Spatial Analysis Of Poverty Impact Factors Of Contiguous Poverty Areas In Gansu Province

Selecting 36 provincial-level poverty-stricken counties in Gansu Province covering ethnic minority areas,deep stone mountain areas,and red revolutionary old areas to establish an indicator system for the study area to quantify the depth of poverty caused by natural factors,as well as the suppression effect of construction development and policy tilt on poverty.Perform a full-scale polygon diagram to analyze indicators with strong poverty impact in different poverty-stricken counties;and use global distribution model(OLS)and the geographically weighted regression model(GWR)to analyze the spatial distribution characteristics of the indicators,and the following conclusions are obtained:1.The overall comprehensive poverty impact index for the study area is 0.180,which is moderately high.The regional poverty average impact index was ranked in Weinan City 0.212> Linxia Hui Autonomous Prefecture 0.204> Dingxi City 0.169> Pingliang City 0.168> Baiyin Huining County 0.166> Gannan Tibetan Autonomous Prefecture 0.159> Tianshui City 0.154> Lanzhou Yuzhong County 0.148,that is,comprehensive.The areas of poverty are concentrated in deep and shallow areas in the deep stone mountainous areas,ethnic minority areas,and red revolutionary old areas.2.There are commonalities and differences in poverty factors in regional categories.There are common poverty problems in the study area(natural drought,steep slope),inadequate infrastructure(road),and economic development(threeproduct power shortage).The differences in regional categories are as follows:(1)The poverty alleviation in the Shenshishan area is large,but the development resistance of the harsh natural conditions is still relatively large;(2)the lack of infrastructure in minority areas,the low level of education,and the backward development level of counties(3)The red cultural tourism resources in the old red revolutionary area have low utilization rate,and the economic level varies with the location and the convenience of transportation;(4)The overall development level of poverty-stricken counties in Tianshui City is good,and the poverty phenomenon is reduced to Point poverty.3.The correlation coefficient between natural poverty alleviation factor and poverty problem accounts for 50.94% of the total correlation coefficient.The topographic and climatic conditions are bad.The two indexes of slope and soil desertification have larger coefficients in the regression equation: the absolute value of the slope coefficient in the OLS model is 0.198,soil.The absolute value of the desertification index coefficient is 0.544.The absolute value of the slope coefficient in the GWR model is 0.373,and the absolute value of the soil desertification index coefficient is 1.270.4.Socioeconomic factors can effectively weaken the natural poverty factor,but the correlation coefficient accounted for 49.06% and the correlation coefficient of natural poverty index accounted for 50.94%,which means that the natural poverty factor can not be eliminated completely.The absolute value of the highway coefficient in the OLS model is 0.061,the absolute value of the per capita primary industry GDP coefficient is 0.163,the absolute value of the GDP per capita secondary industry is 0.072,and the absolute value of the GDP per capita tertiary industry is 0.139.The absolute value of the per capita public finance expenditure coefficient.It is 0.265;the absolute value of the highway index coefficient in the GWR model is up to 0.096,and the absolute value of the poverty alleviation fund index coefficient is up to 0.066.At the same time,poverty-stricken counties generally have problems of low education level.The scarce areas in education are in minority areas.As a potential factor to curb poverty,its status is very important.5.The spatial distribution of the main natural poverty indicators:(1)The negative correlation coverage of the slope index coefficient reaches 2/3 of the study area,including the minority areas and the Shenshishan area;the positive correlation of Tianshui City indicates that the economic development can overcome small Rugged terrain.(2)The soil desertification index is spatially divided into three parts: ethnic minority areas,red revolutionary old districts,some counties and districts in Tianshui City,and deep stone mountainous areas.The coefficients are gradually weakened from the three poles of northwest,northeast and southeast to the center.The influence of this indicator in the central part of the study area is weak.6.The spatial distribution of major social and economic indicators:(1)The positive correlation coefficient of highway indicators is gradually reduced from the northwestern minority areas and the southeastern deep stone mountain areas to the central red revolutionary old areas in the three regional categories;the northeast is other.In the category of Tianshui City,the degree of negative correlation gradually diminished from this point.(2)The positive and negative correlations of the per capita public finance expenditure coefficient are divided into south and north directions.It appears from south to north,that is,from the depth of poverty to a shallow extent.The negative correlations are distributed in ethnic minority areas and red revolutionary old areas;the positive correlation distribution is centered on Weinan City,and the per capita public financial expenditures in different municipalities promote rural per capita disposable income in the counties under the jurisdiction of cities.Based on the above conclusions,five recommendations corresponding to poverty influencing factors are proposed for different regional categories.