The Method of Multi-Angle Remote Sensing Observation Based on Unmanned Aerial Vehicles and the Validation of BRDF

Author:

Cao Hongtao12,You Dongqin2,Ji Dabin2ORCID,Gu Xingfa23,Wen Jianguang2,Wu Jianjun1,Li Yong1,Cao Yongqiang1,Cui Tiejun14,Zhang Hu4

Affiliation:

1. Academy of Eco-Civilization Development for JING-JIN-JI Megalopolis, Tianjin Normal University, Tianjin 300387, China

2. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

3. National Engineering Laboratory for Satellite Remote Sensing Applications, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

4. School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China

Abstract

The measurement of bidirectional reflectivity for ground-based objects is a highly intricate task, with significant limitations in the capabilities of both ground-based and satellite-based observations from multiple viewpoints. In recent years, unmanned aerial vehicles (UAVs) have emerged as a novel remote sensing method, offering convenience and cost-effectiveness while enabling multi-view observations. This study devised a polygonal flight path along the hemisphere to achieve bidirectional reflectance distribution function (BRDF) measurements for large zenith angles and all azimuth angles. By employing photogrammetry’s principle of aerial triangulation, accurate observation angles were restored, and the geometric structure of “sun-object-view” was constructed. Furthermore, three BRDF models (M_Walthall, RPV, RTLSR) were compared and evaluated at the UAV scale in terms of fitting quality, shape structure, and reflectance errors to assess their inversion performance. The results demonstrated that the RPV model exhibited superior inversion performance followed, by M_Walthall; however, RTLST performed comparatively poorly. Notably, the M_Walthall model excelled in capturing smooth terrain object characteristics while RPV proved applicable to various types of rough terrain objects with multi-scale applicability for both UAVs and satellites. These methods and findings are crucial for an extensive exploration into the bidirectional reflectivity properties of ground-based objects, and provide an essential technical procedure for studying various ground-based objects’ in-plane reflection properties.

Funder

Open Fund of State Key Laboratory of Remote Sensing Science

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Automated Workflow for Pixel-Level BRDF Extraction Using UAV-Based Multispectral Images;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. Preliminary Evaluation of Angular Reflectance Downscaling Using FSDAF Spatiotemporal Fusion Model and MODIS BRDF Data;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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