基于地表温度-植被指数特征空间的区域土壤水分反演

 针对目前西北地区广泛存在的农业干旱问题,选取了新疆塔里木盆地北缘渭干河-库车河三角洲绿洲为研究区,选择云量较少的两幅TM影像,建立地表温度-植被指数特征空间。首先利用线性方程拟合了特征空间的上下边界,比较利用归一化植被指数(NDVI)建立的地表温度-植被指数特征空间Ts/NDVI和利用改进型土壤调整植被指数(MSAVI)构建的地表温度-植被指数特征空间Ts/MSAVI形状的差异,并计算得到两种温度植被干旱指数(Temperature vegetation dryness index—TVDI,分别为TVDIN和MTVDI)。对TVDI与同期野外不同深度的实测土壤重量含水量数据进行回归分析,建立TVDI估测土壤水分的经验模型并对模型进行验证。研究结果表明,TVDIN和MTVDI均能够反演表层土壤水分,其中MTVDI与土壤水分相关性比TVDIN与土壤水分相关性要高,MTVDI能够更好地反映区域土壤水分状况,是一种更有效的土壤水分监测方法,对农业干旱监测具有一定的科学依据。

Regional Soil Moisture Inversion Based on Surface Temperature and Vegetation Index Characteristic Spaces

Monitoring of soil moisture is very important in drought agricultural region in northwest China.We choose a delta oasis between the Weigan River and the Kuqa River in north rim of the Tarim Basin as study area,and two TM images with relatively less cloud shadow contamination are used to establish the surface temperature-vegetation index(Ts/VI) characteristic spaces.The lower and upper boundaries of the Ts/VI characteristic spaces are approximately fitted with linear regression functions,so that the dry and wet edges of the space can be determined.Two Ts/VI spaces were established based on the Ts/NDVI and Ts/MSAVI,and their differences of shapes were investigated.Two kinds of the Temperature-Vegetation Dryness Index(TVDI) were calculated from the Ts/NDVI and the Ts/MSAVI spaces: TVDIN and MTVDI.Regression analysis was made between TVDI and contemporaneous field measured soil moisture data,so that with the regression model,soil moisture could be assessed based on TVDI.Results showed that TVDIN and MTVDI could all be used to predict the near surface soil moisture,except that the MTVDI had a better correlation with soil moisture compared to the TVDIN,and MTVDI can effectively reflect the near surface soil moisture.Therefore,MTVDI is a useful method to monitor and assess soil moisture,and it can be used as a guide for monitoring agriculture drought.