Abstract
This study aimed to prepare forest fire susceptibility mapping (FFSM) using a ubiquitous GIS and an ensemble of adaptive neuro fuzzy interface system (ANFIS) with genetic (GA) and simulated annealing (SA) algorithms (ANFIS-GA-SA) and an ensemble of radial basis function (RBF) with an imperialist competitive algorithm (ICA) (RBF-ICA) model in Chaharmahal and Bakhtiari Province, Iran. The forest fire areas were determined using MODIS satellite imagery and a field survey. The modeling and validation of the models were performed with 70% (183 locations) and 30% (79 locations) of forest fire locations (262 locations), respectively. In order to prepare the FFSM, 10 criteria were then used, namely altitude, rainfall, slope angle, temperature, slope aspect, wind effect, distance to roads, land use, distance to settlements and soil type. After the FFSM was prepared, the maps were designed and implemented for web GIS and mobile application. A receiver operating characteristic (ROC)- area under the curve (AUC) index was used to validate the prepared maps. The ROC-AUC results showed an accuracy of 0.903 for the ANFIS-GA-SA model and an accuracy of 0.878 for the RBF-ICA model. The results of the spatial autocorrelation showed that the occurrence of fire in the study area has a cluster distribution and most of the spatial dependence is related to the distance to settlement, soil and rainfall variables.
Highlights
Forests are among the most important natural resources that have positive ecological, economic and social effects [1]
In order to implement the hybrid model and create the training and test datasets, 70% of the past fire locations (183 locations) with values of 1 and 183 locations were randomly assigned to the study area with zero values and 30% of the past fire locations (79 locations) with values of 1 and 79 locations were randomly assigned to the study area with a value of zero being used
The trained network was applied to all pixels in the study area after training the model with the hybrid algorithm, and the forest fire susceptibility mapping (FFSM) was prepared in ArcGIS 10.3 software
Summary
Forests are among the most important natural resources that have positive ecological, economic and social effects [1]. Little research has been done on forest fires using mobile GIS, web GIS and ubiquitous GIS technologies. In this regard, Dong et al [25] used a GIS mobile system to manage forest information. The purpose of this research was to prepare an FFSM based on ubiquitous GIS using the ensemble ANFIS with combined genetic (GA) and simulated annealing (SA) algorithms as well as combining the radial basis function (RBF) interpolation method imperialist competitive algorithm (ICA) algorithm. Hong et al [31] used a GA algorithm to determine the optimal parameters affecting forest fires and prepared an FFSM using the RF and SVM models in the southwest of Jiangxi Province, China. The innovation of the present study was to combine the two metaheuristic algorithms with ANFIS, optimize the RBF with the ICA algorithm, and present an FFSM in the ubiquitous system as a mobile application
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