结合Landsat时间序列和GEDI数据,在野火模拟中更好地表征燃料类型和树冠指标
Viktor Myroniuk1, Sergiy Zibtsev2, Vadym Bogomolov3
1National University of Life and Environmental Sciences of Ukraine, 15 Heroiv Oborony St., Kyiv, 03041, Ukraine.
Journal of environmental management
|August 5, 2023
概括
在切尔诺贝利禁区 (CEZ) 绘制野火燃料类型和树冠特征对风险评估至关重要. 这项研究结合了Landsat时间序列和GEDI LiDAR数据,以创建精确的燃料地图,以改进野火模拟.
科学领域:
- 环境科学 环境科学
- 遥感 遥感 遥感 遥感
- 林业林业 林业 林业 林业
背景情况:
- 切尔诺贝利禁区 (CEZ) 等受放射性污染地区的野火,由于放射性核酸重悬浮,造成风险.
- 准确的燃料类型和树冠数据对于CEZ中有效的野火行为模拟和管理至关重要.
研究的目的:
- 开发和演示一种有效的方法来绘制燃料类型,树冠高度 (CH) 和树冠覆盖 (CC) 在被放射性核素污染的地区的地图.
- 整合Landsat时间序列 (LTS) 和全球生态系统动态调查 (GEDI) 的LiDAR数据进行全面的绘图.
主要方法:
- 使用Landsat时间序列 (LTS) 数据进行土地覆盖和现象学分析.
- 综合全球生态系统动态调查 (GEDI) 对于树冠结构指标的LiDAR观测.
- 采用了带有现象学指标和近邻归算的分类模型来绘制燃料类型,CH和CC.
主要成果:
- 在绘制土地覆盖面和燃料类型方面取得了充分的整体准确性 (75%).
- 通过使用LTS现象学指标,成功区分了光谱相似的植被类型.
- 以30米分辨率生成CH和CC的墙壁到墙壁地图,捕捉野火后的动态.
结论:
- 综合的LTS和GEDI方法为污染区的野火模拟提供了关键数据.
- 持续更新土地覆盖和树冠燃料数据对于有效的火灾管理和在放射性污染的景观中的决策至关重要.
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