![]() ![]() Therefore, you will only download the data you really want.t. STAC allows you to subset your desired data collection by region, time, and band. Using cloud hosted publicly available archive from LP DAAC Cumulus cloud, you will not need to download HLS source data files for your research needs anymore. The primary objective of this tutorial is to show how to query and subset HLS data using the NASA CMR-STAC application programming interface (API). NASA’s Land Processes Distributed Active Archive Center (LP DAAC) archives and distributes HLS products in the LP DAAC Cumulus cloud archive as Cloud Optimized GeoTIFFs (COG). Numerous studies such as land cover change, agricultural management, disaster response, water resources, and vegetation phenology will vastly benefit from higher temporal resolution of this dataset. ![]() Using sets of algorithms, all the necessary radiometric, spectral, geometric, and spatial corrections have been applied to make HLS into seamless timeseries that are stackable and comparable.ĭense timeseries of HLS are creating unique and exciting opportunities to monitor, map dynamics in land surface properties with unprecedented spatial detail. ![]() The Harmonized Landsat Sentinel-2 (HLS) project is a NASA initiative aiming to produce a consistent, harmonized surface reflectance product from Landsat 8 and Sentinel-2 data acquired by the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat 8 and Sentinel-2 satellites, respectively. This tutorial demonstrates how to work with the HLS Landsat 8 ( HLS元0.002) and Sentinel-2 ( HLSS30.002) data products in R. ![]()
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