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I've been working on a proof of concept that finds the minimum images necessary to cover an AOI for an input set of STAC image features. There's a lot going on and some moving pieces I have omitted out of simplicity. The general advantage of the solution is updating only the images intersecting area (or priority) based on the previous image in O(1). This is ...


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The basic idea below is: find the image that covers the largest area in your AOI store in list find the next image that covers the most remaining area store in list repeat until there is no area left to cover from shapely.geometry import Polygon, MultiPolygon, box import json import requests def find_largest_intersect(small_polys, large_poly):...


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For anyone struggling with bitpacked mask values in MODIS (like I was), I made a package to deal with them more easily. Details are here https://pypi.org/project/unpackqa/ Code to pull the aerosol quantity from the above MOD09 file is as follows from osgeo import gdal from matplotlib import pyplot as plt import unpackqa # Define how qa/qc flags are from ...


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