Techn. University, Diss., 2006--Darmstadt.

Techn. Universiẗat, Diss., 2006--Darmstadt.

Zugl.: Kassel, University, Diss., 2005. / Download lizenzpflichtig.

Zugl.: Innsbruck, University, Diss., 2008.

Universiẗat, Diss., 2000--Kassel. / Lizenzpflichtig.

Mountainous regions are ubiquitously dissected by river networks. These networks are the main drivers by which climate and tectonic signals are transmitted to the rest of the landscape, and control the response timescale of the landscape to these external forcings. Furthermore, river systems set the downslope boundary conditions for hillslope sediment transport, which controls landscape denudation. Therefore, understanding the controls on the organisation and structure of river networks in upland landscapes is an important goal in Earth surface processes research. The recent introduction of high-resolution topographic data, such as airborne lidar data, has revolutionised our ability to extract information from the topography, providing new opportunities for linking geomorphic process with landscape form. This thesis is focused on developing techniques for analysing high-resolution topographic data to quantify and understand controls on the structure of fiuvial systems in upland landscapes. Firstly, I develop and test new algorithms for objective feature extraction from lidar-derived digital elevation models (DEMs). I present a new method for identifying the upstream extent of channel processes by identifying scaling breaks in river long profiles. I then compare this new method to three existing methods of channel extraction, using field-mapped channel heads from four field sites in the US. I find that the new method presented here, along with another method of identifying channels based on valley geometry, most accurately reproduces the measured channel heads in all four field sites. I then present a new method for identifying floodplains and fiuvial terraces from DEMs based on two thresholds: local gradient, and elevation compared to the nearest channel. These thresholds are calculated statistically from the DEM using quantile-quantile plots and do not need to be set manually for each landscape in question. I test this new method against field-mapped floodplain initiation points, published flood hazard maps, and digitised terrace surfaces from eight field sites in both the US and the UK. This method provides a new tool for rapidly and objectively identifying floodplain and terrace features on a landscape scale, with applications including flood risk mapping, landscape evolution modelling, and quantification of sediment storage and routing. Finally, I apply these new algorithms to examine the density of channel networks across a range of mountainous landscapes, and explore implications for fluvial incision models. I compare the relationship between drainage density (Dd) and erosion rate (E) using both analytical solutions and numerical modelling, and find that varying the channel slope exponent (n) in detachment-limited fluvial incision models controls the relationship between Dd and E. Following on from this, I quantify Dd for five field sites throughout the US. For two of these field sites I compare Dd to cosmogenic radionuclide (CRN)-derived erosion rates, and for each site I use mean hilltop curvature as a proxy for erosion rate where CRN-derived erosion rates are not available. I find that there is a significant positive relationship between Dd, E, and hilltop curvature across four out of the five field sites. In contrast to assumptions made in many studies of fluvial incision, this positive relationship suggests that the channel slope exponent n is greater than unity for each of these landscapes, with fundamental implications for both landscape evolution and sediment transport.

This diploma thesis is focused on examination of effect topography on yield on the field. Theoretical research is given in literary overview and it is focused on sources of elevation data in conditions of the Czech Republic. Further there is given description of topographic attributes, which have influence on crop on the agricultural field. Practical part of this thesis processed data about agricultural field in Vendolí near Svitavy in East Bohemia. One of aims of this thesis was to compare two sets of elevation data. First set of elevation data was provided by Czech office for surveying, mapping and cadastre, data came from airborne laser scanning. Second set of elevation data was measured by DGPS receiver placed on combine harvester during the harvest. Topographic attributes were derived from these two sets of elevation data with help of tools in software ArcGIS 10.2. In the further process topographic attributes were compared with yield of winter wheat from 2014 to assess relationship between topography and yield. In given data there was found dependence of yield on digital elevation model (higher amount of yield was found in higher elevations). Significant relationship between yield and other topographic attributes has not been proved.

