Characteristics of Soil Moisture Distributions at the Spatio-Temporal Scales Based on the Land Surface Features Using MODIS Images
2017
Kim, S., Kyungpook National University, Daegu, Republic of Korea | Shin, Y., Kyungpook National University, Daegu, Republic of Korea | Lee, T., Kyungpook National University, Daegu, Republic of Korea | Lee, S.H., Kyungpook National University, Daegu, Republic of Korea | Choi, K.S., Kyungpook National University, Daegu, Republic of Korea | Park, Y., Kongju National University, Gongju, Republic of Korea | Lim, K., Kangwon National University, Chuncheon, Republic of Korea | Kim, J., Kangwon National University, Chuncheon, Republic of Korea
In this study, we analyzed the impacts of land surface characteristics on spatially and temporally distributed soil moisture values at the Yongdam and Soyang-river dam watersheds in 2014 and 2015. The soil moisture, NDVI (Normalized Difference Vegetation Index) and temperature values at the spatio-temporal scales were estimated using satellite-based MODIS (MODerate Resolution Imaging Spectroradiometer) products. Then the Pearson correlations between soil moisture and land surface characteristics (NDVI, temperature and DEM-digital elevation model) were estimated and analyzed, respectively. Overall, the monthly soil moisture values at the time step were highly influenced by the precipitation amounts. Also, the results showed that the soil moisture has the strong correlation with DEM while the temperature was inversely correlated with the soil moisture. However the monthly correlations between NDVI and soil moisture were highly varied along the time step. These findings indicated that water loss near the land surface are highly occurred by soil and plant activities as evapotranspiration and infiltration during the no/less precipitation period. But the high precipitation amounts reduce the impacts of land surface characteristics because of saturated condition of land surface. Thus these results demonstrated that soil moisture values are highly correlated with land surface characteristics. Our findings can be useful for water resources/environmental management, agricultural drought, etc.
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