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首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure
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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:森林扰动与恢复:星空遥感对地上生物量和冠层结构的影响的一般回顾

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[1] Abrupt forest disturbances generating gaps >0.001 km~2 impact roughly 0.4-0.7 million km~2 a~(-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 opticalear-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 Earth's 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:[1]造成森林间隙大于0.001 km〜2的突然森林干扰影响大约0.4-0.7百万km〜2 a〜(-1)。火灾,暴风雨,伐木和耕作转移是主要的干扰。较小的贡献是土地改建,洪水,山体滑坡和雪崩。所有这些都会对冠层生物量和结构产生重大影响。量化干扰位置,程度,严重性以及受干扰生物质的命运将改善碳预算估算,并导致更好的初始化,参数化和/或森林碳循环模型测试。星载遥感可以绘制出大规模森林干扰发生,位置和程度的地图,尤其是使用中分辨率和精细分辨率的无源光学/近红外(NIR)仪器。高分辨率遥感技术(例如,约1 m的被动光学/ NIR或小面积激光雷达)可绘制冠状几何形状和间隙,但很少系统地用于研究大范围的小规模干扰和自然死亡间隙动态。为减少扰动和恢复对全球森林碳平衡的影响的不确定性,需要量化(1)扰动前的森林生物量; (2)干扰对立式生物量及其命运的影响; (3)恢复过程中生物量的积累率。主动遥感数据(例如,激光雷达,雷达)比被动仪器数据更直接地表明冠层生物量和许多结构特性;旨在对冠层生物量和结构进行全球覆盖/采样的新一代仪器可以提高我们量化地球森林碳平衡的能力。利用星载遥感技术来生成对冠层生物量和结构的扰动影响的高质量定量评估,需要全面,精心设计和协调良好的实地计划,该计划应收集高质量的地面数据以及可使用此信息的动力学模型的链接。

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