The problem of constructing high quality point clouds based on measurements from a moving and rotating single-photon counting lidar is considered in this report. The movement is along a straight rail while the lidar sensor rotates side to side. The point clouds are constructed in three steps, which are all studied in this master’s thesis. First, point clouds are constructed from raw lidar measurements from single sweeps with the lidar. In the second step, the sensor transformation between the point clouds constructed in the first step are obtained in a registration step using iterative closest point (ICP). In the third step the point clouds are combined to a coherent point cloud, using the full measurement. A method using simultaneous localization and mapping (SLAM) is developed for the third step. It is then compared to two other methods, constructing the final point cloud only using the registration, and to utilize odometric information in the combination step. It is also investigated which voxel discretization that should be used when extracting the point clouds. The methods developed are evaluated using experimental data from a prototype photon counting lidar system. The results show that the voxel discretization need to be at least as large as the range quantization in the lidar. No significant difference between using registration and SLAM in the third step is observed, but both methods outperform the odometric method.

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There are considerable expenditures by government and private forest industry to enhance the growth of forests and reduce time required for crop rotation. The effectiveness of some of these treatments is dependent on site productivity. In addition, as responsible stewards of the forest resource and habitat, it is important that the state of forests are actively monitored, especially in the face of a changing climate and increased rates of disturbance. This dissertation reports on the development of a method for estimating and mapping forest productivity. The Shawnigan Lake thinning and fertilization forest installation, established in 1971 by CFS, was selected as the study site largely for its rich mensuration history. Square treatment plots were 0.04ha in area and included two thinning levels (1/3 & 2/3 of the basal area), two fertilization treatments (224kg & 448kg N/ha) with repeated fertilizations and macronutrient experiments (S, P) and control plots. A sample of plots was selected for high precision ground based lidar reference surveys. In September of 2012 a multi-sensor airborne survey of SLP was conducted that collected high-density lidar (up to ~70pnts/m2) and VNIR imaging spectroscopy. A thorough empirical radiometric calibration was conducted in addition to a spatial calibration at the Victoria International Airport. A combination of area based height percentile, point density ratios and statistical moments with individual lidar tree metrics including height distribution and proximity metrics were generated. Topographic metrics were also generated from the lidar ground classified point cloud. A library of spectral indices was computed from the imaging spectrometer data, with an emphasis on those indices known to be associated with vegetation health. These metrics were summarized to the plot level for a coarse scale regression analysis. A control survey and ground based lidar was used to facilitate an individual tree based fine scale of analysis, where reference data could unambiguously be matched to airborne collected data through the projected positions. Regression analysis was conducted applying the best subset regression with exhaustive feature selection search criteria and included a critical evaluation of the resulting selected features. Models were investigated considering the data source and in combination, that is, lidar metrics were considered independent of spectroscopy as well as the converse, and lidar metrics in combination with spectral metrics. The contribution of this study is the revelation that existing area based point cloud metrics are highly correlated, potentially noisy and sensitive to variations in point density, resulting in unstable feature selection and coefficients in model building. The approach offered as an alternative is the gridded lidar treetops method, which is evidently lacking within the literature and which this study overwhelmingly advocates. Additionally, the breadth and diversity of metrics assessed, the size and quality of the reference data applied, and the fine spatial scale of analysis are unique within the research area. This study also contributes to the knowledge base, in that, productivity can be estimated by remote sensing technologies. The use of gridded generalizations of the individual tree approach reduced estimation errors for both structural and productivity attributes. At the plot-level, crown structure and crown health features best estimated productivity. This study emphasizes the dangers of empirical modeling; at the even-aged SLP installation, growth is strongly tied to structure and the extrapolation to other sites is expected to provide biased values. It is my perspective that physical lidar structural models of the dominant and co-dominant crown classes be used to augment spatially explicit tree and stand growth models. In addition, direct measures should be obtained by multi-temporal lidar surveys or as an alternative photogrammetric point clouds after an initial lidar survey to quantify growth and aid in calibrating growth models. / Graduate