设施POI(point of interest)在城市地理空间中往往聚集分布,呈现热点特征。对该类POI分布热点的分析大多采用基于欧氏距离的空间密度估计,忽略了城市空间通达、连接是沿着街道路径的事实,从而很难准确、客观地反映城市功能的热点布局。本研究针对该缺陷,利用基于网络路径距离的核密度计算方法确定热点的区域密度,并提出了一种简单、高效的网络分析算法。该算法扩展二维栅格膨胀操作,以一维形态算子的连续扩展计算POI在网络单元上的密度值,通过评价试验表明,该算法比现有算法具有更好的性能和可扩展性。通过实际POI数据分析发现,考虑街道网络约束的热点范围可凸显设施功能沿交通网络布局的空间特征,为区域规划、导航以及地理信息查询等应用提供有价值的空间知识与信息服务。
The distribution pattern of urban facility POIs (points of interest) usually forms clusters (i.e. "hotspots") in urban geographic space. To detect such type of hotspot, the methods mostly employ spatial density estimation based on Euclidean distance, ignoring the fact that the service function and interrelation of urban feasibilities is carried out on the network path distance, neither than conventional Euclidean distance. By using these methods, it is difficult to exactly and objectively delimitate the shape and the size of hotspot. Therefore, this research adopts the kernel density estimation based on the network distance to compute the density of hotspot and proposes a simple and efficient algorithm. The algorithm extends the 2D dilation operator to the 1D morphological operator, thus computing the density of network unit. Through evaluation experiment, it is suggested that the algorithm is more efficient and scalable than the existing algorithms. Based on the case study on real POI data, the range of hotspot can highlight the spatial characteristic of urban functions along traffic routes, in order to provide valuable spatial knowledge and information services for the applications of region planning, navigation and geographic information inquiring.
[1] XU Xueqiang, ZHOU Yixing, NING Yuemin. Urban Geography [M]. Beijing: Higher Education Press, 1997. (许学强, 周一星, 宁越敏. 城市地理学[M]. 北京: 高等教育出版社, 1997.)
[2] BAILEY T C, GATRELL A C. Interactive Spatial Data Analysis[M]. Harlow: Longman, 1995.
[3] SCHABENBERGER O, GOTWAY C A. Statistical Methods for Spatial Data Analysis [M]. Boca Raton: Chapman & Hall/CRC, 2005.
[4] CHEN Fei, DU Daosheng. Application of the Integration of Spatial Statistical Analysis with GIS to the Analysis of Regional Economy[J]. Geomatics and Information Science of Wuhan University, 2002, 27(4): 391-396. (陈斐, 杜道生. 空间统计分析与GIS在区域经济分析中的应用[J]. 武汉大学学报: 信息科学版, 2002, 27(4): 391-396.)
[5] HU Qingwu, WANG Ming, LI Qingquan. Urban Hotspot and Commercial Area Exploration with Check-in Data[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(3): 314-321. (胡庆武, 王明, 李清泉. 利用位置签到数据探索城市热点与商圈[J]. 测绘学报, 2014, 43(3): 314-321.)
[6] THURSTAIN-GOODWIN M, UNWIN D. Defining and Delineating the Central Areas of Towns for Statistical Monitoring Using Continuous Surface Representations[J]. Transactions in GIS, 2000, 4(4): 305-317.
[7] BORRUSO G, PORCEDDU A. 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: Springer, 2009: 37-56.
[8] OKABE A, OKUNUKI K. A Computational Method for Estimating the Demand of Retail Stores on a Street Network and Its Implementation in GIS[J]. Transactions in GIS, 2001, 5(3): 209-220.
[9] YAMADA I, THILL J C. Local Indicators of Network-Constrained Clusters in Spatial Point Patterns[J]. Geographical Analysis, 2007, 39(3): 268-292.
[10] XIE Shunping, FENG Xuezhi, WANG Jiechen, et al. Radiation Domain of Commercial Centers in Nanjing Based on Analysis of Road Network Weighted Voronoi Diagram[J]. Acta Geographica Sinica, 2009, 64(12): 1467-1476. (谢顺平, 冯学智, 王结臣, 等. 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, 2009, 64(12): 1467-1476.)
[11] WANG Xinsheng, YU Ruilin, JIANG Youhua. Delimitating the Store Market Field Based on the Metric of the City-block Distance[J]. Geographical Research, 2008, 27(1): 85-92. (王新生, 余瑞林, 姜友华. 基于道路网络的商业网点市场域分析[J]. 地理研究, 2008, 27(1): 85-92.)
[12] XIE Shunping, FENG Xuezhi, LU Wei. Algorithm for Constructing Voronoi Area Diagram Based on Road Network Analysis[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(1): 88-94. (谢顺平, 冯学智, 鲁伟. 基于道路网络分析的Voronoi面域图构建算法[J]. 测绘学报, 2010, 39(1): 88-94.)
[13] XIE Shunping, FENG Xuezhi, DU Jinkang. Maximal Covering Spatial Optimization Based on Network Voronoi Diagrams Heuristic and Swarm Intelligence[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(6): 778-784. (谢顺平, 冯学智, 都金康. 基于网络Voronoi图启发式和群智能的最大覆盖空间优化[J]. 测绘学报, 2011, 40(6): 778-784.)
[14] AI Tinghua, YU Wenhao. Algorithm for Constructing Network Voronoi Diagram Based on Flow Extension Ideas[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(5): 760-766. (艾廷华, 禹文豪. 水流扩展思想的网络空间Voronoi图生成[J]. 测绘学报, 2013, 42(5): 760-766.)
[15] TU Wei, LI Qingquan, FANG Zhixiang. Large Scale Multi-depot Logistics Routing Optimization Based on Network Voronoi Diagram[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(10): 1075-1082, 1091. (涂伟, 李清泉, 方志祥. 基于网络Voronoi图的大规模多仓库物流配送路径优化[J]. 测绘学报, 2014, 43(10): 1075-1082, 1091.)
[16] BORRUSO G. Network Density Estimation: Analysis of Point Patterns over a Network[M]//Gervasi O, Gavrilova M L, Kumar V, et al. Lecture Notes in Computer Science: Computational Science and Its Applications-ICCSA 2005. Berlin Heidelberg: Springer, 2005, 3482: 126-132.
[17] BORRUSO G. Network Density Estimation: A GIS Approach for Analysing Point Patterns in a Network Space[J]. Transactions in GIS, 2008, 12(3): 377-402.
[18] OKABE A, SATOH T, SUGIHARA K. A Kernel Density Estimation Method for Networks, Its Computational Method and a GIS-based Tool[J]. International Journal of Geographical Information Science, 2009, 23(1): 7-32.
[19] Urban Planning Land and Resources Commission of Shenzhen Municipality. The Comprehensive Plan of Shenzhen City (2010-2020).[2014-10-01] . http://www.szpl.gov.cn/xxgk/csgh/csztgh/201009/t20100929_60694.htm. (深圳市规划和国土资源委员会. 深圳市城市总体规划(2010-2020).[2014-10-01] . http://www.szpl.gov.cn/xxgk/csgh/csztgh/201009/t20100929_60694.htm.)
[20] Urban Planning Land and Resources Commission of Shenzhen Municipality, The Standard Land Price of Shenzhen City (2013).[2015-01-13] http://www.szpl.gov.cn/xxgk/tzgg/othersgg/201301/t20130111_78391.html. (深圳市规划和国土资源委员会. 深圳市基准地价(2013).[2015-01-13] . http://www.szpl.gov.cn/xxgk/tzgg/othersgg/201301/t20130111_78391.html.)
