Generally, soil moisture plays an important role in water cycle, water resources and other diverse applications over land.
Passive microwave remote sensors (e.g., ASCAT, AMSR-E, SMOS, and SMAP) have successfully used for estimating
the amount of soil moisture irrespective of their low temporal and special resolutions. In this study, we present a TVDI
(temperature-vegetation dryness index)-based soil moisture retrieval algorithm based on visible and infrared remote
sensors. The TERRA/MODIS products such LST (MOD11A2) and NDVI (MOD13A2) data were used. Far-East Asia
area including the Korean peninsula were investigated for the case study. In particular, we found the elevation
dependence on the soil moisture retrieval. We developed a correction method for this elevation effect. The proposed
TVDI-based soil moisture algorithm in visible and infrared bands were compared and validated with soil moisture
contents estimated from GCOM-W1/AMSR-2 observations in microwave bands.
Young-Joo Kwon, Hyunju Ban, and Sungwook Hong, "Elevation effect on TVDI-based soil moisture retrieval algorithm using MODIS LST and NDVI products," Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 104210U (Presented at SPIE Remote Sensing: September 13, 2017; Published: 2 November 2017); https://doi.org/10.1117/12.2278020.
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