A Novel Method of Modeling Grassland Wildfire Dynamics Based on Cellular Automata: A Case Study in Inner Mongolia, China

Li, Yan; Wu, Guozhou; Zhang, Shuai; Li, Manchun; Nie, Beidou; Chen, Zhenjie

doi:10.3390/ijgi12120474

Cited by 3 publications

(2 citation statements)

References 87 publications

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“…The cellular automata algorithm is a popular algorithm which is well used in fire spread simulation. Although the algorithm has a rapid computational speed [30], in terms of accuracy, it is not superior to the maze algorithm used by FIRER. The Kappa coefficients in related studies are also lower, such as Kappa = 0.74, Hyrcanian, Iran, 2010 in Eskandari [76], and Kappa = 0.6352, Greater Khingan Mountains, China, May 2006, as reported by Rui et al [77].…”

Section: Forest Fire Spread Algorithmmentioning

confidence: 99%

“…Because of the ability of the meta-cellular automata model to simulate the evolutionary process of complex systems, it is widely used in forest fire spread simulations [30][31][32]. With the in-depth study of machine learning, the algorithms of random forests, neural networks, and support vector machines have performed well in forest fire spread simulations [33][34][35].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Different Models to Simulate Forest Fire Spread: A Case Study

Ning,

Liu,

et al. 2024

Forests

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With the development of computer technology, forest fire spread simulation using computers has gradually developed. According to the existing research on forest fire spread, the models established in various countries have typical regional characteristics. A fire spread model established in a specific region is only suitable for the local area, and there is still a great deal of uncertainty as to whether or not the established model is suitable for fire spread simulation for the same fuel in other regions. Although many fire spread models have been established, the fuel characteristics applicable to each model, such as the fuel loading, fuel moisture content, combustibility, etc., are not similar. It is necessary to evaluate the applicability of different fuel characteristics to different fire spread models. We combined ground investigation, historical data collection, model improvements, and statistical analysis to establish a multi-model forest fire spread simulation method (FIRER) that shows the burning time, perimeter, burning area, overlap area, and spread rate of fire sites. This method is a large-scale, high-resolution fire growth model based on fire spread in eight directions on a regular 30 m grid. This method could use any one of four different physical models (McArthur, Rothermel, FBP, and Wang Zhengfei (China)) for fire behavior. This method has an option to represent fire breaks from roads, rivers, and fire suppression. We can evaluate which model is more suitable in a specific area. This method was tested on a single historical lightning fire in the Daxing’an Mountains. Different scenarios were tested and compared: using each of the four fire behavior models, with fire breaks on or off, and with a single or suspected double fire ignition location of the historical fire. The results show that the Rothermel model is the best model in the simulation of the Hanma lightning fire; the overlap area is 5694.4 hm2. Meanwhile, the real fire area in FIRER is 5800.9 hm2; both the Kappa and Sørensen values exceed 0.8, providing high accuracy in fire spread simulations. FIRER performs well in the automatic identification of fire break zones and multiple ignited points. Compared with FARSITE, FIRER performs well in predicting accuracy. Compared with BehavePlus, FIRER also has advantages in simulating large-scale fire spread. However, the complex data preparation stage of FIRER means that FIRER still has great room for improvement. This research provides a practical basis for the comparison of the practicability and applicability of various fire spread models and provides more effective practical tools and a scientific basis for decision-making and the management of fighting forest fires.

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Section: Forest Fire Spread Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of Different Models to Simulate Forest Fire Spread: A Case Study

Ning,

Liu,

et al. 2024

Forests

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Visualization of the occurrence and spread of wildfires in three-dimensional natural scenes

Meng,

Huai,

et al. 2024

Vis Comput

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The Geographic Automata Tool: A New General-Purpose Geosimulation Extension for ArcGIS Pro

van Duynhoven,

Dragićević

2024

Applied Sciences

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The theoretical paradigm of geographic automata systems (GAS) underpins a wide range of studies to represent dynamic complex geospatial phenomena. Specifically, cellular automata (CA) were used extensively over the past 40 years for geospatial applications, though primarily for modeling urban growth. Currently, the hyper-specialized and fragmented geospatial technology ecosystem supporting CA model implementation often necessitates programmed solutions or use of disconnected programs with graphical user interfaces (GUIs) separate from common geographic information systems (GIS) software. Therefore, the main goal of this study is to present a general-purpose, GIS-based CA modeling framework and extension for Esri’s ArcGIS Pro software environment. The methodological approach centered around (1) developing generic functions for building binary or multi-class CA models to capture various spatiotemporal systems and (2) enabling end-to-end CA modeling projects that can incorporate built-in functionality available in ArcGIS Pro versions 3.1 and newer. Two case studies demonstrate the add-in capabilities to support geosimulation model-building activities and exploration of new hybrid models. This research contributes to advancing flexible, transparent spatiotemporal modeling tools within existing GIS software. The proposed approach addresses the lack of streamlined geospatial technologies capable of simulating numerous dynamic geospatial phenomena, exploring human and environmental processes, and examining possible futures with CA in research, decision making, or educational settings.

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A Novel Method of Modeling Grassland Wildfire Dynamics Based on Cellular Automata: A Case Study in Inner Mongolia, China

Cited by 3 publications

References 87 publications

Comparison of Different Models to Simulate Forest Fire Spread: A Case Study

Comparison of Different Models to Simulate Forest Fire Spread: A Case Study

Visualization of the occurrence and spread of wildfires in three-dimensional natural scenes

The Geographic Automata Tool: A New General-Purpose Geosimulation Extension for ArcGIS Pro

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