面向森林火灾的应急管理信息化关键技术

doi:10.16265/j.cnki.issn1003-3033.2022.09.2693

中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (9): 182-191.doi: 10.16265/j.cnki.issn1003-3033.2022.09.2693

面向森林火灾的应急管理信息化关键技术

姜文宇¹^,²(), 王飞¹^,²^,^**(), 苏国锋¹, 李鑫³, 孟庆祥⁴, 王冠宁¹

1 清华大学工程物理系,北京 100084
2 清华大学深圳国际研究生院安全科学与技术研究所,广东深圳 518000
3 佛山市城市安全研究中心有限公司,广东佛山 528000
4 武汉大学遥感信息工程学院,湖北武汉 430070

收稿日期:2022-02-11 修回日期:2022-06-01 出版日期:2022-10-19 发布日期:2023-03-28
通讯作者: 王飞
作者简介:
姜文宇 (1995—),男,江西南昌人,博士研究生,主要研究方向为火灾科学、环境建模、地理信息系统、计算机视觉等。E-mail: jwy21@mails.tsinghua.edu.cn。
王飞副教授
苏国锋研究员
基金资助:
深圳市学科布局项目(JCYJ20180508152055235); 广东省重点研发项目(2019B111104001)

Key technologies of emergency management informatization for forest fires

JIANG Wenyu¹^,²(), WANG Fei¹^,²^,^**(), SU Guofeng¹, LI Xin³, MENG Qingxiang⁴, WANG Guanning¹

1 Department of Engineering Physics, Tsinghua University, Beijing 100084, China
2 Institute of Safety Science and Technology, Tsinghua Shenzhen International Graduate School, Shenzhen Guangdong 518000, China
3 Foshan Urban Safety Research Center, Foshan Guangdong 528000, China
4 School of Remote Sensing and Information Engineering, Wuhan University, Wuhan Hubei 430070, China

Received:2022-02-11 Revised:2022-06-01 Online:2022-10-19 Published:2023-03-28
Contact: WANG Fei

摘要/Abstract

摘要：

为全面、高效地辅助应急管理部门开展森林火灾防控与对应行动,基于森林火灾“防”和“救”的应急管理全要素与多角色协同联动的业务需求,自主研发一套覆盖森林火灾应急管理全流程的软件森林火灾监测预警与应急指挥系统。该系统针对森林火灾的风险评估、监测预警、应急处置与事件复盘等重要环节,集成自研的各类算法模型,重点研究多尺度动态风险评估、空天地一体化监测与预警、森林火灾蔓延预测、基于时间戳的可视化事故复盘等关键信息化技术。该系统在广东、浙江等多地落地应用示范,并在多起森林火灾应急指挥中发挥了重要作用。结果表明:该系统能够实现对森林火灾全流程的信息化管理,为应急管理中各类型角色用户提供自主研发的智能化辅助分析服务,可显著提升政府应急管理部门科学防控与应对森林火灾的现代化能力。

关键词: 森林火灾, 应急管理信息化, 风险评估, 监测预警, 应急指挥, 事件复盘

Abstract:

In order to comprehensively and efficiently assist emergency management agencies to carry out forest fire prevention, control and response actions, an independent "Forest Fire Early Warning and Emergency Command System" was developed to cover the whole process of emergency management based on comprehensive elements like "prevention" and "rescue" as well as multi-agent collaboration needs. In consideration of important steps of risk assessment, monitoring and early warning, emergency response and case review, this system developed various independent algorithm models with its focus on key information technologies such as multi-scale dynamic risk assessment, air-space-earth integration monitoring and early warning, forest fire spread prediction, and timestamp-based visual case review. The system had been applied in many places such as Guangdong province and Zhejiang province, which played an important role in emergency command of many forest fires. The results show that it can achieve informatization management of the whole forest fire process, provide independent intelligent assistant analysis services in critical aspects of emergency management, which significantly improves the modernization capability of government emergency agencies in prevention and response to forest fires.

Key words: forest fire, emergency management informatization, risk assessment, monitoring and early warning, emergency command, case review

姜文宇, 王飞, 苏国锋, 李鑫, 孟庆祥, 王冠宁. 面向森林火灾的应急管理信息化关键技术[J]. 中国安全科学学报, 2022, 32(9): 182-191.

JIANG Wenyu, WANG Fei, SU Guofeng, LI Xin, MENG Qingxiang, WANG Guanning. Key technologies of emergency management informatization for forest fires[J]. China Safety Science Journal, 2022, 32(9): 182-191.

