玻里亚森林火灾:无人机收集的野火检测和烟雾细分数据集
Julius Pesonen1,2, Anna-Maria Raita-Hakola3, Jukka Joutsalainen3
1Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, Espoo, 02150, Finland. julius.pesonen@nls.fi.
Scientific data
|August 13, 2025
概括
本研究介绍了北极森林火灾数据集,其中包括用于野火检测的共同注释的无人机图像. 这种开放访问的数据有助于推进自动化野火检测模型培训.
科学领域:
- 计算机视觉 计算机视觉
- 林业科学 林业科学
- 遥感 遥感 遥感 遥感
背景情况:
- 自动化野火检测系统需要广泛的,注释的数据集,目前缺乏这些数据.
- 现有的数据集往往无法从无人机 (UAV) 的角度捕捉北极森林环境的特定条件.
研究的目的:
- 通过创建一个开放访问,注释数据集来解决自动野火检测中的数据短缺问题.
- 为训练和验证野火检测模型提供有价值的数据,特别是在北极森林环境中.
主要方法:
- 采集了使用无人机在芬兰北极森林中发生的多起燃烧事件的图像和视频.
- 使用人类专家和计算机视觉基础模型共同注释视觉数据.
- 将数据集结构化成三个部分:带有边界框的图像,标记的视频剪辑和带有细分面具的图像.
主要成果:
- 通过使用先前研究中开发的数据集,成功训练了野火检测模型,证明了其有效性.
- 数据集包括各种注释,这些注释对于稳健的模型开发至关重要.
- 发布了伴随代码,以促进数据利用和模型实施.
结论:
- 玻里亚森林火灾数据集有效地弥合了用于野火检测的开放访问,注释数据的差距.
- 数据集的质量和全面性支持在具有挑战性的环境中推进自动化野火检测技术.
- 数据和代码的可用性促进了该领域的进一步研究和开发.
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