西北地区县域脆弱性时空格局演变

doi:10.18306/dlkxjz.2017.04.002

摘要/Abstract

摘要：

人地耦合系统的脆弱性研究作为未来地理科学的十大科学研究命题之一,已成为人地关系和区域可持续发展研究的重要领域。本文以西北地区316个县(市)为研究单元,以2003、2008和2013年社会经济统计数据、气象数据、遥感影像数据和空间矢量数据为基础,综合运用模糊层次分析和变异系数分析等方法,构建西北地区人地系统脆弱性评价模型并说明其时空演化过程。研究表明：①西北地区县域脆弱性指数整体呈现北低南高、东低西高的格局。大中型城市对周边区域产生显著的影响并已形成以自身为核心的低脆弱圈层,各低脆弱圈层逐渐关联形成大范围的低脆弱片区;②4个子系统的脆弱性水平分别表现出一定的地域分异格局,社会子系统和经济子系统脆弱性的空间集聚特征明显且变化显著,资源环境子系统和政策子系统脆弱性则趋于碎片化且相对稳定;③西北地区人地系统脆弱性的空间差异度呈缓慢增大趋势,社会脆弱性差异度的变化趋势为先增加后下降,经济脆弱性与资源环境脆弱性差异度均表现出持续下降的态势,政策扶持性在地区间的差异较大且整体格局稳定;④在政策的引导和扶持下,资源开发促使经济发展、环境质量和人类福祉发生转变,最终影响社会发展水平和社会的稳定程度,而社会的发展和稳定又反作用于经济发展、环境质量、资源开发和政策制定。本文以“脆弱性”的视角解构西北地区人地系统时空动态变化过程,为西北地区社会经济发展提供理论方法参考和实践应用借鉴。

关键词: 人地系统脆弱性, 模糊层次分析法, 区域差异, 西北地区

Abstract:

As one of the most important scientific research propositions in the field of geographic studies, the research on coupled human-environment system has become an important part of the study of human-environment relationship and regional sustainable development. This study constructed a human-environment system evaluating model of vulnerability in counties of northwest China and its spatial and temporal change based on statistical data, meteorological data, remote sensing data, and spatial vector data in 2003, 2008, and 2013 for 316 counties and districts, using the fuzzy analytic hierarchy process (FAHP) method and coefficient of variation analysis. The results show that: (1) Vulnerability index values of counties in the south are higher than in the north and the west higher than the east. The large and medium-sized cities have a significant impact on surrounding counties and have formed some low vulnerability circles centered around them. Meanwhile, these circles are gradually connected to become large scale low vulnerability areas. (2) The vulnerable levels of four subsystems in northwest China also reveal some regional differentiation patterns. The spatial pattern of vulnerability in social and economic subsystems is congregated and has changed significantly. The spatial pattern of vulnerability of resource-environment and support of policy subsystems tends to be fragmented and stable. (3) The vulnerability diversity of the human-environment system slowly increased in northwest China, the vulnerability diversity of social system first increased and then dropped, the vulnerability diversity of both the economic and the resource-environment systems tends to fall, and the policy support systems are significantly different and stable among different regions. (4) Under policy guidance and support, resource exploitation, economic development, environmental quality, and human wellbeing change becomes coupled, which influence social development and stability. Meanwhile, these two factors react upon economic development, environmental quality, resource exploitation, and policy making. This article deconstructs spatial and temporal changes in northwest China from the perspective of "vulnerability" and aims to provide a theoretical reference and practical application for socioeconomic development in northwest China.

Key words: human-environment system vulnerability, fuzzy analytic hierarchy process, regional differences, northwest China

鲁大铭, 石育中, 李文龙, 杨新军. 西北地区县域脆弱性时空格局演变[J]. 地理科学进展, 2017, 36(4): 404-415.

Daming LU, Yuzhong SHI, Wenlong LI, Xinjun YANG. Spatiotemporal change of vulnerability in counties of northwest China[J]. PROGRESS IN GEOGRAPHY, 2017, 36(4): 404-415.

