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MODIS — Daily Satellite Observations

Provider
NASA (Terra and Aqua satellites)
Website
GEE | lpdaac.usgs.gov
Access Level
🔵 GEE (best) | 🟡 USGS Earth Data
Resolution
250m, 500m, or 1km depending on product
Revisit Time
Daily (Terra at 10:30am, Aqua at 1:30pm)
Archive
February 2000 to present

Key MODIS Products for India

Product ID Name Resolution Frequency Use
MOD13Q1 NDVI/EVI 250m 16-day Crop monitoring, phenology
MOD11A1 Land Surface Temperature 1km Daily Heat islands, drought
MCD64A1 Burned Area 500m Monthly Forest fire tracking
MOD09GA Daily Surface Reflectance 500m Daily True colour, indices
MOD14A1 Active Fire/Thermal Anomalies 1km Daily Fire alerts
MOD16A2 Evapotranspiration 500m 8-day Water stress, irrigation
MOD44W Water Mask 250m Annual Permanent water bodies

MODIS in GEE: Crop Season Detection

// GEE: MODIS NDVI Seasonal Profile for Punjab (Double Cropping)
var punjab = ee.Geometry.Rectangle([73.5, 29.5, 77.0, 32.5]);

// Load MOD13Q1 (16-day NDVI) for 2023
var modis = ee.ImageCollection("MODIS/061/MOD13Q1")
  .filterBounds(punjab)
  .filterDate('2023-01-01', '2023-12-31')
  .select('NDVI');

// Scale NDVI (MODIS NDVI is stored *10000)
var scaleNDVI = function(img) {
  return img.multiply(0.0001).copyProperties(img, ['system:time_start']);
};
modis = modis.map(scaleNDVI);

// Chart: NDVI over time (shows two crop peaks = wheat + rice)
var chart = ui.Chart.image.series(modis, punjab, ee.Reducer.mean(), 500)
  .setOptions({
    title: 'MODIS NDVI Seasonal Profile — Punjab 2023\n(Two peaks = Rabi wheat + Kharif rice)',
    hAxis: {title: 'Date'},
    vAxis: {title: 'NDVI', minValue: 0, maxValue: 0.9},
    lineWidth: 2,
    colors: ['#228B22']
  });
print(chart);

What you'll see: Two NDVI peaks in Punjab — one in ~March (wheat harvest) and one in ~October (rice harvest). This "double-hump" pattern is the signature of India's most productive agricultural system.

MODIS Land Surface Temperature (LST) — Urban Heat Islands

// GEE: Urban Heat Island — MODIS LST
var delhi = ee.Geometry.Rectangle([76.8, 28.4, 77.5, 28.9]);

var lst = ee.ImageCollection("MODIS/061/MOD11A1")
  .filterBounds(delhi)
  .filterDate('2023-05-01', '2023-05-31')  // Peak summer
  .select('LST_Day_1km')
  .mean()
  .multiply(0.02).subtract(273.15);  // Convert to Celsius

Map.centerObject(delhi, 10);
Map.addLayer(lst, {min: 30, max: 50, palette: ['blue','yellow','orange','red']},
             'LST Delhi May 2023 (°C)');

✏️ Practice Exercise

Exercise 5.5 — NDVI Seasonal Profile for Your District

Goal: Plot how vegetation greenness changes through the year in your district.

  1. In GEE, modify the Punjab code above with your district's coordinates
  2. Run it for 2023 — you'll get a chart showing NDVI month by month

Interpret the chart: - [ ] How many NDVI peaks are there? (1 peak = single crop, 2 peaks = double crop) - [ ] When is the peak NDVI? (corresponds to the main crop season) - [ ] How low does NDVI drop in the dry season? (indicates how barren the land is) - [ ] Compare your district with a neighbouring district that has different agriculture

Continue to Chapter 6: APIs & Web Services →