Introduction to Satellite Bands

Satellite sensors capture different wavelengths of light, each providing unique information about the Earth's surface. Understanding band combinations is crucial for effective remote sensing analysis.

Sentinel-2 Bands

Band Wavelength (nm) Resolution (m) Description
B1 443 60 Aerosols
B2 490 10 Blue
B3 560 10 Green
B4 665 10 Red
B5 705 20 Red Edge 1
B6 740 20 Red Edge 2
B7 783 20 Red Edge 3
B8 842 10 NIR
B8A 865 20 Narrow NIR
B9 945 60 Water Vapor
B10 1375 60 Cirrus
B11 1610 20 SWIR 1
B12 2190 20 SWIR 2

Common Band Combinations

Natural Color (4,3,2)

Bands: Red (B4), Green (B3), Blue (B2)

Application: True color representation, general visualization

Features: Appears similar to what the human eye sees

False Color Urban (12,11,4)

Bands: SWIR 2 (B12), SWIR 1 (B11), Red (B4)

Application: Urban area mapping, built-up areas

Features: Highlights urban areas in blue, vegetation in green

Agriculture (8,4,3)

Bands: NIR (B8), Red (B4), Green (B3)

Application: Vegetation health, crop monitoring

Features: Healthy vegetation appears bright red

Vegetation Analysis (8,11,2)

Bands: NIR (B8), SWIR 1 (B11), Blue (B2)

Application: Vegetation stress, moisture content

Features: Highlights stressed vegetation in yellow

Water Bodies (8,4,3)

Bands: NIR (B8), Red (B4), Green (B3)

Application: Water body detection, water quality

Features: Water appears dark blue/black

Comparison with Landsat 7

Application Sentinel-2 Bands Landsat 7 Bands Advantages
Natural Color 4,3,2 3,2,1 Sentinel-2 has higher resolution (10m vs 30m)
Vegetation Analysis 8,4,3 4,3,2 Sentinel-2 has higher resolution (10m vs 30m)
Urban Mapping 12,11,4 7,5,3 Sentinel-2 has more spectral bands
Water Quality 8,4,3 4,3,2 Sentinel-2 has better temporal resolution
Agriculture 8,11,2 4,5,2 Sentinel-2 has red edge bands

Vegetation and Water Indices

Normalized Difference Vegetation Index (NDVI)

Formula: (NIR - Red) / (NIR + Red)

Sentinel-2 Bands: (B8 - B4) / (B8 + B4)

Landsat 7 Bands: (B4 - B3) / (B4 + B3)

Application: Vegetation health monitoring, crop assessment

Range: -1 to 1 (healthy vegetation typically 0.2-0.8)

Features:

  • Higher values indicate healthier vegetation
  • Values near 0 indicate bare soil
  • Negative values typically indicate water

Normalized Difference Water Index (NDWI)

Formula: (Green - NIR) / (Green + NIR)

Sentinel-2 Bands: (B3 - B8) / (B3 + B8)

Landsat 7 Bands: (B2 - B4) / (B2 + B4)

Application: Water body detection, moisture content

Range: -1 to 1 (water typically > 0.2)

Features:

  • Positive values indicate water bodies
  • Negative values indicate vegetation
  • Useful for flood monitoring

Enhanced Vegetation Index (EVI)

Formula: 2.5 * (NIR - Red) / (NIR + 6*Red - 7.5*Blue + 1)

Sentinel-2 Bands: 2.5 * (B8 - B4) / (B8 + 6*B4 - 7.5*B2 + 1)

Landsat 7 Bands: 2.5 * (B4 - B3) / (B4 + 6*B3 - 7.5*B1 + 1)

Application: Vegetation monitoring in high biomass areas

Advantages:

  • Less sensitive to atmospheric conditions than NDVI
  • Better performance in high biomass areas
  • Reduces soil background influence

Modified Normalized Difference Water Index (MNDWI)

Formula: (Green - SWIR) / (Green + SWIR)

Sentinel-2 Bands: (B3 - B11) / (B3 + B11)

Landsat 7 Bands: (B2 - B5) / (B2 + B5)

Application: Urban water body extraction

Advantages:

  • Better at distinguishing water from built-up areas
  • More effective in urban environments
  • Reduces confusion with shadows

Soil Adjusted Vegetation Index (SAVI)

Formula: (1 + L) * (NIR - Red) / (NIR + Red + L)

Sentinel-2 Bands: (1 + L) * (B8 - B4) / (B8 + B4 + L)

Landsat 7 Bands: (1 + L) * (B4 - B3) / (B4 + B3 + L)

Application: Vegetation monitoring in areas with exposed soil

Features:

  • L is a soil adjustment factor (typically 0.5)
  • Reduces soil background effects
  • Better for sparse vegetation

Best Practices

Band Selection Tips

  • Purpose-Driven Selection

    Choose bands based on the specific feature or phenomenon you want to analyze

  • Resolution Consideration

    Be aware of different spatial resolutions across bands

  • Atmospheric Correction

    Consider atmospheric effects when working with different bands

Common Applications

  • Environmental Monitoring

    Use appropriate band combinations for specific environmental features

  • Change Detection

    Select bands that highlight the changes you want to detect

  • Feature Classification

    Use multiple band combinations for better classification accuracy