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参考文献 37

[1]	陈佳, 杨新军, 尹莎, 等. 2016. 基于VSD框架的半干旱地区社会: 生态系统脆弱性演化与模拟[J]. 地理学报, 71(7): 1172-1188. doi: 10.11821/dlxb201607007
	[Chen J, Yang X J, Yin S, et al.2016. The vulnerability evolution and simulation of the social: Ecological systems in the semi-arid area based on the VSD framework[J]. Acta Geographica Sinica, 71(7): 1172-1188.] doi: 10.11821/dlxb201607007
[2]	方创琳, 王岩. 2015. 中国城市脆弱性的综合测度与空间分异特征[J]. 地理学报, 70(2): 234-247. doi: 10.11821/dlxb201502005
	[Fang C L, Wang Y.2015. A comprehensive assessment of urban vulnerability and its spatial differentiation in China[J]. Acta Geographica Sinica, 70(2): 234-247.] doi: 10.11821/dlxb201502005
[3]	方修琦, 殷培红. 2007. 弹性、脆弱性和适应: IHDP三个核心概念综述[J]. 地理科学进展, 26(5): 11-22. doi: 10.3969/j.issn.1007-6301.2007.05.002
	[Fang X Q, Yin P H.2007. Review on the three key concepts of resilience, vulnerability and adaptation in the research of global environmental change[J]. Progress in Geography, 26(5): 11-22.] doi: 10.3969/j.issn.1007-6301.2007.05.002
[4]	韩瑞玲, 佟连军, 佟伟铭, 等. 2012. 基于集对分析的鞍山市人地系统脆弱性评估[J]. 地理科学进展, 31(3): 344-352. doi: 10.11820/dlkxjz.2012.03.010
	[Han R L, Tong L J, Tong W M, et al.2012. Research on vulnerability assessment of human-land system of Anshan City based on set pair analysis[J]. Progress in Geography, 31(3): 344-352.] doi: 10.11820/dlkxjz.2012.03.010
[5]	李凤民, 徐进章, 孙国钧. 2003. 半干旱黄土高原退化生态系统的修复与生态农业发展[J]. 生态学报, 23(9): 1901-1909.
	[Li F M, Xu J Z, Sun G J.2003. Restoration of degraded ecosystems and development of water-harvesting ecological agriculture in the semi-arid Loess Plateau of China[J]. Acta Ecologica Sinica, 23(9): 1901-1909.]
[6]	刘学录, 任继周. 2002. 河西走廊山地—绿洲—荒漠复合系统耦合的景观生态学机制[J]. 应用生态学报, 13(8): 979-984.
	[Liu X L, Ren J Z.2002. Landscape ecological mechanism on system coupling of the meta-ecosystem consisted of mountain, desert and oasis in Hexi Corridor, Gansu, China[J]. Chinese Journal of Applied Ecology, 13(8): 979-984.]
[7]	刘毅, 黄建毅, 马丽. 2010. 基于DEA模型的我国自然灾害区域脆弱性评价[J]. 地理研究, 29(7): 1153-1162. doi: 10.11821/yj2010070001
	[Liu Y, Huang J Y, Ma L.2010. The assessment of regional vulnerability to natural disasters in China based on DEA model[J]. Geographical Research, 29(7): 1153-1162.] doi: 10.11821/yj2010070001
[8]	彭建, 王仰麟, 张源, 等. 2004. 滇西北生态脆弱区土地利用变化及其生态效应: 以云南省永胜县为例[J]. 地理学报, 59(4): 629-638.
	[Peng J, Wang Y L, Zhang Y, et al.2004. Land use change and its ecological effect in the ecotone of northwest of Yunnan Province, China: A case study of Yongsheng County[J]. Acta Geographica Sinica, 59(4): 629-638.]
[9]	田亚平, 向清成, 王鹏. 2013. 区域人地耦合系统脆弱性及其评价指标体系[J]. 地理研究, 32(1): 55-63. doi: 10.11821/yj2013010006
	[Tian Y P, Xiang Q C, Wang P.2013. Regional coupled human-natural systems vulnerability and its evaluation indexes[J]. Geographical Research, 32(1): 55-63.] doi: 10.11821/yj2013010006
[10]	王利平, 文明, 宋进喜, 等. 2016. 1961-2014年中国干燥度指数的时空变化研究[J]. 自然资源学报, 31(9): 1488-1498.
	[Wang L P, Wen M, Song J X, et al.2016. Spatial-temporal variation of aridity index during 1961-2014 in China[J]. Journal of Natural Resources, 31(9): 1488-1498.]
[11]	杨新军, 张慧, 王子侨. 2015. 基于情景分析的西北农村社会-生态系统脆弱性研究: 以榆中县中连川乡为例[J]. 地理科学, 35(8): 952-959.
