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为探讨近年来广泛使用的低空间分辨率的MODIS数据以及高空间分辨率的Landast 8数据对同一地区的旱情状况,选择内蒙古自治区干旱频发的乌审旗荒漠草原为研究区,借助分裂窗算法反演地表温度(Ts),获取归一化植被指数(NDVI),建立温度植被干旱指数(TVDI)的干旱监测模型,分别反演MODIS-TVDI和Landast8-TVDI,并与同期野外实测的不同深度土壤含水量进行回归分析。结果发现,基于MODIS和Landast8 2种遥感数据计算得到的TVDI与各层的土壤水分线性相关显著,两者都能表征地表的干旱分布,且Landast8-TVDI与各层土壤含水量的相关性大于MODIS-TVDI与各层土壤含水量的相关性,其中0~10 cm表层土壤含水量的相关性要好于0~20 cm、0~30 cm的相关性。因此Landast8-TVDI能够更好地反映乌审旗荒漠草原的土壤水分状况,更适宜于旱情监测。
In order to explore the low spatial resolution MODIS data widely used in recent years and the Landast 8 data with high spatial resolution in the same area, the drought-prone Wushen Banner desert grassland of Inner Mongolia Autonomous Region was chosen as the study area. The surface temperature (Ts) was retrieved to obtain the normalized NDVI, and the drought monitoring model of the TVDI was established. The MODIS-TVDI and Landast8-TVDI were retrieved and compared with the field observations at different depths Soil water content regression analysis. The results showed that there was a significant linear correlation between TVDI and soil moisture calculated by MODIS and Landast8 remote sensing data. Both of them can characterize the surface drought distribution, and the correlation between Landast8-TVDI and soil water content of each layer is greater than that of MODIS The correlation between TVDI and soil water content in all layers, of which 0 ~ 10 cm surface soil moisture content correlation is better than 0 ~ 20 cm, 0 ~ 30 cm correlation. Therefore Landast8-TVDI can better reflect the soil moisture status of Wushen Banner desert steppe and is more suitable for drought monitoring.