斯堪的纳维亚半岛及周边地区城镇发展适宜性评价

doi:10.12082/dqxxkx.2018.180054

地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (8): 1083-1093.doi: 10.12082/dqxxkx.2018.180054

• 地理空间分析综合应用 • 上一篇下一篇

斯堪的纳维亚半岛及周边地区城镇发展适宜性评价

李鑫杨^1,²(), 刘庆生^1,^*(), 刘高焕¹, 黄翀¹, 李贺¹, 付东杰¹, 梁立^1,², 陈卓然^1,²

1. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京 100101
2. 中国科学院大学,北京 100049

收稿日期:2018-01-19 修回日期:2018-04-16 出版日期:2018-08-25 发布日期:2018-08-24
通讯作者: 刘庆生 E-mail:lixy.15s@igsnrr.ac.cn;liuqs@lreis.ac.cn
作者简介:
作者简介：李鑫杨（1992-）,女,硕士生,研究方向为遥感和地理信息系统应用。E-mail: lixy.15s@igsnrr.ac.cn
基金资助:
国家重点研发计划课题（2016YFC1402701）

A Suitability Evaluation of Urban Development in Scandinavian Peninsula and Surrounding Areas

LI Xinyang^1,²(), LIU Qingsheng^1,^*(), LIU Gaohuan¹, HUANG Chong¹, LI He¹, FU Dongjie¹, LIANG Li^1,², CHEN Zhuoran^1,²

1. State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2018-01-19 Revised:2018-04-16 Online:2018-08-25 Published:2018-08-24
Contact: LIU Qingsheng E-mail:lixy.15s@igsnrr.ac.cn;liuqs@lreis.ac.cn
Supported by:
National Key Research and Development Program of China, No.2016YFC1402701.

摘要/Abstract

摘要：

城镇发展适宜性研究有助于了解城镇发展的优势条件,为确定城镇建设规划的扩展方向提供依据。在北极与亚北极开展研究对中国开展在城镇化、重大基础设施、廊道建设方面的国际合作有重大意义。本文使用多源数据,在采样的基础上利用逐步法的思想进行变量筛选,共筛选出5个显著指标,用logistic方法拟合出最终的模型进行城镇发展适宜性评价,最终得到研究区城镇发展适宜性分级图。研究结果表明：筛选后的显著指标对研究区城镇分布的影响作用大小排序为,温度（正向）、交通网密度（正向）、海拔高度（反向）、人口密度（正向）、距港口距离（反向）;温度、交通网密度、海拔高度、人口密度、距最近港口距离增加1个单位,城镇发展的几率分别比原来增加了38.4%、16.7%、9%、0.4%、0.1%;研究区的Ⅰ（不适宜）、Ⅱ（中度适宜）、Ⅲ（高度适宜）的城镇发展适宜性均值分别为0.03、0.16、0.68（分别约占研究区总面积的76.82%、21.82%、1.37%）;城镇发展适宜性总体呈现出随纬度升高而降低、随经度升高而增加的趋势,适宜城镇发展的气候地理条件是温带大陆性湿润气候带和温带海洋性气候带以及平原与低地地区;研究区的城镇发展适宜性俄罗斯西北部为0.08、瑞典为0.07、芬兰为0.06、挪威为0.03。俄罗斯西北部城镇发展适宜性整体上呈现出北低南高,南部呈现两边高中间低的空间布局;瑞典呈现出西北低东南高,沿海大于内陆的空间布局;芬兰呈现出北（高原）低南（沿海）高,中部次高的空间布局;挪威呈现出南部沿海高,西部沿海次高,其他区域低的空间布局。

关键词: 城镇发展适宜性, 逻辑回归, 多指标评价, 北极与亚北极, 斯堪的纳维亚半岛

Abstract:

