How to Scrape Satellite Imagery Metadata at Scale

Introduction Satellite imagery metadata powers applications from agricultural monitoring to urban planning and disaster response. Platforms like NASA Earthdata, Copernicus, and USGS Earth Explorer provide vast catalogs of imagery metadata that can be scraped and analyzed programmatically. This tutorial shows you how to build scalable satellite metadata scrapers. Setup import requests from bs4 import BeautifulSoup import pandas as pd import json import time from datetime import datetime , timedelta # For accessing protected catalogs at scale # Get your API key: https://www.scraperapi.com?fp_ref=the52 SCRAPER_API_KEY = " your_key_here " BASE_URL = " http://api.scraperapi.com " Querying NASA Earthdata CMR API NASA's Common Metadata Repository provides a free, powerful API: def search_nasa_granules ( collection , bbox , start_date , end_date , limit = 100 ): """ Search NASA CMR for satellite imagery granules. """ url = " https://cmr.earthdata.nasa.gov/search/granules.json " params = { " co