河北省县域贫困度多维评估
Multidimensional evaluation of county poverty degree in Hebei Province
查看参考文献22篇
|
文摘
|
在京津冀加快区域经济一体化的背景下,河北省出现环绕京津地区的贫困带引起了学界与公众的普遍关注。目前国内贫困县的设定往往以经济指标为唯一度量标准,本文在经济维度基础上增加社会维度(代表人类贫困)和自然维度(代表自然贫困)两方面评价指标,构建县域贫困度多维评价指标体系,对河北省136个县的贫困状况分别进行经济单维度与经济—社会—自然三维评估,并基于SOFM网络将全省县域贫困度划分为五级,与河北省现有各类贫困县分布进行对比。结果表明,基于经济单维度与经济—社会—自然多维度评估的聚类分析得到的高贫困度县域均与现有贫困县有很好的对应,与河北省贫困县分布现状基本吻合;由于经济—社会—自然的多维度贫困度评估综合考虑了贫困现状及其潜在可能性,评估更加全面和深入。基于自然维度的潜在贫困度对多维贫困度的影响分析表明:环京津地区的贫困现状比较严重、且潜在贫困程度高,应积极依托京津,承接产业转移。而在冀中南地区,尽管贫困现状较为严重,但潜在贫困程度较低,因其较易脱贫而容易被忽视;同时,还存在大量非贫困县转化为贫困县的可能性;应进一步加强对该地区贫困问题的关注,分类扶贫、防治结合、区域联动,促进京津冀区域一体化、社会财富同步增长。 |
|
其他语种文摘
|
With the economic integration of the Beijing-Tianjin-Hebei Region, there exists a poverty belt around Beijing and Tianjin within Hebei Province, which has received attention from academia and the public, so as to put the setting standards of poor counties into the spotlight. Despite some applications of not merely economic indicators but also social and natural indexes to identify poverty in academic researches, the setting of poor counties is only based on economic indicators in China. This paper adds indicators in social dimension representing human poverty and in natural dimension representing natural poverty to build a multidimensional poverty index system, and utilizes SOFM (self-organizing feature mapping) nonlinear clustering tool to classify all of the 136 counties in Hebei Province into 5 categories in view of the county poverty degree by the economic dimension & economic-social-natural dimensions separately. Clustering maps are compared with the map of currently poor counties in Hebei Province afterwards. The results show that the counties with low grades are the ones with high poverty degree. Meanwhile, counties with low grades are the majority, suggesting a high poverty degree all over Hebei Province. About the clustering results, whether in the single economic dimension or economic-social-natural dimensions, they are both consistent with the current distribution pattern of poor counties in Hebei Province which helps the transformation of "relative poverty" to "absolute poverty". Besides, in comparison to the results based on the single (economic) dimension, multidimensional (economic-social-natural) evaluation is more comprehensive because it takes current situation and potential of poverty into overall consideration. Furthermore, potential poverty degree in the natural dimension influences the comprehensive poor degree, indicating that both the current and potential poverty degree of poverty areas around Beijing and Tianjin are high and the region should cooperate with Beijing and Tianjin actively. In contrast, the potential poverty degree of poor counties in the south and middle Hebei Province is relatively low and the region is more easily to be lifted out of poverty. Moreover, these regions covers many counties that are not considered to be poor ones but very likely to become poor ones. Therefore, these regions deserve more attention and being treated differently. To make advances in the poverty relief and development work, the government should not only deal with things distinctively but also combine prevention with treatment and link the areas together. In this way we can expect the achievement of Beijing-Tianjin-Hebei coordinated development and the harmoniously simultaneous growth of wealth of society. |
|
来源
|
地理科学进展
,2014,33(1):124-133 【核心库】
|
|
关键词
|
经济—社会—自然
;
多维贫困度
;
SOFM
;
潜在贫困度
;
河北省
|
|
地址
|
北京大学城市与环境学院, 地表过程分析与模拟教育部重点实验室, 北京, 100871
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
1007-6301 |
|
基金
|
国家自然科学基金重点项目
|
|
文献收藏号
|
CSCD:5044421
|
参考文献 共
22
共2页
|
|
1.
陈扬乐. 湖南县域经济发展水平的空间差异与扶贫开发.
经济地理,2003,23(2):183-186
|
CSCD被引
7
次
|
|
|
|
|
2.
方迎风. 中国贫困的多维测度.
当代经济科学,2012,34(4):7-15
|
CSCD被引
5
次
|
|
|
|
|
3.
郝成元. 基于SOFM的区域界线划分方法.
地理科学进展,2008,27(5):121-127
|
CSCD被引
17
次
|
|
|
|
|
4.
胡芳肖. 基于量图分析法的中国贫困省区划分研究.
人文地理,2011,26(5):82-87
|
CSCD被引
2
次
|
|
|
|
|
5.
黄姣. 基于GIS与SOFM网络的中国综合自然区划.
地理研究,2011,30(9):1648-1659
|
CSCD被引
27
次
|
|
|
|
|
6.
李佳. 基于县域要素的三江源地区旅游扶贫模式探讨.
资源科学,2009,31(11):1818-1824
|
CSCD被引
23
次
|
|
|
|
|
7.
李双成. 青藏高原生态资产地域划分中的SOFM网络技术.
自然资源学报,2002,17(6):750-756
|
CSCD被引
23
次
|
|
|
|
|
8.
陆康强. 加法可分性贫困指数的比较研究.
统计研究,2009,26(7):98-103
|
CSCD被引
1
次
|
|
|
|
|
9.
马程. 基于SOFM网络的京津冀地区生态系统服务分区.
地理科学进展,2013,32(9):1383-1393
|
CSCD被引
33
次
|
|
|
|
|
10.
毛汉英. 县域经济和社会同人口、资源环境协调发展研究.
地理学报,1991,46(4):385-395
|
CSCD被引
41
次
|
|
|
|
|
11.
沈红. 中国贫困研究的社会学评述.
社会学研究,2000,2(9):91-103
|
CSCD被引
1
次
|
|
|
|
|
12.
孙强. 基于SOFM网络的中国耕地压力综合分区.
北京大学学报: 自然科学版,2008,44(4):625-631
|
CSCD被引
11
次
|
|
|
|
|
13.
王卫.
河北地理,2012
|
CSCD被引
7
次
|
|
|
|
|
14.
王小林. 中国多维贫困测量:估计和政策含义.
中国农村经济,2009,25(12):4-10
|
CSCD被引
80
次
|
|
|
|
|
15.
许月卿. 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.
地理科学进展,2006,25(3):79-85, 140
|
CSCD被引
26
次
|
|
|
|
|
16.
叶敏婷. 基于SOFM网络的云南省土地利用程度类型划分研究.
地理科学进展,2007,26(2):97-105
|
CSCD被引
14
次
|
|
|
|
|
17.
曾永明. 基于GIS和BP神经网络的区域农村贫困空间模拟分析----一种区域贫困程度测度新方法.
地理与地理信息科学,2011,27(2):70-75
|
CSCD被引
17
次
|
|
|
|
|
18.
赵跃龙. 中国脆弱生态环境分布及其与贫困的关系.
人文地理,1996,11(2):1-7
|
CSCD被引
25
次
|
|
|
|
|
19.
周杜辉. 陕西省县域综合发展水平空间分异及机理.
地理科学进展,2011,30(2):205-214
|
CSCD被引
10
次
|
|
|
|
|
20.
邹薇. 怎样测度贫困: 从单维到多维.
国外社会科学,2012,35(2):63-69
|
CSCD被引
4
次
|
|
|
|
|
了解气象卫星更多信息，请访问