气象科学2025，Vol.45Issue(3)：385-392,8.DOI:10.12306/2025jms.0004
一种基于多源数据的干旱事件监测方法
A method for monitoring drought events using multi-source data
摘要
Abstract
Drought has many adverse effects on social and economic development.Using remote sensing technology to timely grasp the occurrence and development of drought is of great significance for the government to improve the ability of disaster resistance and mitigation.At present,the influencing factors used in most drought remote sensing researches are relatively single,lacking the fusion application of multi-source data.Based on the evaluation of the microwave remote sensing data product quality from ESA CCI_SM(European Space Agency Climate Change Initiative Soil Moisture),this study integrated the Daily Evapotranspiration Deficit Index(DEDI)and precipitation data to construct both a multiple linear regression model and a Radial Basis Function Neural Network(RBFNN)model,which were then comparatively evaluated against in-situ soil moisture measurements from 14 agrometeorological stations in Jiangsu province.Results show that the ESA CCI_SM products can reflect the changes of soil moisture in Jiangsu province to a certain extent.Considering various drought related factors,the accuracy of monitoring soil moisture using multiple linear regression model and RBFNN model was improved to varying degrees compared to the ESA CCI_SM product itself.Among them,the RBFNN model was more sensitive to drought monitoring in the study area and showed higher applicability for drought warning and monitoring.Combined with the continuous drought events in summer and autumn in 2019,this study further shows that the RBFNN model can accurately reflect the occurrence and development of drought.The above results indicate that the RBFNN model could provide a new method for drought monitoring with remote sensing.关键词
ESA CCI_SM/干旱/多元线性回归/RBFNNKey words
ESA CCI_SM/drought/multiple linear regression/RBFNN分类
天文与地球科学引用本文复制引用
李菁,姜有山,沈澄,李聪,王珂清,戴竹君..一种基于多源数据的干旱事件监测方法[J].气象科学,2025,45(3):385-392,8.基金项目
江苏省气象局青年基金资助项目(KQ202009) （KQ202009）
江苏省气象局面上资助项目(KM202010 （）
KM202207) （）