	[Yang X J, Zhang H, Wang Z Q.2015. Vulnerability assessment of rural social-ecological system based on scenario analysis: A case study of Zhonglianchuan Town in Yuzhong County[J]. Scientia Geographica Sincia, 35(8): 952-959.]
[12]	尹莎, 陈佳, 吴孔森, 等. 2016. 干旱环境胁迫下农户适应性研究: 基于民勤绿洲地区农户调查数据[J]. 地理科学进展, 35(5): 644-654. doi: 10.18306/dlkxjz.2016.05.011
	[Yin S, Chen J, Wu K S, et al.2016. Adaptation of farming households under drought stress: Based on a survey in the Minqin Oasis[J]. Progress in Geography, 35(5): 644-654.] doi: 10.18306/dlkxjz.2016.05.011
[13]	余中元, 李波, 张新时. 2015. 湖泊流域社会生态系统脆弱性时空演变及调控研究: 以滇池为例[J]. 人文地理, 30(2): 110-116.
	[Yu Z Y, Li B, Zhang X S.2015. Study of time-space evolution and control of vulnerability of lake basin social ecological system: A case of the Dianchi Lake[J]. Human Geography, 30(2): 110-116.]
[14]	张吉军. 2000. 模糊层次分析法(FAHP)[J]. 模糊系统与数学, 14(2): 80-88. doi: 10.3969/j.issn.1001-7402.2000.02.016
	[Zhang J J.2000. Fuzzy analytical hierarchy process[J]. Fuzzy Systems and Mathematics, 14(2): 80-88.] doi: 10.3969/j.issn.1001-7402.2000.02.016
[15]	张立新, 杨新军, 陈佳, 等. 2015. 大遗址区人地系统脆弱性评价及影响机制:以汉长安城大遗址区为例[J]. 资源科学, 37(9): 1848-1859.
	[Zhang L X, Yang X J, Chen J, et al.2015. Vulnerability assessment and mechanism of human-land systems in the Han Dynasty Chang'an large relic area[J]. Resources Science, 37(9): 1848-1859.]
[16]	张强, 姚玉璧, 李耀辉, 等. 2015. 中国西北地区干旱气象灾害监测预警与减灾技术研究进展及其展望[J]. 地球科学进展, 30(2): 196-213. doi: 10.11867/j.issn.1001-8166.2015.02.0196
	[Zhang Q, Yao Y B, Li Y H, et al.2015. Research progress and prospect on the monitoring and early warning and mitigation technology of meteorological drought disaster in Northwest China[J]. Advances in Earth Science, 30(2): 196-213.] doi: 10.11867/j.issn.1001-8166.2015.02.0196
[17]	赵东升, 吴绍洪. 2013. 气候变化情景下中国自然生态系统脆弱性研究[J]. 地理学报, 68(5): 602-610. doi: 10.11821/xb201305003
	[Zhao D S, Wu S H.2013. Responses of vulnerability for natural ecosystem to climate change in China[J]. Acta Geographica Sinica, 68(5): 602-610.] doi: 10.11821/xb201305003
[18]	赵雪雁, 刘春芳, 王学良, 等. 2016. 干旱区内陆河流域农户生计对生态退化的脆弱性评价: 以石羊河中下游为例[J]. 生态学报, 36(13): 4141-4151. doi: 10.5846/stxb201506201250
	[Zhao X Y, Liu C F, Wang X L, et al.2016. Assessment of the vulnerability of farmers' livelihoods to ecological degradation in arid regions of a continental river basin: A case study of the middle-lower reaches of the Shiyang River in China[J]. Acta Ecologica Sinica, 36(13): 4141-4151.] doi: 10.5846/stxb201506201250
[19]	Barbier E B.2000. The economic linkages between rural poverty and land degradation: Some evidence from Africa[J]. Agriculture, Ecosystems & Environment, 82(1-3): 355-370. doi: 10.1016/S0167-8809(00)00237-1
[20]	Bardhan P.2006. Globalization and rural poverty[J]. World Development, 34(8): 1393-1404. doi: 10.1057/9780230625501_6
[21]	Birkmann J.2007. Risk and vulnerability indicators at different scales: Applicability, usefulness and policy implications[J]. Environmental Hazards, 7(1): 20-31.
[22]	Chang D Y.1996. Applications of the extent analysis method on fuzzy AHP[J]. European Journal of Operational Research, 95(3): 649-655. doi: 10.1016/0377-2217(95)00300-2
[23]	Cheng J, Tao J P.2010. Fuzzy comprehensive evaluation of drought vulnerability based on the analytic hierarchy process: An empirical study from Xiaogan City in Hubei Province[J]. Hydrometallurgy, 1(4): 126-135. doi: 10.1016/j.aaspro.2010.09.015
