基于地表温度日较差-植被覆盖度特征空间的土壤含水量反演方法

doi:10.7523/j.issn.2095-6134.2018.06.008

中国科学院大学学报 ›› 2018, Vol. 35 ›› Issue (6): 771-781.DOI: 10.7523/j.issn.2095-6134.2018.06.008

基于地表温度日较差-植被覆盖度特征空间的土壤含水量反演方法

茹晨^1,2, 段四波², 姜小光¹, 冷佩², 高懋芳², 霍红元², 李召良²

1 中国科学院大学资源与环境学院, 北京 100049;
2 中国农业科学院农业资源与农业区划研究所, 北京 100081

收稿日期:2017-07-31 修回日期:2017-10-31 发布日期:2018-11-15
通讯作者: 段四波
基金资助:
国家自然科学基金（41571352，41231170，41471297）资助

A method for surface soil moisture estimation based on the DTR-FVC space

RU Chen^1,2, DUAN Sibo², JIANG Xiaoguang¹, LENG Pei², GAO Maofang², HUO Hongyuan², LI Zhaoliang²

1 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China;
2 Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Received:2017-07-31 Revised:2017-10-31 Published:2018-11-15

摘要/Abstract

摘要： 土壤含水量是气候、水文和生态等研究的重要参数。地表温度-植被指数特征空间法是遥感监测土壤含水量的常用方法。以欧洲伊比利亚半岛为研究区，使用MSG-SEVIRI （Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager）晴空数据，构建地表温度日较差-植被覆盖度特征空间。在此特征空间上，结合研究区土壤质地数据，建立土壤含水量反演模型反演土壤体积含水量。利用西班牙REMEDHUS （REd de MEDiciòn de la HUmedad del Suelo）土壤含水量观测网络的实测数据对反演结果进行验证，均方根误差均在0.05m³/m³以内，具有较高的精度。与常用的地表温度-植被覆盖度特征空间的结果对比证明，以地表温度日较差替代地表温度，能够减小地表温度反演误差导致的土壤含水量估算误差，从而提高土壤含水量反演精度。

关键词: 土壤含水量, MSG数据, 地表温度日较差, 植被覆盖度, 三角形特征空间

Abstract: Soil moisture is a key parameter for the studies of climatology, hydrology, and ecology. The commonly used remotely sensed approach is based on the land surface temperature-vegetation index (LST-VI) space. With the Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) data, the study is conducted over Ibérian Peninsula. In this study, we use the diurnal temperature range (DTR), instead of surface temperature, to compose a diurnal temperature range-fraction vegetation coverage (DTR-FVC) space. Based on the DTR-FVC space, the soil moisture retrieval model is established to estimate soil moisture with the soil texture data. The results are validated by in situ measurements from 19 meteorological stations in Spain, and the root mean square error (RMSE) is about 0.05m³/m³. Compared with the LST-VI space, the DTR-FVC space reduces the retrieval error caused by the uncertainty of instantaneous land surface temperature, and thus the accuracy of soil moisture is improved.

Key words: soil moisture, MSG data, DTR, FVC, triangle space

中图分类号:

TP722.5

茹晨, 段四波, 姜小光, 冷佩, 高懋芳, 霍红元, 李召良. 基于地表温度日较差-植被覆盖度特征空间的土壤含水量反演方法[J]. 中国科学院大学学报, 2018, 35(6): 771-781.

RU Chen, DUAN Sibo, JIANG Xiaoguang, LENG Pei, GAO Maofang, HUO Hongyuan, LI Zhaoliang. A method for surface soil moisture estimation based on the DTR-FVC space[J]. , 2018, 35(6): 771-781.

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基于地表温度日较差-植被覆盖度特征空间的土壤含水量反演方法

A method for surface soil moisture estimation based on the DTR-FVC space

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