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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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