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dc.contributorFaculty of Construction and Environmenten_US
dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.contributor.advisorShea, Yu-kai Geoffrey (LSGI)-
dc.creatorTam, Wai Ming-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/10539-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleEvaluation of meteorology factor on wildfire prediction using GISen_US
dcterms.abstractBeing in a densely populated society and heavily developed modern world, wildfire is a major environmental issue, creating economic and ecological damage to human life. Forest and vegetation area are getting scarcer and scarcer as urban development putting the green to the brink. The occurrence of forest fire also known as wildfire is amajor cause which destroy the forest preservation and vegetation land. The occurrence of wildfire may due to multiple causes and despite an increasing of expenses to controlthis disaster, each year millions of forest hectares are destroyed all around the world. (Paulo Cortsz and Anibal Morais) Wildfire early detection and accurate prediction are the key elements in successful wildfire prevention. There has been an emphasis to develop an automated fire detection solution to avoid human inefficiency due to subjective factors. They can be grouped into satellite based remote sensing, infra-red/smoke scanning and sensor based monitoring. On this paper, we focus on fire prediction. Weather conditions, such as temperature and air humidity; topography such as slope and aspect; and fuel type such as vegetation formation and forest composition, are known to affect fire occurrence. Since weather stations and meteorology satellite service are often available, such data can be collected in real-time, with low costs, we would like to evaluate the importance of this factor in fire spread. In the past, meteorological data has been incorporated into numerical indices, which are used for prevention and warning the public of a fire danger and to support fire management decisions (Paulo Cortsz and Anibal Morais). In this paper we would like to evaluate the significant influence of meteorology factor on wildfire prediction and make use of GIS to illustrate and analyze wildfire prediction model, as GIS is an important and intuitive tools to illustrate data in geo-located and 3D manner which help further enhance the usability on the predicted result.en_US
dcterms.extentix, 57 pages : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2018en_US
dcterms.educationalLevelM.Sc.en_US
dcterms.educationalLevelAll Masteren_US
dcterms.LCSHWildfire forecastingen_US
dcterms.LCSHGeographic information systemsen_US
dcterms.LCSHWildfires—Prevention and controlen_US
dcterms.LCSHFire weatheren_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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