Bandwidth determination for kernel density analysis of wildfire events at forest sub-district scale

被引:24
|
作者
Kuter, Semih [1 ]
Usul, Nurunnisa [2 ]
Kuter, Nazan [3 ]
机构
[1] Cankiri Karatekin Univ, Dept Forest Engn, TR-18200 Cankiri, Turkey
[2] Middle E Tech Univ, Dept Civil Engn, TR-06531 Ankara, Turkey
[3] Cankiri Karatekin Univ, Dept Landscape Architecture, TR-18200 Cankiri, Turkey
关键词
Forest fire; Kernel density estimation; Kernel bandwidth; Grid resolution; Correlation; HOME-RANGE; ESTIMATORS; FIRES;
D O I
10.1016/j.ecolmodel.2011.06.006
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Forest fire is regarded as one of the most significant factors leading to land degradation. While evaluating fire hazard or producing fire risk zone maps, quantitative analyses using historic fire data is often required, and during all these modeling and multi-criteria analysis processes, the fire event itself is taken as the dependent variable. However, there are two main problematic issues in analyzing historic fire data. The first difficulty arises from the fact that it is in point format, whereas a continuous surface is frequently needed for statistically analyzing the relationship of fire events with other factors, such as anthropogenic, topographic and climatic conditions. Another, and probably the most bothersome challenge is to overcome inaccuracy inherent in historic fire data in point format, since the exact coordinates of ignition points are mostly unknown. In this study, kernel density mapping, a widely used method for converting discrete point data into a continuous raster surface, was used to map the historic fire data in Mumcular Forest Sub-district in Mugla, Turkey. The historic fire data was transferred onto the digital forest stand map of the study area, where the exact locations of ignition points are unknown; however, the exact number of ignition points in each compartment of the forest stand map is known. Different random distributions of ignition points were produced, and for each random distribution, kernel density maps were produced by applying two distinct kernel functions with several smoothing parameter options. The obtained maps were compared through correlation analysis in order to illustrate the effect of randomness, choice of kernel function and smoothing parameter. The proposed method gives a range of values rather than a single bandwidth value: however, it provides a more reliable way than comparing the maps with different bandwidths subjectively by eye. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:3033 / 3040
页数:8
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