ISPRS Commission III, Vol.34, Part 3A ,,Photogrammetric Computer Vision“, Graz, 2002
these methods can also be applied to other forest areas with
different stand structures, in particular to mixed forest areas.
It can be expected that improved algorithms and more detailed
data will result in a further improvement of the methods devel-
oped.
Improvements in algorithms:
- Knowledge - based tree top detection and segmentation
considering minimum distances of tree tops depending on
tree species and tree height (age)
- Fusion methods to combine laser scanning data with other
data sources (e.g. very high resolution optical data, inten-
sity values of the laser signal or existing forest maps)
Improvements in data:
- Availability of multispectral data acquired simultaneously
(TopoSys II)
- Availability of intensity values
- Better ground resolution in order to detect smaller trees
and trees in dense stands
The advantages of laser scanning based inventories can be
summarized as follows:
- Laser scanning provides a quick overview of forested ar-
eas
- Automated assessment of inventory data in an objective
manner
- Multiple use of the data: e.g. DTM for road construction
and planning of harvesting activities, assessment of forest
parameters as basis for forest management activities
- Data can be shared with other users, e.g. administration
and planning offices, hydrology
- Alternative to yield tables, which are of limited use as an
inventory tool (Hasenauer et al. 1994)
In spite of the high potential of laser scanning for forest inven-
tories, laser scanning will most likely not substitute the field
work of foresters, since not all information can be derived by
means of this new method.
LITERATUR
Hasenauer, H.; Stampfer, E.; Rohrmoser, C. & Sterba, H.
(1994): Solitárdimensionen der wichtigsten Baumarten Oster-
reichs. Ósterreichische Forstzeitschrift, Jahrgang 1994, Heft 3.
Hyyppà, J., Hyyppd, H., Samberg, A., 1999, Assessing Forest
Stand Attributes by Laser Scanner, Laser Radar Technology and
Applications IV, 3707: 57-69.
Lindeberg T., 1993: On Scale Selection for Differential Opera-
tors, Computational Vision and Active Perception Laboratory,
Royal Institute of Technology, Sweden
Lindeberg T. and B.M.H. Romeny, 1994: Linear scale-space,
Kluwer Academic Publishers, Netherlands
Nüsset, E. 1997: “Estimating timber volume of forest stands
using airborne laser scanner data”, Remote Sensing of Envi-
ronment, 61, pp. 246-253.
Pollanschiitz J., 1974: Formzahlfunktionen der Hauptbaumarten
— Form value equations of main tree species, Osterreichische
Allg. Forstzeitung 85 (12), in German
Ruppert G.S., A. Wimmer, R. Beichel, M. Ziegler, 2000: "An
adaptive multi-resolutional algorithm for high precision forest
floor DTM generation", Proceedings of AeroSense'2000, Laser
Radar Technology and Applications V, 4035, Orlando / Flor-
ida, April 2000
Roerdink J. & A. Meijster, 1999: The Watershed Transform:
Definitions, Algorithms and Parallelization Strategies, Univer-
sity of Groningen, Netherlands
Samberg, A., Hyyppä, J., Ruppert, G., Hyyppà, H., Ziegler, M.,
Schardt, M., Soininen, A., 1999, Evaluation of the laser scanner
data in the forest area, Laser Radar Technology and Applica-
tions IV, 3707: 570-581.
Soille P., 1999: Morphological Image Analysis, Springer.
Ziegler, M., Konrad, H., Hofrichter, J., Wimmer, A., Ruppert,
G., Schardt, M., Hyyppä, J., Assessment of forest attributes and
single-tree segmentation by means of laser scanning, Proceed-
ings of AeroSense'2000, Laser Radar Technology and Applica-
tions V, 4035, 12 p, April 2000.
A - 309
