基于多源遥感数据的温度-土壤湿度-降水干旱指数（TMPDI）的构建与应用
收稿日期: 2021-01-11
修回日期: 2021-03-03
网络出版日期: 2021-09-24
基金资助
国家自然基金项目(41861013);国家自然基金项目(41761083)
Development and application of the temperature soil moisture precipitation drought index (TMPDI) based on multi-source remote sensing data
Received date: 2021-01-11
Revised date: 2021-03-03
Online published: 2021-09-24
干旱在全球范围内产生了深远的社会和经济影响,可靠的干旱监测对防旱抗旱工作具有重要指导意义。由于在植被覆盖度和农作物种植率较低区域使用植被状态或单因子进行干旱监测时精度较低,故本文采用地表温度（LST）、降水量（P）和土壤湿度（SM）数据,基于三维欧氏几何空间中欧氏距离方法构建了一种新的干旱指数：温度-土壤湿度-降水干旱指数（TMPDI）用于干旱监测。并以甘肃省为研究区,利用SPI、SPEI、遥感数据以及小麦单位面积单产对TMPDI进行验证。结果表明：TMPDI与SPI、SPEI高度相关（R2>0.64）,且在干旱监测中兼顾降水量与气温影响的同时,降低了使用降水量或地表温度进行干旱监测的不确定性,提高了土壤湿度在农业干旱监测中的准确性与有效性,能准确地描述干旱事件的时空演变特征,同时也能较好地反映出干旱强度与干旱面积率的变化对小麦产量造成的影响,说明TMPDI在农业干旱监测中具有较高的有效性和可靠性。
满元伟,李净,邢立亭 . 基于多源遥感数据的温度-土壤湿度-降水干旱指数（TMPDI）的构建与应用[J]. 干旱区研究, 2021 , 38(5) : 1442 -1451 . DOI: 10.13866/j.azr.2021.05.27
Drought has a profound social and economic impact on the whole world. Reliable drought monitoring is of great significance to drought prevention and drought relief. In the areas with low vegetation coverage and crop planting rate, the accuracy of using vegetation status or single factor for drought monitoring is low, based on the simple and objective Euclidean distance method in three-dimensional Euclidean geometry space, a new drought index, temperature soil moisture precipitation drought index (TMPDI), was constructed for drought monitoring. Taking Gansu Province as the research area, the TMPDI was verified by using SPI, SPEI, other remote sensing data and wheat yield per unit area. The results showed that: TMPDI was highly correlated with SPI and SPEI(R2>0.64), which reduced the uncertainty of drought monitoring using precipitation or surface temperature, improved the accuracy and effectiveness of soil moisture in agricultural drought monitoring, and accurately describe the temporal and spatial evolution characteristics of drought events. At the same time, it can also better reflect the impact of drought intensity and drought area rates on wheat yield, which proves that TMPDI its high effectiveness and reliability in agricultural drought monitoring.
Key words： drought index; drought monitoring; remote sensing; MODIS; TRMM; GLEAM
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