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干旱是人类历史上的重大自然灾害之一,而土壤水分是干旱监测最重要的指标。利用遥感手段反演地表土壤水分,可以充分反映土壤水分的时空变化特征,适合进行大范围动态监测。研究基于Landsat TM数据,运用普适性单通道算法得到地表温度(LST,Land Surface Temperature),然后选用增强型植被指数(EVI,Enhanced Vegetation Index),构建了LST-EVI特征空间,计算出温度植被干旱指数(TVDI,Temperature-Vegetation Dryness Index)。在对实测土壤含水量数据和对应TVDI值进行回归分析的基础上,反演出2010年6月14日黄骅市自然地表20cm深度处的体积含水量。结果表明:TVDI方法在该研究区是完全可行的,拟合精度较高;研究区自然地表土壤体积含水量分布差异明显,中等含水量地区面积最大,西南和部分北部地区含水量较低,而含水量高的区域主要分布在苇洼和沿海地区。
Drought is one of the major natural disasters in human history, and soil moisture is the most important indicator of drought monitoring. Using remote sensing to retrieve surface soil moisture can fully reflect the temporal and spatial variation of soil moisture and is suitable for large-scale dynamic monitoring. Based on Landsat TM data, LST-EVI feature space was constructed by using universal single-channel algorithm to obtain LST (Land Surface Temperature) and enhanced vegetation index (EVI) TVDI (Temperature-Vegetation Dryness Index). On the basis of regression analysis of the measured soil moisture data and the corresponding TVDI values, the volumetric water content at the depth of 20cm of the natural ground surface of Huanghua City on June 14, 2010 was inverted. The results show that the TVDI method is completely feasible in this study area, and the fitting accuracy is high. The distribution of soil water content of natural surface soil in the study area is obviously different. The area of medium water content is the largest, while the moisture content of southwest and some northern areas is low. The areas with high water content are mainly distributed in Weiwa and the coastal area.