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Acquisition of Forest Attributes for Decision Support at the Forest Enterprise Level Using Remote-Sensing Techniques—A Review

机译：遥感技术在森林企业一级获取用于决策支持的森林属性的评论

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摘要

In recent decades, remote sensing techniques and the associated hardware and software have made substantial improvements. With satellite images that can obtain sub-meter spatial resolution, and new hardware, particularly unmanned aerial vehicles and systems, there are many emerging opportunities for improved data acquisition, including variable temporal and spectral resolutions. Combined with the evolution of techniques for aerial remote sensing, such as full wave laser scanners, hyperspectral scanners, and aerial radar sensors, the potential to incorporate this new data in forest management is enormous. Here we provide an overview of the current state-of-the-art remote sensing techniques for large forest areas thousands or tens of thousands of hectares. We examined modern remote sensing techniques used to obtain forest data that are directly applicable to decision making issues, and we provided a general overview of the types of data that can be obtained using remote sensing. The most easily accessible forest variable described in many works is stand or tree height, followed by other inventory variables like basal area, tree number, diameters, and volume, which are crucial in decision making process, especially for thinning and harvest planning, and timber transport optimization. Information about zonation and species composition are often described as more difficult to assess; however, this information usually is not required on annual basis. Counts of studies on forest health show an increasing trend in the last years, mostly in context of availability of new sensors as well as increased forest vulnerability caused by climate change; by virtue to modern sensors interesting methods were developed for detection of stressed or damaged trees. Unexpectedly few works focus on regeneration and seedlings evaluation; though regenerated stands should be regularly monitored in order to maintain forest cover sustainability.
机译：在最近的几十年中，遥感技术以及相关的硬件和软件有了长足的进步。借助可获得亚米级空间分辨率的卫星图像，以及新的硬件，尤其是无人驾驶飞机和系统，新的机会不断涌现，可以改善数据采集，包括可变的时间和频谱分辨率。结合全波激光扫描仪，高光谱扫描仪和航空雷达传感器等航空遥感技术的发展，将这种新数据纳入森林管理的潜力是巨大的。在这里，我们概述了数千或数万公顷的大森林地区当前的最新遥感技术。我们研究了用于获取可直接用于决策问题的森林数据的现代遥感技术，并对可使用遥感获取的数据类型进行了概述。在许多作品中，最容易获得的森林变量是林分或树木的高度，其次是其他存量变量，例如基础面积，树木数量，直径和体积，这在决策过程中至关重要，特别是对于间伐和采伐计划以及木材运输优化。有关分区和物种组成的信息通常被描述为更难评估。但是，通常不需要每年提供此信息。近年来，关于森林健康的研究数量呈增长趋势，主要是在获得新传感器以及气候变化导致森林脆弱性增加的背景下;借助于现代传感器，开发了用于检测受压或受损树木的有趣方法。出乎意料的是，很少有作品专注于再生和幼苗评估。尽管应定期监测再生林，以保持森林覆盖的可持续性。

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