Identification And Spatial Pattern Analysis Of Multi-dimensional Poverty-stricken Areas In Guizhou Province Based On Nighttime Light Data

Poverty reduction and elimination have always been issues of great concern to the international communities.Narrowing the gap between urban and rural areas and promoting sustainable and balanced regional development is the direction of the continuous efforts of all countries in the world.The ice of poverty is not the cold of a day,and the work of breaking the ice is not the warmth of one spring.Poverty is a complex social phenomenon which is the result of a combination of many factors.President Xi Jinping made the first important instruction of “seeking truth from facts,adapting measures to local conditions,guiding classification,and precising poverty alleviation” when he visited Xiangxi,Hunan.The important concept of “precise poverty alleviation” pointed out the direction for China's poverty alleviation in the new era.To this end,a series of poverty alleviation policies and measures have been promulgated and achieved world-renowned poverty alleviation achievements.Under the current poverty standards,832 impoverished counties have been lifted out of poverty,and nearly 100 million rural poor people have all been lifted out of poverty.Among them,Guizhou Province,as the main battlefield for China's poverty alleviation,implemented China's largest relocation for poverty alleviation.1.88 million people moved from remote mountain villages to cities and towns,completely changing the conditions for survival and changed from the province with the largest number of poverty-stricken people in China to the province with the largest number of poverty reduction in China,which has written the Guizhou chapter of China's poverty reduction miracle.Getting rid of poverty is the starting point of new lifestyle and new struggle,instead of the end.How to consolidate the results of poverty alleviation and effectively connect with rural revitalization,and to monitor regional development has become an urgent problem.Therefore,Long-time series exploration of the temporal and spatial evolution characteristics of the regional poverty pattern and analysis of the main poverty-causing factors are of great significance for the formulation of targeted development strategies.Remote sensing images can quickly and objectively identify poverty-stricken areas,providing an effective way for long-term monitoring of regional development.Providing a basis for enriching and perfecting information in poverty-stricken areas,developing characteristic economic industries based on local conditions,expanding the achievements of poverty alleviation,and promoting high-quality development of rural revitalization.Night light data can objectively and truly reflect the socio-economic development of the area,and has the advantages of fast update,small amount of data,and easily available.This study uses night light data,selects Guizhou Province,which has large poverty areas and deep poverty levels,as the research area,and introduces a sustainable livelihood framework to build a multi-dimensional poverty evaluation system.Based on game theory,the multidimensional poverty index(MPI)is calculated by assigning index weights and extracted the total night light index(TNLI)and the mean night light index(MNLI)of the area were compared and analyzed.Finally,the MNLI index and the MPI index were selected for modeling,and a multi-dimensional poverty estimation model based on night light data was constructed.The MPI estimates that passed through the error test were used to identify and compare the multi-dimensional poverty areas,analyze the spatial distribution characteristics of the multi-dimensional poverty areas in Guizhou Province,and further exploration of the main factors affecting the poverty situation in Guizhou Province.The results show:(1)Refer to the sustainable livelihood framework to select indicators,and the multi-dimensional poverty index MPI constructed through the combination of game theory and weighting can better reflect the development status of the study area.The fitting effect of the MNLI index and the MPI index is better than the TNLI index.Combined with the natural geographical conditions of Guizhou Province,the multi-dimensional poverty estimation model constructed has a higher accuracy.The overall average relative error from 2010 to 2018 is 7.07%,which is more accurate than previous scholars' studies.(2)Use the estimated multi-dimensional poverty index to identify the poverty situation in Guizhou Province and compare it with the list of poverty-stricken counties announced by the state.In 2012,66 counties were identified as multidimensional poverty areas,of which 63 counties are consistent with the key counties for poverty alleviation and development in the concentrated contiguous poverty-stricken areas in Guizhou Province.In 2019,9 counties were identified as multidimensional poverty areas,and 6 of them are consistent with the key counties for poverty alleviation and development in the concentrated contiguous poverty-stricken areas in Guizhou Province.(3)The Overvall Morans' I index in 2010 and 2019 were 0.425 and 0.544,respectively,indicating that the poverty level of the 88 counties in Guizhou Province has obvious spatial agglomeration.The poverty level presents a "horseshoe-shaped" spatial distribution pattern with low poverty levels in the central and northern regions,and deeper poverty levels in the eastern,western and southern regions.The overall results show that the poverty reduction effects of various counties and cities(districts)in Guizhou Province from 2010 to 2019 are very obvious,which effectively confirms that Guizhou Province has firmly promoted the poverty alleviation process,actively carried out various poverty alleviation work,and the results of poverty reducation achieved through a series of targeted poverty alleviation policies and measures.(4)The proportion of poor counties in the geomorphic area of Guizhou Province shows that the spatial pattern of poverty in the county is related to the geomorphic subregion to a certain extent,reflecting the natural geographical conditions such as landforms are the main factors causing poverty in the counties of Guizhou.The unique natural geographical environment can be converted into advantageous resources,the characteristic leading industries can be developed according to local conditions,and the "hematopoiesis" function can be enhanced to realize the sustainable development of the region.