[24]	Cumming G S, Barnes G, Perz S, et al.2005. An exploratory framework for the empirical measurement of resilience[J]. Ecosystems, 8(8): 975-987. doi: 10.1007/s10021-005-0129-z
[25]	Frazier T G, Thompson C M, Dezzani R J.2014. A framework for the development of the SERV model: A spatially explicit resilience-vulnerability model[J]. Applied Geography, 51: 158-172. doi: 10.1016/j.apgeog.2014.04.004
[26]	Kwong C K, Bai H.2003. Determining the importance weights for the customer requirements in QFD using a fuzzy AHP with an extent analysis approach[J]. IIE Transactions, 35(7): 619-626. doi: 10.1080/07408170304355
[27]	Li L, Shi Z H, Yin W, et al.2009. A fuzzy analytic hierarchy process (FAHP) approach to eco-environmental vulnerability assessment for the Danjiangkou reservoir area, China[J]. Ecological Modelling, 220(23): 3439-3447. doi: 10.1016/j.ecolmodel.2009.09.005
[28]	Luers A L, Lobell D B, Sklar L S, et al.2003. A method for quantifying vulnerability, applied to the agricultural system of the Yaqui Valley, Mexico[J]. Global Environmental Change, 13(4): 255-267. doi: 10.1016/S0959-3780(03)00054-2
[29]	Lüdeke M K B, Moldenhauer O, Petschel-Held G.1999. Rural poverty driven soil degradation under climate change: The sensitivity of the disposition towards the Sahel Syndrome with respect to climate[J]. Environmental Modeling and Assessment, 4(4): 315-326. doi: 10.1023/A:1019032821703
[30]	Metzger M J, Leemans R, Schröter D.2005. A multidisciplinary multi-scale framework for assessing vulnerabilities to global change[J]. International Journal of Applied Earth Observation and Geoinformation, 7(4): 253-267.
[31]	O'Brien K, Leichenko R, Kelkar U, et al.2004. Mapping vulnerability to multiple stressors: Climate change and globalization in India[J]. Global Environmental Change, 14(4): 303-313. doi: 10.1016/j.gloenvcha.2004.01.001
[32]	Portnov B A, Safriel U N.2004. Combating desertification in the Negev: Dryland agriculture vs. dryland urbanization[J]. Journal of Arid Environments, 56(4): 659-680. doi: 10.1016/S0140-1963(03)00087-9
[33]	Rahman N, Ansary M A, Islam I.2015. GIS based mapping of vulnerability to earthquake and fire hazard in Dhaka City, Bangladesh[J]. International Journal of Disaster Risk Reduction, 13: 291-300. doi: 10.1016/j.ijdrr.2015.07.003
[34]	Rebotier J.2012. Vulnerability conditions and risk representations in Latin-America: Framing the territorializing urban risk[J]. Global Environmental Change, 22(2): 391-398. doi: 10.1016/j.gloenvcha.2011.12.002
[35]	Sietz D, Lüdeke M K B, Walther C.2011. Categorisation of typical vulnerability patterns in global drylands[J]. Global Environmental Change, 21(2): 431-440. doi: 10.1016/j.gloenvcha.2010.11.005
[36]	Turner II B L, Kasperson R E, Matson P A, et al.2003. A framework for vulnerability analysis in sustainability science[J]. Proceedings of the National Academy of Sciences of the United States of America, 100(14): 8074-8079. doi: 10.1073/pnas.1231335100 pmid: 12792023
[37]	Vezina K, Bonn F, Van C P.2006. Agricultural land-use patterns and soil erosion vulnerability of watershed units in Vietnam's northern highlands[J]. Landscape Ecology, 21(8): 1311-1325. doi: 10.1007/s10980-006-0023-x

