A Modified Temperature-Vegetation Dryness Index (MTVDI) for Assessment of Surface Soil Moisture Based on MODIS Data

被引:7
作者
Wang, Hao [1 ]
Li, Zongshan [2 ]
Zhang, Weijuan [3 ]
Ye, Xin [4 ]
Liu, Xianfeng [1 ]
机构
[1] Shaanxi Normal Univ, Sch Geog & Tourism, Dept Geog, Xian 710119, Peoples R China
[2] Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China
[3] Fujian Normal Univ, Coll Marxism, Fuzhou 350117, Peoples R China
[4] Minist Environm Protect Peoples Republ China, Nanjing Inst Environm Sci, Nanjing 210042, Peoples R China
基金
中国国家自然科学基金;
关键词
surface soil moisture; Temperature-Vegetation Dryness Index (TVDI); vegetation index; MODIS; Modified Temperature-Vegetation Dryness Index (MTVDI); AIR-TEMPERATURE; TRAPEZOID MODEL; LOESS PLATEAU; SATELLITE; WATER; EVAPOTRANSPIRATION; DROUGHT; COVER; TVDI; RETRIEVAL;
D O I
10.1007/s11769-022-1288-y
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation ecosystems. The temperature-vegetation dryness index based on the triangle or trapezoid method has been used widely in previous studies. However, most existing studies simply used linear regression to construct empirical models to fit the edges of the feature space. This requires extensive data from a vast study area, and may lead to subjective results. In this study, a Modified Temperature-Vegetation Dryness Index (MTVDI) was used to monitor surface soil moisture status using MODIS (Moderate-resolution Imaging Spectroradiometer) remote sensing data, in which the dry edge conditions were determined at the pixel scale based on surface energy balance. The MTVDI was validated by field measurements at 30 sites for 10 d and compared with the Temperature-Vegetation Dryness Index (TVDI). The results showed that the R-2 for MTVDI and soil moisture obviously improved (0.45 for TVDI, 0.69 for MTVDI). As for spatial changes, MTVDI can also better reflect the actual soil moisture condition than TVDI. As a result, MTVDI can be considered an effective method to monitor the spatio-temporal changes in surface soil moisture on a regional scale.
引用
收藏
页码:592 / 605
页数:14
相关论文
共 53 条
[11]   SOURCES OF VARIATION IN RADIOMETRIC SURFACE-TEMPERATURE OVER A TALLGRASS PRAIRIE [J].
FRIEDL, MA ;
DAVIS, FW .
REMOTE SENSING OF ENVIRONMENT, 1994, 48 (01) :1-17
[12]   Integrating temperature vegetation dryness index (TVDI) and regional water stress index (RWSI) for drought assessment with the aid of LANDSAT TM/ETM plus images [J].
Gao, Zhiqiang ;
Gao, Wei ;
Chang, Ni-Bin .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2011, 13 (03) :495-503
[13]   Accuracy of the Temperature-Vegetation Dryness Index using MODIS under water-limited vs. energy-limited evapotranspiration conditions [J].
Garcia, M. ;
Fernandez, N. ;
Villagarcia, L. ;
Domingo, F. ;
Puigdefabregas, J. ;
Sandholt, I. .
REMOTE SENSING OF ENVIRONMENT, 2014, 149 :100-117
[14]   Combining UAV-based hyperspectral imagery and machine learning algorithms for soil moisture content monitoring [J].
Ge, Xiangyu ;
Wang, Jingzhe ;
Ding, Jianli ;
Cao, Xiaoyi ;
Zhang, Zipeng ;
Liu, Jie ;
Li, Xiaohang .
PEERJ, 2019, 7
[15]   Estimating Soil Moisture Conditions of the Greater Changbai Mountains by Land Surface Temperature and NDVI [J].
Han, Yang ;
Wang, Yeqiao ;
Zhao, Yunsheng .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2010, 48 (06) :2509-2515
[16]   Assessment of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery and Artificial Neural Networks [J].
Hassan-Esfahani, Leila ;
Torres-Rua, Alfonso ;
Jensen, Austin ;
McKee, Mac .
REMOTE SENSING, 2015, 7 (03) :2627-2646
[17]   Cross-estimation of Soil Moisture Using Thermal Infrared Images with Different Resolutions [J].
Hsu, Wei-Ling ;
Chang, Kuan-Tsung .
SENSORS AND MATERIALS, 2019, 31 (02) :387-398
[18]   Human Activity Influences on Vegetation Cover Changes in Beijing, China, from 2000 to 2015 [J].
Jiang, Meichen ;
Tian, Shufang ;
Zheng, Zhaoju ;
Zhan, Qian ;
He, Yuexin .
REMOTE SENSING, 2017, 9 (03)
[19]   COMBINING VEGETATION INDEXES AND SURFACE-TEMPERATURE FOR LAND-COVER MAPPING AT BROAD SPATIAL SCALES [J].
LAMBIN, EF ;
EHRLICH, D .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 1995, 16 (03) :573-579
[20]  
Li HJ, 2010, J FOOD AGRIC ENVIRON, V8, P1141