中文摘要：

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。

英文摘要：

Soil salinization is one of the major causes for soil desertification and ecological degradation in arid region. Acquiring large-scale and high-precision soil salinization information in real or near-real time is critical for preventing and mitigating soil salinization. The study area is located in Weigan-Kuqa oasis on the northern margin of the Tarim Basin. By analyzing Landsat-TM satellite image and soil samples obtained from field survey, we intend to investigate the relationship between Wet Index （WI） and Modified Soil-adjusted Vegetation Index （MSAVI）. These two indices are often regarded as very important land cover biophysical parameters that are strongly descriptive of soil salinization in a certain degree. The study proposes a concept of MSAVI-WI feature space and builds a soil salinity monitoring index （MWI） model based on the analysis. The results indicate that there is a strong correlation between the MWI and surface soil salinity （with an R-squared of 0.844）. Monitoring soil salinization with MWI is more precise than the salt indexes commonly used in traditional remote sensing monitoring methods. Difference matrix analysis also suggests that MWI detects different degrees of soil salinity and the changes of different combination of the vegetation and soil moisture better in the study area. Additionally, this index has a clear biophysical meaning that is often well accepted and understood. The study suggests that MWI will be helpful to monitor and evaluate soil salinization in arid region on large scale.