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Separate retrievals of soil and vegetation temperatures using two methods

文献类型:期刊论文

作者Jiang, Yazhen; Meng, Xiangyu; Tang, Ronglin; Li, Zhao-Liang; Bian, Zunjian; Liu, Jingxiu
刊名INTERNATIONAL JOURNAL OF REMOTE SENSING
出版日期2023-07-23
卷号N/A
ISSN号0143-1161
关键词Evapotranspiration Soil and vegetation temperatures Separate retrieval MODIS Sentinel-3 >
DOI10.1080/01431161.2023.2234096
产权排序1
文献子类Article ; Early Access
英文摘要Soil temperature (Ts) and vegetation temperature (Tv) provide significant information for various practical applications such as evapotranspiration estimation, water requirement analysis for vegetation, and drought monitoring during the crop growth. In this study, we estimated Ts and Tv with a land surface temperature (LST)-vegetation index (VI) trapezoidal space-based method (hereafter abbreviated as the trapezoidal method) and a dual-angle algorithm in which the estimation equations for Ts and Tv were established with thermal infrared observations from two angles and solved to using the least squares method. The Ts and Tv estimations were conducted using Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-3 data from the Google Earth Engine platform, together with auxiliary meteorological data from eight sites with various land cover types in the Heihe River Basin in 2019, and compared with corresponding in-situ measurements and temperatures from Landsat. The results showed that (1) both estimation methods outperformed the Ts retrievals compared to those of Tv; (2) the trapezoidal method overall had a similar but slightly better performance compared to the dual-angle algorithm, with the root mean square error for Ts retrievals of 3.7 K and 5.7 K, and for Tv retrievals of 6.5 K and 7.2 K, respectively, in comparison with temperatures from Landsat; (3) the trapezoidal method had higher accuracy over sites with grassland, desert, or meadow for Ts retrieval and sites with forests for Tv retrieval. This study provides advice about the method for Ts and Tv estimations and might be useful for rational utilization and more accurate monitoring of soil and vegetation.
WOS关键词COMPONENT TEMPERATURES ; MODEL ; SATELLITE ; FLUX ; CROP
WOS研究方向Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者TAYLOR & FRANCIS LTD
WOS记录号WOS:001032234900001
源URL[http://ir.igsnrr.ac.cn/handle/311030/194546]  
专题资源与环境信息系统国家重点实验室_外文论文
作者单位1.Institute of Geographic Sciences & Natural Resources Research, CAS
2.Institute of Agricultural Resources & Regional Planning, CAAS
3.Chinese Academy of Agricultural Sciences
4.Ministry of Agriculture & Rural Affairs
5.China University of Geosciences
6.University of Chinese Academy of Sciences, CAS
7.Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Jiang, Yazhen,Meng, Xiangyu,Tang, Ronglin,et al. Separate retrievals of soil and vegetation temperatures using two methods[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2023,N/A.
APA Jiang, Yazhen,Meng, Xiangyu,Tang, Ronglin,Li, Zhao-Liang,Bian, Zunjian,&Liu, Jingxiu.(2023).Separate retrievals of soil and vegetation temperatures using two methods.INTERNATIONAL JOURNAL OF REMOTE SENSING,N/A.
MLA Jiang, Yazhen,et al."Separate retrievals of soil and vegetation temperatures using two methods".INTERNATIONAL JOURNAL OF REMOTE SENSING N/A(2023).

入库方式: OAI收割

来源:地理科学与资源研究所

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