In: Wagner W., Székely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
638 
Baatz, M., and Schäpe, A., 2000. Multiresolution Segmentation 
- an optimization approach for high quality multi-scale image 
segmentation. In J. Strobl, T. Blaschke and G. Griesebner 
(eds.), Angewandte Geographische Informationsverarbeitung 
Vol. XII (pp. 12-23). Heidelberg, Germany: Wichmann 
Burrough, P.A., 1986. Principles of Geographical Information 
Systems for Land Resources Assessment. New York: Oxford 
University Press, 50 p. 
Brändli, U.-B., 2010. Schweizerisches Landesforstinventar. 
Ergebnisse der dritten Erhebung 2004-2006. Birmensdorf, 
Eidgenössische Forschungsanstalt für Wald, Schnee und 
Landschaft WSL. Bern, Bundesamt für Umwelt, BAFU. 312 p. 
Brandtberg, T., 2002. Individual tree-based species 
classification in high spatial resolution aerial images of forests 
using fuzzy sets. Fuzzy Sets and Systems, 132, pp. 371-387. 
Brassel, P. and Lischke, H., 2001. Swiss National Forest 
Inventory: methods and models of the second assessment. 
Birmensdorf, Swiss Federal Research Institute WSL, 336 p. 
Chubey, M., Stehle, K., Albricht, R., Gougeon, F., Leckie, D., 
Gray, S., Woods, M., and Courville, P., 2009). Semi-Automated 
Species Classification in Ontario Great Lakes - St.Lawrence 
Forest Conditions. Final Report: Great Lakes - St. Lawrence 
ITC Project (2005/2008). Ontario Ministry of Natural 
Resources. January 2009. 71 p. 
Gonzales, R.C., & Woods, R.E., 2002. Digital image 
processing. Second edition. New Jersey: Upper Saddle River. 
Guisan, A., Weiss, S.B., and Weiss, A.D., 2004). GLM versus 
CCa spatial modeling of plant species distribution. Plant 
Ecology 143(1), pp. 107-122. 
Heinzei, J.N., Weinacker, H., and Koch, B., 2008. Full 
automatic detection of tree species based on delineated single 
tree crowns - a data fusion approach for airborne laser scanning 
data and aerial photographs, Proceedings of the SilviLaser 8th 
international conference on LiDAR applications in forest 
assessment and inventory, (pp. 76-85), September 18-19, 2008, 
Edinburgh, UK. 
Hirschmugl, M., Ofner, M., Raggam, J., and Schardt, M., 2007. 
Single tree detection in very high-resolution remote sensing 
data. Remote Sensing of Environment, 110, pp. 533-544. 
Holmgren, J., Persson, Ä., and Söderman, U., 2008. Species 
identification of individual trees by combining high resolution 
LiDAR data with multi-spectral images. International Journal 
of Remote Sensing, 29, pp. 1537-1552. 
Hosmer, D.W., and Lemeshow, S., 2000. Applied logistic 
regression, 2 nd edition, New York: Wiley, 373 p. 
Key, T., McGra, J.B., and Fajvan, M.A., 2001. A comparison of 
multispectral and multitemporal information in high spatial 
resolution imagery for classification of individual tree species 
in a temperate hardwood forest. Remote Sensing of 
Environment, 75, pp. 100-112. 
Küchler, M., Ecker, K., Feldmeyer-Christe, E., Graf, U., 
Küchler, H., & Waser, L.T., 2004. Combining remotely sensed 
spectral data and digital surface models for fine-scale modelling 
of mire ecosystems. Community Ecology, 5(1), pp. 55-68. 
McCullagh, P., and Nelder, J.A., 1983. Generalized linear 
models. London: Chapman and Hall, 511 p. 
Moore, I. D., Grayson, R. B., and Landson, A. R., 1991. Digital 
Terrain Modelling: a Review of Hydrological, 
Geomorphological, and Biological Applications. Hydrological 
Processes. Vol. 5, pp. 3-30. 
Olofsson, K., Wallermann, J., Holmgren, J., and Olsson, H., 
2006. Tree species discrimination using Z/I DMC imagery and 
template matching of single trees. Scandinavian Journal of 
Forest Research, 21, pp. 106-110. 
Reulke, R., Becker, S., Haala, N., and Tempelmann, U., 2006. 
Determination and improvement of spatial resolution of the 
CCD-line-scanner system ADS40. ISPRS Journal of 
Photogrammetry & Remote Sensing, 60, pp. 81-90. 
Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, 
M., and Wall, B., 2002. Predicted species occurrences: issues 
of accuracy and scale, Island Press, Covelo, California, 868 p. 
St-Onge, B., Jumelet, J., Cobello, M., and Vega, C., 2004. 
Measuring individual tree height using a combination of 
stereophotogrammetry and lidar. Canadian Journal of Forest 
Research, 54(10), pp. 2122-2130. 
Waser, L.T., Küchler, M., Ecker, K., Schwarz, M., Ivits, E., 
Stofer, S., and Scheidegger, C. (2007). Prediction of Lichen 
Diversity in an Unesco Biosphere Reserve - Correlation of high 
Resolution Remote Sensing Data with Field Samples. 
Environmental Modeling & Assessment, 12(4), pp. 315-328 
Waser, L.T., Baltsavias, E., Ecker, K., Eisenbeiss, H., Ginzler, 
C., Küchler, M., Thee, P., and Zhang, L. (2008a). High- 
resolution digital surface models (DSM) for modelling 
fractional shrub/tree cover in a mire environment. International 
Journal of Remote Sensing, 29(5), pp. 1261 - 1276 
Waser, L.T., Ginzler, C., Kuechler, M., and Baltsavias, E. 
(2008b). Potential and limits of extraction of forest attributes by 
fusion of medium point density LiDAR data with ADS40 and 
RC30 images. Proceedings of the SilviLaser 8th international 
conference on LiDAR applications in forest assessment and 
inventory, September 18-19, 2008, Edinburgh, U, pp. 625-634. 
Waser, L.T., Klonus, S., Ehlers, M., Küchler, M., and Jung, A., 
2010. Potential of Digital Sensors for Land Cover and Tree 
Species Classifications - A Case Study in the Framework of the 
DGPF-Project. Photogrammetrie, Fernerkundung und Geo 
information, Vol. 10 (2), pp. 132- 141. 
8. ACKNOWLEDGEMENTS 
The study was carried out within the framework of the Swiss 
National Forest Inventory (NFI) and funded by the Swiss 
Federal Office for the Environment (FOEN) and WSL. We are 
grateful to Patrick Thee for his valuable help in the field 
surveys.