Forested environments are subject to large and high intensity unplanned fire events, owing to, among other factors, the high quantity and complex structure of fuel in these environments. Compiling accurate and spatially comprehensive fuel information is necessary to inform various aspects of land management in forested environments. Remote sensing may offer distinct advantages for this in comparison to traditional site-based approaches. We conducted a literature review of the past 10 years of research in the remote sensing of fire fuel in forested environments, with a focus on emerging methods of fuel estimation, and the fuel attributes estimated. We position our review of remote sensing research in relation to the fuel attributes that influence fire behaviour, as suggested by contemporary physics-based fire behaviour knowledge, and a summary of fuel inputs to widely applied forest fire behaviour models. We find a disconnect between recent remote sensing research and fuel characterisations relevant to contemporary fire behaviour knowledge. Specifically, we find a tendency in remote sensing research towards estimation of forest overstorey fuel attributes, and a relative lack of research that estimates more obscured, though highly relevant, fuel components such as understorey, surface, and bark fuel. We also find a tendency for recent remote sensing research to conceptualise fire fuel by existing fire behaviour models, with particular emphasis on matching pre-existing fuel model classifications. A case is made for remotely sensed forest fuel estimation grounded in current knowledge of fire behaviour processes and the fuel attributes known to influence these processes. Shortcomings in remote sensing of key forest fuel attributes are partly due to inherent limitations of current technologies, and we discuss recent and expected advancements in remote sensing research and technology that may drive significant future advancement in forest fuel estimation. Further, we suggest that recognition of interactions between fuel attributes and measurable biophysical forest properties can assist in addressing present limitations in remote sensing of key forest fuel attributes. Such process-based methods would be more spatially and temporally applicable, encourage new techniques for estimating fuel attributes using remote sensing data, and may encourage the development of fire behaviour and risk prediction systems that are more suited to remote sensing.

造成森林环境易受大型和高强度计划外火灾的影响，这是由于除其他因素外，这些环境中燃料的数量庞大且结构复杂。为了在森林环境中进行土地管理的各个方面，必须收集准确且空间全面的燃料信息。与传统的基于站点的方法相比，遥感可以为此提供独特的优势。我们对森林环境中火燃料遥感的近十年研究进行了文献综述，重点是新兴的燃料估计方法和估计的燃料属性。正如当代基于物理学的火灾行为知识所建议的，我们将遥感研究的回顾与影响火灾行为的燃料属性相关联，以及广泛应用的森林火灾行为模型的燃料输入摘要。我们发现最近的遥感研究与与现代火灾行为知识相关的燃料特性之间存在脱节。具体而言，我们发现在遥感研究中倾向于估计森林过剩燃料的属性，并且相对缺乏研究来估计更加模糊的燃料成分（尽管高度相关），例如下层，地面和树皮燃料。我们还发现，最近的遥感研究有一种趋势，即通过现有的火灾行为模型来概念化燃料，特别是要对已存在的模型进行匹配。我们发现遥感研究趋向于估计森林过高燃料的属性，并且相对缺乏研究来估计更加模糊的燃料组分，尽管它们之间的相关性很高，例如下层，地面和树皮燃料。我们还发现，最近的遥感研究有一种趋势，即通过现有的火灾行为模型来概念化燃料，特别是要对已存在的模型进行匹配。我们发现遥感研究趋向于估计森林过高的燃料属性，并且相对缺乏研究来估计更加模糊的燃料成分，尽管它们之间的相关性很高，例如下层，地面和树皮燃料。我们还发现，最近的遥感研究有一种趋势，即通过现有的火灾行为模型来概念化燃料，特别是要对已存在的模型进行匹配。燃油模型分类。基于火灾行为过程的当前知识以及已知会影响这些过程的燃料属性，提出了基于遥感的森林燃料估算的案例。关键森林燃料属性遥感的不足部分是由于当前技术的固有局限性，我们讨论了遥感研究和技术的最新进展和预期进展，这些进展可能会推动未来森林燃料估算的重大进展。此外，我们建议对燃料属性和可测量的生物物理森林属性之间的相互作用的认识可以帮助解决目前在关键森林燃料属性的遥感中的局限性。这样的基于过程的方法将在空间和时间上更具适用性，鼓励使用遥感数据估算燃料属性的新技术，