The study of urban development suitability is used for understanding the advantageous conditions of urban development, provides evidence for determining the expansion direction of town development project. Research in the arctic and the sub-arctic is of great significance for China's international cooperation in urbanization, major infrastructure and corridor construction. This article using multi-source data, on the basis of samplingpoints, 5 significant indicators were selected after filtering variables with the idea of stepwise method, the final logistic model was used to assess the suitability of urban development. Finally, the classified map of suitability of urban development was got. Finally, we get the classified map of suitability of urban development in study area. The result show that the ranking of significant indicators is, temperature (forward), traffic network density (forward), altitude (reverse), population density (forward), distance to nearest port (reverse). The above factors increase by 1 unit, the probability of urban development increased by 38.4%, 16.7%, 9%, 0.4%, and 0.1% respectively; The overall suitability of urban development shows a trend of decreasing with increasing latitude and it shows a trend of increasing with increasing longitude. The climatic and geographical conditions suitable for urban development are cool summer humid continental climates zone (Dfb, abbreviation in Koppen Climate Classification)and temperate oceanic climates zone (Cfb) with plains and lowland regions; The suitability of urban development in the study area sorted from the largest to the smallest is 0.08 in northwestern Russia, 0.07 in Sweden, 0.06 in Finland and 0.03 in Norway. The overall suitability of urban development in northwestern Russia is low in northern area and high in southern area. Sweden presents a trend that is low suitability in northwest area along with high suitability in southeast area, and suitability of coast is greater than that of inland. The suitability of Norway presents a spatial layout that is higher in the western coast, highest in the southern coast and low in other regions.

Key words: suitability evaluation of urban development, logistic regression, multicriteria evaluation, Arctic and Sub-arctic, Scandinavian Peninsula

李鑫杨, 刘庆生, 刘高焕, 黄翀, 李贺, 付东杰, 梁立, 陈卓然. 斯堪的纳维亚半岛及周边地区城镇发展适宜性评价[J]. 地球信息科学学报, 2018, 20(8): 1083-1093.DOI:10.12082/dqxxkx.2018.180054

LI Xinyang,LIU Qingsheng,LIU Gaohuan,HUANG Chong,LI He,FU Dongjie,LIANG Li,CHEN Zhuoran. A Suitability Evaluation of Urban Development in Scandinavian Peninsula and Surrounding Areas[J]. Journal of Geo-information Science, 2018, 20(8): 1083-1093.DOI:10.12082/dqxxkx.2018.180054

图/表 11

图1

表1

表2

表3

表4

图2

图3

图4

表5

表6

附表A

指标因子数据来源与信息"

指标	数据名称	机构	网址
人口密度	Gridded Population of the World (GPWv4)	哥伦比亚大学国际地球科学信息网络中心Center for International Earth Science Information Network (CIESIN), Columbia University	http://sedac.ciesin.columbia.edu/data/set/gpw-v4-population-density
交通网	Vmap0	美国国家地理空间情报局National Geospatial-Intelligence Agency (NGA)	http://gis-lab.info/qa/vmap0-eng.html
交通网	OSM	开放街图基金会OpenStreetMap Foundation	http://osm2shp.ru/index.php?isLike
温度	GHCN_CAMS Gridded 2m Temperature (Land)	美国国家海洋和大气管理局地球系统研究实验室NOAA/OAR/ESRL	https://www.esrl.noaa.gov/psd/data/gridded/data.ghcncams.html
海拔高度	GMTED2010	美国地质调查局U.S. Geological Survey	https://globalmaps.github.io/el.html
油气管线	Crude Oil Pipelines、Natural Gas Inter Intrastate Pipelines、Petroleum Product Pipelines	美国能源部U.S. Energy Information Administration (EIA)	https://www.eia.gov/maps/layer_info-m.php
油气管线	Global Oil Pipelines	哈佛大学地理分析中心The Center for Geographic Analysis(CGA), Harvard University	http://worldmap.harvard.edu/data/geonode:global_oil_pipelines_7z9
港口	World Port Index (Pub 150)	国家地理空间情报局National Geospatial-Intelligence Agency (NGA)	http://msi.nga.mil/NGAPortal/MSI. portal?_nfpb=true&_pageLabel=msi_portal_page_62&pubCode=0015
自然保护区	The World Database on Protected Areas (WDPA)	联合国环境与自然保护联盟UN Environment and IUCN	https://www.protectedplanet.net/
地震	Global Earthquake Hazard Frequency and Distribution, v1 (1976-2002)	哥伦比亚大学Columbia University	http://sedac.ciesin.columbia.edu/data/set/ndh-earthquake-frequency-distribution
滑坡	Global estimated risk index for landslide hazard triggered by precipitations	联合国环境规划署UNEP/DEWA/GRID-Europe	http://preview.grid.unep.ch/index.php?preview=data&events=landslides&ev cat=7&lang=eng

