Canopy Density Model: A New ALS-Derived Product to Generate Multilayer Crown Cover Maps | INSTITUT DE PHYSIQUE DU GLOBE DE PARIS


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  Canopy Density Model: A New ALS-Derived Product to Generate Multilayer Crown Cover Maps

Type de publication:

Journal Article


IEEE Transactions on Geoscience and Remote Sensing, Volume 53, Nombre 12, p.6776-6790 (2015)


airborne laser scanner, ALS data, ALS multiecho capability, ALS-derived product, Bandwidth, canopy density model, compute forest crown cover, Density estimation robust algorithm, Estimation, forest structure characterization, forestry, geophysical techniques, ground vegetation, Kernel, kernel density estimators, lasers, multilayer crown cover maps, nonparametric density estimation technique, Probability density function, Remote sensing, single-layer forest canopies, Three-dimensional displays, vegetation, vegetation features, vegetation mapping


The canopy density model (CDM), a new product interpolated from airborne laser scanner (ALS) data and dedicated to forest structure characterization is presented. It exploits both the multiecho capability of the ALS and a nonparametric density estimation technique called kernel density estimators (KDEs). The CDM is used to delineate the outmost perimeter of vegetation features and to compute forest crown cover (CrCO). Contrary to other works that focus on single-layer forest canopies, CrCo is derived here for each layer, namely, the overstory, the understory, and ground vegetation. The root-mean-square error of prediction determined by using field data acquired over 44 forest stands in a forest in Portugal allows the testing of the reliability of the method: It ranges from 6.21% (overstory) to 13.76% (ground vegetation). In addition, we investigate the ability of the CDM to map the CrCo for individual trees. Finally, two existing methods have been applied to our study site in order to assess improvements, advantages, and drawbacks of our approach.