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FlexBRDF: A Flexible BRDF Correction for Grouped Processing of Airborne Imaging Spectroscopy Flightlines
Natalie Queally1, Zhiwei Ye1, Ting Zheng1
1Department of Forest and Wildlife Ecology University of Wisconsin-Madison Madison WI USA.
Journal of Geophysical Research. Biogeosciences
|July 22, 2022
Summary
Flexible bidirectional reflectance distribution function (FlexBRDF) corrects vegetation analysis issues in airborne imaging spectroscopy. This method improves mosaicking accuracy for large datasets, enhancing vegetation mapping across diverse landscapes.
Area of Science:
- Earth and Planetary Sciences
- Remote Sensing
- Ecology
Background:
- Bidirectional reflectance distribution function (BRDF) effects complicate vegetation analysis in airborne imaging spectroscopy, particularly when merging adjacent flightlines.
- Large-scale airborne imaging initiatives necessitate flexible and automatable methods for diverse land cover types.
Purpose of the Study:
- To introduce and validate Flexible bidirectional reflectance distribution function (FlexBRDF), an enhanced kernel-based method for BRDF correction.
- To improve the accuracy and consistency of vegetation analysis in large airborne imaging spectroscopy datasets.
Main Methods:
- FlexBRDF utilizes stratified random sampling, dynamic land cover stratification via NDVI, interpolation of correction coefficients, and a reference solar zenith angle.
- The method was tested on extensive AVIRIS-Classic, AVIRIS-Next Generation, and NEON datasets across varied geographic locations and land cover types.
Main Results:
- Models built using multiple flightlines demonstrated superior performance compared to single-image models, with RMSE improving up to 2.3% and MAD by 2.5%.
- Standardizing solar zenith angles and interpolating coefficients across NDVI bins enhanced correction accuracy and minimized boundary effects.
Conclusions:
- FlexBRDF provides an open-source, automatable solution for BRDF correction in large airborne imaging spectroscopy datasets.
- This method is crucial for the calibration and validation of future spaceborne imaging spectroscopy missions, especially for diverse land cover analysis.
