Spatio-Temporal Clustering of Road Accidents: GIS Based Analysis and Assessment

Prasannakumar, V.; Vijith, H.; Charutha, R.; Geetha, N.

doi:10.1016/j.sbspro.2011.07.020

Cited by 249 publications

(152 citation statements)

References 12 publications

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“…A pesar de que existe una gran cantidad de estudios sobre incendios forestales realizado en los últimos años en México, la comparación cuantitativa de las características espaciales en la agrupación de puntos de calor es novedosa. La mayoría de los estudios reportados se relacionan con accidentes de tráfico (Mohan 2009, Prasannakumar et al 2011, con aplicaciones en mercado inmobiliario (Islam y Asami 2011) y con áreas forestales incendiadas (Chuvieco y Congalton 1989, Bohórquez et al 2011, entre otras temáticas. Por ello, el análisis espacial de la ocurrencia de incendios forestales resulta un factor clave para comprender su comportamiento y para propósitos de planeación, diseño de estrategias y acciones apropiadas para el manejo del fuego en ecosistemas forestales (Gollberg et al 2001).…”

Section: Introductionunclassified

Determinación de la tendencia espacial de los puntos de calor como estrategia para monitorear los incendios forestales en Durango, México

Pompa-García¹,

González

2012

Bosque (Valdivia)

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SUMMARYIn Mexico hotspots detection is a useful tool to provide opportune information on forest fire fighting. The aim of this study was to assess hotspots for the period of 2001-2010 in various ecozones in the north of México. The study area was divided into 1,343 physiographical units, and quantitative indices of clustering were calculated using the Getis-Ord statistics. As a statistical test on the validity of the clustering, a p-value test was carried out. Results revealed that the locations of hotspots showed a clustered distribution that was remarkable on conifer-oak ecosystems. A remaining challenge is to conduct more detailed analyses that investigate the underlying mechanisms responsible for the spatial clustered fire. Historical data were attractive in terms of simplicity, low costs, and transparency. They also provide useful information to researchers to conceptualize where ignitions could occur. The approach could be applied at a finer time and space scale where ignition data are available.Key words: fire, spatial analysis, G statistics, geostatistics. RESUMENEn México la detección de puntos de calor es una herramienta que provee información oportuna para el combate de incendios forestales. El objetivo de este estudio fue evaluar el grado de agrupamiento de puntos de calor para el periodo 2001 al 2010 en diferentes ecozonas del norte de México. El área de estudio fue dividida en 1.343 unidades fisiográficas sobre las cuales se aplicó el estadístico G de GetisOrd para calcular el grado de agrupamiento, incluyendo una prueba estadística de su validez. Los resultados revelan que el patrón espacial de los puntos de calor muestra una distribución agrupada acentuada en los ecosistemas de coníferas y encinas. Se discute la necesidad de contar con análisis más detallados para investigar los mecanismos responsables del agrupamiento. Los datos históricos resultaron atractivos en términos de simplicidad, bajos costos y son útiles para apoyar a los investigadores a conceptualizar donde pueden ocurrir los incendios forestales. Además este procedimiento puede aplicarse a escalas más finas de tiempo y espacio en donde los datos estén disponibles.Palabras clave: fuego, análisis espacial, estadístico G, geoestadística.

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Section: Introductionunclassified

Determinación de la tendencia espacial de los puntos de calor como estrategia para monitorear los incendios forestales en Durango, México

Pompa-García¹,

González

2012

Bosque (Valdivia)

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“…Using the kernel function, the optimized hot spot analysis calculates the Getis-Ord statistic for each feature in a dataset to identify the location of local clusters for site-effect parameters (G€ okkaya 2016). The Getis-Ord Gi Ã of the target feature is included in the analysis, and shows where hot spots (clusters of high values) or cold spots (clusters of low values) exist in the area (Getis and Ord 1996;Prasannakumar et al 2011). This method works by examining each feature within the context of neighbouring features.…”

