【摘要】：農(nóng)村貧困空間是社會(huì)空間不可分割的一部分,其分布特征和演變機(jī)理研究一直為鄉(xiāng)村地理學(xué)和農(nóng)村社會(huì)學(xué)研究的主要內(nèi)容之一。農(nóng)村貧困格局、貧困風(fēng)險(xiǎn)及調(diào)控研究對(duì)于識(shí)別貧困因素、制作農(nóng)村貧困地圖和豐富農(nóng)村貧困理論、制定地區(qū)扶貧政策都具有重要的理論和現(xiàn)實(shí)意義。本研究突破傳統(tǒng)的單一收入貧困理論,從地理空間視角著手研究農(nóng)村貧困問(wèn)題,構(gòu)建涵蓋自然、經(jīng)濟(jì)和社會(huì)三大方面的村域空間貧困地理資本指標(biāo),分解為26個(gè)原始指標(biāo)或生成指標(biāo)。將地貌資料查閱和地理信息技術(shù)地形診斷相結(jié)合,對(duì)研究各縣區(qū)的地貌進(jìn)行劃分；運(yùn)用簡(jiǎn)單隨機(jī)抽樣方法和層權(quán)分配法計(jì)算和分配樣本村和樣本戶量：通過(guò)參與式農(nóng)村評(píng)估法和滾雪球調(diào)查法進(jìn)村入戶獲取調(diào)研數(shù)據(jù),并對(duì)地理資本體系進(jìn)行分解以獲取研究所需的生成數(shù)據(jù)；基于MATLAB2013a,借助BP神經(jīng)網(wǎng)絡(luò)方法對(duì)研究區(qū)致貧、消貧因素進(jìn)行空間模擬,輸出致貧指數(shù)和消貧指數(shù),并通過(guò)差運(yùn)算和條件約束得出和識(shí)別空間貧困指數(shù)和貧困風(fēng)險(xiǎn)區(qū),最后通過(guò)ArcGIS的空間表達(dá)模塊,完成各縣區(qū)貧困地圖制作。研究發(fā)現(xiàn)：(1)經(jīng)濟(jì)落后不是寧夏六盤(pán)山區(qū)之所以貧困的重要原因,經(jīng)濟(jì)因素是消貧因素,僅是在緩解貧困的程度上各異；自然因素是導(dǎo)致地區(qū)貧困的主要因素,而社會(huì)因素在貧困地區(qū)較多地呈現(xiàn)致貧性。(2)貧困分布和地貌類(lèi)型呈現(xiàn)出很強(qiáng)的空間相關(guān)性。整體上,河谷平川區(qū)消貧能力較強(qiáng)而致貧指數(shù)相對(duì)較低；相反,黃土丘陵區(qū)和土石質(zhì)山區(qū)消貧能力弱而致貧指數(shù)相對(duì)較高。(3)寧夏六盤(pán)山貧困風(fēng)險(xiǎn)區(qū)與重度貧困區(qū)具有較強(qiáng)的一致性,貧困風(fēng)險(xiǎn)區(qū)主要位于第三列弧形山地、葫蘆河西南部、茹河北部、隆德縣南部整個(gè)黃土丘陵區(qū)和同心縣的中部干旱山區(qū)。(4)研究發(fā)現(xiàn),寧夏六盤(pán)山區(qū)貧困和風(fēng)險(xiǎn)較高是自然因素主導(dǎo)其他因素相互交織的結(jié)果。經(jīng)濟(jì)方面,貧困地區(qū)生活信息化程度低、農(nóng)戶貸款難、農(nóng)閑經(jīng)濟(jì)家庭收入貢獻(xiàn)率不高等問(wèn)題導(dǎo)致經(jīng)濟(jì)的緩貧作用得不到彰顯；社會(huì)方面,貧困人口多、勞動(dòng)力文盲率高、社會(huì)保障體系覆蓋不全、居民居住質(zhì)量低下是主要的社會(huì)致貧原因；距離成本高、地形起伏度高、農(nóng)業(yè)災(zāi)損率高是重要的自然致貧因素。(5)貧困是地區(qū)的貧困,地區(qū)貧困導(dǎo)致了人的貧困。遵循貧困動(dòng)態(tài)性、地理性、系統(tǒng)性的基本特點(diǎn),構(gòu)建“內(nèi)源發(fā)展,外源拉動(dòng)”的基本脫貧思路,提出了針對(duì)性較強(qiáng)的內(nèi)源性和外源性的脫貧調(diào)控對(duì)策。
[Abstract]:Rural poverty space is an inseparable part of social space. The study of its distribution characteristics and evolution mechanism has been one of the main contents of rural geography and rural sociology. The study of rural poverty pattern, poverty risk and adjustment and control has important theoretical and practical significance in identifying poverty factors, making maps of rural poverty and enriching rural poverty theory, and formulating regional poverty alleviation policies. This study breaks through the traditional theory of single income poverty, studies the problem of rural poverty from the perspective of geographical space, and constructs the geographical capital index of rural spatial poverty covering natural, economic and social aspects. Decomposed into 26 original indicators or generated indicators. Combining geomorphological data retrieval with geographic information technology (GIS) topographic diagnosis, the geomorphology of each county and district is divided. Simple random sampling method and layer weight distribution method are used to calculate and distribute sample villages and sample households. And the geographical capital system is decomposed to obtain the generated data needed by the research. Based on MATLAB2013a, BP neural network method is used to simulate the poverty and poverty reduction factors in the study area, and the poverty index and poverty reduction index are outputted, and the spatial poverty index and the poverty risk area are obtained and identified by differential operation and conditional constraints. Finally, through the spatial expression module of ArcGIS, the poverty map of each county and district is made. The results show that: (1) the economic backwardness is not the important reason of poverty in Liupan Mountain area of Ningxia, the economic factor is the anti-poverty factor, but the degree of alleviating poverty is different; Natural factors are the main factors leading to poverty in the region, while social factors are more likely to cause poverty in poor areas. (2) the distribution of poverty and the types of landforms show strong spatial correlation. On the whole, the ability of eliminating poverty is stronger and the index of causing poverty is relatively low in Pingchuan district of river valley. On the contrary, the poverty reduction ability of loess hilly area and the soil-stone mountain area is weak and the poverty index is relatively high. (3) the poverty risk area of Liupanshan Mountain in Ningxia is consistent with that of the severe poverty area, and the poverty risk area is mainly located in the third row arc mountain area. The southern part of Hulu River, Ru Hebei part, the whole loess hilly area in the south of Longde County and the central arid mountain area of Tongxin County. (4) the study found that the poverty and high risk in Liupan mountain area of Ningxia are the result of the intertwining of other factors dominated by natural factors. In terms of economy, the poor areas have low level of life informatization, difficult loans for farmers, and low contribution rate of household income to the rural leisure economy, which lead to economic poverty alleviation. In terms of society, the poor population, the high illiteracy rate of labor force, the incomplete coverage of social security system and the poor living quality of residents are the main causes of social poverty. High distance cost, high terrain fluctuation and high agricultural damage rate are important natural poverty factors. (5) Poverty is regional poverty, which leads to human poverty. Following the basic characteristics of poverty dynamics, rationality and systematicness, this paper constructs the basic idea of "endogenous development and exogenous pull", and puts forward some countermeasures of anti-poverty regulation and control.
【學(xué)位授予單位】：寧夏大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：F323.8

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