Hyperspectral BRDF based on UAV measurements can characterize optical properties of flat desert surfaces: A comprehensive comparison with laboratory and satellite data

Desert is a crucial component of terrestrial ecosystems, and its optical reflection properties are essential for understanding land surface radiative balance. Combining the hyperspectral and angular measurements has been considered as an effective method to characterize optical reflection properties of desert surfaces. However, the ground and satellite-based instruments cannot obtain both hyperspectral and angular reflectance of desert surfaces at appropriate scales due to the limitations of their measurement configurations. We employed an unmanned aerial vehicle (UAV) equipped with a spectrometer to perform hyperspectral BRDF measurements of six desert areas in Northwest China to overcome the limitations. In the comparison with those obtained from laboratory and satellite observations at the same geometries, it is found that UAV-measured hyperspectral reflectance has a spectral shape similar to that of spectra measured in laboratory settings, and UAV-measured angular reflectance shows a good match of BRDF characterization as the satellite observations in the hemispherical space. Moreover, we compared the modeled angular reflectance, which are derived from BRDF models, with measured angular reflectance of deserts at selected wavelengths from MODIS. The BRDF models using UAV-measured hyperspectral BRDF have superior performance in spectral BRDF simulation. The uncertainty analysis based on a Bayesian inversion further confirmed the reliability of the UAV data in effectively characterizing optical properties of the desert surface. These results demonstrate the robustness of UAV-based spectral and angular measurements in quantifying the hyperspectral BRDF, which provide comprehensive in-situ optical properties of desert surfaces. These data can serve as valuable validation for future studies on radiative balance of desert surfaces. • UAV equipped with a spectrometer can capture hyperspectral BRDF of desert surfaces. • Consistency with lab and satellite data confirms the validity of UAV observations. • Low uncertainty in BRDF model inversion indicates the stability of UAV measurements.

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Publication Details

Journal
Remote Sensing of Environment
Published
2026-01-05
DOI
https://doi.org/10.1016/j.rse.2025.115228
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Hyperspectral BRDF based on UAV measurements can characterize optical properties of flat desert surfaces: A comprehensive comparison with laboratory and satellite data

Xiuqing HU, Zhongqiu Sun Zhongqiu Sun, Yuechao Sheng, Lin Chen et al.
Remote Sensing of Environment
Remote Sensing in Agriculture
article

Hyperspectral BRDF based on UAV measurements can characterize optical properties of flat desert surfaces: A comprehensive comparison with laboratory and satellite data

Xiuqing HU, Zhongqiu Sun Zhongqiu Sun, Yuechao Sheng, Lin Chen, Xingwei He, Shan Lu
article en

Abstract

Desert is a crucial component of terrestrial ecosystems, and its optical reflection properties are essential for understanding land surface radiative balance. Combining the hyperspectral and angular measurements has been considered as an effective method to characterize optical reflection properties of desert surfaces. However, the ground and satellite-based instruments cannot obtain both hyperspectral and angular reflectance of desert surfaces at appropriate scales due to the limitations of their measurement configurations. We employed an unmanned aerial vehicle (UAV) equipped with a spectrometer to perform hyperspectral BRDF measurements of six desert areas in Northwest China to overcome the limitations. In the comparison with those obtained from laboratory and satellite observations at the same geometries, it is found that UAV-measured hyperspectral reflectance has a spectral shape similar to that of spectra measured in laboratory settings, and UAV-measured angular reflectance shows a good match of BRDF characterization as the satellite observations in the hemispherical space. Moreover, we compared the modeled angular reflectance, which are derived from BRDF models, with measured angular reflectance of deserts at selected wavelengths from MODIS. The BRDF models using UAV-measured hyperspectral BRDF have superior performance in spectral BRDF simulation. The uncertainty analysis based on a Bayesian inversion further confirmed the reliability of the UAV data in effectively characterizing optical properties of the desert surface. These results demonstrate the robustness of UAV-based spectral and angular measurements in quantifying the hyperspectral BRDF, which provide comprehensive in-situ optical properties of desert surfaces. These data can serve as valuable validation for future studies on radiative balance of desert surfaces. • UAV equipped with a spectrometer can capture hyperspectral BRDF of desert surfaces. • Consistency with lab and satellite data confirms the validity of UAV observations. • Low uncertainty in BRDF model inversion indicates the stability of UAV measurements.

Remote Sensing of EnvironmentVol. 334
China Meteorological Administration (CN), Northeast Normal University (CN)
Life in Land
Openalex Percentile: Top 98%
Remote Sensing in Agriculture
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