LEADER 05666nam 2200709Ia 450 001 9910141257503321 005 20230801223309.0 010 $a1-119-96776-7 010 $a1-280-77575-0 010 $a9786613686145 010 $a1-119-96710-4 010 $a1-119-96709-0 035 $a(CKB)2670000000205666 035 $a(EBL)945114 035 $a(OCoLC)796383240 035 $a(SSID)ssj0000679203 035 $a(PQKBManifestationID)11365650 035 $a(PQKBTitleCode)TC0000679203 035 $a(PQKBWorkID)10609893 035 $a(PQKB)10220688 035 $a(MiAaPQ)EBC945114 035 $a(Au-PeEL)EBL945114 035 $a(CaPaEBR)ebr10570739 035 $a(CaONFJC)MIL368614 035 $a(EXLCZ)992670000000205666 100 $a20111026d2012 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSpatial analysis along networks$b[electronic resource] $estatistical and computational methods /$fAtsuyuki Okabe, Kokichi Sugihara 210 $aHoboken, N.J. $cWiley$d2012 215 $a1 online resource (308 p.) 225 1 $aStatistics in practice 300 $aDescription based upon print version of record. 311 $a0-470-77081-3 320 $aIncludes bibliographical references and index. 327 $aSpatial Analysis along Networks: Statistical and Computational Methods; Contents; Preface; Acknowledgements; 1 Introduction; 1.1 What is network spatial analysis?; 1.1.1 Network events: events on and alongside networks; 1.1.2 Planar spatial analysis and its limitations; 1.1.3 Network spatial analysis and its salient features; 1.2 Review of studies of network events; 1.2.1 Snow's study of cholera around Broad Street; 1.2.2 Traffic accidents; 1.2.3 Roadkills; 1.2.4 Street crime; 1.2.5 Events on river networks and coastlines; 1.2.6 Other events on networks; 1.2.7 Events alongside networks 327 $a1.3 Outline of the book 1.3.1 Structure of chapters; 1.3.2 Questions solved by network spatial methods; 1.3.3 How to study this book; 2 Modeling spatial events on and alongside networks; 2.1 Modeling the real world; 2.1.1 Object-based model; 2.1.1.1 Spatial attributes; 2.1.1.2 Nonspatial attributes; 2.1.2 Field-based model; 2.1.3 Vector data model; 2.1.4 Raster data model; 2.2 Modeling networks; 2.2.1 Object-based model for networks; 2.2.1.1 Geometric networks; 2.2.1.2 Graph for a geometric network; 2.2.2 Field-based model for networks; 2.2.3 Data models for networks 327 $a2.3 Modeling entities on network space 2.3.1 Objects on and alongside networks; 2.3.2 Field functions on network space; 2.4 Stochastic processes on network space; 2.4.1 Object-based model for stochastic spatial events on network space; 2.4.2 Binomial point processes on network space; 2.4.3 Edge effects; 2.4.4 Uniform network transformation; 3 Basic computational methods for network spatial analysis; 3.1 Data structures for one-layer networks; 3.1.1 Planar networks; 3.1.2 Winged-edge data structures; 3.1.3 Efficient access and enumeration of local information 327 $a3.1.4 Attribute data representation 3.1.5 Local modifications of a network; 3.1.5.1 Inserting new nodes; 3.1.5.2 New nodes resulting from overlying two networks; 3.1.5.3 Deleting existing nodes; 3.2 Data structures for nonplanar networks; 3.2.1 Multiple-layer networks; 3.2.2 General nonplanar networks; 3.3 Basic geometric computations; 3.3.1 Computational methods for line segments; 3.3.1.1 Right-turn test; 3.3.1.2 Intersection test for two line segments; 3.3.1.3 Enumeration of line segment intersections; 3.3.2 Time complexity as a measure of efficiency; 3.3.3 Computational methods for polygons 327 $a3.3.3.1 Area of a polygon 3.3.3.2 Center of gravity of a polygon; 3.3.3.3 Inclusion test of a point with respect to a polygon; 3.3.3.4 Polygon-line intersection; 3.3.3.5 Polygon intersection test; 3.3.3.6 Extraction of a subnetwork inside a polygon; 3.3.3.7 Set-theoretic computations; 3.3.3.8 Nearest point on the edges of a polygon from a point in the polygon; 3.3.3.9 Frontage interval; 3.4 Basic computational methods on networks; 3.4.1 Single-source shortest paths; 3.4.1.1 Network connectivity test; 3.4.1.2 Shortest-path tree on a network; 3.4.1.3 Extended shortest-path tree on a network 327 $a3.4.1.4 All nodes within a prespecified distance 330 $aIn the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Process 410 0$aStatistics in practice. 606 $aSpatial analysis (Statistics) 606 $aSpatial analysis (Statistics)$xData processing 606 $aGeography$xNetwork analysis 615 0$aSpatial analysis (Statistics) 615 0$aSpatial analysis (Statistics)$xData processing. 615 0$aGeography$xNetwork analysis. 676 $a519.5/36 700 $aOkabe$b Atsuyuki$f1945-$0871584 701 $aSugihara$b Ko?kichi$f1948-$0546289 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910141257503321 996 $aSpatial analysis along networks$91945604 997 $aUNINA