Single tree detection in forest areas with high-density LIDAR data

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 36, Issue , 2007, Pages 139-144

  Reitberger, J ^a   Heurich, M ^b   Krzystek, P ^a   Stilla, U ^c  

^a MUNICH UNIVERSITY OF APPLIED SCIENCES   (Germany)

^b BAVARIAN FOREST NATIONAL PARK   (Germany)

^c TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Analysis; Forestry; LIDAR; Segmentation; Vegetation

Indexed keywords

FORESTRY; IMAGE SEGMENTATION; OPTICAL RADAR; PHOTOGRAMMETRY; VEGETATION;

AIRBORNE LIDAR DATA; ANALYSIS; BAVARIAN FOREST NATIONAL PARK; CANOPY HEIGHT MODELS; FULL-WAVEFORM DATA; HIER-ARCHICAL CLUSTERING; POSITIONING ERROR; WATER-SHED ALGORITHM;

IMAGE ANALYSIS;

EID: 50849113017     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Brandtberg, T., 2007, Classifying individual tree species under leaf-off and leaf-on conditions using airborne LIDAR. ISPRS Journal of Photogrammetry and Remote Sensing, 61, pp. 325 – 340.
2. Heijden, F. van der, Duin, R.P.W., Ridder, D. de, Tax, D.M.J., 2004. Classification, parameter estimation and state estimation – An engineering approach using MATLAB. John Wiley & Sons Ltd, The Attrium, southern Gate, Chichester, West Sussex PO19 8SQ, England.
3. Heurich, M., 2006, Evaluierung und Entwicklung von Methoden zur automatisierten Erfassung von Waldstrukturen aus Daten flugzeuggetragener Fernerkundungssensoren. Schriftenreihe des Wissenschaftszentrums Weihenstephan für Ernährung, Landnutzung und Umwelt der Technischen Universität München und der Bayerischen Landesanstalt für Wald und Forstwirtschaft, Forstlicher Forschungsbericht München, Nr. 202, ISBN 3-933506-33-6. http://meadiatum2/ub.tum.de/ (Accessed February 18, 2007).
4. Holmgren, J., Persson, Ǻ., 2004, Identifying species of individual trees using airborne laser scanner. Remote Sensing of Environment 90 (2004) 415-423.
5. th October, Freiburg, pp. 82 – 89.
6. Hyyppä, J., Kelle, O., Lehikoinen, M., Inkinen, M., 2001. A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners. IEEE Transactions on Geoscience and remote Sensing, 39:969-975.
7. Jutzi B., Stilla U. 2005. Waveform processing of laser pulses for reconstruction of surfaces in urban areas. In: Moeller M, Wentz E (eds) 3th International Symposium: Remote sensing and data fusion on urban areas, URBAN 2005. International Archives of Photogrammetry and Remote Sensing. Vol 36, Part 8 W27.
8. Krzystek, P., Wild, D., 1992, Experimental accuracy analysis of automatically measured digital terrain models. Robust Computer Vision: Quality of vision algorithms. Förstner, Ruhwiedel (ed.). Wichman Verlag, Karlsruhe, pp. 372-390.
9. Persson, A., Holmgren, J. and Söderman, U., 2002. Detecting and measuring individual trees using an airborne laserscanner. Photogrammetric Engineering & Remote Sensing 68(9), pp. 925–932.
10. Pyysalo, U., Hyyppä, H., 2002. Reconstructing Tree Crowns from Laser Scanner Data for Feature Extraction. In ISPRS Commission III, Symposium 2002 September 9 - 13, 2002, Graz, Austria, pages B-218 ff (4 pages).
11. Reitberger, J., Krzystek, P., Stilla, U. 2006. Analysis of Full Waveform Lidar Data for Tree Species Classification. Symposium ISPRS Commission III “Photogrammetric Computer Vision” PCV06, 20 – 22th September, Bonn, Germany.
12. Solberg, S., Naesset, E., Bollandsas, O. M., 2006. Single Tree Segmentation Using Airborne Laser Scanner Data in a Structurally Heterogeneous Spruce Forest. Photogrammetric Engineering & Remote Sensing, Vol. 72, No. 12, December 2006, pp. 1369-1378.
13. Vincent, L., Soille, P., 1991, Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations. IEEE Transactions of Pattern Analysis and Machine Intelligence, Vol. 13, No. 6, June 1991, pp. 583-598.