Forest fire risk analysis via integration of GIS, RS and AHP: The Case of Çanakkale, Turkey
| Autor: | Hasan Tatli, Gurcu Aygün, Bülent Sağlam, Cengiz Akbulak |
|---|---|
| Přispěvatelé: | TUBİTAK |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Crown closure
Risk analysis Geographic information system Geograph 010504 meteorology & atmospheric sciences Risk Analysis GIS business.industry Environmental resource management Analytic hierarchy process Context (language use) 010501 environmental sciences 01 natural sciences Normalized Difference Vegetation Index Forest Fire Risk Analysis GIS AHP Remote Sensing Turkey Geography Preparedness Vegetation type business 0105 earth and related environmental sciences |
| Zdroj: | Uluslararası İnsan Bilimleri Dergisi; Vol 15, No 4 (2018); 2127-2143 Journal of Human Sciences; Vol 15, No 4 (2018); 2127-2143 |
| ISSN: | 2458-9489 1303-5134 |
| Popis: | Forest fire is one of the high-risk natural disasters in the north-western Anatolia section of Turkey. This paper suggests a new approach based on Geographic Information Systems (GIS), Remote Sensing (RS) and Analytical Hierarchy Process (AHP) for the development of forest fire-risk model. The proposed approach includes human factors as well as environmental factors. In this context, the 12 variables defined under anthropogenic and physical factors in the proposed model are the slope, elevation, aspect, vegetation type, crown closure, Normalized Difference Vegetation Index (NDVI), distance to road, settlement, and agricultural areas, population density, previous fires, and Canadian Forest Fire Weather Index (FWI). For each variable, a layer was created in the GIS database environment. GIS-layers were classified, considering the risk of potentially generating forest-fire of the relevant variables. In addition, to generate risk maps, the weights used in these GIS-layers were obtained by applying the AHP technique. One of the major results of the study shows that the rates of “extreme”, “very high”, “high”, and “moderate” risk areas are 3.87%, 63.46%, 32.13% and 0.53%, respectively. Another important result is that there are not observed the so called “no risk" and "low risk" classes in the region. The results let us to make a conclusion that the natural and human factors having significant contributions the region to be fire-prone. Yet, these results also indicate that rather than emphasizing forest-fire preparedness and mitigation, policy-makers manage forest-fires through reactive, crisis-oriented approaches. In contrast to crisis-based management plans, this study suggests that risk-based preventive plans should be developed and implemented. |
| Databáze: | OpenAIRE |
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