Lightning-caused forest fire risk rating assessment based on case-based reasoning: a case study in DaXingAn Mountains of China

2015 ◽  
Vol 81 (1) ◽  
pp. 347-363 ◽  
Author(s):  
Wenliang Liu ◽  
Shixin Wang ◽  
Yi Zhou ◽  
Litao Wang ◽  
Jinfeng Zhu ◽  
...  
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Case Based Reasoning ◽  
Risk Rating ◽  
Forest Fire Risk ◽  
Case Based

Applying GIS to develop a model for forest fire risk: A case study in Espírito Santo, Brazil

2016 ◽  
Vol 173 ◽  
pp. 65-71 ◽  
Author(s):  
Fernando Coelho Eugenio ◽  
Alexandre Rosa dos Santos ◽  
Nilton Cesar Fiedler ◽  
Guido Assunção Ribeiro ◽  
Aderbal Gomes da Silva ◽  
...  
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Espírito Santo ◽  
Espirito Santo ◽  
Forest Fire Risk

scholarly journals Mapping Forest Fire Risk at a Local Scale—A Case Study in Andalusia (Spain)

Environments ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 30 ◽  
Author(s):  
Ismael Vallejo-Villalta ◽  
Estefanía Rodríguez-Navas ◽  
Joaquín Márquez-Pérez
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Moisture Stress ◽  
Forest Environment ◽  
Protection Measures ◽  
Burned Areas ◽  
Fuel Models ◽  
Forest Fire Risk

Forest fires are a critical environmental problem facing current societies, with serious repercussions at ecological, economic and personal safety levels. Detailed maps enabling identification of areas liable to be affected is an indispensable first step allowing different prevention and protection measures vis-à-vis this kind of phenomenon. These maps could be especially valuable for use in land management and emergency planning at a municipality scale. A methodology is shown for producing local maps of mid- and short-term forest fire risk, integrating both natural and human factors. Among natural factors, variables normally used in hazard models are considered as fuel models, slopes or vegetation moisture stress. From the human perspective, more novel aspects have been evaluated, meant either to assess human-induced hazard (closeness to forestland of causative elements or the ability of people to penetrate the forest environment), or to assess vulnerability, considering the population’s location in urban centres and scattered settlements. The methodology is applied in a municipality of Andalusia (Spain) and obtained results were compared to burned areas maps.

Forest Fire Risk Zone Modeling Using Logistic Regression and GIS: An Iranian Case Study

2013 ◽  
Vol 13 (1) ◽  
pp. 117-125 ◽  
Author(s):  
Frouzan Mohammadi ◽  
Mahtab Pir Bavaghar ◽  
Naghi Shabanian
Keyword(s):  
Logistic Regression ◽  
Forest Fire ◽  
Fire Risk ◽  
Risk Zone ◽  
Zone Modeling ◽  
Forest Fire Risk

Assessment of seasonal forest fire risk using NOAA-AVHRR: a case study in central Mexico

2009 ◽  
Vol 30 (19) ◽  
pp. 4991-5013 ◽  
Author(s):  
L. Manzo-Delgado ◽  
S. Sánchez-Colón ◽  
R. Álvarez
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Central Mexico ◽  
Noaa Avhrr ◽  
Forest Fire Risk

scholarly journals Forest Fire Risk Assessment Using Hotspot Analysis in GIS

2017 ◽  
Vol 11 (1) ◽  
pp. 786-801 ◽  
Author(s):  
Safwanah Ni’matullah Binti Mohd Said ◽  
El-Said Mamdouh Mahmoud Zahran ◽  
Shahriar Shams
Keyword(s):  
Forest Fire ◽  
Geographical Information Systems ◽  
Fire Risk ◽  
Geographical Information ◽  
Asian Countries ◽  
Hotspot Analysis ◽  
Brunei Darussalam ◽  
Fire Stations ◽  
Forest Fire Risk

Background: Present intensifying forest fire incidents are becoming a major concern as they pose threats to the environment, economy and human’s safety. This paper aims to identify forest fire hotspots using advanced hotspot analysis in the Geographical Information Systems (GIS), and suggest appropriate preventive measures. Objective: Brunei Darussalam is one of the Southeast Asian countries that is significantly affected by the increase in forest fire incidents in this region. Brunei Muara is the worst-hit district by forest fire in Brunei Darussalam, and hence it was selected as a case study for this research. Results and Conclusion: This research identified and prioritized forest fire hotspots, highlighted the shortage of fire stations within the identified hotspots and suggested the suitable locations for new fire stations in Brunei Muara district.

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