Built-up Area detection using Sentinel-2A Imagery and export as (SHP & CSV) using Earth Engine

In this video, we’ll explore how to detect and map built-up areas using Sentinel-2A satellite imagery in Google Earth Engine (GEE) — from pre-processing to exporting your final results as Shapefiles (SHP) and CSV tables.
You’ll learn how to compute the Normalized Difference Built-up Index (NDBI), apply an appropriate threshold to isolate urban areas, and convert the detected built-up zones from raster to vector polygons with area statistics (in km²).
What You’ll Learn,
How to import and define your study area (AOI), filtering Sentinel-2A imagery by date and cloud percentage, computing NDBI = (B11 - B8) / (B11 + B8) for built-up detection, applying thresholds to extract built-up masks, converting raster results to vector polygons, calculating built-up area in square kilometres, exporting outputs as SHP and CSV directly to Google Drive
Applications
Urban Growth Analysis, land use / land cover mapping, change detection studies, smart city planning & infrastructure monitoring
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Useful link
Code link:
https://code.earthengine.google.com/7...
Harmonized Sentinel-2 MSI: Multispectral Instrument, Level-2A (SR): https://developers.google.com/earth-e...
Subscribe to Terra Spatial for more advanced Earth Engine tutorials, land cover mapping, and hydrology-based GIS workflows.
This tutorial is perfect for researchers, GIS analysts, urban planners, and Earth Engine learners looking to perform automated built-up extraction efficiently.
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