地理学报 ›› 2020, Vol. 75 ›› Issue (4): 753-768.doi: 10.11821/dlxb202004007
收稿日期:
2019-05-29
修回日期:
2020-02-10
出版日期:
2020-04-25
发布日期:
2020-06-25
作者简介:
李寻欢(1998-), 男, 重庆彭水人, 硕士生, 主要从事农村减贫与发展研究。E-mail: lixh.19s@igsnrr.ac.cn
基金资助:
LI Xunhuan1,2,3, ZHOU Yang1,2,3(), CHEN Yufu1,2,3
Received:
2019-05-29
Revised:
2020-02-10
Published:
2020-04-25
Online:
2020-06-25
Supported by:
摘要:
贫困包括区域贫困和个体贫困,两者均具有多维属性。区域多维贫困是贫困地理学研究的重要内容,深度贫困地区是区域多维贫困的集中表现,是当前和未来脱贫攻坚的贫中之贫、困中之困、坚中之坚。本文以空间贫困理论为基础,界定了贫困地域系统和区域多维贫困的概念,并探究了区域多维贫困测度指标体系与评估方法。据此,以中国334个深度贫困县为研究对象,运用BP神经网络模型和ESDA技术刻画了中国深度贫困地区的多维贫困空间格局。结果表明:① 区域多维贫困是贫困地域系统发展演化过程中“人”“地”“业”三个核心要素耦合失调的一种外在表现形式,是特定地域在生态环境劣势、经济劣势、社会福利劣势上的综合表现,包括生态贫困、经济贫困和福利贫困3个维度。② 深度贫困地区最“深”的地方在青藏高原,最“深”的短板在公共服务和基础设施。从单一维度的贫困指数来看,深度贫困地区的福利贫困指数(WPI)>经济贫困指数(EPI)>生态贫困指数(NPI),三者平均值分别为2.77、2.66、1.89,贫困人口社会福利供给不足和公共服务短缺是深度贫困地区最突出的问题;从多维贫困指数来看,青藏高原是区域多维贫困指数(RMP)的高集聚区或热点区,生态贫困、经济贫困和福利贫困程度均显著高于其他地区。③ 区域多维贫困指数能较好地揭示特定区域的贫困状况。在地理位置偏远、生态环境极其脆弱、区域劣势突出的地区,区域贫困和个体贫困在空间上高度重叠。
李寻欢, 周扬, 陈玉福. 区域多维贫困测量的理论与方法[J]. 地理学报, 2020, 75(4): 753-768.
LI Xunhuan, ZHOU Yang, CHEN Yufu. Theory and measurement of regional multidimensional poverty[J]. Acta Geographica Sinica, 2020, 75(4): 753-768.
表1
区域多维贫困测量指标
维度 | 编码 | 指标 | 指标释义 |
---|---|---|---|
生态贫困 | X1 | 平均海拔(m) | 县域平均DEM高程 |
X2 | 地表起伏度(m) | 县域栅格单元的高程范围 | |
X3 | 坡度大于25°土地面积占比(%) | 地表坡度大于25°的土地面积占比 | |
X4 | 生态脆弱区面积占比(%) | 土地沙化区和土壤强度侵蚀区的面积占比 | |
X5 | 人均耕地面积(m2/人) | 水田、旱地的总面积除以户籍人口 | |
经济贫困 | X6 | 人均GDP(元) | 地区生产总值/常住人口 |
X7 | 人均财政收入(元) | 公共财政预算收入/户籍人口 | |
X8 | 固定资产投资(万元) | 社会固定资产投资总额 | |
X9 | 路网密度(km/km2) | 县域交通道路里程/总面积 | |
X10 | 到铁路干线的最短距离(km) | 县域几何中心到铁路干线的最短距离 | |
福利贫困 | X11 | 在校学生数(人) | 普通中学、中职、小学在校学生总数 |
X12 | 平均受教育年限(年) | 居民受教育的平均年限长度 | |
X13 | 医疗卫生机构床位数(床/千人) | 医疗卫生机构床位数/常住人口 | |
X14 | 社会福利性单位床位数(床/千人) | 社会福利性单位床位数/常住人口 |
表2
区域贫困指数BP网络模型的评价标准
NPI | X1 | X2 | X3 | X4 | X5 | 等级 | |||
---|---|---|---|---|---|---|---|---|---|
1 | 1 | 1 | 1 | 1 | 5(高) | ||||
0.8001 | 0.5126 | 0.6636 | 0.6218 | 0.9946 | 4(较高) | ||||
0.5605 | 0.3317 | 0.3932 | 0.3468 | 0.9767 | 3(中) | ||||
0.3331 | 0.2176 | 0.2336 | 0.1735 | 0.9260 | 2(较低) | ||||
0.1533 | 0.1151 | 0.0896 | 0.0614 | 0.0000 | 1(低) | ||||
EPI | X6 | X7 | X8 | X9 | X10 | 等级 | |||
1 | 1 | 1 | 1 | 1 | 5(高) | ||||
0.8504 | 0.9760 | 0.9159 | 0.4288 | 0.9318 | 4(较高) | ||||
0.7531 | 0.9493 | 0.8129 | 0.2366 | 0.8694 | 3(中) | ||||
0.6383 | 0.8901 | 0.6665 | 0.1153 | 0.7630 | 2(较低) | ||||
0.4488 | 0.4202 | 0.3832 | 0.0425 | 0.4770 | 1(低) | ||||
WPI | X11 | X12 | X13 | X14 | 等级 | ||||
1 | 1 | 1 | 1 | 5(高) | |||||
0.9250 | 0.7248 | 0.9245 | 0.9609 | 4(较高) | |||||
0.8312 | 0.5046 | 0.8763 | 0.9181 | 3(中) | |||||
0.6857 | 0.3224 | 0.7686 | 0.8423 | 2(较低) | |||||
0.3970 | 0.1992 | 0.0000 | 0.0000 | 1(低) |
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