附表A

参考文献 37

[1]	Collins M G, Steiner F R, Rushman M J.Land-use suitability analysis in the United States: Historical development and promising technological achievements[J]. Environmental Management, 2001,28(5):611-621. doi: 10.1007/s002670010247
[2]	李坤,岳建伟.我国建设用地适宜性评价研究综述[J].北京师范大学学报(自然科学版),2015,51(s1):107-113. doi: 10.16360/j.cnki.jbnuns.2015.s1.017
	[ Li K, Yue J W.Evaluation of construction land suitability in China: A review[J]. Journal of Beijing Normal University(Natural Science), 2015,51(s1):107-113. ] doi: 10.16360/j.cnki.jbnuns.2015.s1.017
[3]	关小克,张凤荣,郭力娜,等.北京市耕地多目标适宜性评价及空间布局研究[J].资源科学,2010,32(3):580-587.
	[ Guan X K, Zhang F R, Guo L N, et al.A suitability evaluation of cultivated land in Beijing for multi-purposes use and its spatio-temporal investigation[J]. Resources Science, 2010,32(3):580-587. ]
[4]	刘立涛,沈镭.基于人地关系的澜沧江流域人居环境评价[J].资源科学,2012,34(7):1192-1199.
	[ Liu L T, Shen L.Assessment of human settlement environment in Lancang River Basin based on man-land relationship[J]. Resources Science, 2012,34(7):1192-1199. ]
[5]	杨子生. 山区城镇建设用地适宜性评价方法及应用——以云南省德宏州为例[J].自然资源学报,2016,31(1):64-76.
	[ Yang Z S.Land suitability evaluation for urban construction and its application in mountainous areas: A case study in dehong dai-jingpo autonomous prefecture, yunnan province. Journal of Natural Resources, 2016,31(1):64-76. ]
[6]	何丹,金凤君,周璟.资源型城市建设用地适宜性评价研究——以济宁市大运河生态经济区为例[J].地理研究,2011,30(4):655-666.
	[ He D, Jin F J, Zhou J.Urban construction land suitability evaluation in resource-based cities: Taking the Grand Canal ecologic and economic area as an example. Geographical Research, 2011,30(4):655-666. ]
[7]	Jain K, Subbaiah Y V.Site suitability analysis for urban development using GIS[J]. Journal of Applied Sciences, 2007,7(18):2576-2583. doi: 10.3923/jas.2007.2576.2583
[8]	Cerreta M, Toro P D.Urbanization susceptibility maps: A dynamic spatial decision support system for sustainable land use[J]. Earth System Dynamics, 2012,3(2):157-171. doi: 10.5194/esd-3-157-2012
[9]	Effat H A, Hegazy M N.A multidisciplinary approach to mapping potential urban development zones in Sinai Peninsula, Egypt using remote sensing and GIS[J]. Journal of Geographic Information System, 2013,5(6):567-583. doi: 10.4236/jgis.2013.56054
[10]	Kumar M, Biswas V.Identification of potential sites for urban development using GIS based multi criteria evaluation technique: A case study of Shimla Municipal Area, Shimla District, Himachal Pradesh, India[J]. Journal of Settlements & Spatial Planning, 2013,4(1):45-51.
[11]	Youssef A M, Pradhan B, Sefry S A, et al.Use of geological and geomorphological parameters in potential suitability assessment for urban planning development at Wadi Al-Asla basin, Jeddah, Kingdom of Saudi Arabia[J]. Arabian Journal of Geosciences, 2015,8(8):5617-5630. doi: 10.1007/s12517-014-1663-9
[12]	Dyer J S, Fishburn P C, Steuer R E, et al.Multiple criteria decision-making, multiattribute utility-theory-the next 10 years[J]. Management science, 1992,38:645-654. doi: 10.1287/mnsc.38.5.645
