Spatial And Temporal Evolution And Characteristics Of Multidimensional Poverty In Relatively Poor Areas Of Hubei Province

This paper takes the concentrated and difficult areas in Hubei Province as the research object.Firstly,based on the method of identifying poverty by night light image,the continuous correction of DMSP OLS data set and NPP-VIIRS data set is carried out to obtain the night light images of poverty-stricken areas in Hubei Province which can be continuously analyzed in 2005,2010,2015 and 2019.The average night light intensity of each poverty-stricken county is extracted and the regional average light intensity is constructed The light index model obtains the average light index of each poor county.According to the natural breakpoint method,the results are divided into severe poverty,high poverty,moderate poverty and light poverty.The temporal and spatial dynamic analysis of the changes of light index in the poor counties of lake is carried out;then,based on the multi-dimensional poverty theory and spatial poverty theory,the economic density,the proportion of secondary and tertiary industries,the rural residents are selected The index system of multi-dimensional poverty is constructed by 21 indexes,including average net income,local fiscal revenue and expenditure ratio,population density,number of students in ordinary junior high school,health bed,average slope,altitude,vegetation coverage,annual average rainfall and effective irrigation area of medical institutions.The multi-dimensional poverty index of each poverty county is calculated by using comprehensive index method.It is also divided into four grades,and the dimension is carried out The degree decomposition analysis and the spatial and temporal change analysis,finally,the differences and relations between the average light index and the Multidimensional Poverty Index and the decomposition dimension index are analyzed.Then,according to the regional GDP,per capita net income and Multidimensional Poverty Index of poverty-stricken counties in Hubei Province in 2019,the spatial characteristics of poverty evolution are studied to determine whether the poverty relief areas are out of poverty There are traps of space poverty,which will lay the foundation for the dynamic monitoring and targeting of anti-poverty in the future and the establishment of a long-term mechanism for poverty alleviation.The relevant conclusions are as follows:(1)By extracting the average light index of each poor county,it is found that the light index can be used for poverty measurement.In 2005,the light index of each poor county was in a low state,the level of economic development was relatively lagging behind.From2005 to 2010,the average light index of each county did not change significantly.From2010 to 2015,the low value area of the Western light index contracted from north to south,and the scope was further reduced,from the beginning The 21 counties in the period of the period contracted to 13,and the overall coverage of the low value areas decreased.The average light index of poor counties in the easternregion was on the rise.As a whole,the average light index of the Eastern Hubei was higher than that of the western region,and the North and south ends of the western Hubei region were higher than the central region,until 2019,Nanzhang County,Baokang County,Changyang County,Wufeng county and Badong County were also in the low value area.This is the case Some counties are distributed in a ring belt and are the focus of attention in the future.(2)From 2005 to 2010,the multi-dimensional poverty index of poor counties has not changed significantly,and the poverty alleviation process is slow.From 2005 to 2010,due to the support of policies and financial inclination,the poverty level of each county began to change significantly.From 2015 to 2019,the multi-dimensional poverty index of each county changed most significantly,and the poverty alleviation effect was the best.(3)The nighttime light index can identify poverty,but the classification is not objective.The average light index and Multidimensional Poverty Index results account for71.4% of counties with ± 1 level.When comparing single dimension index,the poverty accuracy of night light reflecting economic dimension is the highest,reaching 77.2%.The ability of identifying economic dimension is stronger.If multi-dimensional classification is required,social survey data is required as the data The accuracy of the method is not studied in this paper.(4)The hot spot analysis of poverty-stricken counties in Hubei Province shows that the number of cold spots and hot spots is not much,and most of the areas are developing evenly;the poverty level in Western Hubei Province is greater than that in the East,and the cold spots are concentrated in the west,and the internal development differences are huge.The western areas are both cold and hot spots;the west changes more than the East in2005-2010,2015-2019 The East is larger than the west,and there is a long cold spot in the west,and some counties have spatial poverty trap.(5)Setting up a five-year policy buffer period for poverty alleviation counties in Hubei Province,gradually shift the focus of resources;establish an investigation and monitoring mechanism,track the investigation and monitoring network for key marginal counties,ex situ poverty alleviation counties,and ecological poverty alleviation counties;increase policy preference for spatial poverty trap areas,industrial backward areas,and remote mountainous areas,build a helping mechanism,and tap ecological resources establish an evaluation system,monitor and evaluate from time to time,and strengthen the responsibilities of local governments to prevent large-scale and systematic return to poverty.