Urban Network Analysis Toolbox v1.01 released
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Andres
Sep 28, 2013, 10:21:42 PM9/28/13
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Dear UNA Toolbox users,
Figure 1: Redundant paths that are up to 15% longer than the shortest path between the given origin and destination. The O (left black circle) in this example is an entrance of a public housing block, and the D a light rail station in Punggol, Singapore.
The Redundancy Index computes the ratio of the sum of the lengths of redundant segments to the sum of the lengths of shortest path segments per each O-D pair. If there are multiple destinations for the same origin, we average these multiple values.
Figure 2: Redundancy Index for paths connecting each apartment block entrance to the light rail station (black circle), with a distance quota of 1.1 (or 110 %). The index tells us how many times more linear path length becomes available from an origin to a destination if the walk is extended by a given percentage above the shortest path. If extending walks by 10%, for instance, yields a result of “Redundancy = 5.5”, then this means that 5.5 times more path length becomes available on redundant paths compared to the shortest path alone.
Redundancy analysis typically estimates the ratio of redundant path distances over the shortest path distance. Using weights allows the analysis to alter the ratio from comparing distances to comparing some other attributes of the paths. If the chosen weights describe the number of retailers at each input point, for instance, then the Redundancy Index will return the ratio between the number of retailers found on all redundant paths over the number of retailers on found on the shortest path. The weighted index describes how many more weights can be encountered on redundant paths that are up to a given percent longer than the shortest path.
The Redundant Paths tool can additionally compute the Wayfinding Index for each origin from any given set of destinations. The Wayfinding index for a pair of nodes O and D is the probability of reaching D starting from O and making uniformly random decisions at every intersection, within a given distance quota above the shortest path and with the restriction that all traveled paths must be simple (no repeating nodes). Figure 15 below illustrates the how the index is computed graphically. The probability of reaching D from O with random walks and within a 1.2 distance coefficient (20% longer than shortest path)t in the image is 7 out of 72, or 9.72%.
Figure 3: The Wayfinding Index computes the probability of reaching a destination from an origin while taking random choices at all intersections and limiting the search distance to the given Redundancy Coefficient and allowing only simple paths. The probability of reaching D from O within a Redundancy Coefficient of 1.2 in the image is1/3*1/2*1/3+1/3*1/2*1/2 *1/2=7/72,which is 9.72%.
A new HELP file describes the added functionality in greater detail. This is all pretty new, so if you find any bugs, please let us know by emailing the support forum.
The toolbox can be downloaded from the UNA tools site. And as usual, the code is open source and available on BitBucket. Enjoy!
City Form Lab team.
We are thrilled to release a new version (1.01) of the Urban Network Analysis Toolbox for ArcGIS today. The updated version introduces three new tools: [1] the Redundancy Index tool, [2] the Redundant Paths tool, and [3] the Wayfinding Index tool. Each can be used to study alternative travel options between origins and destinations in a city. They help us understand the encounters and experiences that built environments offer and allow us to evaluate factors that affect pedestrian, bike or vehicula or path choice in complex environments.
Much of spatial network analysis assumes that travel occurs along the shortest available routes. This is not necessarily the case in reality – people often use paths that are slightly longer than the shortest path in order to pass by other locations on the way, to experience a more scenic or interesting route, or to navigate a simpler path. The new Redundancy tools allow you to detect and analyze these alternative paths. The tools find alternative paths that are available between an origin and destination within a given distance quota beyond the shortest path, display the segments or routes that participate in any of the redundant paths, and quantify the their distribution around different destinations.
Figure 1: Redundant paths that are up to 15% longer than the shortest path between the given origin and destination. The O (left black circle) in this example is an entrance of a public housing block, and the D a light rail station in Punggol, Singapore.
The Redundancy Index computes the ratio of the sum of the lengths of redundant segments to the sum of the lengths of shortest path segments per each O-D pair. If there are multiple destinations for the same origin, we average these multiple values.
Figure 2: Redundancy Index for paths connecting each apartment block entrance to the light rail station (black circle), with a distance quota of 1.1 (or 110 %). The index tells us how many times more linear path length becomes available from an origin to a destination if the walk is extended by a given percentage above the shortest path. If extending walks by 10%, for instance, yields a result of “Redundancy = 5.5”, then this means that 5.5 times more path length becomes available on redundant paths compared to the shortest path alone.
Redundancy analysis typically estimates the ratio of redundant path distances over the shortest path distance. Using weights allows the analysis to alter the ratio from comparing distances to comparing some other attributes of the paths. If the chosen weights describe the number of retailers at each input point, for instance, then the Redundancy Index will return the ratio between the number of retailers found on all redundant paths over the number of retailers on found on the shortest path. The weighted index describes how many more weights can be encountered on redundant paths that are up to a given percent longer than the shortest path.
The Redundant Paths tool can additionally compute the Wayfinding Index for each origin from any given set of destinations. The Wayfinding index for a pair of nodes O and D is the probability of reaching D starting from O and making uniformly random decisions at every intersection, within a given distance quota above the shortest path and with the restriction that all traveled paths must be simple (no repeating nodes). Figure 15 below illustrates the how the index is computed graphically. The probability of reaching D from O with random walks and within a 1.2 distance coefficient (20% longer than shortest path)t in the image is 7 out of 72, or 9.72%.
Figure 3: The Wayfinding Index computes the probability of reaching a destination from an origin while taking random choices at all intersections and limiting the search distance to the given Redundancy Coefficient and allowing only simple paths. The probability of reaching D from O within a Redundancy Coefficient of 1.2 in the image is1/3*1/2*1/3+1/3*1/2*1/2 *1/2=7/72,which is 9.72%.
A new HELP file describes the added functionality in greater detail. This is all pretty new, so if you find any bugs, please let us know by emailing the support forum.
The toolbox can be downloaded from the UNA tools site. And as usual, the code is open source and available on BitBucket. Enjoy!
City Form Lab team.
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