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Chapter 5: Remote Sensing & Satellite Imagery

See India from space — track floods, crops, forests, and cities using free satellite data.

Why Remote Sensing?

A satellite can see what 1,000 field workers cannot — it covers the entire country every few days. Modern free datasets like Sentinel-2 and Landsat let anyone monitor land use, flood extent, crop health, and forest change without ever leaving their desk.

Understanding Satellite Data

Before using satellite data, understand two key trade-offs:

Spatial Resolution vs Temporal Resolution

Sensor Spatial Resolution Revisit Time Best For
Cartosat-3 (ISRO) 0.25 m 4 days Urban planning, detailed mapping
WorldView (commercial) 0.3 m 1 day Paid; very high detail
Pleiades (commercial) 0.5 m 1 day Paid
LISS-IV (ISRO) 5.8 m 24 days District-level vegetation, fields
Sentinel-2 (ESA) 10 m 5 days ✅ Best free choice for most uses
Landsat 8/9 (NASA) 30 m 16 days Long-term change detection (1972–now)
LISS-III (ISRO) 23.5 m 24 days Regional mapping
MODIS (NASA) 250m–1km Daily National crop monitoring, fire, LST

Which Sensor to Choose?

  • Mapping fields, urban areas, forests: → Sentinel-2 (10m, 5 days)
  • Tracking change over 20+ years: → Landsat (30m, 1972–now)
  • Daily monitoring (fire, flood, dust): → MODIS (500m, daily)
  • Very detailed city mapping: → Bhuvan Cartosat (free with login)

Chapter Datasets

# Dataset Provider Resolution Access Level
1 Bhuvan Imagery ISRO/NRSC 0.25m–23m 🟡 Login 🟡
2 Google Earth Engine Google varies 🟡 Login 🔵
3 Sentinel-1 & 2 (ESA) ESA/Copernicus 10–20m 🟡 Login 🔵
4 Landsat 8/9 (NASA) USGS/NASA 30m 🟡 Login 🔵
5 MODIS (NASA) NASA 250m–1km 🟡 GEE 🔵

Prerequisites for This Chapter

Skills Needed

Most datasets in this chapter require at least Level 3 skills — either: - QGIS (to visualise downloaded GeoTIFFs) - Python with rasterio and matplotlib - Google Earth Engine (JavaScript or Python API)

If you're new to these, start with Chapter 7: Visualizing Data first.

✏️ First Remote Sensing Exercise

Exercise 5.0 — View Your City from Sentinel-2 in GEE

Goal: Use Google Earth Engine to display a satellite image of your city.

Time needed: 30 minutes (including GEE registration)

  1. Register for GEE at earthengine.google.com/signup
  2. Once approved, go to code.earthengine.google.com
  3. Paste this JavaScript:
// Your city coordinates (change to your city)
var city = ee.Geometry.Point([73.8567, 18.5204]);  // Pune

// Load Sentinel-2 image (cloud-free, recent)
var s2 = ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED")
  .filterBounds(city)
  .filterDate('2023-11-01', '2024-02-28')  // Winter = less clouds
  .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 10))
  .median();

// Display true colour (R-G-B)
var visParams = {bands: ['B4', 'B3', 'B2'], min: 0, max: 3000};
Map.centerObject(city, 12);
Map.addLayer(s2, visParams, 'Sentinel-2 True Colour');
  1. Click Run
  2. Explore the map — zoom in and out

You just viewed a 10-metre resolution satellite image of your city, for free!

Start with: Bhuvan Satellite Data →