Full metadata record
|dc.contributor||Faculty of Construction and Environment||en_US|
|dc.contributor||Department of Land Surveying and Geo-Informatics||en_US|
|dc.contributor.advisor||Shea, Yu-kai Geoffrey (LSGI)||-|
|dc.creator||Tam, Wai Ming||-|
|dc.publisher||Hong Kong Polytechnic University||-|
|dc.rights||All rights reserved||en_US|
|dc.title||Evaluation of meteorology factor on wildfire prediction using GIS||en_US|
|dcterms.abstract||Being 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.extent||ix, 57 pages : color illustrations||en_US|
|dcterms.LCSH||Geographic information systems||en_US|
|dcterms.LCSH||Wildfires—Prevention and control||en_US|
|dcterms.LCSH||Hong Kong Polytechnic University -- Dissertations||en_US|
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