图/表 12

图1

图2

图3

图4

图5

图6

图7

图8

图9

图10

图11

图12

参考文献 20

[1]	WANG Daoping, GUAN Dabao, ZHU Shupeng, et al. Economic footprint of California wildfires in 2018[J]. Nature Sustainability, 2021, 4(3): 252-260. doi: 10.1038/s41893-020-00646-7
[2]	HUANG Zhiling. Muli forest fire[EB/OL].(2019-04-08). https://www.chinadaily.com.cn/a/201904/08/WS5caaa02fa3104842260b4cc3.html.
[3]	HUANG Zhiling. Xichang forest fire[EB/OL].(2020-04-03). http://www.chinadaily.com.cn/a/202004/03/WS5e868e4aa3101282172841c3.html.
[4]	范维澄, 刘奕, 翁文国. 公共安全科技的“三角形”框架与“4+1”方法学[J]. 科技导报, 2009, 27(6): 3.
	FAN Weicheng, LIU Yi, WENG Wenguo. Triangular framework and "4+1" methodology for public security science and technology[J]. Science & Technology Review, 2009, 27(6): 3.
[5]	刘苦育. L市森林防灭火应急管理中存在的问题及对策研究[D]. 广州: 中共广东省委党校, 2021.
	LIU Kuyu. Study of problems and countermeasures in emergency management of forest fire prevention and control in L city[D]. Guangzhou: Party School of the Guangdong Provincial Committee of CPC, 2021.
[6]	蒋琴, 钟少波, 朱伟. 京津冀地区森林火灾综合风险评估[J]. 中国安全科学学报, 2020, 30(10): 119-125. doi: 10.16265/j.cnki.issn 1003-3033.2020.10.017
	JIANG Qin, ZHONG Shaobo, ZHU Wei. Research on comprehensive risk assessment of forest fire in Beijing-Tianjin-Hebei region[J]. China Safety Science Journal, 2020, 30(10): 119-125. doi: 10.16265/j.cnki.issn 1003-3033.2020.10.017
[7]	宗学政, 田晓瑞, 刘畅. 林分尺度上的森林火灾风险评估方法及应用[J]. 林业科学研究, 2021, 34(5): 69-78.
	ZONG Xuezheng, TIAN Xiaorui, LIU Chang. Method and application of forest fire risk assessment on forest stand scale[J]. Forest Research, 2021, 34(5): 69-78.
[8]	KC U, HILTON J, GARG S, et al. A probability-based risk metric for operational wildfire risk management[J]. Environmental Modelling & Software, 2022, 148:DOI: 10.1016/j.envsoft.2021.105286. doi: 10.1016/j.envsoft.2021.105286
[9]	符修文, 李文锋. 无线消防报警网络抗毁性分析与提升方法[J]. 中国安全科学学报, 2014, 24(1): 41-47.
	FU Xiuwen, LI Wenfeng. Analysis of invulnerability of wireless fire-alarming network and methods of improving it[J]. China Safety Science Journal, 2014, 24(1): 41-47.
[10]	袁传武, 张维, 王崇顺, 等. 空天地一体化森林防火监测关键技术及实现[J]. 湖北林业科技, 2021, 50(2): 66-70.
	YUAN Chuanwu, ZHANG Wei, WANG Chongshun, et al. Application of air, space and ground integrated monitoring technology in forest fire prevention[J]. Hubei Forestry Science and Technology, 2021, 50(2): 66-70.
[11]	BOUGUETTAYA A, ZARZOUR H, TABERKIT A M, et al. A review on early wildfire detection from unmanned aerial vehicles using deep learning-based computer vision algorithms[J]. Signal Processing, 2022, 190:DOI: 10.1016/j.sigpro.2021.108309. doi: 10.1016/j.sigpro.2021.108309
[12]	王阿川. 森林火灾防治决策专家系统的研究与实现[J]. 中国安全科学学报, 2005, 15(2): 96-101.
	WANG Achuan. Study and realization of the expert system for forest fire preventive decision-making[J]. China Safety Science Journal, 2005, 15(2): 96-101.
[13]	刘敏, 汪明. 森林火灾灾情快速预判模型[J]. 中国安全科学学报, 2011, 21(5): 59-65.
	LIU Min, WANG Ming. A rapid disaster assessment model for forest fire[J]. China Safety Science Journal, 2011, 21(5): 59-65.
[14]	LOVREGLIO R, KULIGOWSKI E, GWYNNE S, et al. A modelling framework for householder decision-making for wildfire emergencies[J]. International Journal of Disaster Risk Reduction, 2019, 41: DOI: 10.1016/j.ijdrr.2019.101274. doi: 10.1016/j.ijdrr.2019.101274
[15]	TYMSTRA C, STOCKS B J, CAI Xinli, et al. Wildfire management in Canada: review, challenges and opportunities[J]. Progress in Disaster Science, 2020, 5: DOI: 10.1016/j.pdisas.2019.100045. doi: 10.1016/j.pdisas.2019.100045
[16]	佘廉, 郑琛. 非常规突发事件案例复盘的危机学习方法[J]. 华南理工大学学报:社会科学版, 2016, 18(2): 84-92.
	SHE Lian, ZHENG Chen. Crisis learning method of unconventional emergencies case replay:a case analysis framework[J]. Journal of South China University of Technology :Social Science Edition, 2016, 18(2): 84-92.
[17]	朱迎. 基于无人机方案的某起森林火灾扑救行动复盘[J]. 水上消防, 2021 (4): 14-17.
[18]	ZHENG Xiaocui, WANG Fei, QI Mingyao, et al. Planning remote sensing emergency services: bridging the gap between remote sensing science and emergency practice in China[J]. Safety Science, 2021, 141: DOI: 10.1016/j.ssci.2021.105346. doi: 10.1016/j.ssci.2021.105346
[19]	JIANG Wenyu, WANG Fei, FANG Linghang, et al. Modelling of wildland-urban interface fire spread with the heterogeneous cellular automata model[J]. Environmental Modelling & Software, 2021, 135:DOI: 10.1016/j.envsoft.2020.104895. doi: 10.1016/j.envsoft.2020.104895
[20]	滕伟毅. 广东省佛山市高明区“12·5”森林灭火战例剖析[J]. 消防界:电子版, 2020, 6(14): 1-5.

