The Land Change Monitoring, Assessment, and Projection (LCMAP) team is developing a series of tutorials showing users how to interact with LCMAP data in automated, Python-based Jupyter Notebook workflows.
Getting Started with LCMAP Data in Python Tutorial Series:
Chapter 1A: Direct Access of LCMAP Mosaics
This tutorial demonstrates how to perform spatiotemporal queries for LCMAP data by reading and subsetting LCMAP mosaics directly over HTTPS to extract the desired data by product and year for a given region of interest. The mosaics are distributed as internally tiled and compressed GeoTIFFs that allow direct access to the data.
This tutorial demonstrates how to perform spatial and temporal queries for LCMAP data by submitting requests to the USGS EarthExplorer (EE) Machine-to-Machine (M2M) API. The tutorial then shows how to download and unzip LCMAP tile bundles that intersect a given spatiotemporal query.
This tutorial demonstrates how to process LCMAP tile bundles retrieved from USGS EarthExplorer. Processing steps shown below include opening multiple tiles of LCMAP science products, mosaicking them into a single image, clipping to the bounds of a region of interest (ROI), reprojecting the clipped data to a new projection, and exporting the results as cloud optimized GeoTIFFs (COG).
This tutorial demonstrates how to quality filter or mask LCMAP science products. Processing steps shown below include interpreting LCMAP quality data, defining a list of values to be masked, excluding or masking pixels that fall under the given criteria, visualizing the masked science products, and exporting the results as cloud optimized GeoTIFFs (COG).
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