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土壤水分胁迫是干旱区绿洲生态环境和可持续发展面临的主要问题,开展区域尺度下大面积、高精度的土壤水分监测,有利于该地区旱情预报、作物估产、气象水文等领域研究。以Ts-NDVI特征空间为理论基础,以新疆渭干河-库车河三角洲绿洲为研究靶区,选择典型干湿季节下Landsat 8遥感影像,在传统温度-植被干旱指数(TVDI)算法基础上,考虑大尺度研究区下垫面异质性(植被覆被、地形起伏)对辐射能量平衡的影响,分别采用植被水分指数(VWIs)、加入大气温度(Ta)和DEM校正后的地表温度(Ts)与NDVI相结合,构建了植被干旱指数(VDI)和改进型温度-植被干旱指数(iTVDI),并结合同期实测土壤水分数据对3种算法进行比较。结果表明:3种算法在一定程度上均能比较客观反映旱情特征,与表层土壤含水量呈现不同程度的负相关,其中,iTVDI相关性最好,TVDI次之,VDI相关性最低;相较植被生长初期而言,3种算法均在植被生长成熟期具有更好的水分监测能力。
Soil water stress is the main problem that the oasis environment and sustainable development in the arid area are facing. To carry out large-area and high-precision soil moisture monitoring at the regional scale is beneficial to the study of drought forecast, crop yield estimation and meteorology and hydrology in this area. Based on the Ts-NDVI feature space and Landsat 8 remote sensing image under the typical dry-wet season, the Weigan-Kuqa River delta oasis was selected as the research target. Based on the traditional TVDI algorithm Considering the influence of heterogeneity of underlying surface (vegetation cover and topography) on radiation energy balance in large-scale study area, vegetation temperature index (VWIs), atmospheric temperature (Ta) and DEM corrected surface temperature Ts) and NDVI, the VDI and iTVDI were constructed, and the three algorithms were compared with the soil moisture data of the same period. The results show that the three algorithms can objectively reflect the drought characteristics to a certain extent, and have negative correlation with surface soil moisture with different degrees. Among them, iTVDI has the best correlation, TVDI takes second place and VDI has the lowest correlation. Compared with vegetation In the early stage of growth, all three algorithms have better water monitoring ability during vegetation growth and maturity.