![]() New Radiometric Calibration Site Located at Gobabeb, Namib Desert. In Proceedings of the Remote Sensing and Photogrammetry Society Conference: “Measuring Change in the Earth System”, Exeter, UK, 15–17 September 2008 Remote Sensing & Photogrammetry Society: NottinghamCity, UK, 2008 pp. The NPL Gonio RAdiometric Spectrometer System (GRASS). In Proceedings of the 2006 IEEE International Symposium on Geoscience and Remote Sensing, Denver, CO, USA, 31 July–4 August 2006 IEEE: New York, NY, USA, 2006 pp. Design and Testing a New Instrument to Measure the Angular Reflectance of Terrestrial Surfaces. Examining View Angle Effects on Leaf N Estimation in Wheat Using Field Reflectance Spectroscopy. Temporal Variation in Surface Bidirectional Reflectance of the Railroad Valley Vicarious Calibration Test Site in Nevada. Bi-Directional Reflectance Factor Determination of the Railroad Valley Playa. Ground Measurements of Surface BRF and HDRF Using PARABOLA III. Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer. ![]() Reflectance Processing of Remote Sensing Spectroradiometer Data. A Low-Cost Field and Laboratory Goniometer System for Estimating Hyperspectral Bidirectional Reflectance. In Proceedings of the ISPRS Working Group VII/1 Workshop ISPMSRS’07: “Physical Measurements and Signatures in Remote Sensing”, Davos, Switzerland, 12–14 March 2007 ISPRS: Hannover, Germany, 2007 Volume 6. Dual field-of-view goniometer system FIGOS. Reflectance Quantities in Optical Remote Sensing-Definitions and Case Studies. ![]() A Field Goniometer System (FIGOS) for Acquisition of Hyperspectral BRDF Data. Bidirectional Reflectance Distribution Function (BRDF) Characteristics of Smooth Cordgrass (Spartina Alterniflora) Obtained Using a Sandmeier Field Goniometer. The authors declare no conflict of interest. The Reflectance, Bidirectional Reflectance Distribution Function (BRDF) Calculation, and Anisotropy Factor (ANIF) Calculated from P4 Multispectral(P4M) The accuracy of the BRDF was calculated by using 44 check orthophotos. Based on 151 orthophotos, the BRDF was calculated for each flight course and band to calculate the isometric ( k i s o ), geometric ( k g e o), and volumetric k v o l factor. 2 with a Spectralon WR, while the anisotropy factor (ANIF) was calculated using a nadir image (VZA and VAA = 0°) in the center of each hemispheric and reflectance based on the orthophoto reflectance of each VZA and VAA for BRDF fitting. A CRT was calculated using the data of ASD No. In addition, we attached a subset image (512 × 512 pixels) in the center of the corrected vignette orthophoto for BRDF model fitting. The digital elevation model (DEM) and orthophotos were produced based on the image using Metashape. The interior, relative, and absolute orientation was performed using the GCP and RTK of the UAV global navigation satellite system (GNSS). In the study, calculations were conducted using Metashape with the ground control point (GCP). In addition, weather affects irradiance, so it is more effective to conduct fieldwork in clear weather. 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. Furthermore, the high reflectance CRTs, ANIF, and BRDF had similar results. 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. The BRDF was assessed through the anisotropy factor (ANIF) of the CRT reflectance derived from the collected data. 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 ground targets were four calibrated reference tarps (CRTs) of different reflectance, and the UAV was operated five times. Hemispherical reflectance was created from images taken using an UAV multispectral camera. ![]() ![]() 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. 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 bidirectional reflectance distribution function (BRDF) is important for estimating the physical properties of a surface in remote sensing. ![]()
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