AUTOMATIC TREE-CROWN DETECTION IN CHALLENGING SCENARIOS
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 disa...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/575/2016/isprs-archives-XLI-B3-575-2016.pdf |
| Summary: | 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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| ISSN: | 1682-1750 2194-9034 |