[13]	梁辰,王诺.基于Logistic回归的沿海经济区建设用地演变驱动因素研究——以大连市新市区为例[J].地理科学,2014,34(5):556-562.
	[ Liang C, W Nuo. Driving factor analysis of construction land changes in coastal economic zone based on logistic regression: A case study of dalian new urban[J]. Scientia Geographica Sinica, 2014,34(5):556-562. ]
[14]	邱道持,曹蕾,刘力,等.小城镇发展潜力评价探讨——以重庆市渝北区为例[J].西南师范大学学报(自然科学版),2004,29(2):305-309. doi: 10.3969/j.issn.1000-5471.2004.02.035
	[ Qiu D C, Cao L, Liu L, et al.Exploration for evaluation of development potential in towns: A case study of yubei, chongqing city[J]. Journal of Southwest China Normal University(Natural Science Edition), 2004,29(2):305-309. ] doi: 10.3969/j.issn.1000-5471.2004.02.035
[15]	王锋,徐逸伦.基于主成分分析法的城镇发展潜力评价研究——以安徽省临泉县为例[J].江西农业学报,2012,24(3):170-175. doi: 10.3969/j.issn.1001-8581.2012.03.052
	[ Wang F, Xu Y L.Evaluation of urban developmental potential based on principal component analysis: Taking example for linquan county in anhui province[J]. Acta Agriculturae Jiangxi, 2012,24(3):170-175. ] doi: 10.3969/j.issn.1001-8581.2012.03.052
[16]	黄丽明,陈健飞.广州市花都区城镇建设用地适宜性评价研究——基于MCR面特征提取[J].资源科学,2014,36(7):1347-1355.
	[ Huang L M, Chen J F.Suitability evaluation of urban construction land based on features extraction of a mcr surface[J]. Resources Science, 2014,36(7):1347-1355. ]
[17]	Jiang D, Zhuang D, Xu X, et al.Integrated evaluation of urban development suitability based on remote sensing and GIS techniques: A case study in Jingjinji area, China[J]. Sensors, 2008,8(9):5975-5986. doi: 10.3390/s8095975
[18]	Youssef A M, Pradhan B, Tarabees E.Integrated evaluation of urban development suitability based on remote sensing and GIS techniques: Contribution from the analytic hierarchy process[J]. Arabian Journal of Geosciences, 2011,4(3-4):463-473. doi: 10.1007/s12517-009-0118-1
[19]	杨育文,敖晨霞,熊增强.建设用地适宜性的模糊综合评判法及其在 GIS 软件平台上的实现[J].城市勘测,2015(4):152-157. doi: 10.3969/j.issn.1672-8262.2015.04.048
	[ Yang Y W, Ao C X, Xiong Z Q.Fuzzy evaluation on land use suitability and its implementation in GIS software platform[J]. Urban Geotechnical Investigation＆Surveying, 2015(4):152-157. ] doi: 10.3969/j.issn.1672-8262.2015.04.048
[20]	肖莉,李韦,冯长春,等.湖南湘江新区建设用地适宜性评价研究[J].地域研究与开发,2016,35(4):131-136. doi: 10.3969/j.issn.1003-2363.2016.04.025
	[ Xiao L, Li W, Feng C C, et al.Evaluation of the construction land suitability in Hunan Xiangjiang new area[J]. Areal Research and Development, 2016,35(4):131-136. ] doi: 10.3969/j.issn.1003-2363.2016.04.025
[21]	Doxseywhitfield E, Macmanus K, Adamo S B, et al.Taking advantage of the improved availability of census data: A first look at the gridded population of the world, Version 4[J]. Papers in Applied Geography, 2015,1(3):226-234. doi: 10.1080/23754931.2015.1014272
[22]	Fan Y, Dool H V D. A global monthly land surface air temperature analysis for 1948-present[J]. Journal of Geophysical Research Atmospheres, 2008,113(D1):411-411.
[23]	Danielson J J, Gesch D B.Global multi-resolution terrain elevation data 2010 (GMTED2010)[R]. USA: US Geological Survey, 2011.
