【摘要】 以内蒙古西部的额济纳绿洲为研究区,利用2017年8月24日的Landsat 8影像,基于地表温度-植被指数特征空间理论,提取归一化差值植被指数(NDVI)、比值植被指数、土壤调节植被指数、改进型土壤调节植被指数和优化型土壤调节植被指数(OSAVI),分别计算温度-植被干旱指数(TVDI),利用同期实测土壤水分数据进行精度评定与指数优选,反演区域土壤水分,划分干旱等级.结果表明, TVDI能够反映额济纳绿洲土壤水分的分布状况,是区域旱情监测的有效指标; 5种植被指数中,基于OSAVI和NDVI计算的TVDI与土壤水分的R2>0.52, OSAVI优于NDVI,基于OSAVI的TVDI是研究区土壤水分反演的最佳模型;整个研究区以干旱、重旱区为主,干旱现象明显.在空间分布上,除水体以外,旱情状况呈现以绿洲为中心,向四周急剧增加的趋势.更多还原

【Abstract】 With the Ejina oasis in western Inner Mongolia as the research area, a Landsat 8 image acquired on August 24, 2017 was used to extract the following five vegetation indices: normalized difference vegetation index(NDVI), ratio vegetation index, soil-adjusted vegetation index, modified soil-adjusted vegetation index and optimized soil-adjusted vegetation index(OSAVI), based on the theory of land surface temperature-vegetation index feature space. Temperature-vegetation drought index(TVDI)was calculated, and the in situ measured soil moisture applied for accuracy assessment and vegetation index optimization. Regional soil moisture was retrieved and drought levels graded. The results showed that TVDI could reflect the soil moisture distribution pattern in the Ejina oasis, and also serve as an effective indicator for regional drought monitoring; of the five vegetation indices, the R2 values of TVDI calculated by OSAVI and NDVI were relatively higher, both above 0.52. OSAVI was better than NDVI.The TVDI based on OSAVI was considered the optimal model for soil moisture inversion in this area;and drought and severe drought areas had a dominant position in the whole region. From the perspective of spatial distribution, with the exception of water bodies, drought condition spread sharply from the center of the oasis towards the periphery.更多还原