目标层	准则层	指标层	单位	权重	指标性质
社会子系统脆弱性SV	暴露—敏感性S1	农业人口比重	%	0.2039	正指标
		人口密度	人/km²	0.4560	正指标
		在校学生比例	%	0.3401	负指标
	适应能力R1	乡村从业人口比重	%	0.5537	负指标
		每百户拥有通讯设备数量	部/百户	0.1563	负指标
		万人拥有医疗床位数	床/万人	0.2900	负指标
经济子系统脆弱性EV	暴露—敏感性S2	第一产业增加值占GDP比重	%	0.2537	正指标
		第三产业增加值占GDP比重	%	0.3328	负指标
		规模以上工业总产值占GDP比重	%	0.4135	负指标
	适应能力R2	人均GDP	万元/人	0.4097	负指标
		到最近城市距离	km	0.2491	正指标
		人均居民储蓄存款余额	万元/人	0.3412	负指标
资源环境子系统	暴露—敏感性S3	水网密度	km/km²	0.2101	负指标
脆弱性REV		干燥度指数	—	0.2971	正指标
		NDVI指数	—	0.4928	负指标
	适应能力R3	单位面积粮食产量	t/hm²	0.3332	负指标
		人均耕地	hm²/人	0.3648	负指标
		人均肉类总产量	t/人	0.3020	负指标
政策子系统扶持	暴露—敏感性S4	单位从业人员数比例	%	0.3389	正指标
性PS		社会福利收养性单位平均床位数	床/个	0.2240	正指标
		财政收支比	%	0.4371	正指标
	适应能力R4	固定资产投资额	万元	0.3531	正指标
		到最近铁路距离	km	0.3171	负指标
		到最近国道距离	km	0.3298	负指标

指数分级	微度脆弱(扶持)	低度脆弱(扶持)	中度脆弱(扶持)	高度脆弱(扶持)	极度脆弱(扶持)
人地系统脆弱性指数	<6.097	6.098~10.463	10.464~16.487	16.488~26.111	>26.112
社会脆弱性指数	<0.989	0.99~1.424	1.425~1.984	1.985~5.609	>5.610
经济脆弱性指数	<2.377	2.378~3.818	3.819~9.444	9.445~21.235	>21.236
资源脆弱性指数	<2.480	2.481~3.748	3.749~5.910	5.911~12.239	>12.240
政策扶持性指数	<0.132	0.133~0.260	0.261~0.441	0.442~0.747	>0.748

变异系数	2003年	2008年	2013年
人地系统脆弱性差异度	0.582	0.680	0.695
社会脆弱性差异度	0.308	0.507	0.280
经济脆弱性差异度	1.003	0.494	0.389
资源环境脆弱性差异度	0.802	0.566	0.492
政策扶持性差异度	0.810	0.923	9.367
政策扶持性差异度(除西安主城区外)	0.800	0.900	0.895