2022SensorsOpen access

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

Minji Kim, Cheonggil Jin, Sejin Lee, Kyoung-Min Kim, Joongbin Lim, Chuluong Choi

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Abstract

The bidirectional reflectance distribution function (BRDF) is important for estimating the physical properties of a surface in remote sensing. In the laboratory, the BRDF can be estimated quickly and accurately using a goniometer, but it is very difficult to operate in the field. The purpose of this study was to evaluate whether estimating the BRDF with reasonable accuracy using an unmanned aerial vehicle (UAV) with a multispectral camera is possible in the field. Hemispherical reflectance was created from images taken using an UAV multispectral camera. The ground targets were four calibrated reference tarps (CRTs) of different reflectance, and the UAV was operated five times. Down-welling irradiance for reflectance calculation was measured in two ways: a sunlight sensor was mounted on a UAV, and a spectroradiometer with a remote cosine receptor (RCR) was installed on the ground. The BRDF was assessed through the anisotropy factor (ANIF) of the CRT reflectance derived from the collected data. As a result, the irradiance data for the reflectance calculation were more effective from the spectroradiometer with RCR on the ground than from the sunlight sensor mounted on an UAV. Furthermore, the high reflectance CRTs, ANIF, and BRDF had similar results. Therefore, when analyzing the BRDF, the effectiveness can be guaranteed when the reflectance of the target is over 21~46%, because a low reflectance tendency differs due to the adjacency effect. In addition, weather affects irradiance, so it is more effective to conduct fieldwork in clear weather.

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The bidirectional reflectance distribution function (BRDF) is important for estimating the physical properties of a surface in remote sensing. In the laboratory, the BRDF can be estimated quickly and accurately using a goniometer, but it is very difficult to operate in the field. The purpose of this study was to evaluate whether estimating the BRDF with reasonable accuracy using an unmanned aerial vehicle (UAV) with a multispectral camera is possible in the field. Hemispherical reflectance was created from images taken using an UAV multispectral camera. The ground targets were four calibrated reference tarps (CRTs) of different reflectance, and the UAV was operated five times. Down-welling irradiance for reflectance calculation was measured in two ways: a sunlight sensor was mounted on a UAV, and a spectroradiometer with a remote cosine receptor (RCR) was installed on the ground. The BRDF was assessed through the anisotropy factor (ANIF) of the CRT reflectance derived from the collected data. As a result, the irradiance data for the reflectance calculation were more effective from the spectroradiometer with RCR on the ground than from the sunlight sensor mounted on an UAV. Furthermore, the high reflectance CRTs, ANIF, and BRDF had similar results. Therefore, when analyzing the BRDF, the effectiveness can be guaranteed when the reflectance of the target is over 21~46%, because a low reflectance tendency differs due to the adjacency effect. In addition, weather affects irradiance, so it is more effective to conduct fieldwork in clear weather.

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Available abstract

The bidirectional reflectance distribution function (BRDF) is important for estimating the physical properties of a surface in remote sensing. In the laboratory, the BRDF can be estimated quickly and accurately using a goniometer, but it is very difficult to operate in the field. The purpose of this study was to evaluate whether estimating the BRDF with reasonable accuracy using an unmanned aerial vehicle (UAV) with a multispectral camera is possible in the field. Hemispherical reflectance was created from images taken using an UAV multispectral camera. The ground targets were four calibrated reference tarps (CRTs) of different reflectance, and the UAV was operated five times. Down-welling irradiance for reflectance calculation was measured in two ways: a sunlight sensor was mounted on a UAV, and a spectroradiometer with a remote cosine receptor (RCR) was installed on the ground. The BRDF was assessed through the anisotropy factor (ANIF) of the CRT reflectance derived from the collected data. As a result, the irradiance data for the reflectance calculation were more effective from the spectroradiometer with RCR on the ground than from the sunlight sensor mounted on an UAV. Furthermore, the high reflectance CRTs, ANIF, and BRDF had similar results. Therefore, when analyzing the BRDF, the effectiveness can be guaranteed when the reflectance of the target is over 21~46%, because a low reflectance tendency differs due to the adjacency effect. In addition, weather affects irradiance, so it is more effective to conduct fieldwork in clear weather.

Key concepts: Bidirectional reflectance distribution function, Spectroradiometer, Remote sensing, Multispectral image, Goniometer, Irradiance, Environmental science, Calibration

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