Revista Chapingo Serie Ciencias Forestales y del Ambiente
Universidad Autónoma Chapingo
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Volume XXIV, issue 3, - 2018
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Selección de ancho de banda para la estimación de densidad kernel de incendios forestales
Bandwidth selection for kernel density estimation of forest fires

José G. Flores-Garnica; Alejandra Macías-Muro

http://dx.doi.org/10.5154/r.rchscfa.2017.12.074

Received: 2017-12-30

Accepted: 2018-06-25

Available online: 2018-06-27 / pages.313-327

 

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  • descriptionAbstract

    Introduction. The mapping of areas with higher forest fire density can be developed through kernel density estimation, which requires the selection of a function and bandwidth (h). The h value, when defined by subjective (visual) processes, will depend on the knowledge and experience of the person making the selection.
    Objective: To propose a statistical alternative, based on forest fires information (2005-2013) from Jalisco, Mexico, for the selection of h as support for kernel density estimation.
    Materials and methods: A total of 13 h values were defined using seven techniques. The h value was selected using the following statistics: root mean square error, root mean integrated squared error, coefficient of variation and comparative percentage.
    Results and discussion: The h values obtained with the techniques analyzed were between 2 550 and 41 906 m. There was great variation in the results; the range between the maximum and the minimum value was 39 356.34 m with an average of 10 936.74 ± 9 955.04 m. The above implies that there is no single and universal process for all cases. According to the validation criteria, the statistically most adequate h value is between 5 300 and 5 900 m; the closest result was obtained with the mean random distance technique (5 395 m).
    Conclusion: It is possible to select h under a practical statistical perspective, avoiding the use of subjective criteria.

    Keyworks: Fire density; search area; continuous surfaces; mean random distance; mapping of areas

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  • starCite article

    Flores-Garnica, J. G.,  &  Macías-Muro, A. (2018).  Bandwidth selection for kernel density estimation of forest fires. , XXIV(3), 313-327. http://dx.doi.org/10.5154/r.rchscfa.2017.12.074