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High-resolution space-shuttle polarimetry for farm crop classification.

W G Egan, S Israel, W R Johnson

|August 20, 2010

Summary

Polarimetry imaging effectively identified and classified farm crops like rice and soybeans, outperforming traditional photometry. This advance offers new insights into Earth observation from space.

Area of Science:

Earth observation science
Remote sensing technology
Polarimetric imaging

Background:

Traditional remote sensing methods face limitations in crop characterization.
Polarimetry offers a novel approach to analyzing surface features.

Purpose of the Study:

To evaluate the efficacy of polarimetric imaging for terrestrial crop identification.
To compare polarimetry with traditional photometry for agricultural monitoring.

Main Methods:

Acquisition of color imagery using twin Hasselblad cameras with polarization analyzers.
Digitization of imagery in red, green, and blue bands.
Analysis of percent polarization data for crop classification.

Main Results:

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Percent polarization proved superior to photometry for recognizing and characterizing various farm crops (rice, milo, cotton, soybeans) and fallow areas.
Statistical analysis of polarization data enabled unique crop classification.
Ground resolution of 80-90 m was achieved.

Conclusions:

Polarimetric imaging is a powerful tool for agricultural remote sensing.
This technique allows for detailed crop classification and atmospheric effect deduction.
Consideration of space-shuttle window distortion and viewing geometry is crucial for data interpretation.