{"title":"模拟加纳阿哈福地区Bosomkese森林保护区的森林火灾风险","authors":"Adams Elias Dadzie, A. Mary","doi":"10.4314/sajg.v10i1.5","DOIUrl":null,"url":null,"abstract":"Forest fire is a devastating phenomenon in real life, causing huge losses of lives, properties and ecologies. A risk assessment model to identify, classify and map forest fire risk areas is presented in this paper. This model considers four risk models, i.e. ignition model, detection model, response model and fuel model analysis. The first model concentrates on human influence factors in forest fires, including the land use, distance from roads, and distance from settlements and the second model is made up of the possibility of fire visibility from road and settlement viewpoint. The forest fire response included distance from fire stations and motion resistance is the third model. The type of fuel (dry or wet), fuel moisture content, health of the forest vegetation and topography of the area were analysed as the fourth model. The study results indicate that very high-risk zones covered 38.8km2 representing 25.6% of the total forest area. Findings of the research are helpful in developing forest fire management systems. Fast and appropriate direction could be used by management to stop the spread of fire effectively. It also helps to provide effective means for protecting forests from fires as well as to formulate appropriate methods to control and manage forest fire damages and its spread. Recommendations were made at the end of the work to implement fire towers, break lines and employ the use of modern detection techniques such drones, etc to improve fire detection and response.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Modelling the risk of forest to fire for the Bosomkese Forest Reserve, Ahafo Region, Ghana\",\"authors\":\"Adams Elias Dadzie, A. Mary\",\"doi\":\"10.4314/sajg.v10i1.5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Forest fire is a devastating phenomenon in real life, causing huge losses of lives, properties and ecologies. A risk assessment model to identify, classify and map forest fire risk areas is presented in this paper. This model considers four risk models, i.e. ignition model, detection model, response model and fuel model analysis. The first model concentrates on human influence factors in forest fires, including the land use, distance from roads, and distance from settlements and the second model is made up of the possibility of fire visibility from road and settlement viewpoint. The forest fire response included distance from fire stations and motion resistance is the third model. The type of fuel (dry or wet), fuel moisture content, health of the forest vegetation and topography of the area were analysed as the fourth model. The study results indicate that very high-risk zones covered 38.8km2 representing 25.6% of the total forest area. Findings of the research are helpful in developing forest fire management systems. Fast and appropriate direction could be used by management to stop the spread of fire effectively. It also helps to provide effective means for protecting forests from fires as well as to formulate appropriate methods to control and manage forest fire damages and its spread. Recommendations were made at the end of the work to implement fire towers, break lines and employ the use of modern detection techniques such drones, etc to improve fire detection and response.\",\"PeriodicalId\":43854,\"journal\":{\"name\":\"South African Journal of Geomatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2022-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South African Journal of Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/sajg.v10i1.5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/sajg.v10i1.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Modelling the risk of forest to fire for the Bosomkese Forest Reserve, Ahafo Region, Ghana
Forest fire is a devastating phenomenon in real life, causing huge losses of lives, properties and ecologies. A risk assessment model to identify, classify and map forest fire risk areas is presented in this paper. This model considers four risk models, i.e. ignition model, detection model, response model and fuel model analysis. The first model concentrates on human influence factors in forest fires, including the land use, distance from roads, and distance from settlements and the second model is made up of the possibility of fire visibility from road and settlement viewpoint. The forest fire response included distance from fire stations and motion resistance is the third model. The type of fuel (dry or wet), fuel moisture content, health of the forest vegetation and topography of the area were analysed as the fourth model. The study results indicate that very high-risk zones covered 38.8km2 representing 25.6% of the total forest area. Findings of the research are helpful in developing forest fire management systems. Fast and appropriate direction could be used by management to stop the spread of fire effectively. It also helps to provide effective means for protecting forests from fires as well as to formulate appropriate methods to control and manage forest fire damages and its spread. Recommendations were made at the end of the work to implement fire towers, break lines and employ the use of modern detection techniques such drones, etc to improve fire detection and response.