Für die Aufnahme von topographischen Informationen wird verstärkt flugzeuggetragenes Laserscannin... more Für die Aufnahme von topographischen Informationen wird verstärkt flugzeuggetragenes Laserscanning (engl. Airborne Laser Scanning, ALS) eingesetzt. Dabei eignet sich ALS als aktive Fernerkundungsmethode besonders für die Abtastung von bewaldeten Gebieten. Speziell in Forstanwendungen ist die aus ALS Daten abgeleitete Höheninformation der Vegetation eine fundamentale Eingangsgröße, die der Berechnung vieler Forstparameter (Baumhöhen, Stammvolumen, Biomasse) zugrunde liegt. Zusätzlich haben sich ALS Daten als Input für eine, auf Objekthöhen basierte, Waldabgrenzung bereits bewährt. Bis dato werden hauptsächlich Orthophotos für eine manuelle bzw. semi-automatisierte Waldabgrenzung verwendet, wobei schattige Bereiche die Detektierung von Waldrändern und vor allem Waldlücken stark beeinträchtigen. Hier zeigt ALS ein großes Potential und bietet in den meisten Fällen gegenüber einer manuellen Bildinterpretation deutliche Vorteile. Im Rahmen dieser Arbeit wird ein vollautomatischer Ansatz p...
Airborne laser scanning (ALS) data has been established as the standard method for the acquisitio... more Airborne laser scanning (ALS) data has been established as the standard method for the acquisition of high precision topographic data. In addition to the derivation of topographic models, such as digital terrain models (DTM) or digital surface models (DSM), ALS data is the main input data source for a variety of applications, e.g. building modelling, power line modelling or forestry applications. Until now a severe limitation is the availability of tools allowing computations directly on the 3D point cloud for district wide calculations. In complex 3D scenarios such as forests, the point cloud content is commonly converted to raster data (e.g. DTM and DSM) with a notable loss of information. As a result, the information on the vertical structure of vegetation is irretrievably lost. Therefore, a methodology for the delineation of forest areas and subsequent derivation of vertical vegetation strata is proposed. The presented approach combines processing steps directly in the 3D point ...
The objective of this paper is to evaluate a new approach for the automatic delineation of forest... more The objective of this paper is to evaluate a new approach for the automatic delineation of forested areas based on airborne laser scanning (ALS) and national forest inventory (NFI) data. In the Austrian NFI a forest area is mainly defined with four fundamental criteria. One of these criteria, the so called "crown coverage", is the most complex variable and therefore the main focus of this paper is on defining and implementing this criterion in an automatic process to delineate forested areas. Based on Austrian NFI data functions were determined for two different test sites in Austria, describing the criterion crown coverage as a relation between tree height and the distance between trees. Based on the ALS data an automatic method on the basis of adapting -shapes was developed to link these functions to the ALS data. The approach was tested for two different test sites in Austria. For the first test site a tree species independent function was applied. The results of the d...
ABSTRACT In this study, eight airborne laser scanning (ALS)-based single tree detection methods a... more ABSTRACT In this study, eight airborne laser scanning (ALS)-based single tree detection methods are benchmarked and investigated. The methods were applied to a unique dataset originating from different regions of the Alpine Space covering different study areas, forest types, and structures. This is the first benchmark ever performed for different forests within the Alps. The evaluation of the detection results was carried out in a reproducible way by automatically matching them to precise in situ forest inventory data using a restricted nearest neighbor detection approach. Quantitative statistical parameters such as percentages of correctly matched trees and omission and commission errors are presented. The proposed automated matching procedure presented herein shows an overall accuracy of 97%. Method based analysis, investigations per forest type, and an overall benchmark performance are presented. The best matching rate was obtained for single-layered coniferous forests. Dominated trees were challenging for all methods. The overall performance shows a matching rate of 47%, which is comparable to results of other benchmarks performed in the past. The study provides new insight regarding the potential and limits of tree detection with ALS and underlines some key aspects regarding the choice of method when performing single tree detection for the various forest types encountered in alpine regions.
