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Remote Sensing-based Forest Fire Occurrence and Management System

Remote Sensing-based Forest Fire Occurrence and Management System
基于遥感的森林火灾发生与管理系统
批准号:
RGPIN-2022-03039
负责人:
Hassan, Quazi
金额:
$2.62万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

项目摘要

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中文摘要
翻译
在过去的25年里,加拿大平均每年发生7300起火灾,每年约有250万公顷的森林被毁。仅在过去十年中,加拿大人每年就花费8亿至15亿加元用于灭火。虽然火灾是自然循环的一部分,可以使土壤恢复活力,杀死害虫并导致新的生长,但不受控制的火灾也会造成重大的有害影响,例如(i)由于成熟树木的损失而造成的经济损失;(ii)增加大气中的CO2负荷;(iii)火灾期间和之后的空气质量恶化;以及(iv)人类生命和财产的损失。因此,建立一个有效的森林火灾发生和管理系统对于抵消这种不利影响至关重要。这项拟议的研究计划旨在利用各种卫星平台获取的遥感数据(以数字图像的形式),这些卫星平台收集了大面积地理区域的信息,以帮助防止失控火灾的破坏。该方案的长期目标/愿景是开发一个主要使用遥感但由其他辅助数据支持的强大的森林火灾发生预测和管理系统。拟议研究的主要内容是:㈠利用河流流量和土壤湿度之间的关系预测森林火灾危险状况,将这些数据纳入我们最近开发的基于遥感的森林火灾危险预报系统的框架; ㈡确定历史上森林火灾发生的趋势及其与大规模大气环流和气候变量的关系;利用空间平台估计森林火灾的二氧化碳排放量;以及利用(i)的结果和遥感得出的叶面积指数数据(森林冠层的一种测量方法)制定燃料管理战略,以降低火灾的严重程度。成功完成拟议的研究计划将导致一个原型森林火灾发生管理系统。它将在森林火灾管理、森林资源的可持续性和经济性以及指导火灾处理研究和规范方面具有开创性意义。此外,基于遥感的森林火灾二氧化碳排放量的快速和可靠的估计将有助于决策者了解非人为二氧化碳进入大气层的数量。这些知识将对推动加拿大的年度温室气体清单以及泛加拿大清洁增长和气候变化框架产生重大影响,以实现“健康的环境和健康的经济”。“此外,拟议的研究计划将培养四名高素质的专业人员(HQP),他们在可持续增长和加拿大经济进一步发展所需的遥感,自然灾害和资源管理等更广泛领域具有独特的市场准备技能。
英文摘要
Over the past 25 years, Canada has had an average of 7300 fires annually - each year about 2.5 million hectares of forest are destroyed. Over the past decade alone, Canadians have spent between $800 million and $1.5 billion per annum on fighting fires. Though fires are a part of the natural cycle and rejuvenate the soil, kill pests and lead to new growth, uncontrolled fires also cause significant detrimental impacts, such as (i) economic damage due to loss of mature trees; (ii) increase the CO2 loading into the atmosphere; (iii) air quality deterioration during and immediately after the fires; and (iv) loss of human life and property. Thus, the development of an efficient forest fire occurrence and management system is crucial to offset such adverse impacts. This proposed research program aims to use remote sensing data (in the form of digital imagery) acquired by various satellite platforms that gather information over large geographic areas to help prevent the devastation of uncontrolled fires. The long-term goal/vision of this program is to develop a robust operational forest fire occurrence prediction and management system primarily using remote sensing but supported by other ancillary data. The foremost elements of the proposed research are to (i)predict forest fire danger conditions using the relationships of river flow regimes and soil moisture, integrating this data in the framework of our recently developed remote sensing-based forest fire danger forecasting system; (ii)determine trends in the occurrences of historical forest fires and their relationships to large-scale atmospheric circulations and climate variables; (iii) estimate CO2 emissions from forest fires using space-borne platforms; and (iv) develop fuel management strategies to reduce fire severity by using the outcomes of (i) and remote sensing-derived leaf area index data, a measurement of forest canopy. The successful completion of the proposed research program will result in a prototype forest fire occurrence management system. It will be ground-breaking in forest fire management; in sustainability and economics of forest resources; and in guiding research and codes in handling fire instances. Furthermore, remote sensing-based quick and reliable estimation of CO2 emissions from the forest fires will help policy makers understand the amount of non-anthropogenic CO2 entering the atmosphere. Such knowledge will be highly impactful in advancing Canada's annual greenhouse gas inventory as well as the Pan-Canadian Framework on Clean Growth and Climate Change to achieve "A Healthy Environment and a Healthy Economy." Additionally, the proposed research program will train four highly qualified professionals (HQPs) with unique, market-ready skills in the broader field of remote sensing, natural hazard and resource management needed for sustainable growth and further development of the Canadian economy.
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Use of Remote Sensing in Developing a Forest Fire Occurrence Management System
  • 批准号:
    RGPIN-2016-03841
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2021
  • 负责人:
    Hassan, Quazi
  • 依托单位:
Use of Remote Sensing in Developing a Forest Fire Occurrence Management System
  • 批准号:
    RGPIN-2016-03841
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.97万
  • 财政年份:
    2020
  • 负责人:
    Hassan, Quazi
  • 依托单位:
Use of Remote Sensing in Developing a Forest Fire Occurrence Management System
  • 批准号:
    RGPIN-2016-03841
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.32万
  • 财政年份:
    2019
  • 负责人:
    Hassan, Quazi
  • 依托单位:
Use of Remote Sensing in Developing a Forest Fire Occurrence Management System
  • 批准号:
    RGPIN-2016-03841
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $0.65万
  • 财政年份:
    2018
  • 负责人:
    Hassan, Quazi
  • 依托单位:
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