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- 1. URBAN NETWORK ANALYSIS! A Toolbox for ArcGIS 10 City Form Research Group! Andres Sevtsuk! Lecturer in Architecture / Urban Studies & Planning, MITMIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 1 of 33!
- 2. Urbanization!Rapid city building poses the biggest challenge for architecture and planning in the next decades.How does the physical conﬁguration of cities affect their qualities ashosts to human activities? MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 2 of 33!
- 3. Physical conﬁguration of the built environment!How do we evaluate urban form and land use patterns? What do we measure?! Infrastructure Architecture Morphological Network Analysis! analysis Density Land use distribution Social use patterns The form of a city is like… An Elephant, different parts of which are studied by different blind professionals, with no coherent understanding of the whole available across disciplines. (Knaap, Song et al. 2005) MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 3 of 33!
- 4. Areas of application!A case of retail and food services establishments in Cambridge and Somerville, MABusiness locationPatters. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 4 of 33!
- 5. Areas of application!Pedestrian and vehicular trafﬁc patterns. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 5 of 33!
- 6. Areas of application!Land value distribution and development densities. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 6 of 33!
- 7. Spatial Network Analysis!Two graph elements: nodes; edges MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 7 of 33!
- 8. Two key innovations!A weighted network of buildings, nodes, and edges. 1. We add buildings to the graph, introducing a 3-part framework of buildings, nodes, and edges. 2. We add attributes to each graph element, which can be used as weights in the analysis. Building " " "Edge " Node" MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 8 of 33!
- 9. Downloading the toolbox!Contents • Prerquisietes! ArcGIS 10 with ServiecPack2 Network Analyst Extension • Download! http://cityform.mit.edu/projects/urban-network-analysis.html • Contents! MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 9 of 33!
- 10. Installing the toolbox!Steps • Save download to a desired location, unzip. • Add toolbox in ArcGIS 1. 2. 3. 4. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 10 of 33!
- 11. A new toolbox for ArcGIS 10!Urban Network Analysis MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 11 of 33!
- 12. Input Points!A point shapeﬁle (.shp) • Input Points mark the locations of buildings (usually building entrances or centroids) on which we run the network analysis. • From the Input Points shapeﬁle we also obtain the weights for the buildings (if the user chooses to provide them). • How to convert building, parcel or other polygons to point centroids? Use the ArcGIS’ built-in Feature To Point (Data Management) tool. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 12 of 33!
- 13. Input Analysis Network!A Network Dataset File (.ND) • The street (or other) spatial network on which the Input Points are located. • If you do not have one yet, create a Network Dataset from a *.shp, *.dwg or *.dxf ﬁle using ArcCatalog. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 13 of 33!
- 14. Input Analysis Network!A Network Dataset File (.ND) • The street (or other) spatial network on which the Input Points are located. • If you do not have one yet, create a Network Dataset from a *.shp, *.dwg or *.dxf ﬁle using ArcCatalog. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 14 of 33!
- 15. Compute Reach (optional)!How many surrounding destinations j can be reached from building i within a given network radius?! R (i) = ∑ Oij ≤ r j ≠i € MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 15 of 33!
- 16. Compute Reach (optional)!How many surrounding destinations j can be reached from building i within a given network radius?! MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 16 of 33!
- 17. Compute Gravity Index (optional)!Accessibility is proportional to the attractiveness & inversely proportional to the distance of reaching surrounding destinations j.! 1 G (i) = ∑ β j ≠i dij € MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 17 of 33!
- 18. Compute Gravity Index (optional)!Accessibility is proportional to the attractiveness & inversely proportional to the distance of reaching surrounding destinations j.! MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 18 of 33!
- 19. Compute Betweenness (optional)!The betweenness of building i is deﬁned as the fraction of shortest paths between pairs of other buildings in the network that pass by i. (Freeman, 1977)! n jk (i) B (i) = ∑ j ≠i< j ≠k n jk € MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 19 of 33!
- 20. Compute Betweenness (optional)!The betweenness of building i is deﬁned as the fraction of shortest paths between pairs of other buildings in the network that pass by i. (Freeman, 1977)! MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 20 of 33!
