Carlos Brys , David Luis La Red Martínez , Marcelo Marinelli
{"title":"A geospatial model for real-time predicting rural fire propagation velocity using dynamic algorithms and open data for advanced emergency management","authors":"Carlos Brys , David Luis La Red Martínez , Marcelo Marinelli","doi":"10.1016/j.envsoft.2025.106355","DOIUrl":null,"url":null,"abstract":"<div><div>When a fire is detected in a rural environment, it is imperative to know the dynamics of the fire's development. Knowing the fire's trajectory is vital since the firefront will have shifted when first responders reach the ignition site. We developed a fast rural fire propagation calculation algorithm that can predict the fire front trajectory 6 h from the time of detection, taking as input data only the latitude and longitude coordinates of the detected hot spot, and obtaining all the necessary data from open online sources. In response to the pressing demand for effective fire control strategies in rural areas, this paper introduces a computational analytical model to predict the fire speed of rural fire behavior. By integrating topographic, meteorological, and land use data, our system offers on-demand fire behavior forecasts, addressing a critical need in the field. With the key component, a predictor, our system identifies patterns and provides crucial information to decision-makers. This comprehensive approach positions our system as an invaluable tool for rescue teams and decision-makers engaged in the proactive battle against rural fires.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"186 ","pages":"Article 106355"},"PeriodicalIF":4.8000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Modelling & Software","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364815225000398","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
When a fire is detected in a rural environment, it is imperative to know the dynamics of the fire's development. Knowing the fire's trajectory is vital since the firefront will have shifted when first responders reach the ignition site. We developed a fast rural fire propagation calculation algorithm that can predict the fire front trajectory 6 h from the time of detection, taking as input data only the latitude and longitude coordinates of the detected hot spot, and obtaining all the necessary data from open online sources. In response to the pressing demand for effective fire control strategies in rural areas, this paper introduces a computational analytical model to predict the fire speed of rural fire behavior. By integrating topographic, meteorological, and land use data, our system offers on-demand fire behavior forecasts, addressing a critical need in the field. With the key component, a predictor, our system identifies patterns and provides crucial information to decision-makers. This comprehensive approach positions our system as an invaluable tool for rescue teams and decision-makers engaged in the proactive battle against rural fires.
期刊介绍:
Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.