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Resolution of Sensors in Remote Sensing


Spatial Resolution 🗺️

  • Definition: The smallest size of an object on the ground that a sensor can detect.

  • Measured as: The size of a pixel on the ground (in meters).

  • Example:

    • Landsat → 30 m (each pixel = 30 × 30 m on Earth).

    • WorldView-3 → 0.31 m (very detailed, you can see cars).

  • Fact: Higher spatial resolution = finer details, but smaller coverage.

Spectral Resolution 🌈

  • Definition: The ability of a sensor to capture information in different parts (bands) of the electromagnetic spectrum.

  • Measured as: The number and width of spectral bands.

  • Types:

    • Panchromatic (1 broad band, e.g., black & white image).

    • Multispectral (several broad bands, e.g., Landsat with 7–13 bands).

    • Hyperspectral (hundreds of very narrow bands, e.g., AVIRIS).

  • Fact: Higher spectral resolution = better identification of materials (e.g., minerals, vegetation types).

Radiometric Resolution 📊

  • Definition: The ability of a sensor to record subtle differences in energy (brightness levels).

  • Measured as: The number of digital bits.

    • 8-bit → 2⁸ = 256 brightness levels

    • 10-bit → 1024 levels

    • 12-bit → 4096 levels

  • Example:

    • Landsat TM → 8-bit (256 levels)

    • Sentinel-2 → 12-bit (4096 levels, more sensitivity)

  • Fact: Higher radiometric resolution = better detection of slight differences (e.g., healthy vs. stressed vegetation).

Temporal Resolution ⏳

  • Definition: The frequency at which a sensor revisits and captures data for the same location.

  • Measured as: Revisit time (in days or hours).

  • Examples:

    • Landsat → 16 days

    • Sentinel-2 → 5 days

    • MODIS → 1–2 days

  • Fact: Higher temporal resolution = better for monitoring fast-changing phenomena (floods, crops, weather).


Multi-Concept (Integration of Resolutions)

In reality, no single sensor excels in all resolutions. So, remote sensing often combines them:

  • High Spatial + Low Temporal: WorldView → very detailed but not frequent.

  • Moderate Spatial + High Temporal: MODIS → frequent but coarse (global monitoring).

  • Balanced: Sentinel-2 → medium detail (10 m) and good revisit (5 days).

👉 This combination is called the Multi-Resolution Concept: using data from different sensors together to get the best results.


  • Spatial = detail of objects

  • Spectral = colors/wavelengths captured

  • Radiometric = sensitivity to brightness levels

  • Temporal = time gap between observations

  • Multi-concept = integrating different resolutions for better monitoring


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