Abstract
In this paper, we present a novel approach for the automatic extraction of trees and the delineation of the tree crowns from remote sensing data, and report and evaluate the results obtained with different test data sets. The approach is scale-invariant and is based on co-registered colour-infrared aerial imagery and a digital surface model (DSM). Our primary assumption is that the coarse structure of the crown, if represented at the appropriate level in scale-space, can be approximated with the help of an ellipsoid. The fine structure of the crown is suppressed at this scale level and can be ignored. Our approach is based on a tree model with three geometric parameters (size, circularity and convexity of the tree crown) and one radiometric parameter for the tree vitality. The processing strategy comprises three steps. First, we segment a wide range of scale levels of a pre-processed version of the DSM. In the second step, we select the best hypothesis for a crown from the overlapping segments of all levels based on the tree model. The selection is achieved with the help of fuzzy functions for the tree model parameters. Finally, the crown boundary is refined using active contour models (snakes). The approach was tested with four data sets from different sensors and exhibiting different resolutions. The results are very promising and prove the feasibility of the new approach for automatic tree extraction from remote sensing data.
Similar content being viewed by others
References
Andersen, H., Reutebusch, S.E., Schreuder, G.F.: Bayesian object recognition for the analysis of complex forest scenes in airborne laser scanner data. In: Kalliany, R., Leberl, F. (eds.) International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXIV, Nr. WG 3A, ISPRS, Graz, pp. 35–41 (2002)
Beucher, S.: Watersheds of functions and picture segmentation. In: International Conference on Acoustics, Speech and Signal Processing, IEEE, pp. 1928–1931 (1982)
Brandtberg, T.: Structure-based classification of tree species in high spatial resolution aerial images using a fuzzy clustering technique. In: The 11th Scandinavian Conference on Image Analysis, Kangerlussueq, 7–11 June 1999, pp. 165–172
Brandtberg T. and Walter F. (1998). Automated delineation of individual tree crowns in high spatial resolution aerial images by multiple scale analysis. Mach. Vis. Appl. 11: 64–73
Cohen L. (1991). On active contour models and balloons. CVGIP: Image Understand 2(53): 211–218
Gabet L., Giraudon G. and Renouard L. (1994). Construction automatique de modèles numériques de terrain haute résolution en milieu urbain. Bulletin de la Société Française de Photogrammétrie et Télédétection 135: 9–25
Gong P., Sheng Y. and Biging G. (2002). 3D Model based tree measurement from high-resolution aerial imagery. Photogramm. Eng. Remote Sens. 11(68): 1203–1212
Gougeon F.A. (1995). A crown-following approach to the automatic delineation of individual tree crowns in high spatial resolution aerial images. Can. J. Remote Sens. 3(21): 274–284
Gougeon, F., Moore, T.: Individual tree classification using meis-II imagery. In: IGARSS ’88 Geoscience and Remote Sensing Symposium, IEEE, vol. 2, pp. 927–927 (1988)
Haenel, S., Eckstein, W.: Ein Arbeitsplatz zur automatischen Luftbildanalyse, Mustererkennung 1986, Springer, Heidelberg, pp. 38–42 (1986)
Hildebrandt G. (1987). 100 Jahre forstliche Luftbildaufnahme—Zwei Dokumente aus den Anfängen der forstlichen Luftbildinterpretation. Bildmessung und Luftbildwesen 55: 221–224
Hyyppä, J., Hyyppä, H., Ruppert, G.: Automatic derivation of features to forest stand attributes using laser scanner data. In: International Archives of Photogrammetry and Remote Sensing, vol. XXXIII, Nr. Part B3, ISPRS, Amsterdam, pp. 421–428 (2000)
Hyyppä, J., Hyyppä, H., Letkey, P., Yu, X., Haggren, H., Rönnholm, P., Pyysalo, U., Pitkänen, J., Maltamo, M.: Algorithms and methods for airborne laser scanning for forest measurements. Int. Arch. Photogramm. Remote Sens. vol. XXXVI Part 8/W2, pp. 82–89 (2004)
