Landsat Missions

Solar Illumination and Sensor Viewing Angle Coefficient Files

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Landsat Collection 1 Level-1 data products include an Angle Coefficient File (“_ANG.txt”).  This file provides sensor viewing angle model coefficients that can be used to compute the solar and sensor viewing angles for every pixel.  Most applications can continue to use the standard products, but this new information provides opportunities to investigate higher-level science products.

Angle bands allow users to better understand how the sensor viewing geometry and solar illumination geometry affects the object being sensed by the imaging instrument. Angle bands can also be used in science algorithms to produce more accurate results over the current practice of using the solar illumination and sensor viewing angles at the center of Landsat scenes. The solar zenith angle can be used in combination with rescaling factors from the Level-1 metadata to calculate per-pixel top-of-atmosphere (TOA) reflectance. This can be important for analyzing effects such as the Bidirectional Reflectance Distribution Function (BRDF).

The Landsat Angles Creation Tools listed below allow users to create angle bands in a LINUX environment.  Future plans include implementing an end-user web-based tool. Until then, users are responsible for creating usable angle bands.

Landsat 4-5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) - .tgz (100 KB)  README - .txt (4 KB)
Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) - .tgz (100 KB) README - .txt (2 KB)

 

Technical Documentation

Landsat TM and ETM+ Solar and View Angle Generation Algorithm (coming soon)
Landsat 8 Solar and View Angle Generation Algorithm (coming soon)

 

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Landsat represents the world's longest continuously acquired collection of space-based moderate-resolution land remote sensing data. Four decades of imagery provides a unique resource for those who work in agriculture, geology, forestry, regional planning, education, mapping, and global change research. Landsat images are also invaluable for emergency response and disaster relief.

 

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