Für die Aufnahme von topographischen Informationen wird verstärkt flugzeuggetragenes Laserscannin... more Für die Aufnahme von topographischen Informationen wird verstärkt flugzeuggetragenes Laserscanning (engl. Airborne Laser Scanning, ALS) eingesetzt. Dabei eignet sich ALS als aktive Fernerkundungsmethode besonders für die Abtastung von bewaldeten Gebieten. Speziell in Forstanwendungen ist die aus ALS Daten abgeleitete Höheninformation der Vegetation eine fundamentale Eingangsgröße, die der Berechnung vieler Forstparameter (Baumhöhen, Stammvolumen, Biomasse) zugrunde liegt. Zusätzlich haben sich ALS Daten als Input für eine, auf Objekthöhen basierte, Waldabgrenzung bereits bewährt. Bis dato werden hauptsächlich Orthophotos für eine manuelle bzw. semi-automatisierte Waldabgrenzung verwendet, wobei schattige Bereiche die Detektierung von Waldrändern und vor allem Waldlücken stark beeinträchtigen. Hier zeigt ALS ein großes Potential und bietet in den meisten Fällen gegenüber einer manuellen Bildinterpretation deutliche Vorteile. Im Rahmen dieser Arbeit wird ein vollautomatischer Ansatz p...
Airborne laser scanning (ALS) data has been established as the standard method for the acquisitio... more Airborne laser scanning (ALS) data has been established as the standard method for the acquisition of high precision topographic data. In addition to the derivation of topographic models, such as digital terrain models (DTM) or digital surface models (DSM), ALS data is the main input data source for a variety of applications, e.g. building modelling, power line modelling or forestry applications. Until now a severe limitation is the availability of tools allowing computations directly on the 3D point cloud for district wide calculations. In complex 3D scenarios such as forests, the point cloud content is commonly converted to raster data (e.g. DTM and DSM) with a notable loss of information. As a result, the information on the vertical structure of vegetation is irretrievably lost. Therefore, a methodology for the delineation of forest areas and subsequent derivation of vertical vegetation strata is proposed. The presented approach combines processing steps directly in the 3D point ...
The objective of this paper is to evaluate a new approach for the automatic delineation of forest... more The objective of this paper is to evaluate a new approach for the automatic delineation of forested areas based on airborne laser scanning (ALS) and national forest inventory (NFI) data. In the Austrian NFI a forest area is mainly defined with four fundamental criteria. One of these criteria, the so called "crown coverage", is the most complex variable and therefore the main focus of this paper is on defining and implementing this criterion in an automatic process to delineate forested areas. Based on Austrian NFI data functions were determined for two different test sites in Austria, describing the criterion crown coverage as a relation between tree height and the distance between trees. Based on the ALS data an automatic method on the basis of adapting -shapes was developed to link these functions to the ALS data. The approach was tested for two different test sites in Austria. For the first test site a tree species independent function was applied. The results of the d...
ABSTRACT In this study, eight airborne laser scanning (ALS)-based single tree detection methods a... more ABSTRACT In this study, eight airborne laser scanning (ALS)-based single tree detection methods are benchmarked and investigated. The methods were applied to a unique dataset originating from different regions of the Alpine Space covering different study areas, forest types, and structures. This is the first benchmark ever performed for different forests within the Alps. The evaluation of the detection results was carried out in a reproducible way by automatically matching them to precise in situ forest inventory data using a restricted nearest neighbor detection approach. Quantitative statistical parameters such as percentages of correctly matched trees and omission and commission errors are presented. The proposed automated matching procedure presented herein shows an overall accuracy of 97%. Method based analysis, investigations per forest type, and an overall benchmark performance are presented. The best matching rate was obtained for single-layered coniferous forests. Dominated trees were challenging for all methods. The overall performance shows a matching rate of 47%, which is comparable to results of other benchmarks performed in the past. The study provides new insight regarding the potential and limits of tree detection with ALS and underlines some key aspects regarding the choice of method when performing single tree detection for the various forest types encountered in alpine regions.
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Papers by Lothar Eysn