广州市多类型商业中心识别与空间模式

  本文关键词：长春市商业网点空间分布与交通网络中心性关系研究，，由笔耕文化传播整理发布。

[1] 陈晨, 王法辉, 修春亮. 2013. 长春市商业网点空间分布与交通网络中心性关系研究[J]. 经济地理, 33(10): 40-47.
doi: 10.3969/j.issn.1673-0410.2014.11.280

[1] [Chen C, Wang F H, Xiu C L.2013. The relationship between the spatial distribution of commercial networks and street centrality in Changchun[J]. Economic Geography, 33(10): 40-47.]

[2] 陈鹏, 李欣, 胡啸峰, 等. 2015. 北京市长安街沿线的扒窃案件高发区分析及防控对策[J]. 地理科学进展, 34(10): 1250-1258.
doi: 10.18306/dlkxjz.2015.10.005

[2] [Chen P, Li X, Hu X F, et al.2015. Clustering pattern analysis and prevention strategies to pickpocketing offence along the Chang'an Street in Beijing[J]. Progress in Geography, 34(10): 1250-1258.]

[3] 陈蔚珊, 柳林, 梁育填. 2015. 广州轨道交通枢纽零售业的特征聚类及时空演变[J]. 地理学报, 70(6): 879-892.
doi: 10.11821/dlxb201506003

[3] [Chen W S, Liu L, Liang Y T.2015. Characterizing the spatio-temporal evolution of retail business at transfer hubs of Guangzhou metro[J]. Acta Geographica Sinica, 70(6): 879-892.]

[4] 陈彦光. 2009. 基于Moran统计量的空间自相关理论发展和方法改进[J]. 地理研究, 28(6): 1449-1463.
doi: 10.11821/yj2009060002

[4] [Chen Y G.2009. Reconstructing the mathematical process of spatial autocorrelation based on Moran's statistics[J]. Geographical Research, 28(6): 1449-1463.]

[5] 胡庆武, 王明, 李清泉. 2014. 利用位置签到数据探索城市热点与商圈[J]. 测绘学报, 43(3): 314-321.
doi: 10.13485/j.cnki.11-2089.2014.0045

[5] [Hu Q W, Wang M, Li Q Q.2014. Urban hotspot and commercial area exploration with check-in data[J]. Acta Geodaetica et Cartographica Sinica, 43(3): 314-321.]

[6] 贾生华, 聂冲, 温海珍. 2008. 城市CBD功能成熟度评价指标体系的构建: 以杭州钱江新城CBD为例[J]. 地理研究, 27(3): 649-658.
doi: 10.3321/j.issn:1000-0585.2008.03.018

[6] [Jia S H, Nie C, Wen H Z.2008. The construction of the CBD functional maturity index system: A case of Qianjiang new city CBD[J]. Geographical Research, 27(3): 649-658.]

[7] 林彰平, 闫小培. 2006. 转型期广州市金融服务业的空间格局变动[J]. 地理学报, 61(8): 818-828.
doi: 10.3321/j.issn:0375-5444.2006.08.004

[7] [Lin Z P, Yan X P.2006. Analysis on the change of the spatial pattern of financial service industry in Guangzhou during the transition period[J]. Acta Geographica Sinica, 61(8): 818-828.]

[8] 陆娟, 汤国安, 张宏, 等. 2012. 犯罪热点时空分布研究方法综述[J]. 地理科学进展, 31(4): 419-425.
doi: 10.11820/dlkxjz.2012.04.004

[8] [Lu J, Tang G A, Zhang H, et al.2012. A review of research methods for spatiotemporal distribution of the crime hot spots[J]. Progress in Geography, 31(4): 419-425.]

[9] 田光进, 沙默泉. 2010. 基于点状数据与GIS的广州大都市区产业空间格局[J]. 地理科学进展, 29(4): 387-395.
doi: 10.11820/dlkxjz.2010.04.001

[9] [Tian G J, Sha M Q.2010. The spatial pattern of Guangzhou metropolitan area industry based on point data and GIS[J]. Progress in Geography, 29(4): 387-395.]

