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

Author

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  • Kuter, Semih
  • Usul, Nurunnisa
  • Kuter, Nazan

Abstract

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 Muğla, 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.

Suggested Citation

  • Kuter, Semih & Usul, Nurunnisa & Kuter, Nazan, 2011. "Bandwidth determination for kernel density analysis of wildfire events at forest sub-district scale," Ecological Modelling, Elsevier, vol. 222(17), pages 3033-3040.
  • Handle: RePEc:eee:ecomod:v:222:y:2011:i:17:p:3033-3040
    DOI: 10.1016/j.ecolmodel.2011.06.006
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    References listed on IDEAS

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    1. Amatulli, Giuseppe & Peréz-Cabello, Fernando & de la Riva, Juan, 2007. "Mapping lightning/human-caused wildfires occurrence under ignition point location uncertainty," Ecological Modelling, Elsevier, vol. 200(3), pages 321-333.
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    Cited by:

    1. Pengshan Li & Yahui Lv & Chao Zhang & Wenju Yun & Jianyu Yang & Dehai Zhu, 2016. "Analysis and Planning of Ecological Networks Based on Kernel Density Estimations for the Beijing-Tianjin-Hebei Region in Northern China," Sustainability, MDPI, vol. 8(11), pages 1-17, October.
    2. Weckel, Mark & Rockwell, Robert F., 2013. "Can controlled bow hunts reduce overabundant white-tailed deer populations in suburban ecosystems?," Ecological Modelling, Elsevier, vol. 250(C), pages 143-154.

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