
* [Computing climate indicators with xclim](https://planetarycomputer.microsoft.com/dataset/cil-gdpcir-cc0#Climate-indicators)

Hub environments

- Updated to [planetary-computer-containers 2022.05.11.0](https://github.com/microsoft/planetary-computer-containers/releases/tag/2022.05.11.0)

Changes
Changes in behavior that existing users may need to account for:

- The `landsat-8-c2-l2` collection is deprecated. This collection only contained Landsat 8 images from Collection 2. Please use the `landsat-c2-l2` collection, which now has data from Landsat 4 - 9 spanning all the way back to 1982. Existing workflows using landsat-8-c2-l2 items should be able to switch to `landsat-c2-l2` without disruption. `landsat-8-c2-l2` is removed from the website but remains in the STAC API; however it will no longer be updated with new items.
- Some queries on date ranges may return different results with this new release. This is due to corrections in the date range logic in our underlying metadata store, PgSTAC. For Items with all of a `start_datetime`, `end_datetime`, and `datetime` property, only the `start_datetime` and `end_datetime` will be considered, whereas previously `datetime` was the target of the search.

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