[10] 王芳, 高晓路, 许泽宁. 2015. 基于街区尺度的城市商业区识别与分类及其空间分布格局: 以北京为例[J]. 地理研究, 34(6): 1125-1134.
doi: 10.11821/dlyj201506011

[10] [Wang F, Gao X L, Xu Z N.2015. Identification and classification of urban commercial districts at block scale[J]. Geographical Research, 34(6): 1125-1134.]

[11] 王慧, 田萍萍, 刘红, 等. 2007. 西安城市CBD体系发展演进的特征与趋势[J]. 地理科学, 27(1): 31-39.
doi: 10.3969/j.issn.1000-0690.2007.01.005

[11] [Wang H, Tian P P, Liu H, et al.2007. Development of urban CBD system in Xi'an: Characters and tendency[J]. Scientia Geographica Sinica, 27(1): 31-39.]

[12] 王劲峰, 葛咏, 李连发, 等. 2014. 地理学时空数据分析方法[J]. 地理学报, 69(9): 1326-1345.
doi: 10.11821/dlxb201409007

[12] [Wang J F, Ge Y, Li L F, et al.2014. Spatiotemporal data analysis in geography[J]. Acta Geographica Sinica, 69(9): 1326-1345.]

[13] 谢顺平, 冯学智, 王结臣, 等. 2009. 基于网络加权Voronoi图分析的南京市商业中心辐射域研究[J]. 地理学报, 64(12): 1467-1476.
doi: 10.11821/xb200912007

[13] [Xie S P, Feng X Z, Wang J C, et al.2009. Radiation domain of commercial centers in Nanjing based on analysis of road network weighted voronoi diagram[J]. Acta Geographica Sinica, 64(12): 1467-1476.]

[14] 薛东前, 黄晶, 马蓓蓓, 等. 2014. 西安市文化娱乐业的空间格局及热点区模式研究[J]. 地理学报, 69(4): 541-552.
doi: 10.11821/dlxb201404010

[14] [Xue D Q, Huang J, Ma B B, et al.2014. Spatial distribution characteristics and hot zone patterns of entertainment industry in Xi'an[J]. Acta Geographica Sinica, 69(4): 541-552.]

[15] 阎小培, 周春山, 冷勇, 等. 2000. 广州CBD的功能特征与空间结构[J]. 地理学报, 55(4): 475-486.

[15] [Yan X P, Zhou C S, Leng Y, et al.2000. Functional features and spatial structure of CBDs in Guangzhou[J]. Acta Geographica Sinica, 55(4): 475-486.]

[16] 杨振山, 龙瀛, Nicolas Douay.2015. 大数据对人文—经济地理学研究的促进与局限[J]. 地理科学进展, 34(4): 410-417.
doi: 10.11820/dlkxjz.2015.04.002

[16] [Yang Z S, Long Y, Douay N.2015. Opportunities and limitations of big data applications to human and economic geography: The state of the art[J]. Progress in Geography, 34(4): 410-417.]

[17] 于伟, 王恩儒, 宋金平. 2012. 1984年以来北京零售业空间发展趋势与特征[J]. 地理学报, 67(8): 1098-1108.
doi: 10.11821/xb201208008

[17] [Yu W, Wang E R, Song J P.2012. Changing retail spatial patterns in metropolitan Beijing since 1984[J]. Acta Geographica Sinica, 67(8): 1098-1108.]

[18] 张珣, 钟耳顺, 张小虎, 等. 2013. 2004-2008年北京城区商业网点空间分布与集聚特征[J]. 地理科学进展, 32(8): 1207-1215.
doi: 10.11820/dlkxjz.2013.08.004

[18] [Zhang X, Zhong E S, Zhang X H, et al.2013. Spatial distribution and clustering of commercial network in Beijing during 2004-2008[J]. Progress in Geography, 32(8): 1207-1215.]

[19] 周春山, 罗彦, 尚嫣然. 2004. 中国商业地理学的研究进展[J]. 地理学报, 59(6): 1028-1036.
doi: 10.3321/j.issn:0375-5444.2004.06.027

[19] [Zhou C S, Luo Y, Shang Y R.2004. Research progress of commercial geography in China[J]. Acta Geographica Sinica, 59(6): 1028-1036.]

