基于Landsat-8影像的干旱区土壤水分含量反演研究

土壤水分含量的精确监测对区域生态环境保护与可持续发展具有重要意义.本文以内蒙西部额济纳旗东南的居延泽地区为研究区,基于多期Landsat-8遥感影像和野外实测不同深度的土壤水分含量数据,构建了温度植被干旱指数(TVDI)、垂直干旱指数(PDI)、归—化干旱监测指数(NPDI)和土壤湿度监测指数(SMMI)等四种干旱指数...

Study on Soil Moisture Content Inversion in an Arid Area Based on Landsat-8 Imagery

Accurate estimation of soil moisture content is of great significance for eco-environmental conservation and sustainable development in arid areas. In Juyanze, the southeast of Ejina banner, the western Inner Mongolia, 4 drought index models, including Temperature Vegetation Drought Index (TVDI), Perpendicular Drought Index (PDI), Normalized PDI (NPDI), and Soil Moisture Monitoring Index (SMMI), were established based on 3 Landsat-8 images and 150 in-situ soil moisture samples from different soil depths. Model accuracy and applicability were compared and verified, and the optimal model of TVDI was used to retrieve soil moisture content from 2015 to 2017. Five land use types, namely sandy land, saline-alkali land, bare land, vegetation and tidal flats were classified based on random forest classification and their differences in soil moisture content were analyzed. The results showed that all the 4 drought indices were negatively correlated with the measured soil moisture content. The highest fitting accuracy was observed between the 4 drought indices and the surface soil moisture. Meanwhile, the fitting accuracy decreased with the increase of soil depth. The accuracy of TVDI model was higher than that of the other models, particularly in the surface soil, with a R2 of 0.76. Discrepancies of the average soil moisture content were observed in different land use types, and generally the soil moisture content was the lowest in the sandy land, followed by saline-alkali land, bare land, and vegetation, the highest in the tidal flats.