Section: Multivariable Statistical Clusteringmentioning

confidence: 99%

GIS-based regional assessment of seismic site effects considering the spatial uncertainty of site-specific geotechnical characteristics in coastal and inland urban areas

Sun

Kim

2017

Geomatics, Natural Hazards and Risk

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Earthquake-induced hazards are profoundly affected by site effects related to the amplification of ground motions, which are strongly influenced by site-specific geologic conditions such as soil thickness, bedrock depth and soil stiffness. Seismic disasters are often more severe in coastal or riverside locations than over stiff soils or rocks due to differences in local site effects. In this study, a recently developed geographic information system-based framework was applied in coastal and inland urban areas in Korea, and its applicability for regional assessments was evaluated using appropriate geostatistical zonation of site-specific seismic site effects. The proposed framework was composed of four functional components: multivariable statistical clustering, geostatistical optimization, geotechnical analysis, and local visualization. The framework was applied in the Seoul and Busan areas of Korea for consideration of site effects in inland and coastal urban areas. Such zones of thick soil, or with a deep depth to bedrock, are susceptible to ground motion amplification due to site effects during earthquakes. The earthquake losses associated with possible building damage can be estimated based on spatial zoning maps considering geological and topographical characteristics and by a comparison of the spatial correlations of seismic site classes between inland and coastal areas of Korea.

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“…이러한 사업을 진행할 때, 어떤 지점에 안전 대책을 우 선적으로 수립하여야 교통안전을 크게 개선할 수 있는지 파 악하는 것은 매우 중요하다 (Khan et al, 2008). 많은 연구들이 교통사고 핫스팟 선정에 KDE를 사용하였 으며 (Anderson, 2009;Flahaut et al, 2003;Plug et al, 2011;Prasannakumar et al, 2011;Truong and Somenahalli, 2011;Vemulapalli, 2015), 일부 연구들은 KDE를 시행하여 보행자 사고 핫스팟을 선정하였다 (Blazquez and Celis, 2013;Jang et al, 2013;Loo et al, 2011;Pulugurtha et al, 2007;Rankavat and Tiwari, 2013 일부 연구들은 Getis-ord Gi*를 시행하여 교통사고 핫스팟 을 선정하였다 (Khan et al, 2008;Kingham et al, 2011;Kuo et al, 2011;Manepalli et al, 2011;Vemulapalli, 2015). 특히, Getis-ord Gi*를 사용한 기존 연구들은 Getis-ord Gi*로 …”

Section: 서 론unclassified

A Selection of High Pedestrian Accident Zones Using Traffic Accident Data and GIS: A Case Study of Seoul

양종현¹,

김정옥²,

유기윤³

2016

Journal of the Korean Society of Surveying, Geodesy, Photogramm

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To establish objective criteria for high pedestrian accident zones, we combined Getis-ord Gi* and Kernel Density Estimation to select high pedestrian accident zones for 54,208 pedestrian accidents in Seoul from 2009 to 2013. By applying Getis-ord Gi* and considering spatial patterns where pedestrian accident hot spots were clustered, this study identified high pedestrian accident zones. The research examined the microscopic distribution of accidents in high pedestrian accident zones, identified the critical hot spots through Kernel Density Estimation, and analyzed the inner distribution of hot spots by identifying the areas with high density levels.Keywords: Pedestrian Accident, Hotspot, Getis-ord Gi*, Kernel Density Estimation This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Spatio-Temporal Clustering of Road Accidents: GIS Based Analysis and Assessment

Cited by 249 publications

References 12 publications

Determinación de la tendencia espacial de los puntos de calor como estrategia para monitorear los incendios forestales en Durango, México

Determinación de la tendencia espacial de los puntos de calor como estrategia para monitorear los incendios forestales en Durango, México

GIS-based regional assessment of seismic site effects considering the spatial uncertainty of site-specific geotechnical characteristics in coastal and inland urban areas

A Selection of High Pedestrian Accident Zones Using Traffic Accident Data and GIS: A Case Study of Seoul

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