SWCTI: Surface Water Content Temperature Index for Assessment of Surface Soil Moisture Status

The vegetation supply water index (VSWI = NDVI/LST) is an effective metric estimating soil moisture in areas with moderate to dense vegetation cover. However, the normalized difference vegetation index (NDVI) exhibits a long water stress lag and the land surface temperature (LST), sensitive to water...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2018-08, Vol.18 (9), p.2875
Main Authors: Hong, Zhiming, Zhang, Wen, Yu, Changhui, Zhang, Dongying, Li, Linyi, Meng, Lingkui
Format: Article
Language:English
Subjects:
Drought
Land surface temperature
Methods
Moderate Resolution Imaging Spectroradiometer (MODIS)
Moisture content
Monitoring
Normalized difference vegetative index
Photonics
Remote sensing
Sandy loam
Soil moisture
Surface temperature
Surface water
SWCI
SWCTI
Vegetation
VSWI
Water shortages
Water supply
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Summary:The vegetation supply water index (VSWI = NDVI/LST) is an effective metric estimating soil moisture in areas with moderate to dense vegetation cover. However, the normalized difference vegetation index (NDVI) exhibits a long water stress lag and the land surface temperature (LST), sensitive to water stress, does not contribute considerably to surface soil moisture monitoring due to the constraints of the mathematical characteristics of VSWI: LST influences VSWI less when LST value is sufficiently high. This paper mathematically analyzes the characteristics of VSWI and proposes a new operational dryness index (surface water content temperature index, SWCTI) for the assessment of surface soil moisture status. SWCTI uses the surface water content index (SWCI), which provides a more accurate estimation of surface soil moisture than that of NDVI, as the numerator and the modified surface temperature, which has a greater influence on SWCTI than that of LST, as the denominator. The validation work includes comparison of SWCTI with in situ soil moisture and other remote sensing indices. The results show SWCTI demonstrates the highest correlation with in situ soil moisture; the highest correlation R = 0.801 is found between SWCTI and the 0⁻5 cm soil moisture in a sandy loam. SWCTI is a functional and effective method that has a great potential in surface soil moisture monitoring.
ISSN:1424-8220
1424-8220
DOI:10.3390/s18092875