{"title":"阿尔及利亚奥雷什地区森林火灾风险建模和制图","authors":"S. Rahmani, Hassen Benmassoud","doi":"10.15291/geoadria.2846","DOIUrl":null,"url":null,"abstract":"The objective of this study is to modeling and mapping the Forest fire risk in the region of Aures situated in Northeast of Algeria, through the application of multi-criteria analysis methods to integrate geographic information systems (GIS) and remote sensing. The methodology is based on a weighted linear combination of three parameters that influence the initiation and propagation of a forest fire. These are vegetation, topography and anthropogenic index. The result is a vulnerability map classified into four classes according to pixel values. very high risk class forms 18,28% of the study area, high risk class forms 42,42%, moderate risk class forms 5,24% and 34,05% of the area is low risk.","PeriodicalId":42640,"journal":{"name":"Geoadria","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15291/geoadria.2846","citationCount":"3","resultStr":"{\"title\":\"Modeling and mapping forest fire risk in the region of Aures (Algeria)\",\"authors\":\"S. Rahmani, Hassen Benmassoud\",\"doi\":\"10.15291/geoadria.2846\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this study is to modeling and mapping the Forest fire risk in the region of Aures situated in Northeast of Algeria, through the application of multi-criteria analysis methods to integrate geographic information systems (GIS) and remote sensing. The methodology is based on a weighted linear combination of three parameters that influence the initiation and propagation of a forest fire. These are vegetation, topography and anthropogenic index. The result is a vulnerability map classified into four classes according to pixel values. very high risk class forms 18,28% of the study area, high risk class forms 42,42%, moderate risk class forms 5,24% and 34,05% of the area is low risk.\",\"PeriodicalId\":42640,\"journal\":{\"name\":\"Geoadria\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2020-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.15291/geoadria.2846\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geoadria\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15291/geoadria.2846\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoadria","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15291/geoadria.2846","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOGRAPHY","Score":null,"Total":0}
Modeling and mapping forest fire risk in the region of Aures (Algeria)
The objective of this study is to modeling and mapping the Forest fire risk in the region of Aures situated in Northeast of Algeria, through the application of multi-criteria analysis methods to integrate geographic information systems (GIS) and remote sensing. The methodology is based on a weighted linear combination of three parameters that influence the initiation and propagation of a forest fire. These are vegetation, topography and anthropogenic index. The result is a vulnerability map classified into four classes according to pixel values. very high risk class forms 18,28% of the study area, high risk class forms 42,42%, moderate risk class forms 5,24% and 34,05% of the area is low risk.