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全文摘要次数: 1880 全文下载次数: 2292
引用本文:

DOI:

10.11834/jrs.20209137

收稿日期:

2019-05-07

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近实时中高空间分辨率森林火灾监测系统展望
孙福洋1,2,李晓松2,李增元3,覃先林3
1.东北林业大学 林学院 森林生态系统可持续经营教育部重点实验室, 哈尔滨 150040;2.中国科学院遥感与数字地球研究所 数字地球重点实验室, 北京 100094;3.中国林业科学研究院资源信息研究所, 北京 100091
摘要:

森林火灾是最为常见的灾害之一,严重危及人类生命安全。及时准确监测森林火灾的发生及火场状况,对应对火灾及减少损失至关重要。当前,森林火灾卫星遥感监测主要以低空间分辨率的卫星遥感为主,空间分辨率过低导致无法探测规模较小火灾及掌握详细火场态势。针对这一问题,结合近些年中高空间分辨率卫星观测、共享及处理能力的发展,本文从森林火灾卫星遥感监测的基本原理、当前可用中高空间分辨率卫星数据及其特点、中高分辨率森林着火区监测算法,以及数据共享与云端存储与计算等4个技术环节,对森林火灾中高分辨率卫星遥感监测当前研究现状与存在问题进行了总结,阐述了近实时中高空间分辨率森林火灾监测系统的可行性。近实时中高空间分辨率森林火灾监测系统可对已有低空间分辨率森林火灾监测体系形成重要补充,依托其空间分辨率的优势有助于及早、准确发现小规模火情,进而为森林火灾的防治与管理提供更好支撑。

Near-real-time forest fire monitoring system with medium and high spatial resolutions
Abstract:

Forest fires are common disasters that seriously endanger human life. Timely and accurate monitoring of forest fires is essential for fighting fires and reducing losses. At present, active forest fire monitoring mainly uses polar or geostationary orbit satellites with low spatial resolution. The spatial resolution is extremely low, making it difficult to detect small-scale fires and control fire conditions. This paper proposes a near-real-time forest fire monitoring system with medium and high spatial resolutions on the basis of the rapid development of medium and high spatial resolution satellite sensors, data sharing policy, and data processing capabilities in recent years.This paper summarizes the research status and related shortage in four aspects, namely, basic principles of forest fire monitoring, currently available medium and high spatial resolution satellite data and their characteristics, active forest fire monitoring algorithms and data sharing, and cloud storage and computation, and analyze the feasibility of a near-real-time forest fire monitoring system with medium and high spatial resolutions. The proposed near-real-time fire monitoring system with medium and high spatial resolutions can serve as an important supplement to existing forest fire monitoring systems with coarse resolution. It can early and accurately detect small-scale forest fires and provide support for forest fire prevention and management because of its high spatial resolution.

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