Spatial Simulating On Regional Poverty And Poverty Alleviation Status Based On GIS And BP Neural Network

As a hot issue of sociology, economics and geography, regional poverty is one of the most severe challenges that the whole world faces. Poverty, anti-poverty and poverty alleviation have become the focus of many scholars. However, no matter which level of regional poverty they focus on, the final aim is only one that is to solve the human poverty. In China, the issue of poverty is one of the key field that both the government and scholars exploring, especially the rural poverty. This research originates from a thinking on distributional rationality of financial anti-poverty fund (Sichuan), in which three sub-goals, the core problem (the mechanism problem and the space problem )related to regional poverty and poverty alleviation status are put forward. Aiming at the goal to explore, this study selects 36 national anti-poverty counties as the study objects, chose and builds regional poverty index system coupled to nature, society and economics and specifically operable, and then bases on relevant study of Pearson and OLS regression estimation analysis and the spatial simulating analysis of GIS, BP Neural Network, cooperates with the salvation of the core problem, the mechanism problem and the space problem one by one to provide a kind of method, direction and reference to similar problems. On this basis, this research raises a new method of appraisement on regional rural poverty, which can represent extent of regional rural poverty perfectly, gives a realistic way about distribution of financial anti-poverty fund basically for the regional rural poverty. The method would comply with the country anti-poverty policy laying on《Management Method of Financial Anti-Poverty Fund》and finally design financial anti-poverty fund distribution practical program based on regional Pressure of Poverty Alleviation Index(PPAI) to provide reference to government decision.On account of the target realization of this research, we draw conclusion as follow:(1)According relevant study of Pearson, the conclusion of the mechanism problem of regional poverty is: natural condition is the notable impoverishing factor in the key poverty alleviation counties in Sichuan province. However, social condition of causing poverty aggravates the trend of this poverty. Economic condition is the effective factor of eliminating poverty. From OLS regression analysis, we deepen the study of regional poverty mechanism and get better explanation on basis of the relevant study of Pearson. The relevant study of Pearson and OLS regression analysis mutually complement, so that it explains regional poverty system more completely.(2)The spatial simulating study based on GIS and BP Neural Network demonstrates: The counties of higher Natural Impoverishing Index (NII) are mainly centralizing in west, especially centralizing in Liangshan conton of west. The lower NII counties are whole spreading in Sichuan Basin where the terrain is relatively flat.The counties of higher Social Impoverishing Index (SII) are mainly centralizing in the rim of East basin and the provincial boundaries. However, the lower SII counties are centralizing in west montanic state. It forms a sharp contrast with NII spatial distribution. The key cause is the different distribution of poor people in north and west.The counties distribution of Economic Poverty Alleviation Index (EPAI) is relatively messy. Generally, the higher EPAI counties are mostly centralizing in East while the lower EPAI counties are mainly distributing in west. A special case in this is that EPAI in Yanyuan County in southwest is high. It's unusual in the whole west. The reason is the radiation from cities of Panzhihua and Xichang. (3)The analysis of regional poverty level based on PPAI shows that the high PPAI fields are centralizing in most of the poor counties in Liangshan and the provincial boundary of the northeast corner of Sichuan Basin. The reasons can be concluded as three typical factors, the severe natural condition, the overlarge social (population) pressure and economic basis. What's more, the poor counties in these two fields are the firstly focused points in carrying anti-poverty developing work. They should be given propriety on anti-poverty fund distribution and anti-poverty policy inclination.(4)The financial anti-poverty fund distribution case based on PPAI provided in this research, because of which is totally on the basis of the regional poverty level, it has reached the fairness and reasonability, reflecting the correspondence of regional poverty level and financial anti-poverty fund distribution, so that it can offer reference to government decision.