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Bryophyte cover estimation in a boreal black spruce forest using airborne lidar and multispectral sensors

机译:使用机载激光雷达和多光谱传感器在北方黑云杉林中估算苔藓植物

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摘要

Bryophytes are the dominant ground cover vegetation layer in many boreal forests and in some of these forests the net primary production of bryophytes exceeds the overstory. Therefore it is necessary to quantify their spatial coverage and species composition in boreal forests to improve boreal forest carbon budget estimates. We present results from a small exploratory test using airborne lidar and multispectral remote sensing data to estimate the percentage of ground cover for mosses in a boreal black spruce forest in Manitoba, Canada. Multiple linear regression was used to fit models that combined spectral reflectance data from CASI and indices computed from the SLICER canopy height profile. Three models explained 63 ? 79% of the measured variation of feathermoss cover while three models explained 69 ? 92 % of the measured variation of sphagnum cover. Root mean square errors ranged from 3-15% when predicting feathermoss, sphagnum, and total moss ground cover. The results from this case study warrants further testing for a wider range of boreal forest types and geographic regions.
机译:苔藓植物是许多北方森林中占主导地位的地被植物植被层,在其中一些森林中,苔藓植物的净初级生产力超过了林木。因此,有必要量化其在北方森林中的空间覆盖率和物种组成,以改善北方森林碳预算的估算。我们提供了使用机载激光雷达和多光谱遥感数据进行的小型探索性测试的结果,以估算加拿大曼尼托巴北部黑色云杉林中苔藓的地被植物百分比。使用多元线性回归来拟合模型,该模型将CASI的光谱反射率数据与SLICER冠层高度轮廓计算的指标相结合。三种模式解释63?测得的羽毛苔覆盖度变化的79%,而三种模型解释了69%?测得的泥炭覆盖度变化的92%。预测羽毛苔藓,泥炭藓和总苔藓地面覆盖率时,均方根误差为3-15%。此案例研究的结果值得对更广泛的北方森林类型和地理区域进行测试。

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