Street centrality and land use intensity in Baton Rouge, Louisiana

This paper examines the relationship between street centrality and land use intensity in Baton Rouge, Louisiana. Street centrality is calibrated in terms of a node's closeness, betweenness and straightness on the road network. Land use intensity is measured by population (residential) and employment (business) densities in census tracts, respectively and combined. Two CIS-based methods are used to transform data sets of centrality (at network nodes) and densities (in census tracts) to one unit for correlation analysis. The kernel density estimation (KDE) converts both measures to raster pixels, and the floating catchment area (FCA) method computes average centrality values around census tracts. Results indicate that population and employment densities are highly correlated with street centrality values. Among the three centrality indices, closeness exhibits the highest correlation with land use densities, straightness the next and betweenness the last. This confirms that street centrality captures location advantage in a city and plays a crucial role in shaping the intraurban variation of land use intensity. (C) 2010 Elsevier Ltd. All rights reserved

Point pattern analysis: an application to the loyalty networks of chain-stores

At the 41th congress of ERSA., Staufer-Steinnocher (2001) proved that kernel density estimation, a technique of spatial analysis belonging to the point pattern methods, can be usefully applied to geomarketing. Following this point of view, the aim of this paper is to show that other point pattern techniques (center-grahic statistics, global and local autocorrelation indexes, clustering methods, 'nearest neighbour index', 'Ripley's K statistic', etc.) are able to suggest important considerations in marketing researches, making explicit the "geographical knowledge" embedded in available informations. Namely this argument is demonstrated, analysing spatial distributions of big stores chained in a promotional network, finalised to improve fidelity in the consumers.

Correlating densities of centrality and activities in cities : the cases of Bologna (IT) and Barcelona (ES)

This paper examines the relationship between street centrality and densities of commercial and service activities in cities. The aim is to verify whether a correlation exists and whether some 'secondary' activities, i.e. those scarcely specialized oriented to the general public and ordinary daily life, are more linked to street centrality than others. The metropolitan area of Barcelona (Spain) is investigated, and results are compared with those found in a previous work on the city of Bologna (Italy). Street centrality is calibrated in a multiple centrality assessment (MCA) model composed of multiple measures such as closeness, betweenness and straightness. Kernel density estimation (KDE) is used to transform data sets of centrality and activities to one scale unit for correlation analysis between them. Results indicate that retail and service activities in both Bologna and Barcelona tend to concentrate in areas with better centralities, and that secondary activities exhibit a higher correlation

THE VISUALIZATION AND ANALYSIS OF URBAN FACILITY POIS USING NETWORK KERNEL DENSITY ESTIMATION CONSTRAINED BY MULTI-FACTORS

The urban facility, one of the most important service providers is usuallyrepresented by sets of points in GIS applications using POI (Point of Interest) modelassociated with certain human social activities. The knowledge about distributionintensity and pattern of facility POIs is of great significance in spatial analysis,including urban planning, business location choosing and social recommendations.Kernel Density Estimation (KDE), an efficient spatial statistics tool for facilitatingthe processes above, plays an important role in spatial density evaluation, becauseKDE method considers the decay impact of services and allows the enrichment ofthe information from a very simple input scatter plot to a smooth output densitysurface. However, the traditional KDE is mainly based on the Euclidean distance,ignoring the fact that in urban street network the service function of POI is carriedout over a network-constrained structure, rather than in a Euclidean continuousspace. Aiming at this question, this study proposes a computational method of KDEon a network and adopts a new visualization method by using 3-D “wall” surface.Some real conditional factors are also taken into account in this study, such astraffic capacity, road direction and facility difference. In practical works theproposed method is implemented in real POI data in Shenzhen city, China to depictthe distribution characteristic of services under impacts of multi-factors

Spatial analysis of road crashes involving vulnerable road users in support of road safety management strategies

n/

Flame Detection for Video-based Early Fire Warning Systems and 3D Visualization of Fire Propagation

Early and accurate detection and localization of flame is an essential requirement of modern early fire warning systems. Video-based systems can be used for this purpose; however, flame detection remains a challenging issue due to the fact that many natural objects have similar characteristics with fire. In this paper, we present a new algorithm for video based flame detection, which employs various spatio-temporal features such as colour probability, contour irregularity, spatial energy, flickering and spatio-temporal energy. Various background subtraction algorithms are tested and comparative results in terms of computational efficiency and accuracy are presented. Experimental results with two classification methods show that the proposed methodology provides high fire detection rates with a reasonable false alarm ratio. Finally, a 3D visualization tool for the estimation of the fire propagation is outlined and simulation results are presented and discussed.The original article was published by ACTAPRESS and is available here: http://www.actapress.com/Content_of_Proceeding.aspx?proceedingid=73

Urban monitoring using NetKDE and VGI: network based kernel density estimation on volunteered geographic information applied to Baghdad, Iraq

This paper presents a methodology for urban monitoring using volunteered geographic information (VGI) and journalism data Iraq war logs with network based kernel density estimation (NetKDE). It investigates, using spatio-temporal analysis, the evolution of urban events in Baghdad between 2004 and 2009. The extracted street network is based on the data distributed by OpenStreetMap (OSM). A total of 21,876 logged events, 66,648 network segments, 22,644 gridpoints (200m resolution grid) and 362,304 gridpoints (50m resolution grid) are used for the analysis. The methodology combines and adapts these VGI data and is mainly based on open source and/or publicly available software. It handles very large datasets with multiscale, multi-resolution and temporal perspectives. Fuzzy-set map comparison (FMC) is used to identify level of changes between each period of time. The methodology is already used in other fields of research being biology, urban planning, criminology or economic evelopment. It should help stakeholders in respective domain to analyze the evolution of network constrained events in multiple contexts. This paper is divided in three parts. Firstly, conceptual background of VGI, NetKDE and FMC is presented. Secondly, the methodology is illustrated using data Iraq war logs, OSM data and grids with two different resolutions. Thirdly, spatio-temporal analysis results are presented and discussed.Peer Reviewe