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Automatic tree-crown detection in challenging scenarios

: Bulatov, Dimitri; Wayand, Isabell; Schilling, Hendrik

Fulltext urn:nbn:de:0011-n-4106231 (4.6 MByte PDF)
MD5 Fingerprint: 12cdbd4cd2d718f2df978ffe0522f89d
Created on: 25.8.2016

Halounova, L. ; International Society for Photogrammetry and Remote Sensing -ISPRS-:
XXIII ISPRS Congress 2016. Commission III : 12-19 July 2016, Prague, Czech Republic; From Human History to the Future with Spatial Information
Istanbul: ISPRS, 2016 (ISPRS Archives XLI-B3)
International Society for Photogrammetry and Remote Sensing (ISPRS Congress) <23, 2016, Prague>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
3D-modeling; classification; hotspots detection; surface reconstruction; tree; Watershed Transformation

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.