基于多源遥感数据的TVDI方法在荒漠草原旱情监测的应用

发布时间：2018-04-11 03:27

本文选题：多源遥感数据 + 温度植被干旱指数　；参考：《安徽农业大学学报》2017年03期

【摘要】：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。
[Abstract]:In order to study the drought situation in the same area with low spatial resolution MODIS data and high spatial resolution Landast 8 data widely used in recent years, Wushenqi desert steppe with frequent drought occurrence in Inner Mongolia Autonomous region was selected as the study area.By using the split window algorithm to retrieve the surface temperature (TsN), the normalized vegetation index (NDVI) was obtained, and the drought monitoring model of the temperature and vegetation drought index (TVDI) was established. The MODIS-TVDI and Landast8-TVDIwere retrieved, respectively, and the regression analysis was carried out with the measured soil water content in different depths in the field during the same period.The results showed that the linear correlation between TVDI and soil moisture in each layer was significant based on MODIS and Landast8 remote sensing data. Both of them could characterize the surface drought distribution.The correlation between Landast8-TVDI and soil water content in each layer was greater than that between MODIS-TVDI and soil water content in each layer, and the correlation of surface soil moisture content in 0 ~ 10 cm layer was better than that of 0 ~ 20 cm ~ (-1) 0 ~ 30 cm soil moisture content.Therefore, Landast8-TVDI can better reflect the soil moisture status of Wushenqi desert steppe, and is more suitable for drought monitoring.
【作者单位】：内蒙古农业大学水利与土木建筑工程学院;
【基金】：内蒙古自治区自然科学基金(2015MS0513) 内蒙古自治区科技计划项目(20140153) 内蒙古自治区水利科技项目(NSK201403)共同资助
【分类号】：S812.1;TP79

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