remote-sensing-scripts

A collection of unrelated scripts useful for remote sensing.

read_nlcd.ipynb shows how to plot a National Landcover Database (NLCD) GeoTIFF in Python and adjust the colormap to match the NLCD legend. This assumes you have an NLCD tif file reprojected (if needed) and ready.
- NLCD data can be downloaded here: https://www.usgs.gov/centers/eros/science/national-land-cover-database
get_modis_ndvi_gee is a short demonstration of how to do these things in Google Earth Engine (gee):
- download MODIS Normalized Difference Vegetation Index (NDVI) data over a multi-year time period
- select a specific image from an image collection using the image index
- MODIS NDVI data on GEE: https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13A2

Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
__pycache__		__pycache__
data		data
gifs		gifs
NLCD_Land_Cover_Legend.PNG		NLCD_Land_Cover_Legend.PNG
README.md		README.md
analyze_s1_data_from_gee.ipynb		analyze_s1_data_from_gee.ipynb
create_s1_gif_with_gee.ipynb		create_s1_gif_with_gee.ipynb
download_s1.ipynb		download_s1.ipynb
get_copernicus_dem.ipynb		get_copernicus_dem.ipynb
get_copernicus_land_cover.ipynb		get_copernicus_land_cover.ipynb
get_cygnss_data_from_aws.ipynb		get_cygnss_data_from_aws.ipynb
get_data_from_gee.ipynb		get_data_from_gee.ipynb
get_era5_precipitation.ipynb		get_era5_precipitation.ipynb
get_era5_winds.ipynb		get_era5_winds.ipynb
get_modis_lst.ipynb		get_modis_lst.ipynb
get_modis_ndvi_gee		get_modis_ndvi_gee
get_s1_data_in_polygon.ipynb		get_s1_data_in_polygon.ipynb
get_s1_from_gee.ipynb		get_s1_from_gee.ipynb
get_s2_and_dw_data_in_polygon.ipynb		get_s2_and_dw_data_in_polygon.ipynb
get_s2_from_gee.ipynb		get_s2_from_gee.ipynb
hyrdafloods_example.ipynb		hyrdafloods_example.ipynb
make_ridgeline_plot.py		make_ridgeline_plot.py
modis_lst_timeseries.ipynb		modis_lst_timeseries.ipynb
nandabetenv.yml		nandabetenv.yml
read_nlcd.ipynb		read_nlcd.ipynb
s1_timelapse.ipynb		s1_timelapse.ipynb
speckle_filter.py		speckle_filter.py
wildfires_canada_2023jun.ipynb		wildfires_canada_2023jun.ipynb
working_with_gee.ipynb		working_with_gee.ipynb

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