Multi-objective spatial optimization of forest fire monitoring networks: An integrated GIS-MCDM framework enhanced by improved genetic algorithms.

ABSTRACT: As one of the most destructive and rapidly spreading natural hazards, forest fires pose a severe threat to the stability of ecosystems. To effectively mitigate fire risks, this study proposes a site-selection model that integrates Multi-Criteria Decision Making (MCDM), Genetic Algorithm (GA), and Geographic Information System (GIS), with the aim of optimizing the spatial distribution of forest fire monitoring points and enhancing fire surveillance efficiency. The model is designed with three primary objectives: maximizing monitoring coverage, minimizing road network distance, and optimizing economic costs. To achieve adaptive decision-making, the Analytic Hierarchy Process (AHP) is employed to dynamically allocate objective weights. Building upon this, differential evolution operators and

SUBMITTER: Wang L 

PROVIDER: S-EPMC12716776 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature