Calibration of BRDF Based on the Field Goniometer System Using a UAV Multispectral Camera

Area of Science:

• Remote Sensing
• Geophysics
• Photogrammetry

Background:

• Bidirectional reflectance distribution function (BRDF) is crucial for surface property estimation in remote sensing.
• Laboratory BRDF measurements using goniometers are accurate but impractical for field applications.
• Developing field-deployable methods for BRDF estimation is essential for remote sensing research.

Purpose of the Study:

• To evaluate the feasibility of estimating BRDF with reasonable accuracy in the field using an unmanned aerial vehicle (UAV) equipped with a multispectral camera.
• To compare the effectiveness of different methods for measuring down-welling irradiance for reflectance calculations in a UAV-based remote sensing context.
• To determine the optimal conditions and target reflectance for accurate field-based BRDF assessment.

Main Methods:

• Acquired hemispherical reflectance data using a UAV multispectral camera, capturing images of calibrated reference tarps (CRTs) with varying reflectance.
• Measured down-welling irradiance using both a UAV-mounted sunlight sensor and a ground-based spectroradiometer with a remote cosine receptor (RCR).
• Assessed BRDF through the anisotropy factor (ANIF) derived from CRT reflectance data, analyzing the impact of irradiance measurement methods and target reflectance.

Main Results:

• Ground-based spectroradiometer measurements provided more effective irradiance data for reflectance calculations compared to UAV-mounted sensors.
• High-reflectance CRTs (21-46% reflectance) yielded ANIF and BRDF results that showed greater consistency.
• The adjacency effect significantly influenced BRDF estimations for low-reflectance targets.

Conclusions:

• Field-based BRDF estimation using UAVs is feasible, particularly with ground-based irradiance measurements.
• Accurate BRDF analysis requires target reflectance above 21-46% to mitigate adjacency effects.
• Conducting fieldwork under clear weather conditions is recommended to minimize irradiance variability and enhance measurement reliability.