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A comparative assessment between linear and quadratic discriminant analyses (LDA-QDA) with frequency ratio and weights-of-evidence models for forest fire susceptibility mapping in China

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Abstract

Forest fire is known as an important natural hazard in many countries which causes financial damages and human losses; thus, it is necessary to investigate different aspects of this phenomenon. In this study, performance of four models of linear and quadratic discriminant analysis (LDA and QDA), frequency ratio (FR), and weights-of-evidence (WofE) was investigated to model forest fire susceptibility in the Yihuang area, China. For this purpose, firstly, a forest fire locations map was prepared implementing MODIS satellite images and field surveys. Then, it was classified into two groups including training (70%) and validation (30%) by a random algorithm. In addition, 13 forest fire effective factors were prepared and used such as slope degree, slope aspect, altitude, Topographic Wetness Index (TWI), plan curvature, land use, Normalized Difference Vegetation Index (NDVI), annual rainfall, distance from roads and rivers, wind effect, annual temperature, and soil texture. Using the training dataset and effective factors, LDA, QDA, FR, and WofE models were applied and forest fire susceptibility maps were prepared. Finally, area under the curve (AUC) of receiver operating characteristics (ROC) was implemented for investigating the performance of the models. The results depicted that WofE had the best performance (AUC = 82.2%), followed by FR (AUC = 80.9%), QDA (AUC = 78.3%), and LDA (AUC = 78%), respectively. The results of this study showed the high contribution of altitude, slope degree, and temperature. On the other hand, it was seen that slope aspect and soil had the lowest importance in forest fire susceptibility mapping. From the AUC results, it can be concluded that FR, WofE, LDA, and QDA had acceptable performance and could be used for forest fire susceptibility mapping at the regional scale.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China (41472202) and General Program of Jiangxi Meteorological Bureau. We also would like to appreciate two anonymous reviewers for their valuable comments on the earlier version of the paper.

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Authors and Affiliations

  1. College of Geographic Sciences, Nanjing Normal University, Nanjing, Jiangsu, 210023, China

    Haoyuan Hong

  2. Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing, Jiangsu, 210023, China

    Haoyuan Hong

  3. Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran

    Seyed Amir Naghibi

  4. Department of Watershed Management Engineering, College of Natural Resources, Tarbiat Modares University, Noor, Mazandaran, Iran

    Mostafa Moradi Dashtpagerdi

  5. Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran

    Hamid Reza Pourghasemi

  6. School of Geology and Environment, Xi’an University of Science and Technology, Xi’an, 710054, China

    Wei Chen

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  1. Haoyuan Hong
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  3. Mostafa Moradi Dashtpagerdi
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Correspondence to Seyed Amir Naghibi.

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Hong, H., Naghibi, S.A., Moradi Dashtpagerdi, M. et al. A comparative assessment between linear and quadratic discriminant analyses (LDA-QDA) with frequency ratio and weights-of-evidence models for forest fire susceptibility mapping in China. Arab J Geosci 10, 167 (2017). https://doi.org/10.1007/s12517-017-2905-4

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