Managing fuels is a key strategy for mitigating the negative impacts of wildfires on people and the environment. The use of satellite‐based Earth observation data has become an important tool for managers to optimize fuel treatment planning at regional scales. Fortunately, several new sensors have been launched in the last few years, providing novel opportunities to enhance fuel characterization. Herein, we summarize the potential improvements in fuel characterization at large scale (i.e., hundreds to thousands of km2) with high spatial and spectral resolution arising from the use of new spaceborne instruments with near‐global, freely‐available data. We identified sensors at spatial resolutions suitable for fuel treatment planning, featuring: lidar data for characterizing vegetation structure; hyperspectral sensors for retrieving chemical compounds and species composition; and dense time series derived from multispectral and synthetic aperture radar sensors for mapping phenology and moisture dynamics. We also highlight future hyperspectral and radar missions that will deliver valuable and complementary information for a new era of fuel load characterization from space. The data volume that is being generated may still challenge the usability by a diverse group of stakeholders. Seamless cyberinfrastructure and community engagement are paramount to guarantee the use of these cutting‐edge datasets for fuel monitoring and wildland fire management across the world.

中文翻译：

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利用下一代星载地球观测进行燃料监测和荒地火灾管理


管理燃料是减轻野火对人类和环境负面影响的关键策略。基于卫星的地球观测数据的使用已成为管理人员在区域范围内优化燃料处理规划的重要工具。幸运的是，过去几年推出了几种新传感器，为增强燃料特性提供了新的机会。在此，我们总结了大规模（即数百至数千公里）燃料表征的潜在改进2 ）具有高空间和光谱分辨率，这是由于使用具有近全球、免费可用数据的新型星载仪器而产生的。我们确定了适合燃料处理规划的空间分辨率的传感器，其特点是： 用于表征植被结构的激光雷达数据；用于检索化合物和物种组成的高光谱传感器；以及来自多光谱和合成孔径雷达传感器的密集时间序列，用于绘制物候学和湿度动态。我们还重点介绍了未来的高光谱和雷达任务，这些任务将为太空燃料负载表征的新时代提供有价值的补充信息。正在生成的数据量可能仍然会挑战不同利益相关者群体的可用性。无缝的网络基础设施和社区参与对于保证这些尖端数据集在世界各地的燃料监测和荒地火灾管理中的使用至关重要。