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Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure

机译:森林骚扰和恢复:在地下生物量和冠层结构的空间遥感的背景下的一般审查

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摘要

Abrupt forest disturbances generating gaps u3e0.001 km2 impact roughly 0.4–0.7 million km2a−1. Fire, windstorms, logging, and shifting cultivation are dominant disturbances; minor contributors are land conversion, flooding, landslides, and avalanches. All can have substantial impacts on canopy biomass and structure. Quantifying disturbance location, extent, severity, and the fate of disturbed biomass will improve carbon budget estimates and lead to better initialization, parameterization, and/or testing of forest carbon cycle models. Spaceborne remote sensing maps large-scale forest disturbance occurrence, location, and extent, particularly with moderate- and fine-scale resolution passive optical/near-infrared (NIR) instruments. High-resolution remote sensing (e.g., ∼1 m passive optical/NIR, or small footprint lidar) can map crown geometry and gaps, but has rarely been systematically applied to study small-scale disturbance and natural mortality gap dynamics over large regions. Reducing uncertainty in disturbance and recovery impacts on global forest carbon balance requires quantification of (1) predisturbance forest biomass; (2) disturbance impact on standing biomass and its fate; and (3) rate of biomass accumulation during recovery. Active remote sensing data (e.g., lidar, radar) are more directly indicative of canopy biomass and many structural properties than passive instrument data; a new generation of instruments designed to generate global coverage/sampling of canopy biomass and structure can improve our ability to quantify the carbon balance of Earthu27s forests. Generating a high-quality quantitative assessment of disturbance impacts on canopy biomass and structure with spaceborne remote sensing requires comprehensive, well designed, and well coordinated field programs collecting high-quality ground-based data and linkages to dynamical models that can use this information.
机译:突然森林干扰产生的差距 u3e0.001平方公里的影响大约0.4-0.7亿km2a-1。火,风暴,记录和轮作是显性紊乱;次要的贡献者是土地转化,洪水,泥石流,雪崩和。所有可能对冠层生物量和结构产生重大影响。量化干扰的位置,范围,严重程度和干扰生物的命运将提高碳概算,并带来更好的初始化参数,和/或森林碳循环模型的测试。空间遥感映射大规模森林干扰发生,位置,和程度,特别是中度和精细尺度分辨率无源光/近红外(NIR)的仪器。高分辨率遥感(例如,〜1米无源光/ NIR,或占地面积小激光雷达)可以映射冠几何形状和间隙,但很少被系统地施加在大区域来研究的小规模干扰和自然死亡率间隙动力学。在全球森林碳平衡紊乱和恢复的影响,减少不确定性,需要(1)predisturbance森林生物量的量化;在现存生物量和它的命运(2)扰动的影响;及(3)恢复期间生物量积累的速率。活性遥感数据(例如,激光雷达,雷达)的更直接指示树冠的生物量和比被动仪器数据的许多结构特性;新一代/仪表设计产生的全球覆盖树冠生物量和结构的采样,可以提高我们的量化地球 u27s森林的碳平衡能力。产生的冠层生物量和结构星载遥感扰动影响高质量的定量评估,需要全面,精心设计,并很好地协调实地方案来收集高质量的基于地面的数据和联系,以动态的模型,可以使用这些信息。

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