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从地表蒸散的角度出发,利用基于Priestley-Taylor公式与地表温度-植被指数(LSTVI)三角形特征空间的半经验蒸散模型,对农业干旱遥感监测方法进行改进,推导得到简化型蒸散胁迫指数(SESI).利用2008、2009年3—11月的MODIS陆地标准产品数据,构造了3种特征空间建模计算了SESI,对京津冀平原地区开展了农业旱情监测试验,并与温度植被干旱指数(TVDI)进行比较.结果表明:SESI有效地简化了基于地表蒸散估算的遥感干旱监测方法,对土壤表层水分(10、20 cm)有着良好的指示作用.该方法春、秋季监测效果优于夏季,且不同时相SESI的可比性优于TVDI.将SESI指数应用于大面积农业旱情连续监测具有一定可行性.
From the perspective of surface evapotranspiration, a semi-empirical evapotranspiration model based on the Priestley-Taylor formula and the surface temperature-vegetation index (LSTVI) triangular feature space was used to improve the monitoring method of agricultural drought remote sensing. The simplified evapotranspiration stress index (SESI) Based on MODIS land standard product data from March to November in 2008 and 2009, three kinds of feature space models were constructed to calculate SESI, and agricultural drought monitoring tests were carried out in the plain area of Beijing, Tianjin and Hebei, and were compared with the TVDI ) Were compared.The results showed that SESI effectively simplified the remote sensing drought monitoring method based on the estimation of surface evapotranspiration and had a good indication of soil surface water content (10 and 20 cm) .The monitoring results in spring and autumn were better than those in summer The comparability of SESI in different phases is better than that of TVDI. It is feasible to apply SESI index to continuous monitoring of large-scale agricultural drought.