Evaluation and Assessment of the Impacts of the Spatial Resolution on the Accuracy of the Digital Elevation Model (original) (raw)

Creation and Evaluation of Digital Elevation Models from Ground Surveying Measurements

Creation of a Digital Elevation Model (DEM) from point support files requires exploitation of an interpolation approach in order to get a continuous surface forming a DEM. The Inverse Distance Weighting (IDW) and the thin plate spline methods are two local interpolation methods that are very often exploited in the creation of DEMs. Different interpolation techniques have to be expected to provide different quality DEMs. This research has been focused towards evaluation of the quality of the DEMs generated from ground surveying measurements using IDW and thin plate spline. A test site in a hilly corrugated terrain area has been established and digital elevation measurements have been collected from field using conventional ground surveying methods where a total station instrument has been used for measuring the three dimensional coordinates (x, y, z) of the selected spot points. DEMs have been created from the field data using commercial spatial analysis systems; in addition qualitat...

An Assessment of Digital Elevation Models (DEMs) From Different Spatial Data Sources

Digital Elevation Model (DEM) represents a very important geospatial data type in the analysis and modelling of different hydrological and ecological phenomenon which are required in preserving our immediate environment. DEMs are typically used to represent terrain relief. DEMs are particularly relevant for many applications such as lake and water volumes estimation, soil erosion volumes calculations, flood estimate, quantification of earth materials to be moved for channels, roads, dams, embankment etc.

The accuracy of grid digital elevation models linearly constructed from scattered sample data

International Journal of …, 2006

In this paper, a theoretical-empirical model is developed for modelling the accuracy of a grid digital elevation model (DEM) linearly constructed from scattered sample data. The theoretical component integrates sample data accuracy in the model by means of the error-propagation theory. The empirical component seeks to model what is known as information loss, i.e. the sum of the error due purely to sampling the continuous terrain surface with a finite grid interval and the interpolation error. For this purpose, randomly spaced data points, supposed to be free of error, were converted into regularly gridded data points using triangulation with linear interpolation. Original sample data were collected with a 262 m sampling interval from eight different morphologies, from flat terrain to highly rugged terrain, applying digital photogrammetric methods to large-scale aerial stereo imagery (1 : 5000). The DEM root mean square error was calculated by the true validation method over several sets of check points, obtaining the different sampling densities tested in this work. Several empirical models are calibrated and validated with the experimental data set by modelling the DEM accuracy by combining two variables such as sampling density and a descriptive attribute of terrain morphology. These empirical models presented a morphology based on the product of two potential functions, one related to the terrain roughness and another related to the sampling density. The terrain descriptors tested were average terrain slope, standard deviation of terrain slope, standard deviation of unitary vectors perpendicular to the topographic surface (SDUV), standard deviation of the difference in height between adjacent samples in the grid DEM (SDHD), and roughness estimation by first-, second-, or third-degree surface fitting error. The values obtained for those terrain descriptors were reasonably independent from the number and spatial distribution of the sample data. The models based on descriptors SDHD, SDUV, and standard deviation of slope provided a good fitting to the data observed (R 2 .0.94) in the calibration phase, model SDHD being the one that yielded the best results in validation. Therefore, it would be possible to establish a priori the optimum grid size required to generate or store a DEM of a particular accuracy, with the saving in computing time and file size that this would mean for the digital flow of the mapping information in GIS.

Review and critical analysis on digital elevation models

Geofizika

Nowadays, digital elevation model (DEM) acts as an inevitable component in the field of remote sensing and GIS. DEM reflects the physical surface of the earth helps to understand the nature of terrain by means of interpreting the landscape using modern techniques and high-resolution satellite images. To understand and analyze the nature of the terrain, DEM is required in many fields in the improvement of developing the product and decision making, mapping purpose, preparing 3D simulations, estimating river channel and creating contour maps to extract the elevation and so on. DEM in various applications will be useful to replicate the overall importance of the availability of worldwide, consistent, high-quality digital elevation models. The present article represents the overall review of DEMs, its generation, development using various techniques derived from topographic maps and high-resolution satellite images over a decade to present. It is useful to understand the nature of topography, address the practical problems and fix them by applying innovative ideas, upcoming high-resolution satellite images and techniques.