[24]	李彦卿. 小城镇人口规模研究[D].天津:天津大学,2004.
	[ Li Y Q.The Research of Population Scale in Small Town[D]. Tianjin:Tianjin University, 2004. ]
[25]	张洪,曹京,董世杰.基于GIS的低丘缓坡土地利用建设适宜性评价——以大理市为例[J].安徽农业科学,2017,45(6):212-217.
	[ Zhang H, Cao J, Dong S J.Suitability evaluation of land construction use about gentle hills based on GIS: A case study of dali city[J]. Journal of Anhui Agricultural Sciences, 2017,45(6):212-217. ]
[26]	王成金,张岸.基于交通优势度的建设用地适宜性评价与实证——以玉树地震灾区为例[J].资源科学,2012,34(9):1688-1697.
	[ Evaluation of transport dominance and delimitation of land suitability for construction in the yushu earthquake region[J]. Resources Science, 2012,34(9):1688-1697. ]
[27]	夏俊士,杜培军,张海荣,等.基于遥感数据的城市地表温度与土地覆盖定量研究[J].遥感技术与应用,2010,25(1):15-23. doi: 10.3969/j.issn.1008-1283.2016.09.020
	[ Xia J S, Du P J, Zhang H R, et al.The quantitative relationship between land surface temperature and land cover types based on remotely sensed data[J]. Remote Sensing Technology and Application, 2010,25(1):15-23. ] doi: 10.3969/j.issn.1008-1283.2016.09.020
[28]	Hinkel K M, Klene A E, Nelson F E.The summer climate of an arctic coastal village: Preliminary observations from the Barrow urban heat-island study[J]. Polar Geography, 2004,28(3):197-221. doi: 10.1080/789610187
[29]	毛蒋兴,李志刚,闫小培,等.深圳土地利用时空变化与地形因子的关系研究[J].地理与地理信息科学,2008,24(2):71-76.
	[ Mao J X, Li Z G, Yan X P, et al.Research on the spatio-temporal changes of land use in relation to topography factors in ShenZhen City[J], Geography and Geo-information Science, 2008,24(2):71-76. ]
[30]	黄瑞红. GIS在城镇发展用地适宜性评价中的应用——以广东五华县华城镇为例[J].中山大学学报:自然科学版,1997,36(6):108-113.
	[ Huang R H.A land suitability study for town development by means of GIS: case study of Huacheng, China[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 1997,36(6):108-113. ]
[31]	李德华. 城市规划原理[M].北京:中国建筑工业出版社,2001.
	[ Li D H.Theory of urban planning[M]. Beijing:China Architecture & Building Press,2011. ]
[32]	南晓娜. GIS支持下的山地城市建设用地适宜性评价研究[D].西安:西北大学,2009.
	[ Nan X N, Study on suitability evaluation of mountainous city construction land supported by GIS[D]. Xi'an:Northwest University, 2009. ]
[33]	卢景美,邵滋军,房殿勇,等.北极圈油气资源潜力分析[J].资源与产业,2010(4):29-33.
	[ Lu J M, Shao Z J, Fang D Y, et al.Analysis of oil-gas resources potential in the Arctic Circle[J]. Resources & Industries, 2010(4):29-33. ]
[34]	陈航. 港城互动的理论与实证研究[D].大连:大连海事大学,2009.
	[ Chen H.Research on theory and empirical for interaction between ports and cities[D]. Dalian: Dalian Maritime University, 2009. ]
[35]	Freedman D A.Statistical models: theory and practice[M]. United Kingdom:Cambridge University Press, 2009.
[36]	Cox D R.The regression analysis of binary sequences[J]. Journal of the Royal Statistical Society-Series B (Methodological), 1958,20(2):215-242. doi: 10.2307/2343310
[37]	Hu Z, Lo C P.Modeling urban growth in Atlanta using logistic regression[J]. Computers Environment & Urban Systems, 2007,31(6):667-688. doi: 10.1016/j.compenvurbsys.2006.11.001

