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1593334 B882.Pdf UNIVERSITY OF GOTHENBURG Department of Economy and Society, Human Geography & Department of Earth Sciences Geovetarcentrum/Earth Science Centre Detecting small-scale glacial landforms in LiDAR derived digital elevation models A case study of roches moutonnées on the Swedish west coast Gunnar Palm ISSN 1400-3821 B882 Bachelor of Science thesis Göteborg 2015 Mailing address Address Telephone Telefax Geovetarcentrum Geovetarcentrum Geovetarcentrum 031-786 19 56 031-786 19 86 Göteborg University S 405 30 Göteborg Guldhedsgatan 5A S-405 30 Göteborg SWEDEN Abstract The purpose of this study was to develop a method to detect and map what Sugden and John (1976) calls, “the hallmark of glacial erosion”, namely the characteristically asymmetrical rock mounds known as roches moutonnées. The roches moutonnées was to be detected in the new national elevation model provided by the Swedish mapping authority. The national elevation model was produced using an active remote sensing technique called light detection and ranging (LiDAR). LiDAR uses laser light to measure elevation and can produce very accurate digital elevation models (DEM). During the study data from the national elevation model was processed and a high resolution raster DEM was generated, processed and analyzed using geographical information systems (GIS) including ArcGIS and FME Desktop. The location of a number of roches moutonnées were marked using a GPS receiver during a field campaign. The coordinates from the GPS receiver were imported into a GIS environment in order to study the values in and around the perimeters of the surveyed roches moutonnées. The aim of this was to identify the distinctive properties of the landform, which in turn would permit a search for these properties, and thus the landform, in the entire study area. To put the performance of the national elevation model in perspective, the same method was applied to a local elevation model with higher resolution provided by the City of Gothenburg. The GIS method detected 996 roches moutonnées in the national elevation model within an area of two square kilometers on the west coast of Sweden. A comparison of the results from the local elevation model provided by the City of Gothenburg revealed that the method detected the same roches moutonnées in the two different elevation models. The method detected 31% more roches moutonnées in the local elevation model than in the national elevation model. A validation of a sample of the predicted roches moutonnées verified that the method in that case was 97.6% accurate, and that a majority all the roches moutonnées that the method detected in the national elevation model most likely corresponded to actual roches moutonnées found in the study area. Key words Roches Moutonnées Geographical Information Systems Digital Elevation Models Table of Contents 1. Introduction .................................................................................................................................. 1 2. Background .................................................................................................................................. 3 2.1 LiDAR - a brief overview ...................................................................................................... 3 2.2 The National Elevation Model ............................................................................................... 4 2.2.1 The Local Elevation Model ............................................................................................. 5 2.3 Roches Moutonnées ............................................................................................................... 5 3. Study Area .................................................................................................................................... 7 4. Materials and Methods ................................................................................................................. 9 4.1 Data ........................................................................................................................................ 9 4.1.1 LASer (LAS) file format ................................................................................................. 9 4.1.2 Glacial striations .............................................................................................................. 9 4.2 Data processing .................................................................................................................... 10 4.2.1 Preprocessing of LAS files ............................................................................................ 10 4.2.2 Generating a Raster Digital Elevation Model ............................................................... 12 4.3 Survey of Roches Moutonnées ............................................................................................. 13 4.4 Calculation and Analysis of DEM Derivatives .................................................................... 14 4.4.1 Slope .............................................................................................................................. 15 4.4.2 Curvature ....................................................................................................................... 16 4.4.3 Aspect ............................................................................................................................ 17 4.4.4 Contour lines ................................................................................................................. 18 4.5 Classification Predicted Roches Moutonnées ...................................................................... 19 4.5.1 Stoss and Lee Sides ....................................................................................................... 19 4.5.2 Delimitation of Predicted Roches Moutonnées ............................................................. 21 4.6 Validation of Predicted Roches Moutonnées ....................................................................... 21 5. Results ........................................................................................................................................ 23 5.1 Results of the GIS Analysis ................................................................................................. 23 5.1.1 Results from the National Elevation Model .................................................................. 23 5.1.2 Results from the Local Elevation Model ....................................................................... 24 5.1.3 Comparison of the Results ............................................................................................ 26 5.2 Validation of Predicted Roches Moutonnées in the Field .................................................... 28 6. Discussion .................................................................................................................................. 29 6.1 Results Discussion ................................................................................................................ 29 6.1.1 Predicted Roches Moutonnées ...................................................................................... 29 6.1.2 Validation ...................................................................................................................... 30 6.2 Method Discussion ............................................................................................................... 30 6.2.1 Input Data ...................................................................................................................... 30 6.2.2 Classification criteria ..................................................................................................... 30 6.3 Further studies ...................................................................................................................... 31 7. Conclusion .................................................................................................................................. 32 Acknowledgements ........................................................................................................................ 32 References ...................................................................................................................................... 33 1. Introduction In 2009 the Swedish mapping, cadastral and land registration authority (hereafter referred to as the Swedish mapping authority) began work on a new LiDAR derived high resolution digital elevation model (DEM) with national coverage (Lantmäteriet, 2014). A DEM is a digital representation of the land surface, stripped from vegetation and anthropogenic structures. Although the data set was originally intended for landslide and flood management, several other applications have been identified in different research sectors since its arrival (Dowling, Alexanderson, & Möller, 2013). The national elevation model has for example been used to map the distribution and structure of urban vegetation (Lindberg, Johansson & Thorsson, 2013). This project will examine the potential application of the new high resolution DEM for glacial geomorphology, specifically for the detection of small-scale glacial landforms. A number of studies concerning the segmentation and classification of land cover or fluvial geomorphological features using similar LiDAR derived DEMs have been published internationally (Brennan & Webster, 2006; Tarolli, 2014). The Geological Survey of Sweden has used the new DEM to map large scale
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