Showing papers in "Computers, Environment and Urban Systems in 2015"

TL;DR: VR has a strong potential to be used as an empirical research tool in psychological and architectural research and that future studies could supplement behavioral validation, according to the main conclusion.

TL;DR: The study compares the results of two quantitative techniques in defining the extent of land-use zones at a large scale urban planning scenario and demonstrates that in the early stage of the planning process, simplified methods can be sufficient.

TL;DR: This paper reviews the use of virtual reality environments for research and teaching in the context of three disciplines: architecture, landscape architecture and environmental planning, and describes current VR research opportunities and challenges in each discipline.

TL;DR: Estimating the urban heat island intensities of the 50 most populous cities in the United States using gridded minimum temperature datasets and quantifying each city's urban morphology with spatial metrics indicated that the spatial contiguity of urban development, regardless of its density or degree of sprawl, was a critical factor that influenced the magnitude of theUrban heat island effect.

TL;DR: A coherent framework for extracting and understanding urban AOI based on geotagged photos, identified using DBSCAN clustering algorithm, understood by extracting distinctive textual tags and preferable photos, and discussed the spatiotemporal dynamics as well as some insights derived from the AOi are presented.

TL;DR: In this paper, the authors demonstrate a complete process that comprises the collection, unification, classification and validation of a type of VGI data and develop methods to utilize such POI data to estimate disaggregated land use (i.e., employment size by category) at a very high spatial resolution (census block level) using part of the Boston metropolitan area as an example.

TL;DR: Wang et al. as discussed by the authors combined bus SCD for a one-week period with a oneday household travel survey, as well as a parcel-level land use map to identify job-housing locations and commuting trip routes in Beijing.

TL;DR: Practical indicators and algorithms developed for large-scale vulnerability analyses, from the conceptual definition of vulnerability measures through the derivation of practical indicators and models adapted to available data and their implementation in computational procedures, are described.

TL;DR: A semantic topic model classification and spatial autocorrelation analysis is applied to detect tweets indicating specific human social activities, showing an overall strong positive correlation in comparison with workplace population census data, being a good indicator and representative proxy for analyzing workplace-based activities.

TL;DR: The objective of this research is to combine the simulation skills of CA with the machine learning approach called support vector machines (SVM), which enables the dynamical simulation of different growth types on the one hand as well as the analyses of various geophysical and socio-economic driving forces on the other hand.

TL;DR: A key finding of this work is that walking activity can be robustly detected in the data stream, which, in turn, acts as a separator for partitioning the data streams into other activity segments.

TL;DR: This paper identifies travel modes with a Bayesian network, whose structure is established based on a K2 algorithm and corresponding conditional probability tables are estimated with maximum likelihood methods and demonstrates that GPS travel surveys provide an opportunity to supplement traditional travel surveys.

TL;DR: This paper builds a recommendation system that provides users with the most popular landmarks as well as the best travel routings between the landmarks and applies a spatial clustering method to identify the main travel landmarks and subsequently rank these landmarks.

TL;DR: A multidisciplinary approach, based on remote sensing techniques and Geographical Information System (GIS) analysis, is presented, in order to assess the overall risk in the Paphos district (Cyprus), which has a great deal of archaeological sites and isolated monuments.

TL;DR: This project provides fast and accurate tourist destination detection by mining large amounts of geo-tagged Flickr images from 2007 on and provides insight in applying the RHadoop platform to strengthen large geospatial data analytics.

TL;DR: A semi-automated method is proposed that accounts for and resolves the major problems in the streamlined manual process of 3D as-built model creation in BIM, limited to building interiors consisting of planar structures.

TL;DR: Great variation in residential density development is observed, but it is found that densities increase within designated urban development zones and areas that rich in amenities, while restrictive planning regulations related to natural and landscape values tend to limit residential densities.

TL;DR: A loosely coupled model based on a genetic algorithm and game theory is constructed to improve the ability of existing land-use spatial optimization models for addressing local land- use competitions (the competitions on land units).

TL;DR: This paper compares the social properties of Twitter users’ networks with the spatial proximity of the networks and found that the density of networks and the spatial clustering depends on the size of the network; smaller networks are more socially clustered and extend a smaller physical distance and larger networks are physically more dispersed with less social clustering.

TL;DR: In this article, a hierarchical spatiotemporal data cube model is developed based on collections of space-time trajectories to represent the collective dynamics of social media users across aggregation boundaries at multiple spatial-time scales.

TL;DR: A GIS-based procedure to estimate the potential PV-electricity generation time series for every roof-top section within a study area using open source software is introduced.

TL;DR: The simulation results demonstrate that this combination of theoretically sound micro-foundations in agents’ behavior and empirical data is feasible and opens opportunities to explore various methodological and policy-relevant research questions including exploration of abrupt non-marginal changes in markets and regime shifts in coupled socio-environmental systems.

TL;DR: In most studies of economic resilience, much effort is attributed to the development of factors and measures representing economic and related resilience.

TL;DR: This research is the first study to use empirical data and game theory to analyze the decision-making process in urban development in the Wuhan area and shows that the game-theory based agent-cellular model is shown to be more effective than a pure cellular automata model in urban growth simulation.

TL;DR: This work investigates the role ontologies play as a key component in the process of semantic information extraction and shows how ontologies can be used in conjunction with natural language gazetteers in order to process semantic information about hazard events and augment spatiotemporal extraction with semantics.

TL;DR: In this article, the authors explore the capacity of one increasingly prevalent source of these data, geographically encoded photographs, to capture spatial expressions of place in an urban environment and show that there is a significant interaction between tag-space semantics and spatial aggregation which suggests that consideration of scale effects should be integral to analysis of tagged VGI for exploring citizens' sensing of urban environments.

TL;DR: This work addresses the regional variability hypothesis by trying to prove that all place types are created equal with respect to their temporal signatures, i.e., temporal check-in behavior does not change across space.

TL;DR: The directions which academic literature in the recent years took to improve the treatment of the four components in accessibility modelling are described, including topological/connectivity structures in the accessibility analyses.

TL;DR: A new vector CA-based prototype is presented making use of cadastral parcels and cellular space is combined with graph theory to get a better operability and neighbourhood factors are defined more flexible since every parcel is different from the rest.

TL;DR: The results show that, for the case study of Sardinia, this hypothesis that scarcely accessible spatial units are classifiable as rural areas is not always true, as some urban areas are not always highly accessible.