Author Archives: Martin Rutzinger

Earth Observation, Moisture Mapping & Forest Applications

End of March the 4D-FORMAT team conducted an expert workshop for discussing current research results and applications in the field Earth Observation – Moisture Mapping – Forest Applications. It was a very successful event demonstrating the benefits and further needs of research in this area. Presentations of this day can be downloaded by scrolling to the lower section of the dissemination page of 4D-FORMAT. A big thank you to the colleagues of BFW for hosting the workshop.

Stand scale reconstruction of architectural tree models from unmanned aerial vehicle laser scanning (ULS) data

New results on 3D tree modelling from Unmanned Aerial Vehicle Laser Scanning have been presented at this years EGU in Vienna.

Bremer, M., Rutzinger, M., Kollert, A. (2019. Stand scale reconstruction of architectural tree models from unmanned aerial vehicle laser scanning (ULS) data. Geophysical Research Abstracts, 21(EGU2019-10292).

 

Automated Area-Wide Tree Species Mapping Based on Sentinel-2 Imagery

4D-FORMAT will present first results in the session EO for Biodiversity at the ESA Living Planet Symposium (Milan, Italy). Come, visit and discuss with us…

Kollert, A., Rutzinger, M., Bremer, M, Hollaus, M., Pfeifer, N., Bruggisser, M., Bauer-Marschallinger, B., Hagen, K., Schadauer, K., Gartner, K., Bauerhansl, C., Löw, M., (2019). Automated Area-Wide Tree Species Mapping Based on Sentinel-2 Imagery: Influence of Topography and Forest Structure on Classification Quality. ESA Living Planet Symposium. Milan, Italy.

 

Abgrenzung homogener Waldstücke in ALS-Punktwolken

New publication about segmentation of forest patches online.

Wir stellen ein flexibles Rahmenwerk vor, mit dem sich homogene Wald-flächen in ALS-Punktwolken abgrenzen lassen. Für die Segmentierung werden vorab Wald-strukturmetriken aus der Punktwolke berechnet. Kernstück der Segmentierung ist ein iterati-ver k-means Clustering-Schritt im Merkmalsraum. Beginnend mit der gesamten Punktwolke als initiales Cluster, werden die Punkte solange in zwei Sub-Cluster aufgespaltet, bis jedes Sub-Cluster eine gewünschte Homogenität aufweist. Wir demonstrieren die Funktionsweise der entwickelten Methode für zwei Testgebiete für die Segmentierung von Waldstücken mit homogenen Eigenschaften in Bezug auf den Wasserkreislauf. Die Segmentierungen zeigen Konsistenzen von R2=0.65-0.91 in den relevanten Waldstrukturmetriken.

Bruggisser, M., Hollaus, M., Wang, D., & Pfeifer, N. (2019). Abgrenzung homogener Waldstücke in ALS-Punktwolken. Dreiländertagung der DGPF, der OVG und der SGPF. Vienna, Austria, 28, 498-509.

Adaptive Framework for the Delineation of Homogeneous Forest Areas Based on LiDAR Points

New publication about forest area segmentation online.

We propose a flexible framework for automated forest patch delineations that exploits a set of canopy structure features computed from airborne laser scanning (ALS) point clouds. The approach is based on an iterative subdivision of the point cloud using k-means clustering followed by an iterative merging step to tackle oversegmentation. The framework can be adapted for different applications by selecting relevant input features that best measure the intended homogeneity. In our study, the performance of the segmentation framework was tested for the delineation of forest patches with a homogeneous canopy height structure on the one hand and with similar water cycle conditions on the other. For the latter delineation, canopy components that impact interception and evapotranspiration were used, and the delineation was mainly driven by leaf area, tree functional type, and foliage density. The framework was further tested on two scenes covering a variety of forest conditions and topographies. We demonstrate that the delineated patches capture well the spatial distributions of relevant canopy features that are used for defining the homogeneity. The consistencies range from R2=0.84 to R2=0.86 and from R2=0.80 to R2=0.91 for the most relevant features in the delineation of patches with similar height structure and water cycle conditions, respectively.

Bruggisser, M., Hollaus, M., Wang, D., & Pfeifer, N. (2019). Adaptive Framework for the Delineation of Homogeneous Forest Areas Based on LiDAR Points. Remote Sensing, 11(2), 189

Singel Tree Detection and Modelling Tree Architecture

Processing of the LiDAR-UAV point clouds for tree parametrisation continued. After single tree detection followed by stem extraction the 3D tree architecture models are derivable for area-wide data sets. This will be the basis for further analysis of forest moisture conditions on detailed scale.

 

 

 

 

Bremer, M., Wichmann, V. & Rutzinger, M. (2018): Multi-temporal fine-scale modelling of Larix decidua forest plots using terrestrial LiDAR and hemispherical photographs. Remote Sensing of Environment. Vol. 206, pp. 189–204.

First results from LiDAR UAV acquisition available

In spring 2018 the first LiDAR UAV acquisition has been conducted with the Riegl RiCOPTER VUX-1LR. Thirteen strips were flown for a 4D-FORMAT test plot in Fürstenfeld (Austria) resulting in point densities ranging from 8.000 to 20.000 pts/m² including multi echoes. Figures below show flight preparation, conduction, intensity coloured and RGB coloured point cloud respectively.

 

  

  

Ongoing Ground Truth Measurments

During the snow free period the 4D-FORMAT team conducts ground truth measurements of soil moisture, which are collected simultaneously during Sentinel-1 overflights. The test areas for probing comprise selected forest types and open agricultural land for calibration.

The Alps from Space Workshop

The 4D-FORMAT team presents initial results about automated tree species mapping at the Earth Observation for Alps (eo4alps) workshop held from 27-29th of June 2018 in Innsbruck Austria and organised by ESA. The abstract is available here.

 

Kollert, A., Rutzinger, M., Bremer, M., Hollaus, M., Pfeifer, N., Bruggisser, M., Bauer-Marschallinger, B., Hagen, K., Schadauer, K., Gartner, K. & Bauerhansl, C. (2018): Mapping Tree Species in Complex Terrain Based on Sentinel-2 Time Series. In: eo4alps. Innsbruck, Austria.

 

 

 

Kick-off Meeting

The 4D-FORMAT consortium consisting of the Austrian Academy of Sciences, the Austrian Research Centre for Forests, and the TU Wien met in July for the project kick-off meeting in Vienna presenting the planned tasks and first work in progress. In the afternoon the 4D-FORMAT consortium visited selected test sites in the Vienna Woods, their instrumentation, and discussed the potential in-situ data sampling strategies.