气候变化领域集成服务门户(CCPortal): Modeling the directional anisotropy of fine-scale TIR emissions over tree and crop canopies based on UAV measurements

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DOI	10.1016/j.rse.2020.112150
	Modeling the directional anisotropy of fine-scale TIR emissions over tree and crop canopies based on UAV measurements
	Bian Z.; Roujean J.-L.; Cao B.; Du Y.; Li H.; Gamet P.; Fang J.; Xiao Q.; Liu Q.
发表日期	2021
ISSN	00344257
卷号	252
英文摘要	Land surface temperature (LST) is a vital parameter for the achievement of the surface energy budget and in thorough investigations of water cycle processes. Lightweight thermal infrared (TIR) sensors onboard unmanned aerial vehicles (UAVs) are rapidly becoming key instruments for extracting high-resolution LSTs given the flexibility they offer in capturing different scales. With this expansion, there has been increasing concern regarding the growing demand to obtain a mapping of normalized LST given the directional anisotropy (DA) of surface fine-scale emissions. To date, this topic suffers from a lack of deep analysis and practical solutions for characterizing the DA of fine-scale TIR data from UAV measurements over tree and crop canopies. In this paper, the first objective was to understand the pattern of brightness temperatures (BTs) DAs at a high spatial resolution by using UAV-based multiangle observations and three-dimensional (3D) radiative transfer model simulations. This study highlighted the need for first performing an angular normalization of the BTs of fine-scale pixels prior to any application, as these were easily affected by adjacent pixels and displayed broad spatial variability from 0.5 °C to 5.0 °C due to 3D occlusion. The second objective of the present study was to appraise the reliability of a modified kernel-driven model, in comparison to the model from which it was derived, with an additional kernel designed to mimic the adjacency effect, plus, a quadratic function used to simplify the estimate of the directional emissivity kernel. The root mean square error of the best fit between the measured UAV dataset and the modified kernel-driven model was approximately 0.65 °C, which proves its efficiency since the DA indexes of the BTs were about 1.40 °C. This outlined the role of the model to normalize from directional effects the camera image pixels and thereby deliver fine-scale BTs. In addition, results from LESS simulations also demonstrated the good performance of the modified kernel-driven model for simulating the DAs of thermal emissions for both tree and row-planted scenes. Index Terms—Land surface temperature, UAV, directional anisotropy, high spatial resolution. © 2020 Elsevier Inc.
语种	英语
scopus关键词	Anisotropy; Antennas; Atmospheric temperature; Budget control; Crops; Forestry; Image resolution; Mean square error; Pixels; Radiative transfer; Surface measurement; Surface properties; Trees (mathematics); Unmanned aerial vehicles (UAV); Brightness temperatures; Directional emissivity; High spatial resolution; Multi-angle observations; Practical solutions; Root mean square errors; Surface energy budget; Threedimensional (3D) radiative transfers; Land surface temperature; brightness temperature; energy budget; hydrological cycle; land surface; parameterization; pixel; spatial resolution; surface energy; surface temperature; three-dimensional modeling; unmanned vehicle
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179062
作者单位	State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China; CESBIO - Centre d'Etudes Spatiales de la BIOsphère, CESBIO UMR 5126, Toulouse, 31401, France; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
推荐引用方式 GB/T 7714	Bian Z.,Roujean J.-L.,Cao B.,et al. Modeling the directional anisotropy of fine-scale TIR emissions over tree and crop canopies based on UAV measurements[J],2021,252.
APA	Bian Z..,Roujean J.-L..,Cao B..,Du Y..,Li H..,...&Liu Q..(2021).Modeling the directional anisotropy of fine-scale TIR emissions over tree and crop canopies based on UAV measurements.Remote Sensing of Environment,252.
MLA	Bian Z.,et al."Modeling the directional anisotropy of fine-scale TIR emissions over tree and crop canopies based on UAV measurements".Remote Sensing of Environment 252(2021).