Fire Analysis and Production of Fire Risk Maps: The Trabzon Experience

Nişancı, Recep; Yıldırım, Volkan; Erbas, Yasar Selcuk

doi:10.5772/33183

Cited by 22 publications

(27 citation statements)

References 10 publications

(6 reference statements)

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“…(Sternlieb, Burchell 1973;Bertrand, Lawrence 1976;Karter et al 1977Karter et al , 1978USFA 2004USFA , 2009). 21st century brought more studies in Europe (Corcoran et al 2007a(Corcoran et al , 2007bšpatenkova, Stein 2010), Asia (Urban Research Institute 2004;Nisanci 2010;Zhao 2011;Lu et al 2013), Australia Chhetri et al 2009;Sufianto, Green 2012). A number of them applied spatial and temporal analysis and resulted in prognostic maps Wu 2007;Rohde et al 2010;Zhao 2011) and mathematical models (Wu, Ren 2009;Ceyhan et al 2013;Zhang 2013).…”

Section: Introductionmentioning

confidence: 96%

Spatial Analysis of Fires in Vilnius City in 2010–2012

Vasiliauskas

Beconytė

2015

Geodesy and Cartography

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The paper describes the results of investigation into urban fires in the city of Vilnius, Lithuania in the three-year period of 2010-2012. Cartographic and geospatial analysis of fires is needed due to dynamism of this phenomenon, risks for inhabitants, importance to city's socio-economic development and lack of geographic approach to research of urban fires in Lithuania. The registered fires were mapped and grouped by their type (abandoned building fires, open space fires, fires in tower blocks of flats, garbage can fires, vehicle fires and arsons), cause, location type (open space and premises) and by fatality rate. Spatial distribution of fires at different scales was analysed using cartographic method and spatial analysis with GIS. Some unexpected patterns have been revealed, analysed and compared with building materials that dominate in different areas of the city. It was found out that relative frequency of fires depends on complex parameters of socio-demographic environment whereas constructional materials have little or no impact. We expected to observe a relationship between criminal activities and fires due to similar influencing socio-demographic factors. Positive correlation, though insignificant, supported this hypothesis. The study showed that fire distribution patterns may be very specific for an individual city and difficult to explain by general assumptions. Different methods of spatial, statistical and cartographic analysis must be combined in order to make reliable generalisations.

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Section: Introductionmentioning

confidence: 96%

Spatial Analysis of Fires in Vilnius City in 2010–2012

Vasiliauskas

Beconytė

2015

Geodesy and Cartography

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“…The main target in watershed management is; conservation of natural resources, bringing the environment into a state where it can renew itself, and sustainable management of resources. Geographical Information Systems (GIS) are seen as a technological and indispensable tool for the preparation of the environments necessary for the collection of the data for the basin and its storage in the digital environment [2].…”

Section: Introductionmentioning

confidence: 99%

Mapping of Precipitation, Temperature and Evaporation Distributions in the Porsuk Basin Using Distant Forecasting Methods

Bakış¹,

Bayazıt²,

Uyguçgil³

et al. 2017

CWEEE

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Geographical data are of great importance in meteorology and climate science. These data can create the areal distribution models analyzed by spatial interpolation methods. The values of the areas without measurement data are estimated with these distribution models. In this study, distribution of meteorological parameters such as precipitation, temperature and evaporation in Porsuk basin, which is determined as research area, was investigated by Inverse Distance Weighting (IDW) and Ordinary Kriging methods. Actual meteorological data analyzed of the basin do not show a normal distribution statistically. Therefore, the data were firstly subjected to normalization and then analyzed according to the IDW and Ordinary Kriging methods to create distribution maps of precipitation, temperature and evaporation data. Quadratic mean error values were compared to investigate the reliability of analyzes. In this study, the analysis results of precipitation, temperature and evaporation data have been calculated by two different methods. Ordinary Kriging method has been determined as the method making the most accurate estimation.

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“…Bu faktörler arasında eğitim, yaş yapısı, aile tipi, hane halkı sayısı (Sarıkaya, 2011) (Nisanci, 2010).…”

Section: Sosyo-ekonomik Zarar Görebilirlik Unsurlarıunclassified