Comprehensive Evaluation Of Multidimensional Poverty And Its Influencing Factors From County Perspective In The Southeast Of Gansu Province

As an essential part of Gansu Province,the southeast region of Gansu Province has a fragile ecological environment and socio-economic poverty.It belongs to the Liupan Mountains,Qinba District,and Tibetan areas.It is a densely distributed poverty area in Gansu Province.In order to respond to the country's call to fight poverty and ensure a well-off society by 2020,the research area located in 21 counties of the three municipal administrative regions of Tianshui,Longnan,and Gannan Tibetan Autonomous Prefecture in Gannan Province.These include 16poverty-stricken national counties,which are critical national poverty alleviation and development areas.This thesis is based on the theory of multi-dimensional poverty measurement,taking the southeast of Gansu Province as an example,using remote sensing and geographic information technology,Landsat TM / ETM + / OLI remote sensing data,land use data,and socio-economic data.Starting from the three sub-system levels of society,economy and ecology,a multi-dimensional comprehensive evaluation index system for poverty is established.This paper first using the entropy method and the analytic hierarchy process to determine the index weights to obtain a multi-dimensional poverty comprehensive index,Secondly,the spatiotemporal differentiation of the multi-dimensional poverty comprehensive index is analyzed through the coupling coordination degree model and the spatial autocorrelation model.Finally,the obstacle degree model is used to measure the main controlling factors affecting multi-dimensional poverty.It aims to promote the sustainable development of society in the southeast region of Gansu Province.The research results show that the multi-dimensional poverty level in the southeast of Gansu Province improved from 2001 to 2015 and has the following characteristics:(1)The multi-dimensional poverty level in the study area is slowly growing from 2001 to 2015.Among them,the multi-dimensional poverty levels in Wenxian,Xihexian,Lixian,Huixian,Lintan and Zhouquxian counties improved from 2001 to2005.From 2005 to 2010,except for Ganguxian,ZhangjiachuanHuizuZizhixian,Chengxian,Liangdangxian,Maquxian,and Luquxian,the multi-dimensional poverty level at the county level showed an improvement trend.From 2010 to 2015,except for Wushanxian,Wenxian,Xihexian,and Zhouquxian,the multi-dimensional poverty level at the county level showed a pattern of improvement.The relatively high-value areas of the multi-dimensional poverty index are mainly distributed in Lixian,Chengxian,Ganguxian,Tai'anxian,and Wuduxian in the east of the area;the relatively low-value regions are mostly distributed in Maquxian in the west of the area.Noticeable changes occurred mainly in Maquxian,Dangchangxian,Zhouquxian,and Wenxian in the western and central regions.(2)From 2001 to 2015,the overall level of the "social-economic," "social-ecological," and "economic-ecological" coupling of the multi-dimensional poverty comprehensive evaluation system in the southeast of Gansu Province is at an antagonistic stage.The level of coupling between the "social-economic" systems is high.As of 2015,except for Zhouquxian and Luquxian,which are in a low-level coupling stage,the other counties have transitioned to the antagonistic stage.The degree of coupling and coordination between the two sub-sub systems is still at a relatively low level,especially in the socio-ecological and economic-ecological two sub-systems.The degree of coupling and coordination is particularly low,and a healthy development state of mutual promotion has not been achieved.(3)In terms of the dynamics of changes in the multi-dimensional poverty index level in the study area from 2001 to 2015,Qingshui County's multi-dimensional poverty index changed the fastest,with an absolute value of up to 82.64%,and Lixian's multi-dimensional poverty index changed the slowest,with a total value of1.29%.The multi-dimensional poverty level in the study area began to show global spatial autocorrelation after 2010.Therefore,the multi-dimensional poverty level in the 21 county-level administrative regions showed an aggregated distribution between2010 and 2015.(4)By using the obstacle degree model to diagnose the main controlling factors,the main obstacles in the social sub-system are the per capita housing area and the number of beds in various social welfare adoption units.The main challenges to theeconomic sub-system are economic density and the proportion of the primary industry's GDP.The main obstacles to social sub-system are fertilizer application intensity and agricultural production potential.The barriers caused by ecological and economic factors in the study area are relatively high.