Temperature-Soil Moisture Dryness Index for Remote Sensing of Surface Soil Moisture Assessment

Mai Son Le, Yuei An Liou

研究成果: 雜誌貢獻期刊論文同行評審

摘要

Surface water availability and its temperature are fundamental factors in describing the characteristics of land surface properties. In this study, a new temperature-soil moisture dryness index (TMDI) to quantify surface soil moisture (SSM) is proposed. It is defined as a function of land surface temperature variation and its relationship to surface water availability. The spatial pattern of TMDI has been analyzed over two time points of dry and rainy seasons for the plain area of Tainan, Taiwan, using Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) image acquired on January 20 and October 19, 2014. The effectiveness of TMDI in reflecting the SSM status was then evaluated by the results of the simulated evapotranspiration (ET) and verified by the near-surface air temperature ( T_{\text {air}} ) and humidity (RHair) measured by the ground-based weather stations. The results indicated that TMDI exhibited a significantly negative correlation with the simulated ET and positive correlation with in situ measured T_{\text {air}} from seven stations ( r = - 0.95 and -0.9 for simulated ET and r = 0.94 and 0.78 for T_{\text {air}} corresponding to January 20 and October 19, respectively). We further compared the performance of the TMDI with the existing remotely sensed dryness assessment methods, including temperature vegetation dryness index (TVDI) and Surface Energy Balance Algorithm for Land (SEBAL) model. The advantages of the TMDI in reflecting SSM, especially in the nonvegetation area, are clearly demonstrated. It is concluded that the TMDI is a reliable indicator for determining the SSM status with a large degree of freedom for further applications since it does not require any other ground-based measurements.

原文???core.languages.en_GB???
期刊IEEE Geoscience and Remote Sensing Letters
19
DOIs
出版狀態已出版 - 2022

指紋

深入研究「Temperature-Soil Moisture Dryness Index for Remote Sensing of Surface Soil Moisture Assessment」主題。共同形成了獨特的指紋。

引用此