How to Scrape Satellite Data: Sentinel Hub and NASA Earthdata

Satellite imagery and Earth observation data are freely available from NASA and ESA. These datasets power everything from climate research to precision agriculture. Let's build Python tools to access and process this data. Available Satellite Data Sources Sentinel Hub (ESA): Sentinel-1 (radar), Sentinel-2 (optical), Sentinel-3 (ocean/land) NASA Earthdata : Landsat, MODIS, VIIRS, GPM (precipitation) NOAA : Weather satellites, ocean data Planet (commercial): Daily global imagery Setting Up pip install requests rasterio numpy matplotlib sentinelhub Accessing NASA Earthdata NASA's CMR (Common Metadata Repository) API lets you search their entire catalog: import requests import json def search_earthdata ( keyword , start_date , end_date , bbox = None ): """ Search NASA Earthdata for datasets. """ url = " https://cmr.earthdata.nasa.gov/search/granules.json " params = { " keyword " : keyword , " temporal[] " : f " { start_date } , { end_date } " , " page_size " : 50 , " sort_key " : " -start_