Niels Anders

Introducing...

I work as a PhD student in the Computational Geo-Ecology research group of the Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, under supervision of prof. dr. ir. W. Bouten (promotor) and dr. A.C. Seijmonsbergen (co-promotor). My research includes digital terrain analysis to indentify, classify and dynamically simulate the current state and future development of landscape evolution. My project is divided into two main parts: 1) semi-auomated mapping of geomorphological features, and 2) the dynamic simulation of landscape evolution. In both parts the analysis of high-res LiDAR data, and therefore dealing with enormous data sets, is crucial for more efficient research of geo-ecosystems.


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Click here to find out more about Computational Geo-Ecology

All computational logistics are supported by the IBED GIS-Studio (http://www.gis-studio.nl)

See also nielsanders.nl

Segmentation optimization and stratified object-based analysis for semi-automated geomorphological mapping

Semi-automated geomorphological mapping techniques are gradually replacing classical techniques due to increasing availability of high-quality digital topographic data. In order to efficientlyanalyze such large amounts of data, there is a need for optimizing the processing of automated mapping techniques. In this context, we developed a novel approach to semi-automatically map alpine geomorphology using stratified object-based image analysis. We used a 1 m Digital Terrain Model (DTM) derived from laser altimetry data from a mountainous catchment from which we calculated various Land-Surface Parameters (LSPs). The LSPs ‘slope angle’ and ‘topographic openness’ have been combined into a single composite layer for selecting reference material and delineating training samples. We developed a novel method to semi-automatically assess segmentation results by comparing 2D frequency distribution matrices of training samples and image objects. The segmentation accuracy assessment allowed us to automate optimization of the scale parameter and LSPs used for segmentation. We concluded that different geomorphological feature types have different sets of optimal segmentation parameters. The feature-dependent parameters were used in a new approach of stratified feature extraction for classifying karst, glacial, fluvial and denudational landforms. In this way, we have used stratified object-based image analysis to semi-automatically extract contrasting geomorphological features from high-resolution digital terrain data. A further step would be to also automate the optimization of classification rules. We would then be able to create a library of feature characteristics that could be transferred and applied to other mountain regions and further automate geomorphological mapping strategies.

The lower left figure is an example of the field work area near Lech - Austria. The lower right figure represents a LiDAR-derived openness map. Topographic openness can be described as the enclosure of a location in the landscape, and is calculated as mean the angle of a point to its horizon in the eight wind directions (black is enclosed, white is open). Suchmaps are especially useful to identify geomorphological feature boundaries.

Link to full research paper

Modelling channel incision and alpine hillslope development using laser altimetry data

We have developed a new approach to simulate drainage basin evolution which demonstrates that high resolution elevation data can be used as useful tool for a dynamic simulation of Alpine landscape development, in which channel incision is incorporated in high spatial detail. A vector channel incision model (CIM) uses 1 m high-resolution laser altimetry data for simulation of longitudinal profile development. The CIM is combined with a grid cell-based hillslope erosion model to incorporate the hillslope response to incising bedrock rivers in a simulation of landscape evolution. The combined simulation model is applied to a geologically diverse Alpine catchment to simulate landscape development from reconstructed late glacial conditions towards the current situation. The model is time-efficient and realistically adapts to contrasting geological substrata, while spatially and temporally variable incision values, knick-point recession and variable hillslope development result in a realistic simulation of post-glacial landscape evolution. High resolution elevation data, in combination with dynamic geomorphological simulation models, facilitate research of complex and difficult-to-access Alpine terrain at greater detailthan before. It potentially paves the way for more efficient landscape evolution research and can contribute to increasing the understanding of the functioning of geo-ecological systems.

The lower left figure is an example of the study area of Gamperdona Valley, near Nenzing - Austria. Glacially shaped valleys upstream are followed by deeply incised river gorges. The lower center figure illustrates the detailed river path - derived from the LiDAR-based 1m DTM - that is overlain on top of a coarse (50m) DEM. The blue grid cells represent the cells over which the river is flowing and are directly subject to river incision; the remaining cells are subject to hillslope processes indirectly affected by the lowering of channel grid cells. The lower right figure is an example of the drainage basin evolution model in action. 

Link to full research paper

Publications

Journal papers         
 
Anders NS, Seijmonsbergen AC, Bouten W., 2011. Segmentation optimization and stratified object-based analysis for semi-automated geomorphological mapping. Remote Sensing of Environment 115, 2976-2985, http://dx.doi.org/10.1016/j.rse.2011.05.007
 
Anders NS, Seijmonsbergen AC, Bouten W., 2009. Modelling channel incision and alpine hillslope development using laser altimetry data. Geomorphology 113, 35-46, http://dx.doi.org/10.1016/j.geomorph.2009.03.022

Book chapters        
 
Seijmonsbergen AC, Hengl T, Anders NS, 2011. Semi-automated identification and extraction of geomorphological features using digital elevation data. Smith, M.J.,Paron, P. and Griffiths, J. (Eds). Geomorphological Mapping: a professional handbook of techniques and applications, Developments in Earth Surface Processes, Elsevier, 297-335, http://dx.doi.org/10.1016/B978-0-444-53446-0.00010-0
 
Conference proceedings/abstracts 
 
Anders NS, Smith MJ, Seijmonsbergen AC, Bouten W. Optimizing object-based image analysis for semi-automated geomorphological mapping. In Geomorphometry 2011, edited by T Hengl, IS Evans, JP Wilson and M Gould, 117-120, Redlands, CA.  http://www.geomorphometry.org/Anders2011

Anders NS, Seijmonsbergen AC, Bouten W, 2010. Stratified object-based image analysis of high-res laser altimetry data for semi-automatic geomorphological mapping inan alpine area. Geophysical Research Abstracts, Vol. 12,EGU2010-9959-1, 2010   

Anders NS, Seijmonsbergen AC, Bouten W, 2009. Multi-Scale and Object-Oriented Image Analysis of High-Res LiDAR Data for Geomorphological Mapping in Alpine Mountains. Proceedings of Geomorphometry 2009

Anders NS, Seijmonsbergen AC, Bouten W, 2009. Modelling channel incision and drainage basin evolution with a multi-scale simulation model. Geophysical Research Abstracts, Vol. 11, EGU2009-9303, 2009         
 
Other      
 
Anders NS,Seijmonsbergen AC, 2008. Laser altimetry and terrain analysis- A revolution in Geomorphology. GIM-International (coverstory), Vol. 22 (11): 36-39 

Acknowledgements

This research is financially supported by the  Research Foundation for Alpine and Subalpine Environments (RFASE). In addition, it was carried out in the context of the Virtual Lab for e-Science (vl-e) project, which is supported by a BSIK grant from the  Dutch Ministry of Education, Culture and Science (OC & W) and is part of the ICT innovation program of the  Ministry of Economic Affairs (EZ). The ‘Land Vorarlberg’ has kindly allowed us to use the 1 m LiDAR DTM. We also thank ‘inatura, Naturerlebnis Dornbirn’ for their support.