Soil Moisture Monitoring Based on Land Surface Temperature-Vegetation Index Space Derived from MODIS Data

Soil moisture has been considered as one of the main indicators that are widely used in the fields of hydrology, climate, ecology and others. The land surface temperature-vegetation index （LST-VI） space has comprehensive information of the sensor from the visible to thermal infrared band and can well reflect the regional soil moisture conditions. In this study, 9 pairs of moderate-resolution imaging spectroradiometer （MODIS） products （MOD09A1 and MODllA2）, covering 5 provinces in Southwest China, were chosen to construct the LST-VI space, and then the spatial distribution of soil moisture in 5 provinces of Southwest China was monitored by the temperature vegetation dryness index （TVDI）. Three LST-VI spaces were constructed by normalized difference vegetation index （NDVI）, enhanced vegetation index （EVI）, and modified soil-adjusted vegetation index （MSAVI）, respectively. The correlations between the soil moisture data from 98 sites and the 3 TVDIs calculated by LST-NDVI, LST-EVI and LST-MSAVI, respectively, were analyzed. The results showed that TVDI was a useful parameter for soil surface moisture conditions. The TVDI calculated from the LST-EVI space （TVDIE） revealed a better correlation with soil moisture than those calculated from the LST-NDVI and LST-MSAVI spaces. From the different stages of the TVDIE space, it is concluded that TVDIE can effectively show the temporal and spatial differences of soil moisture, and is an effective approach to monitor soil moisture condition.

基于MSAVI-WI特征空间的新疆渭干河-库车河流域绿洲土壤盐渍化研究

土壤盐渍化是造成干旱区土地荒漠化及生态恶化的重要原因,及时获取大尺度高精度土壤盐渍信息是防治工作的基础。选取新疆塔里木盆地北缘渭干河—库车河流域三角洲绿洲为研究区,利用Lansat-TM数据与野外实测数据分析盐渍化土壤与修改型土壤调整植被指数(MSAVI)、湿度指数(WI)之间的关系,在此基础上提出了MSAVI-WI特征空间概念,构建了土壤盐渍化遥感监测指数模型(MWI)。结果表明:MWI与土壤表层含盐量相关性较高,其相关性为0.844,精度高于土壤盐渍监测常用的盐分指数与实测数据的相关性。MWI能较好的反映盐渍化土壤地表植被及土壤水分的组合变化,具有明确的生物物理意义,并且特征参量简单,理论上易于理解,实践上易于实现,MWI模型的构建有利于干旱区大尺度土壤盐渍化定量监测与评价工作的开展。

基于MSAVI-SI特征空间的玛纳斯河流域灌区土壤盐渍化研究

玛纳斯河灌区是新疆重要的农业绿洲之一,其发展受土壤盐渍化制约,土壤盐渍化信息获取成为首要问题。以Landsat-OLI卫星影像和野外调查数据为基础,对修改型土壤调整植被指数（MSAVI）和盐分指数（SI）之间的关系进行了综合分析,并提出了MSAVI-SI特征空间概念,进而构建了盐渍化遥感信息提取指数模型（MSI）。结果表明：1不同程度盐渍化类型MSI平均值差异特征明显,其差值在0.35~0.43,因此,MSI指数可以作为盐渍化信息快速提取的指标。2灌区土壤受盐渍化侵扰严重,尤其从下游农业生产区到古尔班通古特沙漠过渡的生态脆弱区,受地下水影响明显的中段,土壤盐渍化仍是土地退化的重要原因。本研究对土壤盐渍化遥感监测和管理,以及区域环境保护具有重要意义。