Research on Drought Disaster Risk Assessment Based on Machine Learning in Hunan Province
Drought is the main factor restricting agricultural development.In order to improve the ability of Hunan Province to re-spond to drought disasters,a machine learning based agricultural drought risk assessment model is constructed to explore the spatio-temporal distribution characteristics of agricultural drought hazards in Hunan Province.The results show that the comprehensive risk of agricultural drought in Hunan Province has decreased from west to east,and the overall risk is at a medium to low level,with small fluctuations and good stability.The disaster rate of drought is consistent with the comprehensive risk distribution of agricultur-al drought.This article uses Pearson's test to compare the comprehensive risk of drought with the failure rate and disaster rate,and finds a significant correlation between the comprehensive risk of agricultural drought in Hunan Province and the failure rate and di-saster rate,proving the effectiveness of the drought risk assessment model in this study.
agriculturedrought disasterrisk assessmentmachine learningHunan Province
NETL
NSTL
万方数据
