Xingdong Li, Hewei Gao, Chengqi Han, Yangwei Wang, Tongxin Hu, Long Sun, Yanling Guo


 Forecasting of forest fire area is of great significance to effectively control the spread of forest fire. In this paper, the forest fire spreading velocity model and the forest fire spreading simulation technology based on huygens principle are used to estimate the forest fire area. Firstly, binocular camera is used to collect the firing state data of wild forest fire, and segment the firing image, extract the firing line,
locate the firing line and calculate the three-dimensional coordinates of the firing line pixels according to perspective projection model;. Secondly, the forest fire spreading velocity model based on Wang Zhengfei’s model is redesigned. The model parameters of forest fire area were optimized by gradient method. The prediction accuracy is much higher than that of the model before optimization.


Forest fire area prediction; Wang Zhengfei’s model; Huygens principle; Binocular camera; Image segmentation; Regression analysis

Full Text:



Wang Xiaohong et al. 2013. Research progress of forest fire spreading simulation. Journal of Central South University of Forestry and Technology, 33(10):69–78. DOI:10.14067/j.cnki.1673-923x.2013.10.014

Han Xianfeng et al. 2017. Video fire detection based on Gaussian Mixture Model and multi-color features. Signal Image and Video Processing, 11(8):1419–1425. DOI:10.1007/s11760-017-1102-y

Wu Xiyin et al. 2015. Fire detection based on fusion of multiple features.

CAAI Transactions on Intelligent Systems, 10(2):240-247. DOI:10.3969/j.issn.1673-4785.201406022

Yang Fulong et al. 2016. Study on simulation of three dimensional simulation of forest fire spread based on cellular automaton. Computer Engineering and Application, 52(19):37–41. DOI:10.3778/j.issn.1002-8331.1508-0093

Tang Liyu et al. 2015. Three-dimensional visual simulation of forest fire spread based on FARSITE. Journal of Natural Disasters, 24(2):221–227.


Wang Yue et al. 2019.Estimation of extrin sic parameters for dynamic binocular stereo vision using unknown-sized rectangle images.The Review of scientific instruments, 90(6):65-108. DOI:10.1063/1.5086352

Technikova Lenka and Tunak Maros. 2016. Comparison of Two Different Principles of 3D Fabric Surface Reconstruction. Fibres and Textiles In Easastern

Europe, 24(5):38–43. DOI:10.5604/12303666.1215525

Zhao Mandan et al. 2018. A Method for Single Image Distortion Correction Using a Straight Line Feature. Geomatics and Information Science of Wuhan University, 43(1):60–66. DOI:10.13203/j.whugis20150445

Liu Xiaozhi et al. 2017. Camera Calibration Method Based on Distortion Separation. Journal of Northeastern University. Natural Science, 38(5):620–624. DOI:10.3969/j.issn.1005-3026.2017.05.003

Al-Tairi and Zaher Hamid. 2014. Skin Segmentation Using YUV and RGB Color Spaces. Journal of Information Processing Systems, 10(2):283–299.


Ervilha A. R. et al. 2017. On the parametric uncertainty quantification of the Rothermel’s rate of spread model. Applied Mathematical Modelling, 41:37–53. DOI:10.1016/j.apm.2016.06.026

Chen Zhe et al. 2012. Forest fire spread fast model based on 3D cellular automaton in spatially heterogeneous area. Journal of Beijing Forestry

University, 37(1):86–91. DOI:10.13332/j.1000-1522.2012.01.014

Richards and Gwynfor D. 1994. The properties of elliptical wildfire growth for time dependent fuel and meteorological conditions. Combustion Science

and Technology, 95(1-6):357–383.

Anderson H.E. 1993. Predicting wind-driven wild land fire size and shape [fire behavior models]. Usda Forest Service Research Paper Int.

Zendehdel J. et al. 2018. Testing exponentiality for imprecise data and its application. Soft Computing, 22(10):3301–3312. DOI:10.1007/s00500-017-2566-y

Jia Ruiyu and Li Yugong. 2018. K-means algorithm of clustering number and centers selfdetermination. Computer Engineering and Application, 54(7):152–158. DOI:10.3778/j.issn.1002-8331.1610-0342

Li Qingkui and LV Zhiping. 2008. Fuzzy Adaptive Kalman Filtering Algorithm Based on the Statistics of t Distribution. Acta Geodetica et Cartographica Sinica, 37(4):428–432. DOI:10.3321/j.issn:1001-1595.2008.04.005


  • There are currently no refbacks.


© 2008 Mathematical and Computational Forestry & Natural-Resource Sciences