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首页> 外文期刊>Scandinavian Journal of Forest Research >Developing an airborne laser scanning dominant height model from a countrywide scanning survey and national forest inventory data
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Developing an airborne laser scanning dominant height model from a countrywide scanning survey and national forest inventory data

机译:根据全国范围的扫描调查和国家森林清单数据开发机载激光扫描优势高度模型

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摘要

An airborne laser scanning (ALS) dominant height model was developed based on data from a national scanning survey with the aim of developing a digital terrain model (DTM) for Denmark. Data obtained in the ongoing Danish national forest inventory (NFI) were used as reference data. The data comprised a total of 2072 measurements of dominant height on NFI sample plots inventoried in 2006-2007 and their corresponding ALS data. The dominant height model included four variables derived from the ALS point cloud distribution. The variables were related to canopy height, canopy density and species composition on individual plots. The RMSE of the final model was 2.25 m and the model explained 93.9% of the variation (R-2). The model was successful in predicting dominant height across a wide range of forest tree species, stand heights, stand densities, canopy cover and growing conditions. The study demonstrated how low-density ALS data obtained in a survey not specifically aimed at forest applications may be used for obtaining biophysical forest properties such as dominant height, thereby reducing the overall forest inventory costs.
机译:基于国家扫描调查的数据,开发了机载激光扫描(ALS)优势高度模型,旨在为丹麦开发数字地形模型(DTM)。正在进行的丹麦国家森林清单(NFI)中获得的数据用作参考数据。数据包括2006-2007年清点的NFI样地上的2072项主要身高测量值及其相应的ALS数据。优势高度模型包括从ALS点云分布得出的四个变量。这些变量与各个样地的冠层高度,冠层密度和物种组成有关。最终模型的RMSE为2.25 m,该模型解释了93.9%的变化(R-2)。该模型成功地预测了广泛的林木物种,林分高度,林分密度,树冠覆盖率和生长条件的优势高度。这项研究表明,在不专门针对森林应用的调查中获得的低密度ALS数据可如何用于获取生物物理森林特性(例如优势高度),从而降低总体森林清单成本。

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