面向森林火灾的应急管理信息化关键技术

Key technologies of emergency management informatization for forest fires

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 12

参考文献 20

相关文章 15

编辑推荐

Metrics

本文评价

[1]	郑安娜, 李建微, 陈思喜, 郭伟, 陈晓梦. 城市洪涝风险评估中的软件应用及进展[J]. 中国安全科学学报, 2022, 32(9): 118-125.
[2]	朱馨, 李建微, 郭伟, 毕胜, 伍跃飞. 基于机器学习的森林火险预测模型[J]. 中国安全科学学报, 2022, 32(9): 152-157.
[3]	孙树立, 韩旭东, 陈璞. 建筑结构安全分析方法与评估技术综述[J]. 中国安全科学学报, 2022, 32(9): 37-48.
[4]	周勇, 杨波, 唐伟, 李月安, 王月冬, 李泽椿. 面向公共安全的气象监测预报预警软件发展综述[J]. 中国安全科学学报, 2022, 32(9): 76-85.
[5]	李金蓉, 杨玉中. DS理论-贝叶斯网络下的煤矿通风系统风险评估*[J]. 中国安全科学学报, 2022, 32(8): 146-153.
[6]	法慧妍, 帅斌, 吕敏, 黄文成. 基于WBS-RBS和IFWA算子的中欧班列多式联运安全风险评估[J]. 中国安全科学学报, 2022, 32(6): 200-206.
[7]	刘嘉豪, 余杨, 张振兴, 余建星, 王巍巍, 傅一钦. 二维云模型和贝叶斯网络的立管风险评估方法[J]. 中国安全科学学报, 2022, 32(5): 147-154.
[8]	辛保泉, 喻健良, 党文义, 白永忠, 于安峰. 定量风险评估视域下的多组分混合物危险特性[J]. 中国安全科学学报, 2022, 32(4): 80-85.
[9]	卢颖, 赵志攀, 姜学鹏, 吴锦东, 范小鹏. 大数据视域下体育场馆动态火灾风险指标研究[J]. 中国安全科学学报, 2022, 32(4): 155-162.
[10]	黄杰, 张显峰. 以南疆为例的区域暴恐袭击风险评估[J]. 中国安全科学学报, 2022, 32(2): 192-199.
[11]	张鸽. 基于累积接尘量的尘肺病风险评估方法[J]. 中国安全科学学报, 2022, 32(2): 200-206.
[12]	韩鹏, 王军, 王启, 赵嶷飞. 基于飞行剖面的航空器试飞活动空管风险研究[J]. 中国安全科学学报, 2022, 32(1): 149-156.
[13]	刘继川, 桂蕾. 城市公共安全风险评估与控制对策研究:以武汉市为例[J]. 中国安全科学学报, 2022, 32(1): 164-171.
[14]	王鹏. 论铁路企业风险评估与隐患排查的相互应用[J]. 中国安全科学学报, 2021, 31(S1): 80-85.
[15]	杜宇, 钟昊, 李明春. 基于高通量卫星的铁路应急指挥通信系统[J]. 中国安全科学学报, 2021, 31(S1): 187-191.