南疆三地州贫困与旅游资源优势空间关联研究

doi:10.18306/dlkxjz.2016.04.012

摘要/Abstract

摘要：

2020年全面建成小康社会的目标对贫困治理更具现实意义。本文通过构建SOFM神经网络评估模型,聚类分析南疆三地州24个县市的经济--社会--自然多维度贫困。在评价县域旅游资源优势度的基础上,运用空间数据分析方法(ESDA)分析研究区县域贫困度和旅游资源优势度的空间分布格局,将两者在空间匹配后发现：①致贫因子集合向量的Matlab分类显示,南疆三地州各县市贫困类型可划分为经济型贫困、社会型贫困和生态型贫困,并且贫困空间聚合分布态势显著。②旅游资源优势区集中在地理环境结构复杂和多民族聚居的地区,如喀什市、塔县、阿克陶县、和田市;旅游资源优势区局域空间自相关呈现集群分布特征。③贫困类型与旅游资源优势在县域存在显著的空间关联,出现3类拟合性较好的区域。建议采取“旅游+旧城改造”和“旅游+商品基地”、“领头雁”旅游扶贫等旅游扶贫模式。

关键词: 经济--社会--自然多维度贫困, 空间数据分析, 旅游扶贫, SOFM网络聚类, 南疆三地州

Abstract:

This study constructed a self-organizing feature map (SOFM) clustering neural network model to evaluate economic-social-ecological poverty for 24 counties in three southern prefectures of Xinjiang Autonomous Region, constructed the evaluation model of regional tourism resources development, and analyzed the spatial distribution patterns of poverty and tourism resources development advantages in the study area with spatial data analysis method (ESDA). By matching the spatial patterns: (1) Factors of poverty-inducing set Matlab classification vector show that the type of southern counties under poverty can be divided into economic, social, and ecological poverty and there is a clear trend of spatial aggregation of poor counties. (2) Places with advanced tourism resources development are concentrated in areas where the geographical environment structure is complex and multiple ethnic communities reside, such as Kashi, Taxian County, Akto, and Hetian. Advanced tourism resources development areas show clear spatial autocorrelation and are distributed in clusters. (3) There is a significant spatial correlation between poverty and tourism resources development.

Key words: economic-social-ecological poverty, spatial data analysis, poverty elimination by tourism, SOFM clustering, three prefectures in South Xinjiang

安强, 杨兆萍, 徐晓亮, 时卉, 张璐. 南疆三地州贫困与旅游资源优势空间关联研究[J]. 地理科学进展, 2016, 35(4): 515-525.

Qiang AN, Zhaoping YANG, Xiaoliang XU, Hui SHI, Lu ZHANG. Spatial correlation of poverty and tourism resources in three prefactures in South Xinjiang[J]. PROGRESS IN GEOGRAPHY, 2016, 35(4): 515-525.

图/表 7

图1

表1

南疆三地州贫困评价指标体系及释义"

维度	解释	指标	指示内容
经济维度(A1)	总体水平(B1)	人均GDP(C1)	贫困县的宏观经济运行状况
	总体水平(B1)	人均财政扶贫资金(C2)	专项资金对贫困地区发展经济和社会事业的支持力
	发展能力(B2)	农林牧渔产值(C3)	贫困县农业生产总规模和总成果
		特色农作物产量(C4)	建设旅游商品生产加工基地的潜力
		农村居民人均纯收入(C5)	贫困居民再生产能力
		人均财政收入(C6)	政府资金配置能力
		人均旅游收入(C7)	旅游业对贫困县经济支持力
		人均住房建筑面积(C8)	贫困人口居住条件
社会维度(A2)	基础设施(B3)	通车里程(C9)	贫困人口交通条件;游客与商品运输通达性
		人均快递业务量(C10)	贫困人口网络消费能力;电子商务交易能力
		人均互联网占有率(C11)	贫困人口对外联系畅通性;旅游业线上交易基础
	卫生医疗(B4)	医院和卫生院的人均床位数(C12)	贫困地区医疗水平
	卫生医疗(B4)	有卫生室的行政村数(C13)	村级医疗覆盖能力
	教育科技(B5)	青壮年文盲率(C14)	参与现代化大生产的能力
		平均受教育年限(C15)	知识多寡及学习能力
		双语教育覆盖率(C16)	与其他民族(主要指汉族)交往能力
		农村大专以上教育人口(C17)	个人修养、资源获取能力
自然维度(A3)	生存条件(B6)	县域平均海拔(C18)	农作物生长条件、农产品质量、游客舒适度
		地形起伏度(C19)	农作物生长条件、游客舒适度、旅游资源存在潜力
		综合灾情指数(C20)	生存条件、自然灾害影响程度
		初级净生产力(C21)	温度、降水等环境生态生产力
		多年平均气温(C22)	农业发展能力、农产品质量、游客舒适度
	土地利用度(B1)	植被指数(C23)	植物生长状况、生存环境优劣
	土地利用度(B1)	地形破碎度(C24)	地形复杂程度,旅游资源存在潜力

表1

表2

图2

图3

图4

图5

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人均GDP	相关系数r	显著性水平t	农林牧渔产值	相关系数r	显著性水平t
C2	0.703	0.077	C18	-0.641^**	0.008
C3	0.662	0.061	C19	-0.761^*	0.034
C4	0.538	0.062	C20	-0.650^**	0.036
C5	0.735^**	0.001	C21	0.465^**	0.036
C6	0.618^*	0.068	C22	-0.538	0.059
C7	0.832^*	0.059	C23	0.610^*	0.025
C8	0.432	0.071	C24	-0.046^*	0.042
C9	0.542	0.066
C10	0.454^*	0.041
C11	0.656^*	0.035
C12	0.551	0.051
C13	0.712^**	0.007
C14	-0.554	0.068
C15	0.615	0.071
C16	0.454^*	0.084
C17	0.412	0.069