县域空间贫困的地理识别研究——以宁夏泾源县为例

doi:10.11821/dlxb201703014

Abstract

Abstract:

The innovation of spatial poverty measurement method is the key to precisely allocate poverty alleviation resources and improve the quality of rural poverty alleviation. This paper summarized the three-dimensional analysis framework of spatial poverty and constructed the spatial poverty index system at county scale and the method of geographical identification. With Jingyuan county as a study case, the geographical identification of spatial poverty was carried out. The results can be obtained as follows. (1) Spatial poverty index (SPI) in different geographical areas is listed in the order: Plain Area in Valleys Formed by Erosion and Deposition of Rivers (PAVFEDR) (mean value 1.571) > Denudation Structure in Hilly Regions (DSHR) (mean value -0.199) > Erosion Structure in Mountainous Regions (ESMR) (mean value -0.334), indicating that the highest poverty degree is in ESMR, which should be the main area of poverty alleviation. The common feature of spatial poverty in the three geographical areas is economic disadvantage (C₄-C₇, C₁₇). The main differences are: for PAVFEDR, ecological disadvantage (C₂₅, C₁₆) > economic disadvantage (C₅) > location disadvantage (C₂₀) > political disadvantage (C₈); for DSHR, economic disadvantage (C₅-C₇, C₁₇) > location disadvantage > (C₁₈-C₂₀) > ecological disadvantage (C₁₆, C₂₃-C₂₅) > political disadvantage (C₈); for ESMR, economic disadvantage (C₄-C₇, C₁₇) > political disadvantage (C₈) > location disadvantage (C₁₈-C₂₀) > ecological disadvantage (C₁₆, C₂₁-C₂₅). (2) The rank of SPI for different ethnic villages is as follows: Han villages (mean value 1.484) > Hui villages (mean value 1.262) > Hui-Han mixed villages (mean value 1.033), indicating that Hui-Han mixed villages at county scale should be the key villages for poverty alleviation. The common feature of spatial poverty in different ethnic villages is the economic disadvantage resulting from the long distance to the nearest market (C₁₇), as well as the ecological disadvantage due to less arable land per capita (C₂₃) and small crop area, especially economical crop area (C₂₄). The main differences of spatial poverty in different ethnic villages are ecological disadvantage resulting from poor living conditions and high disaster loss rate in Han villages, as well as economic disadvantage caused by lack of loans (C₅). For Hui villages, it is economic disadvantage caused mainly by low level of knowledge (C₁₂, C₁₃) that leads to the high opportunity cost in entering the market. In Hui-Han mixed villages the differences of production and lifestyle resulted in difficulties in allocation of poverty alleviation resources, consequently the satisfaction rate of poverty alleviation policies (C₈) is the lowest for farmers, reflecting that the political disadvantage of spatial poverty is most significant. (3) There are significant differences in spatial poverty among different ethnic villages in the same physical geographical area. The mean values of SPI for Han, Hui, and Hui-Han mixed villages in PAVFEDR are 0.526, 2.557 and 1.644, respectively, which indicates that the Han villages have a high level of poverty and economic disadvantage (C₅); the mean values of SPI for Hui and Hui-Han mixed villages in DSHR are 0.321 and -1.934, respectively, which indicates that the poverty level for Hui-Han mixed villages is high, and economic disadvantage (C₂, C₆, C₇) and ecological disadvantage (C₁₆) are both significant; the mean values of SPI in Han, Hui and Hui-Han mixed villages in ESMR are 1.031, -0.029 and -0.842, respectively, which indicates that the poverty level of Hui-Han mixed villages is high, and economic disadvantage (C₅-C₇, C₁₇), political disadvantage (C₈), location disadvantage (C₁₈-C₂₀) and ecological disadvantage (C₁₆, C₂₅) are all present. Therefore, the Han-villages in PAVFEDR, Hui-Han mixed villages in both DSHR and ESMR should be the key villages of poverty alleviation.

Key words: spatial poverty, geographical identification, geographical capital, spatial poverty index, county scale

Xiaopeng LIU, Yonghong LI, Yajuan WANG, Zhanjun GUO, Fang ZHENG. Geographical identification of spatial poverty at county scale[J].Acta Geographica Sinica, 2017, 72(3): 545-557.

Figures/Tables 9

Fig. 1

Fig. 2

Tab. 1

The indicator system of geographical identification of spatial poverty at county scale"

	维度	序号	指标名称	指标释义
地理资本 A	经济地理资本B₁	C₁	农民人均纯收入(元/人)	以2011年国家标准2300元/人为基数。
		C₂	农闲经济家庭收入贡献率(%)	反应农闲时节贫困农户创收比重。
		C₃	农村恩格尔系数(%)	反应农民的温饱状况,值越大,温饱程度越高。
		C₄	农民生活信息化程度(%)	0.2×彩色电视机普及率+0.4×电话普及率+0.4×计算机普及率。
		C₅	农户贷款满足率(%)	实际贷款金额/期望贷款金额。
		C₆	至少掌握一门致富技术农户比(%)	反应贫困农户可持续致富能力。
		C₇	至少拥有一项致富项目农户比(%)	反应贫困农户可持续致富能力。
		C₈	扶贫政策满意度(%)	包括扶贫政策对脱贫的影响程度,是否存在扶贫政策(项目)区位偏向等,反映是否存在政治劣势。
	社会地理资本B₂	C₉	农村贫困发生率(%)	村贫困人口数量/村总人口数量。
		C₁₀	农村少数民族人数比例(%)	反应不同民族生产生活方式对扶贫脱贫的作用影响。
		C₁₁	农村妇女社会地位提升程度(%)	0.25×妇女体检比率+0.2×参加村级公共事务的妇女比例+0.2×女性劳动时间与男性劳动时间比+0.2×女性平均受教育年限与男性平均受教育年限比+0.15×到本县(区)以外的地方探亲、旅游人数比。
		C₁₂	农村普及义务教育人口覆盖率(%)	反应贫困户“学有所教”社会和政治获得。
		C₁₃	农村青壮年文盲率(%)	反应贫困户“学有所教”社会和政治获得。
		C₁₄	新型农村合作医疗参合率(%)	反应贫困户“病有所医”、“老有所养”社会和政治获得。
		C₁₅	新型农村社会养老保险参保率(%)	反应贫困户“病有所医”、“老有所养”社会和政治获得。
		C₁₆	农村居民居住质量指数	0.1×人均住房面积≥25 m²户数占总户数的比例+0.05×住房结构为钢筋混凝土结构户数占总户数的比例+0.05×住房结构为砖木结构户数占总户数的比例+0.25×饮水状况为自来水的户数占总户数的比例+0.15×家庭能源为燃气和电的户数占总户数的比例+0.25×家庭水冲式卫生厕所占总户数的比例+0.1×室外道路为水泥路或柏油路户数占总户数的比例+0.05×室外道路为石头或石板等硬质路户数占总户数的比例。
	环境地理资本B₃	C₁₇	到最近集市(市场)的距离(km)	指市场的连通性(包括自然连通和人为连通),反应经济整合的脆弱性。
		C₁₈	到最近车站的距离(km)	指市场的连通性(包括自然连通和人为连通),反应经济整合的脆弱性。
		C₁₉	到最近初级中学的距离(km)	指村庄到基础设施(如卫生服务等)的距离,教育的可获得性(到学校距离和成本)。
		C₂₀	到最近乡/镇医院的距离(km)	指村庄到基础设施(如卫生服务等)的距离,教育的可获得性(到学校距离和成本)。
		C₂₁	地形起伏度(m)	代表农业生态基本条件,主要反应土地的可利用性和质量,衡量农业生产率和粮食安全。
		C₂₂	灾损率(%)
		C₂₃	人均耕地面积(hm²/人)
		C₂₄	农作物总播种面积比(%)
		C₂₅	环境质量指数(%)	0.20×生活污水处理率+0.25×生活垃圾处理率+0.30×农药使用量+0.25×化肥使用量。

Tab. 1

Fig. 3

Tab. 2

Tab. 3

Fig. 4

Fig. 5

Fig. 6

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自然地理区域类型	民族构成	样本村	总户数(户)	调查户数(户)
侵蚀堆积河谷平川区	汉族村	董庄村	282	31
	回族村	龙潭村	352	38
	回汉混居村	瓦亭村	307	33
剥蚀构造丘陵区	汉族村	-	-	-
	回族村	王家沟村	251	27
	回汉混居村	蒿店村	426	46
侵蚀构造石山区	汉族村	暖水村	227	25
	回族村	马西坡村	171	19
	回汉混居村	农林村	169	19
合计	-	8	2185	238

地理资本C	相关系数r	显著性水平t	地理资本C	相关系数r	显著性水平t
C₁	1.000	0.000	C₁₄	0.061^*	0.031
C₂	0.311^*	0.011	C₁₅	-0.243^*	0.049
C₃	0.575^**	0.000	C₁₆	0.423^**	0.000
C₄	0.077	0.159	C₁₇	-0.051	0.285
C₅	0.288^*	0.019	C₁₈	-0.082	0.215
C₆	0.223	0.072	C₁₉	-0.175	0.159
C₇	0.299^*	0.015	C₂₀	-0.130	0.297
C₈	0.345^**	0.005	C₂₁	-0.295^*	0.016
C₉	-0.310^*	0.012	C₂₂	-0.353^**	0.004
C₁₀	0.095	0.149	C₂₃	-0.201	0.106
C₁₁	-0.397^**	0.001	C₂₄	0.235	0.057
C₁₂	-0.110	0.098	C₂₅	-0.397^**	0.001
C₁₃	-0.212	0.088

Geographical identification of spatial poverty at county scale

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