山区农村贫困化分异机制探讨
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摘要
山区农村贫困问题是中国普遍关注的社会问题之一,探讨贫困化分异机制对山区贫困农村的发展具有重大意义。以重庆市巫山县为例,运用地理探测器、多元线性回归等模型方法诊断出山区农村贫困化分异的主导因素,结果表明,海拔高度、到县城中心距离、到乡镇中心距离、到主要干道距离和坡耕地占比是影响山区农村贫困化的主导因素;根据巫山县各乡镇贫困分异的主导因素,划分出农村贫困化地域类型;针对影响因素不同的地域类型提出不同的政策措施。
The mountainous rural poverty problem is the one of sharpest social problems in China. It is significant to research the poverty differentiation mechanism of mountainous rural areas for countryside development. Taking Wushan county in Chongqing as an example, the paper diagnoses the dominant factors of differentiation of rural poverty by using the geographical detector model and multiple linear regressions. The results showed that altitude, distance from the center of the county town and the township center, distance to the main roads and proportion of slope farmland are the leading factors affecting the impoverishment of rural areas in mountain areas. According to the leading factors of poverty differentiation in different townships and towns in Wushan county, the types of rural poverty areas are divided. Different policy measures are proposed for different geographical types of influencing factors.
The mountainous rural poverty problem is the one of sharpest social problems in China. It is significant to research the poverty differentiation mechanism of mountainous rural areas for countryside development. Taking Wushan county in Chongqing as an example, the paper diagnoses the dominant factors of differentiation of rural poverty by using the geographical detector model and multiple linear regressions. The results showed that altitude, distance from the center of the county town and the township center, distance to the main roads and proportion of slope farmland are the leading factors affecting the impoverishment of rural areas in mountain areas. According to the leading factors of poverty differentiation in different townships and towns in Wushan county, the types of rural poverty areas are divided. Different policy measures are proposed for different geographical types of influencing factors.
引文
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[13]王劲峰,胡艺.基于地理探测器的环境健康风探测[J].环境建模与软件,2012,33(7):114-115.
[14]王劲峰,李新虎,CHRISTAKOS G,等.基于地理探测器的健康风险评估及其在神经管缺陷的应用:以中国和顺地区为例[J].国际地理信息科学杂志,2010,24:107-127.
[15]毕硕本,计晗,陈昌春,等.地理探测器在史前聚落人地关系研究中的应用与分析[J].地理科学进展,2015,34(1):118-127.
[16]刘彦随,周扬,刘继来.中国农村贫困化地域分异特征及其精准扶贫策略[J].中国科学院院刊,2016,31(3):269-278.
[17]丁悦,蔡建明,任周鹏,等.基于地理探测器的国家级经济技术开发区经济增长率空间分异及影响因素[J].地理科学进展,2014,33(5):657-666.
[2]王介勇,陈玉福,严茂超.我国精准扶贫政策及其创新路径研究[J].中国科学院院刊,2016,31(3):289-295.
[3]黄承伟,覃志敏.我国农村贫困治理体系演进与精准扶贫[J].开发研究,2015(2):56-59.
[4]骆祚炎.利用线性支出系统ELES测定贫困线的实证分析——兼比较几种贫困标准[J].当代财经,2006(3):5-10.
[5]叶初升,罗连发.社会资本、扶贫政策与贫困家庭福利——基于贵州贫困地区农村家户调查的分层线性回归分析[J].财经科学,2011(7):100-109.
[6]许月卿,李双成,蔡运龙.基于GIS和人工神经网络的区域贫困化空间模拟分析——以贵州省猫跳河流域为例[J].地理科学进展,2006(3):79-85,140.
[7]罗翔,卢新海,项歌德.消费风险、科技抑制与中国农村贫困化——基于湖北、安徽两省的实证分析[J].中国人口科学,2014(3):104-114,128.
[8]刘彦随,李进涛.中国县域农村贫困化分异机制的地理探测与优化决策[J].地理学报,2017,72(1):161-173.
[9]刘艳华,徐勇.中国农村多维贫困地理识别及类型划分[J].地理学报,2015,70(6):993-1007.
[10]赵珂,于立.定性与定量相结合:综合集成的数字城市规划[J].城市发展研究,2014,21(2):83-90.
[11]陈旭.重庆地方城市形态的比较研究(1646-1840)[D].重庆:西南大学,2015.
[12]夏添,常鸣.改进逻辑回归方法在滑坡敏感性评价中的应用研究[J].物探化探计算技术,2013,35(2):185-188,119-120.
[13]王劲峰,胡艺.基于地理探测器的环境健康风探测[J].环境建模与软件,2012,33(7):114-115.
[14]王劲峰,李新虎,CHRISTAKOS G,等.基于地理探测器的健康风险评估及其在神经管缺陷的应用:以中国和顺地区为例[J].国际地理信息科学杂志,2010,24:107-127.
[15]毕硕本,计晗,陈昌春,等.地理探测器在史前聚落人地关系研究中的应用与分析[J].地理科学进展,2015,34(1):118-127.
[16]刘彦随,周扬,刘继来.中国农村贫困化地域分异特征及其精准扶贫策略[J].中国科学院院刊,2016,31(3):269-278.
[17]丁悦,蔡建明,任周鹏,等.基于地理探测器的国家级经济技术开发区经济增长率空间分异及影响因素[J].地理科学进展,2014,33(5):657-666.