测绘学报 ›› 2024, Vol. 53 ›› Issue (6): 1086-1097.doi: 10.11947/j.AGCS.2024.20230234

• 智能化测绘 • 上一篇    下一篇

知识引导的森林火灾逃生路网动态生成方法

朱军1(), 陈佩菁1(), 曾超2, 郑全红2, 谢亚坤1, 游继钢1, 廉慧洁1   

  1. 1.西南交通大学地球科学与工程学院,四川 成都 611756
    2.自然资源部四川基础地理信息中心,四川 成都 610041
  • 收稿日期:2023-06-15 发布日期:2024-07-22
  • 通讯作者: 陈佩菁 E-mail:zhujun@swjtu.edu.cn;chenpeijing@my.swjtu.edu.cn
  • 作者简介:朱军(1976—),男,博士,教授,博士生导师,研究方向为虚拟地理环境与灾害场景建模。 E-mail:zhujun@swjtu.edu.cn
  • 基金资助:
    国家重点研发计划(2022YFC3005703);四川省科技计划(2022YFS0533)

Knowledge-guided dynamic generation of escape route networks for forest fires

Jun ZHU1(), Peijing CHEN1(), Chao ZENG2, Quanhong ZHENG2, Yakun XIE1, Jigang YOU1, Huijie LIAN1   

  1. 1.Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 611756, China
    2.Sichuan Basic Geographic Information Center of the Natural Resources Ministry, Chengdu 610041, China
  • Received:2023-06-15 Published:2024-07-22
  • Contact: Peijing CHEN E-mail:zhujun@swjtu.edu.cn;chenpeijing@my.swjtu.edu.cn
  • About author:ZHU Jun (1976—), male, PhD, professor, PhD supervisor, majors in virtual geographical environment and modeling of disaster scene. E-mail: zhujun@swjtu.edu.cn
  • Supported by:
    The National Key Research and Development Program of China(2022YFC3005703);Science and Technology Program Projects in Sichuan Province(2022YFS0533)

摘要:

规划合理的森林火灾逃生路网对应急逃生决策具有重要作用,但现有方法动态适应性弱,且未考虑山沟地带、狭窄山脊等影响人员逃生安全的关键空间信息,导致逃生路网规划准确性差。因此,本文引入智能化测绘技术方法,提出一种知识引导的森林火灾逃生路网动态生成方法,通过突破森林火灾逃生路网规划知识图谱构建、关键空间区域提取等关键技术,建立森林火灾逃生路网通行栅格网络模型,实现改进A*算法的逃生路网动态优化生成,研发原型系统并开展试验分析。结果表明,本文方法能够实现林火蔓延环境下逃生路网的动态生成,可为扑救人员提供有效的逃生决策信息;逃生规划准确率与已有静态森林火灾逃生路网规划方法的逃生规划准确率相比,高安全区重叠率提升了3.06%,逃生路网危险区重叠率降低了27.39%。

关键词: 森林火灾, 知识引导, 关键空间信息, 逃生路网, 动态优化

Abstract:

A reasonably planned forest fire escape road network plays an important role in emergency escape decision-making, but the existing methods have weak dynamic adaptability and do not consider the key spatial information affecting people's escape safety such as ravine areas and narrow ridges, resulting in poor accuracy of escape road network planning. Therefore, this paper introduces intelligent mapping technology methods and proposes a knowledge-guided dynamic generation method of forest fire escape road network, by breaking through the key technologies of forest fire escape road network planning knowledge map construction, key spatial region extraction, et al. Then, it establishes a forest fire escape road network access raster network model, realizes the dynamic optimization generation of escape road network with the improvement of the A* algorithm, develops a prototype system and carries out experimental analysis. The results show that the method in this paper can realize the dynamic generation of escape road network under the environment of forest fire spreading, which can provide effective escape decision-making information for the fire fighters. Compared with the existing static forest fire escape road network planning methods, the accuracy of escape planning improves the overlap rate of the high safety zone by 3.06%, and the overlap rate of the hazardous zone of the escape network reduces by 27.39%.

Key words: forest fire, knowledge-guided, key spatial information, escape route network, dynamic optimization

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