Magnus Bremer

A new multi-scale 3D-GIS-approach for the assessment and dissemination of solar income of digital city models

Abstract In order to support an effective planning of solar panel constructions or passive energy measures, information of potential solar income has to consider multiple levels of scale and detail. It has to consider the regional and the detailed household scale. Recent developments in the field of digital city models and 3D GIS allow combining the advantages of both domains. We present a multi-scale 3D GIS approach for the assessment and dissemination of solar income of a digital city model. For the consideration of long and close range shadows, we combine polygonal geometries, 3D-voxel grids and 2.5D Digital Elevation Models of different resolutions in a multi-scale modelling scene. In order to allow a realistic assessment of the heterogeneous 3D shadowing patterns in urban environments, we present a texture mapping approach for homogeneous surface sampling and efficient data storage. The approach integrates the regional topographic context with detailed 3D assessments on a household scale. In order to show the capabilities of the presented approach, a performance test using different scene compilations was conducted. Comparing the performance of different geometrical representations of a city model tile in terms of computational effort and accuracy of the results, the relevance of high spatial resolutions and the consideration of full 3-dimensionality of the presented modelling approach is proven. The results are compatible to current 3D standards such as CityGML and COLLADA facilitating the dissemination of results to non-expert addressees.

Impact of forest fires on geomorphic processes in the Tyrolean Limestone Alps

Sass, O., Haas, F., Schimmer, C., Heel, M., Bremer, M., Stöger, F. and Wetzel, K.‐F. 2012. Impact of forest fires on geomorphic processes in the Tyrolean Limestone Alps. Geografiska Annaler: Series A, Physical Geography, 94, 117–133. doi:10.1111/j.1468‐0459.2012.00452.x ABSTRACT We investigated geomorphic processes on two slopes (Arnspitze and Bettelwurf) burned by wildfire in the region north of Innsbruck. Both burned in 1946 and both are still characterized by severe vegetation destruction. Sparsely grass‐covered rock and debris slopes have developed replacing the former dwarf pine (Pinus mugo) shrub stands. Our aim was to establish disturbed and undisturbed erosion rates and to decide whether recent debris flows can be assigned to these historical wildfires or not. We measured fluvial erosion by means of collectors, estimated the amount of post‐fire erosion from stratigraphic exposures in the adjacent talus, modelled bedload discharge with a statistical model developed in a nearby study area and quantified recent debris flow activity by combining airborne and terrestrial laser scans. We measured erosion rates of 3–30 gm−2a−1, which is roughly ten times higher than the undisturbed sediment yields. Slopewash was higher than linear fluvial transport in the four years of our investigation. Surplus material was removed from the channels by avalanches and debris flows; both being more important for the sediment budget than fluvial action. The modelling approach allowed measured sediment yields to be transferred to larger slope parts and to calculate scenarios of pre‐fire conditions. The concordance of measured and modelled yields was reasonably good; deviations may be explained by differing amounts of precipitation. Our results support the impression that current debris flow activity at the Bettelwurf was enhanced by the aftermath of the 1946 wildfire.

Deriving 3D displacement vectors from multi-temporal airborne laser scanning data for landslide activity analyses

Information on geometries and kinematics of landslides are necessary to establish geological slope deformation models. We present two complementary geospatial methods to analyze landslide surface changes even in areas affected by strong surface pattern changes, making use of airborne laser scanning (ALS) data. An image correlation method based on shaded relief images with a uniformly diffuse lighting and a feature tracking based on terrain breaklines are applied on a data set of eight ALS flight campaigns analyzing an active deep-seated rockslide in the Eastern Alps (Austria). Both tracking methods are described in detail, including parameter assessment. Additionally, an accuracy assessment of the input data sets has been conducted. 3D vector displacement maps derived from image correlation are well suited for the study of landslides if only slight surface pattern changes occur. The smallest detectable displacements strongly depend on the accuracy of the ALS data and for image correlation results lie within the range of 0.24 and 0.75 m for this study. Displacement vectors derived by breakline tracking only allow to detect displacements greater than 2 m. However, in comparison to image correlation, breakline tracking is not limited to areas with slight surface pattern changes and allows us to detect displacements even in areas with strong surface pattern changes. For a comprehensive interpretation of landslide activity a combination of both methods, with consideration of additional supportive data such as elevation change images and orthoimages, is recommended.