- 21. Compute Closeness (optional)!The closeness centrality of a node is deﬁned as the inverse of distance required to reach from one node to all other nodes in the system along shortest paths (Sabidussi 1966).! 1 C(i) = ∑d ij j € MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 21 of 33!
- 22. Compute Closeness (optional)!The closeness centrality of a node is deﬁned as the inverse of distance required to reach from one node to all other nodes in the system along shortest paths (Sabidussi 1966).! MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 22 of 33!
- 23. Compute Straightness (optional)!The Straightness measure illustrates the extent to which the shortest paths from the building of interest to surrounding buildings within the given network radius resemble straight Euclidian paths. (Porta, Strano et al., 2009)! DEcul.ij S (i) = ∑ j ≠i dij € MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 23 of 33!
- 24. Compute Straightness (optional)!The Straightness measure illustrates the extent to which the shortest paths from the building of interest to surrounding buildings within the given network radius resemble straight Euclidian paths. (Porta, Strano et al., 2009)! MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 24 of 33!
- 25. Building ID Field (optional)!Field Name in the Input Points ﬁle • Choose any column with unique IDs in the Input Points shapeﬁle as building IDs, and the analysis results are returned by the chosen Building ID. • If no IDs are chosen, then the “FID” ﬁeld is used by default. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 25 of 33!
- 26. Building Weights Field (optional)!Field Name in the Input Points ﬁle • Allows the user to choose an attribute column from the Input Points shapeﬁle to be used as building weights in the analysis. • Node weights can describe any meaningful numeric characteristics of buildings – building size, number of residence, the presence of businesses etc. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 26 of 33!
- 27. Impedance Attribute!Cost Attribute in the Network Dataset • Designates which impedance characteristic (metric or topological) associated with the Input Network will be used in all calculations to limit radii and shortest path computations. • The default value ‘Length’ sets linear distance as the impedance attribute. A B MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 27 of 33!
- 28. Search Radius!Limit to the Impedance Attribute • For each Input Building, only other points whose shortest network distance from the given Input Point is less than the Search Radius, are considered in the analysis. Default value is 600m (10 min walking radius). • If no Search Radius is speciﬁed by the user, then the default inﬁnite (n) radius is used to reach all parts of the graph. • The units for Search Radius are the same as the Impedance Attribute units of your Network Dataset: if your network Impedance Attribute is in meters, then the Search Radius is in meters etc. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 28 of 33!
- 29. Max Neighbor Separation!Max distance between neighboring Input Points. • Deﬁnes the maximum distance that the Adjacecny Matrix uses to search for neighboring Input Points. • Units in linear length (e.g. meters, kilometers) • Default set to 600m. Increase if input point further apart in regional networks. MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 29 of 33!
- 30. Beta!Only used for computing the Gravity Index. • Only used for computing the Gravity Index. • Adjusts the effect of distance decay. • Default set to “1”. • For pedestrian trips, empirical research suggest the value “0.18” (Handy & Niemeier, 1997) MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 30 of 33!
- 31. Normalize Results!Applicable to only Betweenness, Closeness, Straightness. • If this value is “True” then the analysis results are divided by the number of Input Points within the speciﬁed Search Radius around each point. • Only used for Betweenness, Closeness and Straightness. • Normalized Betweenness, for instance, makes the resulting values “percentages of trips passing a location”, rather than “number of trips passing a location”. • Useful for points that have a different number of neighbors in a given Search Radius. 47 Neighbors 16 Neighbors MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 31 of 33!
- 32. Computation Steps!Script order 1. Compute Adjacency Matrix (if same inputs have been previously used, the Adj. Matrix is automatically re-used). 2. Construct Graph from Adj. matrix 3. Retrieve Node Weights and X-Y coordinates (if needed) 4. Run Centrality Computation 5. Write Out Results to a *.dbf ﬁle 6. Display Results MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 32 of 33!
- 33. Thank you!! A Toolbox for ArcGIS 10 asevtsuk@mit.edu! City Form Research Group!MIT – DUSP / ARCH | City Form Research Group | Urban Network Analysis: A Toolbox for ArcGIS 10 | 33 of 33!

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