Research On The Geographical Capital Structure And Characteristics Of Spatial Poverty In The County

Poverty and anti-poverty is not only a common big problem for human society to faced, but also the major obstacles for China’s social and economic development to overcome. At present, the poor areas of China are mainly concentrated in the areas of remote location, poor natural conditions, ethnic minorities, showing the characteristics of regional and cluster. This kind of region is either the lack of environmental and social capital, or economic capital is not used effectively, which eventually lead to regional poverty. In order to accurately determine the various social and economic issues highlighted areas, so that targeted poverty alleviation work, It is important to clearly find out the geographical capital structure and characteristics in poor areas.According to the geomorphic types and national composition to determine the research samples, using GIS technology and participatory rural assessment method (PRA) to obtain research data. Using Pearson correlation analysis method to divide the geographic capital of leading to poverty and eliminating poverty, based on GIS and BP neural network model for simulation of regional Poverty Allevation Index, Impoverishing index and spatial distribution, to analyze the capital structure and Jingyuan geographical features, using the entropy method and obstacle degree model to analyze the reasons, and puts forward specific measures. The conclusions of the study are as follows:(1) Geographical capital structure analysis shows that:there is a significant correlation between the geographical capital indicator system and Per capita net income of farmers, indicator select is scientific and rational. Available from the overall situation, The capital are positively correlated with the per capita net income of farmers in economic geography capital, and is the capital of ease or eliminate poverty in study area. At the same time,The correlation coefficient of the slack economy family income contribution rate, rural Engel coefficient, correlation coefficient, the rate of loans to farmers to meet, at least have a rich project than farmers and poverty alleviation policy satisfaction were 0.311,0.575,0.288,0.299 and 0.345, which has a very significant role in Jingyuan County poverty alleviation; The correlation coefficient of the rate of rural women, improving the social status of pension insurance rate and the degree of new rural society happened in social geographical capital were-0.310,-0.397 and -0.243, which was negatively correlated with per capita net income of farmers, and lead to poverty in study area; In addition to the per capita arable land area, the other capital is the capital of impoverishing capital in environmental Geographic capital. The correlation coefficient of the undulating terrain, damage rate and total sown area of crops, food security degree were-0.295,0.353,-0.397-0.306, which is very significant to poverty.(2) Geographical capital characteristic analysis showed that:2010-2015, the SPI (space poverty index) of all geomorphic and national facility showed a rising trend, indicating that the poverty level of Jingyuan County is gradualy coming down in overall. From the perspective of geomorphic types, the order of SPI to each geomorphic type is Vally hirakawa area of erosion and deposition (average 1.571)> Hill area of erosion structure (average 0.199)> Lithoid mountains area of etching structure (average 0.334). To eliminate poverty, Lithoid mountains area of etching structure should arouse attention, The mainly reasons lead to poverty are the large topographic relief, the large area of abandoned in farmland, the large cost of business activities and travel; From the perspective of national types, the order of SPI to each national is Han minority villages (average 1.484)> hui minority villages (average 1.262)> Hui and Han minority mixed villages (average 1.033). Therefore, Hui and Han minority mixed villages should attach importance in the area to eliminate poverty, the mainly reasons lead to poverty are the poor of geographical accessibility, the large area of abandoned in farmland, the low quality of labor and the large natural disaster loss; From the perspective of different nationality in same physiognomy,2010-2015, the SPI in the study area is not very stable, suggests that the funding of poverty vulnerability is big, and easy to poverty due to illness, education, or natural disasters. The average SPI of Han monority, Hui monority and Hui and Han minority in Vally hirakawa area of erosion and deposition is 0.526,2.557 and 1.644, The average SPI of Hui monority and Hui and Han minority in Hill area of erosion structure is 0.321 and-1.934, The average SPI of Han monority, Hui monority and Hui and Han minority in Lithoid mountains area of etching structure is 1.031、-0.029 and -0.842. Therefore, Han mornity villages in Vally hirakawa area of erosion and deposition, Hui and Han minority mixed villages in Hill area of erosion structure and Lithoid mountains area of etching structure should mainly focus on to eliminate poverty in future.(3) combined with the researching on the geographical capital structure and characteristics of Spatial poverty in the County of Jingyuan and put forward some measures to eliminate poverty, such as, strengthening agricultural investment, improving the traffic and communication facilities, controlling the population, improving the living environment and improving the old-age security system and so on.