Vertical accuracy evaluation of digital terrain models created based on line-following digitization of contour maps

Digital terrain models are used in wide variety of domains and applications, of which the most important are: orthorectification of aerial and satellite images, space object modelling, passageways designing, achieving slopes exhibition maps, hydrological modeling, etc. There are several techniques for data acquisition in order to create digital terrain models, such as photogrammetry, radargrammetry, interferometry, airborne laser scanning, surveying and geodetic and cartographic digitization. By using cartographic digitization, digital terrain models are created based on the digitized contour maps on existing maps, which were brought in digital format by scanning process, this method involving low costs and being reach of a large number of users. It must therefore assess the vertical accuracy of digital terrain models created by this method. To achieve results, first were created the digital terrain models based on contour maps and points of known elevations manually digitized on plans at 1: 1000 scale and maps at 1: 25000 scale, using an interpolation grid side of 5m and spline bicubic interpolation method. Then, were determined with precision, by GNSS technology, the coordinates of 18 control points. Based on the grid nodes elevations, using the spline bicubic interpolation method, were calculated the elevations of the 18 control points and then the differences between them and those accurately obtained by GNSS technology. By performing a statistical analysis of these differences, the vertical precision of digital terrain models created from contour maps was determined

Airborne LiDAR for DEM generation: some critical issues

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented

The National Superficial Deposit Thickness Model. (Version 5)

The Superficial Deposits Thickness Model (SDTM) is a raster-based dataset designed to demonstrate the variation in thickness of Quaternary-age superficial deposits across Great Britain. Quaternary deposits (all unconsolidated material deposited in the last 2.6 million years) are of particular importance to environmental scientists and consultants concerned with our landscape, environment and habitats. The BGS has been generating national models of the thickness of Quaternary-age deposits since 2001, and this latest version of the model is based upon DiGMapGB-50 Version 5 geological mapping and borehole records registered with BGS before August 2008

Modelling the spatial distribution of DEM Error

Assessment of a DEM’s quality is usually undertaken by deriving a measure of DEM accuracy – how close the DEM’s elevation values are to the true elevation. Measures such as Root Mean Squared Error and standard deviation of the error are frequently used. These measures summarise elevation errors in a DEM as a single value. A more detailed description of DEM accuracy would allow better understanding of DEM quality and the consequent uncertainty associated with using DEMs in analytical applications. The research presented addresses the limitations of using a single root mean squared error (RMSE) value to represent the uncertainty associated with a DEM by developing a new technique for creating a spatially distributed model of DEM quality – an accuracy surface. The technique is based on the hypothesis that the distribution and scale of elevation error within a DEM are at least partly related to morphometric characteristics of the terrain. The technique involves generating a set of terrain parameters to characterise terrain morphometry and developing regression models to define the relationship between DEM error and morphometric character. The regression models form the basis for creating standard deviation surfaces to represent DEM accuracy. The hypothesis is shown to be true and reliable accuracy surfaces are successfully created. These accuracy surfaces provide more detailed information about DEM accuracy than a single global estimate of RMSE

On daily interpolation of precipitation backed with secondary information

This paper investigates the potential impact of secondary information on rainfall mapping applying Ordinary Kriging. Secondary information tested is a natural area indicator, which is a combination of topographic features and weather conditions. Cross validation shows that secondary information only marginally improves the final mapping, indicating that a one-day accumulation time is possibly too short

Data visualization within urban models

Models of urban environments have many uses for town planning, pre-visualization of new building work and utility service planning. Many of these models are three-dimensional, and increasingly there is a move towards real-time presentation of such large models. In this paper we present an algorithm for generating consistent 3D models from a combination of data sources, including Ordnance Survey ground plans, aerial photography and laser height data. Although there have been several demonstrations of automatic generation of building models from 2D vector map data, in this paper we present a very robust solution that generates models that are suitable for real-time presentation. We then demonstrate a novel pollution visualization that uses these models

Spectral filtering as a method of visualising and removing striped artefacts in digital elevation data

Spectral filtering was compared with traditional mean spatial filters to assess their ability to identify and remove striped artefacts in digital elevation data. The techniques were applied to two datasets: a 100 m contour derived digital elevation model (DEM) of southern Norway and a 2 m LiDAR DSM of the Lake District, UK. Both datasets contained diagonal data artefacts that were found to propagate into subsequent terrain analysis. Spectral filtering used fast Fourier transformation (FFT) frequency data to identify these data artefacts in both datasets. These were removed from the data by applying a cut filter, prior to the inverse transform. Spectral filtering showed considerable advantages over mean spatial filters, when both the absolute and spatial distribution of elevation changes made were examined. Elevation changes from the spectral filtering were restricted to frequencies removed by the cut filter, were small in magnitude and consequently avoided any global smoothing. Spectral filtering was found to avoid the smoothing of kernel based data editing, and provided a more informative measure of data artefacts present in the FFT frequency domain. Artefacts were found to be heterogeneous through the surfaces, a result of their strong correlations with spatially autocorrelated variables: landcover and landsurface geometry. Spectral filtering performed better on the 100 m DEM, where signal and artefact were clearly distinguishable in the frequency data. Spectrally filtered digital elevation datasets were found to provide a superior and more precise representation of the landsurface and be a more appropriate dataset for any subsequent geomorphological applications

Comparative analysis of the differences between using LiDAR and contour-based DEMs for hydrological modeling of runoff generating debris flows in the Dolomites

Present work aims to explore the differences in hydrological modeling when using digital elevation models (DEMs) generated by points from LiDAR surveys and those digitized on the contour lines of the regional technical map (RTM) and their relevance for the simulation of debris flow triggering. Hydrological models for mountainous areas are usually based on digital elevation models (DEMs). DEMs are used to determine the flow path from each pixel, by which the basin is discretized, to the outlet. Hydrological simulations of runoff that triggered debris flows occurred in two rocky headwater basins of Dolomites, Fiames Dimai (area approximately 0.03 km2) and Cancia (area approximately 0.7 km2) are carried out using a DEM-based model designed for simulating runoff that descends from headwater areas. For each basin, the runoff is simulated using DEMs that are generated using points from LiDAR, and those digitized on the contour lines of the regional technical map, respectively. The results show that the peak discharge values corresponding to the simulations carried out using the LiDAR-based DEMs are higher than those corresponding to the simulations carried out using the RTM-based DEMs. Larger differences are observed for the Dimai basin, where the area corresponding to the RTM-based DEM is markedly smaller than the area corresponding to LiDAR-based DEM, whereas for the Cancia basin, the two areas are similar. Both the differences in the peak discharge and the basin area are due to the poor accuracy of the contour-based DEM (i.e., elevation accuracy), that is, a poor representation of the morphological features that leads to errors on the watershed divide and simplifications of the flow paths from each cell to the outlet. This result is highly relevant for estimating the triggering conditions of runoff generated debris flows. An incorrect simulated value of peak discharge can lead to errors both in planning countermeasures against debris flows and in predicting their occurrence