Simulation And Prediction Of Insect Dispersal And Spread Process Of Malus Sieversii,Agrilus Mali Matsumura Pest Based On CA-Markov Model

In recent years,Xinjiang Saiwei apple forest suffered serious diseases and insect pests,which posed a serious threat to Xinjiang wild fruit forest resources2 In order to explore the spreading process of the infestation of Malus sieversii,Agrilus mali,this paper selected Zhuolesai,wild fruit forest,Gongliu County,Yili,Xinjiang as the research area,and took the infestation of Malus sieversii,Agrilus mali as the research object2 Based on Landsat remote sensing image data and UAV high-resolution image data from 2000 to 2018,The spatial and temporal variation of insect pest in the study area in recent ten years was analyzed by using thermal landscape dry shoot index inversion,and the linear regression equation of hot landscape dry shoot index and dry shoot area was established to establish the insect pest level2 The weight of suitability factors affecting the spread and diffusion of insect pest in the study area was simulated by CA-Markov model2 In addition,two types of pest development in 2021 are predicted2 To provide scientific support for the precise prevention and control of Piliaogidine pests and the protection of wild fruit forest resources in Yili,Xinjiang2 The main conclusions of this study are as follows:(1)The thermal landscape index information was extracted from 30 randomly selected sites of 80 plots in Dzhoresay in the study area2 It was found that the thermal landscape index of different landscape types in the study area ranged from20222℃to 31233℃,among which the dry branch index of Sevey’s apple ranged from22225℃to 22225℃,and its average value was 25225℃2 Studies show that altitude,slope aspect,gradient and vegetation coverage are important factors affecting thermal landscape index,and the R~2 of regression equation is not so significant2 Therefore,combining with the correction parameters of the four influencing factors,the thermal landscape dry shoot index is constructed and verified2 The R~2 is all above 0275,and the RMSE value is close to 12 The result of verification shows that the hot landscape branch index is effective2(2)Based on the UAV image twitch rate recognition experiment,each image of 80 experimental sample sites was trained to obtain the identification effect map of vegetation2 By comparing and analyzing the image with the original UAV vegetation image,the recognition accuracy of each image was calculated to be greater than 80%,which had a certain recognition effect2 According to the results of UAV image recognition,the area was calculated,and the insect pest area of 80 experimental samples was finally obtained2(3)Firstly,the correlation model between thermal landscape dry branch index and insect pest area was established,and then the overall and local changes of insect pest area were analyzed from 2000 to 20182 The change trend of insect pest in each stage during 18 years was expressed by analyzing the transfer process of insect pest grade area from 2000 to 20182 Then the spatial and temporal distribution characteristics of the pest were analyzed2 From the perspective of spatial variation,the pest spread from northwest to southeast along the Great and Small Moore River Valley to the whole study area2 Finally,the pest spread from west to east across the mountain ridge2 From the time series,the Pinjiaogidin insect pest began to spread in a large area from 2000 to 2003,and the extremely severe insect pest area was concentrated in the middle of the Great and Small Mohe River from 2003 to 2002,and the spread trend was moderated2 From 2002 to 2002,the spread of the insect pest appeared repeated,and continued to spread across the ridge from west to east2 From2012 to 2015,the pest situation reached its peak2 After 2018,the serious pest situation began to improve,and the Seville’s apples gradually recovered to health2(4)IDRISI software was used to analyze and determine the suitability factors affecting insect classification:elevation,slope,slope aspect,plane curvature,section curvature,distance from residential area,distance from winter grassland,distance from other grassland,distance from ridge line,distance from river,distance from road,distance from valley line and distance from cultivated land2 Based on the data of pest spread distribution from 2000 to 2003 and the atlas of suitability for levels of healthy,mild,moderate,severe and extremely severe pests,the pest situation in 2002 was simulated by using 2003 as the base period,and the results were compared with the actual results2 According to the above steps,the process of the spread of pests from 2002 to 2018 was simulated2 It was found that the most sensitive areas were concentrated in the middle of the Great and Small Mohe River Basin in20022 In 2012,a large-scale outbreak of insect pests began,which affected almost the whole study area,and the Great and Small Mohe areas were particularly affected2 In2015,the pest situation was still not optimistic2 In the south and east of the Great and Small Mohe River,the extremely severe and severe pest areas were partially transferred to the moderate pest areas2 In 2018,the spread of the small giddum in the Sevay apple forest area has been controlled2 The infestation areas of both the Great and the Great Moore watershed have changed from extremely severe to moderate and mild infestation areas,while only a small part of the northern part of the Great and the Great Moore rivers still maintain the situation of severe infestation2 The spread of pests in 2021 is predicted by two different development scenarios2 From the prediction results,it is found that the proportion of healthy pest class area in the case of scientific control and development increases from 12213%in 2018 to 32235%in2021,and the other four types of pest class area all decrease2 The results showed that the spread trend of insect pests was greatly reduced under the scientific control,so the scientific control of insect diseases and pests of Sevey’s apple is the most effective method at present.