对于主动火灾检测的遥感技术的进步:数据集和方法的审查
Songxi Yang1, Qunying Huang1, Manzhu Yu2
1Spatial Computing and Data Mining Lab, Department of Geography, University of Wisconsin-Madison, Madison 53705, WI, USA.
The Science of the total environment
|June 1, 2024
概括
本综述涵盖了用于主动火灾检测的遥感技术的进展,重点是机器学习.
科学领域:
- 环境科学 环境科学
- 遥感技术 遥感技术 遥感技术
- 地理空间分析的研究.
背景情况:
- 自1975年以来,使用遥感的活跃火灾检测已经显著发展.
- 关键的进步包括改善基于卫星的数据集,仪器和检测算法.
研究的目的:
- 综合审查在远程传感方面的积极火灾检测进展.
- 为了确定当前的挑战和未来的研究机会在该领域.
主要方法:
- 从1975年到现在的文学和技术发展的批判性回顾.
- 分析主动火灾检测数据集,仪器和算法.
主要成果:
- 机器学习,特别是深度学习,在积极的火灾检测中发挥着越来越重要的作用.
- 在数据质量,算法复杂性和模型开发方面取得了重大进展.
结论:
- 未来的研究应该专注于数据质量,多模式和自我监督学习,可解释的AI和整合物理模型.
- 开发用于野火动态和场景分析的数字双胞胎是一个关键的未来方向.
- 这一综述为自然资源管理和环境保护提供了资源.
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