Soil Moisture Retrieval Based on Landsat8 OLI Image Data in the Yanhe River Basin

doi:10.11733/j.issn.1007-0435.2018.05.011

Acta Agrestia Sinica ›› 2018, Vol. 26 ›› Issue (5): 1109-1117.DOI: 10.11733/j.issn.1007-0435.2018.05.011

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Soil Moisture Retrieval Based on Landsat8 OLI Image Data in the Yanhe River Basin

YAO Jing¹, XUE Chao-yu², JIAO Feng^1,3

1. Institute of Soil and Water Conservation, Northwest A & F University, Yangling, Shaanxi Province 712100, China;
2. China Sciences Mapuniverse Technology Co., Ltd, Beijing 100000, China;
3. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi Province 712100, China

Received:2018-04-17 Revised:2018-08-27 Online:2018-10-15 Published:2018-11-06

基于Landsat8 OLI遥感影像的延河流域土壤水分反演研究

姚静¹, 薛超玉², 焦峰^1,3

1. 西北农林科技大学水土保持研究所, 陕西杨凌 712100;
2. 中科宇图科技股份有限公司, 北京 100000;
3. 中国科学院水利部水土保持研究所, 陕西杨凌 712100

通讯作者: 焦峰
作者简介:姚静(1993-),女,陕西咸阳人,硕士研究生,主要从事GIS应用、水土保持与环境效应评价研究,E-mail:964920749@qq.com
基金资助:
国家重点研发计划项目（2016YFA0600801）；科技基础性工作专项（2014FY210130）资助

Abstract

Abstract: In the Yanhe River basin,fragile ecological environment and serious soil erosion,remote sensing inversion of soil moisture is of great significance to soil moisture dynamic monitoring and ecological restoration in this area. In order to grasp the changes and distribution of soil moisture in the Yanhe River basin,the Ts-NDVI construct feature space was established by using Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) based on the Landsat8 OLI data,and analyzed the spatiotemporal change of soil moisture. The soil moisture inversion regression models of five soil depth,including the 0~20 cm,20~40 cm,40~60 cm,60~80 cm and 80~100 cm,were established using the TVDI model and combining with soil moisture data measured in 148 field samples to construct the spatial variation characteristics of five soil depth's soil moisture. The other 30 field samples were used to verify the accuracy of the inversion results. The results showed that the distribution of slight drought and drought is wide in Yanhe River Basin,and more distributed in the northwest region. The overall TVDI trend of surface coverage types is:low coverage > middle coverage > high coverage. The measured soil moisture at each soil depth has a good negative correlation with the TVDI inversion value. The correlation between soil moisture at 20~40 cm depth and the regression model of TVDI is strong. It shows that the TVDI index method is suitable to inversion of soil moisture in Yanhe River Basin. TVDI could effectively reflect the variation in soil moisture of 20~40 cm depths,but cannot meet the requirements of the extraction of soil moisture in deeper soil.

Key words: Remote sensing retrieval, Temperature vegetation drought index, Soil moisture, Yanhe River basin

摘要： 在生态环境脆弱、水土流失严重的延河流域，土壤水分的遥感反演对该地区的土壤水分动态监测和生态恢复具有重要的意义。为掌握延河流域的土壤水分变化和分布状况，利用Landsat8 OLI影像数据获取的归一化植被指数（NDVI）和陆地表面温度（Ts），构建Ts-NDVI特征空间，分析土壤水分空间分布变化。结合野外148个实测土壤水分数据，建立0~20 cm，20~40 cm，40~60 cm，60~80 cm和80~100 cm深度的土壤水分遥感反演回归模型，对比分析了5个深度土壤水分的空间变化特征，利用剩余30个样点数据进行精度验证。结果表明：延河流域微旱和干旱的分布范围广且多分布于西北地区，各地表覆盖类型的TVDI总体趋势为：低覆盖度 > 中覆盖度 > 高覆盖度。各土层深度的实测的土壤水分与TVDI的反演值具有较好的负相关性，其中20~40 cm土层的土壤水分与TVDI反演值的相关性较强，表明TVDI指数法适用于延河流域土壤水分反演。TVDI能更稳定反映和指示20~40 cm土层的土壤水分状况，但对于提取更深土层深度的土壤水分信息不能满足精度要求。

关键词: 遥感反演, 温度植被干旱指数(TVDI), 土壤水分, 延河流域

CLC Number:

S153

YAO Jing, XUE Chao-yu, JIAO Feng. Soil Moisture Retrieval Based on Landsat8 OLI Image Data in the Yanhe River Basin[J]. Acta Agrestia Sinica, 2018, 26(5): 1109-1117.

姚静, 薛超玉, 焦峰. 基于Landsat8 OLI遥感影像的延河流域土壤水分反演研究[J]. 草地学报, 2018, 26(5): 1109-1117.

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Soil Moisture Retrieval Based on Landsat8 OLI Image Data in the Yanhe River Basin

基于Landsat8 OLI遥感影像的延河流域土壤水分反演研究

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