Sui Xin-Xin, Qin Qi-Ming, Dong Heng, Wang Jin-Liang, Meng Qing-Ye, Liu Ming-Chao
China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Jan;33(1):201-5.
Farmland drought has the characteristics of wide range and seriously affecting on agricultural production, so real-time dynamic monitored has been a challenging problem. By using MODIS land products, and constructing the spectral space of LST and LAI, the temperature LAI drought index (TLDI) was put forward and validated using ground-measured 0-10 cm averaged soil moisture of Ningxia farmland. The results show that the coefficient of determination (R2) of both them varies from 0.43 to 0.86. Compared to TVDI, the TLDI has higher accuracy for farmland moisture monitoring, and solves the saturation of NDVI during the late development phases of the crop. Furthermore, directly using MODIS land products LST and LAI and avoiding the complicated process of using the original MODIS data provide a new technical process to the regular operation of farmland drought monitoring.
农田干旱具有范围广和对农业生产影响严重的特点，因此实时动态监测一直是一个具有挑战性的问题。利用MODIS陆地产品，构建地表温度（LST）和叶面积指数（LAI）的光谱空间，提出了温度叶面积干旱指数（TLDI），并利用宁夏农田0-10厘米平均土壤湿度实测数据进行了验证。结果表明，二者的决定系数（R2）在0.43至0.86之间变化。与温度植被干旱指数（TVDI）相比，TLDI对农田湿度监测具有更高的精度，并且解决了作物生长后期归一化植被指数（NDVI）的饱和问题。此外，直接使用MODIS陆地产品的LST和LAI，避免了使用原始MODIS数据的复杂过程，为农田干旱监测的常规运行提供了一种新的技术流程。