Calibration and Validation of a Detailed Architectural Canopy Model Reconstruction for the Simulation of Synthetic Hemispherical Images and Airborne LiDAR Data

Canopy density measures such as the Leaf Area Index (LAI) have become standardized mapping products derived from airborne and terrestrial Light Detection And Ranging (aLiDAR and tLiDAR, respectively) data. A specific application of LiDAR point clouds is their integration into radiative transfer models (RTM) of varying complexity. Using, e.g., ray tracing, this allows flexible simulations of sub-canopy light condition and the simulation of various sensors such as virtual hemispherical images or waveform LiDAR on a virtual forest plot. However, the direct use of LiDAR data in RTMs shows some limitations in the handling of noise, the derivation of surface areas per LiDAR point and the discrimination of solid and porous canopy elements. In order to address these issues, a strategy upgrading tLiDAR and Digital Hemispherical Photographs (DHP) into plausible 3D architectural canopy models is suggested. The presented reconstruction workflow creates an almost unbiased virtual 3D representation of branch and leaf surface distributions, minimizing systematic errors due to the object–sensor relationship. The models are calibrated and validated using DHPs. Using the 3D models for simulations, their capabilities for the description of leaf density distributions and the simulation of aLiDAR and DHP signatures are shown. At an experimental test site, the suitability of the models, in order to systematically simulate and evaluate aLiDAR based LAI predictions under various scan settings is proven. This strategy makes it possible to show the importance of laser point sampling density, but also the diversity of scan angles and their quantitative effect onto error margins.

Digital Terrain Model Resolution and its Influence on Estimating the Extent of Rockfall Areas

As rockfall can cause a great deal of damage, it is essential to know its spatial propagation. Rockfall models are sensitive to the resolution of input data, i.e. the Digital Terrain Model (DTM) used. Nowadays, high resolution elevation data are available area-wide from airborne laser scanning (ALS). However, rockfall models are designed for analysis on a certain scale, which means that high resolution input might not necessarily improve model results (e.g. for regional scale studies). Our aim is to estimate the reach of rockfall by analysing different input resolutions of an ALS DTM. The presented empirically–based model, implemented in Python 2.7, is a modified version of the zenital method including an iterative random walk trajectory model, which is designed for rockfall hazard assessment at the regional scale. Trajectories and rockfall probability maps are generated for selected DTM input resolutions. The comparison shows that high resolution DTMs do consider local topography better and thus lead to more realistic results than low resolution DTMs.

Dense image matching of terrestrial imagery for deriving high-resolution topographic properties of vegetation locations in alpine terrain

Abstract The investigation of changes in spatial patterns of vegetation and identification of potential micro-refugia requires detailed topographic and terrain information. However, mapping alpine topography at very detailed scales is challenging due to limited accessibility of sites. Close-range sensing by photogrammetric dense matching approaches based on terrestrial images captured with hand-held cameras offers a light-weight and low-cost solution to retrieve high-resolution measurements even in steep terrain and at locations, which are difficult to access. We propose a novel approach for rapid capturing of terrestrial images and a highly automated processing chain for retrieving detailed dense point clouds for topographic modelling. For this study, we modelled 249 plot locations. For the analysis of vegetation distribution and location properties, topographic parameters, such as slope, aspect, and potential solar irradiation were derived by applying a multi-scale approach utilizing voxel grids and spherical neighbourhoods. The result is a micro-topography archive of 249 alpine locations that includes topographic parameters at multiple scales ready for biogeomorphological analysis. Compared with regional elevation models at larger scales and traditional 2D gridding approaches to create elevation models, we employ analyses in a fully 3D environment that yield much more detailed insights into interrelations between topographic parameters, such as potential solar irradiation, surface area, aspect and roughness.

Derivation of Three-Dimensional Displacement Vectors from Multi-Temporal Long-Range Terrestrial Laser Scanning at the Reissenschuh Landslide (Tyrol, Austria)

Deep-seated gravitational slope deformations (DSGSDs) endanger settlements and infrastructure in mountain areas all over the world. To prevent disastrous events, their activity needs to be continuously monitored. In this paper, the movement of the Reissenschuh DSGSD in the Schmirn valley (Tyrol, Austria) is quantified based on point clouds acquired with a Riegl VZ®-6000 long-range laser scanner in 2016 and 2017. Geomorphological features (e.g., block edges, terrain ridges, scarps) travelling on top of the landslide are extracted from the acquired point clouds using morphometric attributes based on locally computed eigenvectors and -values. The corresponding representations of the extracted features in the multi-temporal data are exploited to derive 3D displacement vectors based on a workflow exploiting the iterative closest point (ICP) algorithm. The subsequent analysis reveals spatial patterns of landslide movement with mean displacements in the order of 0.62 ma−1, corresponding well with measurements at characteristic points using a differential global navigation satellite system (DGNSS). The results are also compared to those derived from a modified version of the well-known image correlation (IMCORR) method using shaded reliefs of the derived digital terrain models. The applied extended ICP algorithm outperforms the raster-based method particularly in areas with predominantly vertical movement.