[20] 周素红, 郝新华, 柳林. 2014. 多中心化下的城市商业中心空间吸引衰减率验证: 深圳市浮动车GPS时空数据挖掘[J]. 地理学报, 69(12): 1810-1820.
doi: 10.11821/dlxb201412007

[20] [Zhou S H, Hao X H, Liu L.2014. Validation of spatial decay law caused by urban commercial center's mutual attraction in polycentric city: Spatio-temporal data mining of floating cars' GPS data in Shenzhen[J]. Acta Geographica Sinica, 69(12): 1810-1820.]

[21] Borruso G, Porceddu A.2009. A tale of two cities: Density analysis of CBD on two midsize urban areas in northeastern Italy[M]//Murgante B, Borruso G, Lapucci A. Geocomputation and urban planning. Berlin & Heidelberg, Germany: Springer: 37-56.

[22] Chainey S, Reid S, Stuart N.2002. When is a hotspot a hotspot? A procedure for creating statistically robust hotspot maps of crime[M]//Kidner D B, Higgs G, White S D. Innovations in GIS 9: Socio-economic applications of geographic information science. London, UK: Taylor & Francis.

[23] Chu H J, Liau C J, Lin C H, et al.2012. Integration of fuzzy cluster analysis and kernel density estimation for tracking typhoon trajectories in the Taiwan region[J]. Expert Systems with Applications, 39(10): 9451-9457.
doi: 10.1016/j.eswa.2012.02.114

[24] Davies D H.1959. Boundary study as a tool in CBD analysis: An interpretation of certain aspects of the boundary of Cape Town's central business district[J]. Economic Geography, 35(4): 322-345.
doi: 10.2307/142466

[25] Goodchild M F.2007. Citizens as sensors: The world of volunteered geography[J]. GeoJournal, 69(4): 211-221.
doi: 10.1007/s10708-007-9111-y

[26] Goodchild M F.2009. Geographic information systems and science: Today and tomorrow[J]. Annals of GIS, 15(1): 3-9.
doi: 10.1016/j.proeps.2009.09.160

[27] Harris R, Sleight P, Webber R.2005. Geodemographics, GIS and neighbourhood targeting[M]. London, UK: John Wiley and Sons.

[28] Li L N, Goodchild M F, Xu B.2013. Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr[J]. Cartography and Geographic Information Science, 40(2): 61-77.
doi: 10.1080/15230406.2013.777139

[29] Liu Y, Liu X, Gao S, et al.2015. Social sensing: A new approach to understanding our socioeconomic environments[J]. Annals of the Association of American Geographers, 105(3): 512-530.
doi: 10.1080/00045608.2015.1018773

[30] Murphy R E, Vance Jr J E.1954. Delimiting the CBD[J]. Economic Geography, 30(3): 189-222.
doi: 10.2307/141867

[31] Okabe A, Satoh T, Sugihara K.2009. A kernel density estimation method for networks, its computational method and a GIS-based tool[J]. International Journal of Geographical Information Science, 23(1): 7-32.?id=1513856
doi: 10.1080/13658810802475491

[32] Thurstain-Goodwin M, Unwin D.2000. Defining and delineating the central areas of towns for statistical monitoring using continuous surface representations[J]. Transactions in GIS, 4(4): 305-317.
doi: 10.1111/1467-9671.00058

[33] Xie Z X, Yan J.2008. Kernel density estimation of traffic accidents in a network space[J]. Computers, Environment and Urban Systems, 32(5): 396-406.
doi: 10.1016/j.compenvurbsys.2008.05.001

[34] Yu W H, Ai T H, Shao S W.2015. The analysis and delimitation of central business district using network kernel density estimation[J]. Journal of Transport Geography, 45: 32-47.
doi: 10.1016/j.jtrangeo.2015.04.008

  本文关键词：长春市商业网点空间分布与交通网络中心性关系研究，由笔耕文化传播整理发布。