Kass M., Witkin A. and Terzopoulus D. (1988). Snakes: active contour models. Int. J. Comput. Vis. 1: 321–331
Koenderink J. (1984). The structure of images. Biol. Cybern. 50: 363–370
Larsen, M., Rudemo, M.: Using ray-traced templates to find individual trees in aerial photos. In: Proceedings of the 10th Scandinavian Conference on Image Analysis, Lappeenranta, vol. 2, pp. 1007–1014 (1997)
Lillesand T.M. and Kiefer R.W. (1994). Remote Sensing and Image Interpretation. Wiley, New York, 750
Lindeberg T. (1994). Scale-Space Theory in Computer Vision. Kluwer, Boston, 423
Persson A., Holmgren J. and Söderman U. (2002). Detecting and measuring individual trees using an airborne laser scanner. Photogramm. Eng. Remote Sens. 9(68): 925–932
Pinz, A.: Final results of the vision expert system VES: finding trees in aerial photographs. In: Proceedings ÖAGM 13. Workshop of the Austrian Association for Pattern Recognition, Oldenbourg Schriftenreihe Österreichische Computer Gesellschaft, Wien München, pp. 90–111 (1989)
Pollock, R.J.: A model-based approach to automatically locating tree crowns in high spatial resolution images. Image Signal Process. Remote Sens. (eds.) Desachy, SPIE, vol. 2315, pp. 526–537 (1994)
Pollock, R.J.: The automatic recognition of individual trees in aerial images of forests based on a synthetic tree crown image model. Dissertation Computer Science, The University of British Columbia, Vancouver, June 1996, 170 p (1996)
Schardt, M., Ziegler, M., Wimmer, A., Wack, R., Hyyppä, J.: Assessment of forest parameter by means of laser scanning. In: Kalliany, R., Leberl, F. (eds.) International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXIV, Nr. 3A,ISPRS, Graz, pp. 302–309 (2002)
Schneider, S.: Luftbild und Luftbildinterpretation. de Gruyter, Berlin 530 p (1974)
Soille P. (1999). Morphological Image Analysis: Principles and Applications. Springer, Heidelberg, 316
Straub, B.: Automatische Extraktion von Bäumen aus Fernerkundungsdaten. Reihe C, Deutsche Geodätische Kommission, München, vol. 572, 99 p (2003)
Straub, B., Heipke, C.: Automatic extraction of trees for 3D-City models from images and height data. In: Baltsavias, M., Gruen, A., van Gool, L. (eds.) Automatic Extraction of Man-Made Objects from Aerial and Space Images III. A.A.Balkema Publishers. Lisse Abingdon Exton (PA), pp. 267–277 (2001)
Ünsalan C. and Boyer K.L. (2004). Linearised vegetation indices based on a formal statistical framework. IEEE Trans. Geosci. Remote Sens. 42(7): 1575–1585
Weinacker, H., Koch, B., Heyder, U., Weinacker, R.: Development of filtering, segmentation and modelling modules for LIDAR and multi-spectral data as a fundament of an automatic forest inventory system. In: International Archives of Photogrammetry and Remote Sensing, vol. XXXVI Part 8/W2, ISPRS, pp. 50–55 (2004)
Winter S. (2000). Uncertain topological relations between imprecise regions. Int. J. Geograph. Inform. Sci. 5(14): 411–430
Wulder M., White J., Niemann K. and Nelson T. (2004). Comparison of airborne and satellite high resolution data for the identification of individual trees with local maxima filtering. Int. J. Remote Sens. 25(11): 2225–2232
Zadeh L. (1965). Fuzzy sets. Inform. Cont. 3(8): 338–353
Author information
Authors and Affiliations
Corresponding author
Additional information
The major part of this work was carried out while both authors worked together at the Institute of Photogrammetry and GeoInformation, University of Hannover.
Rights and permissions
About this article
Cite this article
Wolf (né Straub), BM., Heipke, C. Automatic extraction and delineation of single trees from remote sensing data. Machine Vision and Applications 18, 317–330 (2007). https://doi.org/10.1007/s00138-006-0064-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00138-006-0064-9