Multi-grid remote sensing monitoring method of hail disaster and the temporal-spatial distribution characteristics in Honghe
Hail has occurred frequently and caused significant losses to local agricultural production in Honghe Prefecture,Yunnan Province,since 1961.Hail disaster distribution data at the county or weather station scale,which are obtained by using a statistical analysis method,cannot meet the requirements of agricultural hail prevention.Several hail disaster remote sensing monitoring methods,which are limited by single remote sensing data sources and the characteristics of designing for the global scale,lack applicability in mountainous areas.To capture the spatial and temporal distribution characteristics of hail and build a hail remote sensing monitoring model at the parcel level,this study used hail record data from hail suppression operation stations from 2009 to 2022 and conducted research on a multisource data fusion approach based on Ross Li and STARFM.It then proposed a multilevel grid normalized vegetation index standardization model and a hail remote sensing monitoring recognition index RNDVI_M.The Kneed method was used to extract the trend turning points of RNDVI_M as the threshold for extracting hail disaster areas.Then,the phenomenon universality verification method was applied to verify the effectiveness of the RNDVI_M threshold and evaluate the accuracy of hail monitoring.On the basis of hail survey data from 2009 to 2022,the maximum relative error is 9.08％,the average error is 5.62％,and the standard deviation is 1.66％.The spatial overlay analysis and spatial correlation analysis methods were used to quantitative analyzed hail frequency in different disaster-prone environments,such as landform types,terrain undulations,slopes,and terrain types,at the level of cultivated land plots.The proposed hail disaster risk assessment model calculates the spatial distribution characteristics of hail risk caused by natural conditions,such as climate,meteorology,terrain,and topography.Hail disasters in mountainous areas are significantly correlated with altitude and exhibit moderate correlation with slope and undulation.Hailstones typically move along mountain ranges and valleys,making farmlands along these valleys susceptible to hail disasters.The advantages of this model are as follows.(1)Parameter adaptation for multilevel grid models is used to improve model adaptability under 3D climate conditions of mountainous areas,increasing the accuracy of hail monitoring and risk assessment from county scale to cultivated land plot scale.(2)Spatial correlation quantitative analysis is conducted between the spatial distribution of hail disasters and terrain,such as altitude,slope,undulation,river valleys,valleys,and ridges at the scale of cultivated land plots.(3)The hail susceptibility assessment model is constructed at the cultivated land plot scale.Research results contribute to the rational adjustment of the crop planting structure,the planning and layout of artificial hail control operation points,and the reduction of hail disaster losses.
hail disasterhail remote sensing identification index(RNDVI M)hail disasters remote sensing monitoringtemporal and spatial distribution of hail disastersHonghe
万方数据
维普
