基于高程订正的温度植被干旱指数在河北干旱监测的适用性分析

Application of the Modified Temperature-Vegetation Dryness Index (MTVDI) base on DEM to monitor drought in Hebei

摘要:

基于2017-2021年生长期（4-9月）的MODIS遥感数据，用数字高程模型(Digital elevation model, DEM)对陆面温度（Land surface temperature, LST）进行订正，构建增强植被指数(Enhanced vegetation index, EVI)-LST特征空间，估算订正的温度植被干旱指数（Modified temperature vegetation dryness Index, MTVDI），并结合与土壤湿度以及降水实地观测数据的相关性，探讨MTVDI在河北生长期的适用性。结果表明：（1）基于DEM对构建的EVI-LST特征空间进行订正，订正后的特征空间散点图更符合三角形关系，与温度植被干旱指数（TVDI）原理图更接近；（2）MTVDI与土壤湿度的相关性较订正前提高0.09，且MTVDI等级与土壤湿度等级的空间匹配度超过0.9，表明MTVDI具有反映研究区土壤湿度的能力；（3）MTVDI与降水量呈负相关，从气象因素角度，表明MTVDI对河北省干旱具有一定表征意义；（4）从2019年干旱事件来看，MTVDI能够显示出干旱从东北向全省发展形势。综上所述，用DEM对TVDI进行订正，从一定程度上减小了LST随海拔变化对土壤湿度反演误差的影响，MTVDI能较好指示出河北干旱状况，该研究可为农作物生育期干旱监测的业务化运行以及抗旱减灾决策提供科学参考依据。

Abstract:

MODIS data from April to September were used to build EVI (Enhanced Vegetation Index)-LST (Land Surface Temperature) feature space and calculate temperature vegetation drought index (TVDI) which modified by digital elevation Model (DEM). Based on the correlation between modified TVDI (MTVDI), relative soil moisture and precipitation, the applicability of MTVDI in monitoring drought in Hebei was discussed. The results showed that: (1) the modified EVI-LST feature space was more in line with the triangle relationship and closer to the TVDI Schematic diagram by DEM. (2) The correlation between MTVDI and soil moisture were 0.09 higher than TVDI and soil moisture and the spatial matching degree was above 0.9, indicating MTVDI has the ability to reflect the dry and wet conditions of soil. (3) MTVDI had negative correlation with precipitation, and it showed that MTVDI can represent drought in Hebei to a certain extent from the meteorological view. (4) From the perspective of the 2019 drought event, MTVDI can show the development of drought from northeast to all area of Hebei. In conclusion, MTVDI can reflect the agricultural drought in Hebei. Our study can provide scientific reference for the operation of drought monitoring and the strategy of drought relief.