变量	类型	单位	分辨率
城镇类别	二分类	0,1	500 m
坡度	连续型	°	500 m
交通网密度	连续型	路段数/m²	500 m
温度	连续型	℃	1 km(重采样为500 m)
距最近港口距离	连续型	m	500 m
人口密度	连续型	人数/km²	1 km(重采样为500 m)
距最近管线距离	连续型	m	500 m
管线密度	连续型	个/m²	500 m
海拔高度	连续型	m	500 m
自然保护区与地质灾害危险区	二分类	0,1	500 m

年份	距航道500 m内	距航道500~1000 m	年份	距航道500 m内	距航道500~1000 m
2001	24.59	411.26	2008	24.57	411.57
2002	24.54	411.26	2009	24.50	410.24
2003	24.57	411.31	2010	24.56	411.55
2004	26.71	443.25	2011	24.54	411.62
2005	24.57	411.49	2012	25.60	427.71
2006	24.58	411.52	2013	24.54	411.61
2007	24.51	410.19	变异系数C·V	2.60%	2.33%

指标	系数	标准误	Wald χ2统计量	自由度	P值	优势比
坡度	0.015	0.026	0.322	1	0.570	1.015
交通网密度	0.154	0.017	80.883	1	0.000	1.167
温度	0.319	0.070	20.992	1	0.000	1.375
距最近港口距离	-0.001	0.000	12.567	1	0.000	0.999
人口密度	0.004	0.000	79.564	1	0.000	1.004
距最近管线距离	-0.001	0.002	0.144	1	0.704	0.999
管线密度	0.041	0.171	0.058	1	0.810	1.042
海拔高度	-0.010	0.002	34.562	1	0.000	0.990
常数	-3.598	0.529	46.331	1	0.000	0.027

指标	回归系数（B）	标准误（S.E.）	Wald χ2统计量	自由度（df）	优势比（OR）
交通网密度	0.154	0.017	81.230	1	1.167
温度	0.325	0.068	22.743	1	1.384
人口密度	0.004	0.000	80.904	1	1.004
海拔高度	-0.009	0.002	35.812	1	0.991
距最近港口距离	-0.001	0.000	18.011	1	0.999
常数	-3.666	0.478	58.710	1	0.026

	城镇发展适宜性等级
	Ⅰ	Ⅱ	Ⅲ
适宜性均值	0.03	0.16	0.68
面积/10⁴km²	17.05	4.84	0.30
面积占比/%	76.82	21.82	1.37
温度/℃	3.56	6.39	6.83
交通网密度/（路段数/m)	0.42	1.33	15.12
海拔高度/m	311.19	94.95	90.36
人口密度/（人数/km²)	8.15	35.64	1259.29
距最近港口距离/m	197.36	303.05	255.59

斯堪的纳维亚半岛及周边地区城镇发展适宜性评价

A Suitability Evaluation of Urban Development in Scandinavian Peninsula and Surrounding Areas

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 37

相关文章 3

Metrics

本文评价

推荐阅读 0

			俄罗斯西北部			瑞典		芬兰		挪威
			面积/km²	面积占比/%		面积/km²	面积占比/%	面积/km²	面积占比/%	面积/km²	面积占比/%
适宜性级别		Ⅰ	68701.25	68.95		38132.50	76.11	30674.75	83.85	32839.50	93.04
		Ⅱ	29538.00	29.64		10939.25	21.83	5601.00	15.31	2176.25	6.17
		Ⅲ	1404.25	1.41		1031.00	2.06	308.50	0.84	279.25	0.79
适宜性均值			0.08			0.07		0.06		0.03
指标	温度		4.66			4.17		3.82		3.41
	交通网密度		0.78		0.99		0.66		0.69
	海拔高度		150.85		309.17		156.04		564.00
	人口密度		44.49		22.62		16.77		15.37
	距最近港口距离		377.87		89.75		126.31		54.53

[1]	方志祥, 倪雅倩, 黄守倩. 顾及上网行为特征的手机用户停留行为预测方法[J]. 地球信息科学学报, 2020, 22(1): 136-144.
[2]	李云君, 刘志红, 吕远洋, 柳锦宝, 王平. 四川省滑坡灾害气象预警模型建立与验证[J]. 地球信息科学学报, 2017, 19(7): 941-949.
[3]	葛咏. 地学数据集成及空间决策支持的方法与应用[J]. 地球信息科学学报, 2006, 8(1): 16-20.