surface soil moisture;
Temperature-Vegetation Dryness Index (TVDI);
vegetation index;
MODIS;
Modified Temperature-Vegetation Dryness Index (MTVDI);
D O I:
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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 R2 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.
机构:
College of Marxism, Fujian Normal UniversityDepartment of Geography, School of Geography and Tourism, Shaanxi Normal University
ZHANG Weijuan
YE Xin
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机构:
Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection of the People's Republic of ChinaDepartment of Geography, School of Geography and Tourism, Shaanxi Normal University
机构:
Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R ChinaChinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
机构:
Institute of Agricultural Remote Sensing and Information Technology,Zhejiang UniversityInstitute of Agricultural Remote Sensing and Information Technology,Zhejiang University
ZHANG Li-Wen
SHI Jing-Jing
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机构:
Institute of Agricultural Remote Sensing and Information Technology,Zhejiang UniversityInstitute of Agricultural Remote Sensing and Information Technology,Zhejiang University
机构:
Sejong Univ, Dept Environm Energy & Geoinfomat, 209 Neungdongro, Seoul 05006, South Korea
Korea Polar Res Inst, Unit Arctic Sea Ice Predict, Incheon 21990, South KoreaSejong Univ, Dept Environm Energy & Geoinfomat, 209 Neungdongro, Seoul 05006, South Korea
Kwon, Young-Joo
Ryu, Sumin
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机构:
Sejong Univ, Dept Environm Energy & Geoinfomat, 209 Neungdongro, Seoul 05006, South KoreaSejong Univ, Dept Environm Energy & Geoinfomat, 209 Neungdongro, Seoul 05006, South Korea
Ryu, Sumin
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Cho, Jaeil
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机构:
Lee, Yang-Won
Park, No-Wook
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机构:
Inha Univ, Dept Geoinformat Engn, Incheon 22212, South KoreaSejong Univ, Dept Environm Energy & Geoinfomat, 209 Neungdongro, Seoul 05006, South Korea
Park, No-Wook
Chung, Chu-Yong
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机构:
Korea Meteorol Adm, Natl Meteorol Satellite Ctr, Jincheon Gun 27803, South KoreaSejong Univ, Dept Environm Energy & Geoinfomat, 209 Neungdongro, Seoul 05006, South Korea
Chung, Chu-Yong
Hong, Sungwook
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机构:
Sejong Univ, Dept Environm Energy & Geoinfomat, 209 Neungdongro, Seoul 05006, South KoreaSejong Univ, Dept Environm Energy & Geoinfomat, 209 Neungdongro, Seoul 05006, South Korea