Forest Fire Risk Zone Modeling and Mapping in Bale Mountains National Park (Bmnp), Oromia, Ethiopia
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Date
2016-06
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Addis Ababa Universty
Abstract
Although BMNP is playing a vital role in environmental protection, it is suffering from a frequent forest fire in the past two decades. Despite the observed increasing forest fire incidence in the BMNP, there are limitations of detailed forest fire risk modeling and mapping and identification of factors influencing forest fire. The aim of this study was to identify the key explanatory attributes of forest fire, model and map forest fire risk zones and to validate the model. Landsat 8 OLI of 2015, SRTM 30m DEM, and Topographic map of scale 1:50,000 was used to produce the explanatory attributes. Six explanatory attributes: lulc, elevation, slope, aspect, proximity to settlements and distance from roads were identified using correlation analysis and OLS and GWR regression analysis. The factors were grouped into two sub-models consisting of Biophysical and Ignition sub-models. Pairwise comparison was applied in order to assign weightages for the factors. Multi-criteria decision-making technique was used to derive final forest fire risk model and map of the study area. GPS data was collected from the areas where there was frequent forest fire in order to support model validation. The final forest fire risk map of BMNP was categorized into four categories as extreme, high, moderate and low risk based on their fire susceptibility. The results revealed that 94.28 km2 (4.5%), 868.10 km2 (41.55%), 997 km2 (47.73%) and 129.56 km2 (6.2%) area of BMNP are categorized under extreme, high, moderate and low risk respectively. The result shows that there is significant area under fire risk which needs frequent follow up. It was recommended that incorporating other models, such as fire spread models and fire behaviour models are important for improved understanding fire management in the area.
Key words: BMNP, Explanatory attributes, Forest fire risk zone, GIS, Modeling
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Keywords
BMNP, Explanatory attributes, Forest fire risk zone, Modeling