2021
DOI: 10.1007/978-3-030-76059-5_13
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Developing a GIS-Based Tourist Walkability Index Based on the AURIN Walkability Toolkit—Case Study: Sydney CBD

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Cited by 5 publications
(7 citation statements)
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“…In recent years, a wide variety of approaches and applications have been developed in the field of digital tools and 3D models to address the study of various properties and characteristics [26][27][28][29][30], such as 3D modelling, satellite images, point clouds, and even gamification, allowing users to evaluate physical attributes, such as ground surface and pavement conditions, urban planning, people and vehicular dynamics, and weather conditions, among others. These methods not only allow for the evaluation of physical attributes, such as ground surface and topographical conditions using digital terrain models [20,[31][32][33], but also delve into more detailed aspects of the urban environment being studied, such as the identification of urban furniture, like lampposts, trees, traffic, and pedestrian signs, and so on [34][35][36].…”
Section: Street Digitizationmentioning
confidence: 99%
“…In recent years, a wide variety of approaches and applications have been developed in the field of digital tools and 3D models to address the study of various properties and characteristics [26][27][28][29][30], such as 3D modelling, satellite images, point clouds, and even gamification, allowing users to evaluate physical attributes, such as ground surface and pavement conditions, urban planning, people and vehicular dynamics, and weather conditions, among others. These methods not only allow for the evaluation of physical attributes, such as ground surface and topographical conditions using digital terrain models [20,[31][32][33], but also delve into more detailed aspects of the urban environment being studied, such as the identification of urban furniture, like lampposts, trees, traffic, and pedestrian signs, and so on [34][35][36].…”
Section: Street Digitizationmentioning
confidence: 99%
“…In our approach, we use this quantity to assess isolation, the ISL(i) of a node (7). To evaluate integration, the INT(i) of a node (8), we use the FPT (13) calculated for the anisotropic RBW random walks (5) and denoted as FPT ∞ (i). As the RBW walks (5) are statistically bound to the graph nodes hosting the majority of very long walks, but repelled from the graph structural defects and boundaries, FPT ∞ (i) ≪ FPT 1 (i), for the walking hubs i, at the crossroads of very long walks, far apart from the graph structural irregularities, even though their immediate connectivity (degree) is not very high.…”
Section: Integration Index Of a Node (Int)mentioning
confidence: 99%
“…To evaluate integration, the INT(i) of a node (8), we use the FPT (13) calculated for the anisotropic RBW random walks (5) and denoted as FPT ∞ (i). As the RBW walks (5) are statistically bound to the graph nodes hosting the majority of very long walks, but repelled from the graph structural defects and boundaries, FPT ∞ (i) ≪ FPT 1 (i), for the walking hubs i, at the crossroads of very long walks, far apart from the graph structural irregularities, even though their immediate connectivity (degree) is not very high. Alternatively, considering that the probability of finding an RBW-walker in a remote node i ∈ V, which is not significant for the system of very long walks in the graph, is very low, we can conclude that for such a node, it should be FPT ∞ (i) ≫ FPT 1 (i).…”
Section: Integration Index Of a Node (Int)mentioning
confidence: 99%
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“…To conduct the analyses, first, the locations of UGSs at the scale of the Adelaide Metropolitan Area at the local government area level were Identified using the AURIN's dataset of 'PSMA -Transport & Topography -Greenspace (Polygon) August 2020'. AURIN which stands for Australian Urban Research Infrastructure Network, provides a portal in which researchers can access a vast range of datasets and computational tools for analysing, synthesising and visualising the urban and geographical data for all Australian cities (Bassiri Abyaneh et al, 2021).…”
Section: Case Studymentioning
confidence: 99%