AUTOMATIC TREE-CROWN DETECTION IN CHALLENGING SCENARIOS

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ID: 86038
2016
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Abstract
In this paper, a new procedure for individual tree detection and modeling is presented. The input of this procedure consists of a normalized digital surface model NDSM, and a possibly error-prone classification result. The procedure is modular so that the functionality, the advantages and the disadvantages for every single module will be explained. The most important technical contributions of the paper are: Employing watershed transformation combined with classification results, applying hotspots detectors for identifying treetops in groups of trees, and correcting NDSM by detecting and geometric reconstruction of small anomalies, such as earth walls. Two minor contributions are made up by a detailed literature research on available methods for individual tree detection and estimation of tree-crowns for clearly identified trees in order to reduce arbitrariness by assigning trees to one of the few types in the output model.
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bulatov2016automaticthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bulatov, D.;Wayand, I.;Schilling, H.;
Journal the international archives of the photogrammetry, remote sensing and spatial information sciences
Year 2016
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