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Elevation effect on TVDI-based soil moisture retrieval algorithm using MODIS LST and NDVI products

机译:使用MODIS LST和NDVI产品对TVDI基土壤湿度检索算法的高程影响

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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.
机译:一般来说,土壤水分在水循环,水资源和土地上的其他不同应用中起着重要作用。无源微波远程传感器(例如,ASCAT,AMSR-e,SMOS和SMOS)已成功地用于估算土壤水分量,而不管其低的时间和特殊分辨率如何。在这项研究中,我们提供了基于可见光和红外偏远传感器的土壤湿度检索算法的TVDI(温度 - 植被干燥指数)。使用Terra / MODIS产品如此LST(MOD11A2)和NDVI(MOD13A2)数据。为案例研究调查了包括朝鲜半岛的远东亚洲地区。特别是,我们发现依赖于土壤水分检索的升高。我们开发了一种校正方法,用于这种高程效果。比较可见光和红外条带中所提出的基于TVDI的土壤湿度算法,并验证了从微波带中的GCOM-W1 / AMSR-2观察结果估计的土壤水分含量。

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