Evaluation of vertical accuracy of open source Digital Elevation Model (DEM)

International Journal of …

Digital Elevation Model (DEM) is a quantitative representation of terrain and is important for Earth science and hydrological applications. DEM can be generated using photogrammetry, interferometry, ground and laser surveying and other techniques. Some of the DEMs such as ASTER, SRTM, and GTOPO 30 are freely available open source products. Each DEM contains intrinsic errors due to primary data acquisition technology and processing methodology in relation with a particular terrain and land cover type. The accuracy of these datasets is often unknown and is non-uniform within each dataset. In this study we evaluate open source DEMs (ASTER and SRTM) and their derived attributes using high postings Cartosat DEM and Survey of India (SOI) height information. It was found that representation of terrain characteristics is affected in the coarse postings DEM. The overall vertical accuracy shows RMS error of 12.62 m and 17.76 m for ASTER and SRTM DEM respectively, when compared with Cartosat DEM. The slope and drainage network delineation are also violated. The terrain morphology strongly influences the DEM accuracy. These results can be highly useful for researchers using such products in various modeling exercises.

A comparision of interpolation methods for producing digital elevation models at the field scale

Earth Surface Processes and Landforms, 2009

Digital elevation models have been used in many applications since they came into use in the late 1950s. It is an essential tool for applications that are concerned with the Earth's surface such as hydrology, geology, cartography, geomorphology, engineering applications, landscape architecture and so on. However, there are some differences in assessing the accuracy of digital elevation models for specific applications. Different applications require different levels of accuracy from digital elevation models. In this study, the magnitudes and spatial patterning of elevation errors were therefore examined, using different interpolation methods. Measurements were performed with theodolite and levelling. Previous research has demonstrated the effects of interpolation methods and the nature of errors in digital elevation models obtained with indirect survey methods for small-scale areas. The purpose of this study was therefore to investigate the size and spatial patterning of errors in digital elevation models obtained with direct survey methods for large-scale areas, comparing Inverse Distance Weighting, Radial Basis Functions and Kriging interpolation methods to generate digital elevation models. The study is important because it shows how the accuracy of the digital elevation model is related to data density and the interpolation algorithm used. Cross validation, split-sample and jack-knifing validation methods were used to evaluate the errors. Global and local spatial auto-correlation indices were then used to examine the error clustering. Finally, slope and curvature parameters of the area were modelled depending on the error residuals using ordinary least regression analyses. In this case, the best results were obtained using the thin plate spline algorithm.

Generation and Accuracy Assessment of Digital Elevation Models in Mountain Area

2015

Nowadays DEMs are indispensable tools in studies and analysis regarding Earth’s surface. Generating DEMs closely to the true surfaces and with high accuracy represent a main issue. The aim of the study is to improve the geomorphometric analysis based on DEMs. In this study a statistical approach was used to assess various DEMs generated with different methods to compare their accuracy. DEMs were created on the base of a topographic map using classical interpolation methods (Spline, IDW, Kriging, Simple linear interpolation) and simulated surfaces. The results suggest that data source is more important in error propagation, followed by interpolation methods.

Evaluation of the Accuracy of Digital Elevation Model Produced from Different Open Source Data

Journal of Engineering, 2019

This study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS. Furthermore, the Geographic Information System (GIS) was utilized to analyze, imagine and interpolate data in this study. The result of the statistical analysis revealed that RMSE of DEM related to the differences between the reference points and Google Earth, SRTM DEM and ASTER GDEM are 6.9, 5.5 and 4.8, respectively. What is more, a finding of this study shows convergence the level of accuracy for all open sources used in this study.

Accuracy assessment of digital elevation models using a non-parametric approach

This paper explores three theoretical approaches for estimating the degree of correctness to which the accuracy figures of a gridded Digital Elevation Model (DEM) have been estimated depending on the number of checkpoints involved in the assessment process. The widely used average-error statistic Mean Square Error (MSE) was selected for measuring the DEM accuracy. The work was focused on DEM uncertainty assessment using approximate confidence intervals. Those confidence intervals were constructed both from classical methods which assume a normal distribution of the error and from a new method based on a non-parametric approach. The first two approaches studied, called Chi-squared and Asymptotic Student t, consider a normal distribution of the residuals. That is especially true in the first case. The second case, due to the asymptotic properties of the t distribution, can perform reasonably well with even slightly non-normal residuals if the sample size is large enough. The third approach developed in this article is a new method based on the theory of estimating functions which could be considered much more general than the previous two cases. It is based on a non-parametric approach where no particular distribution is assumed. Thus, we can avoid the strong assumption of distribution normality accepted in previous work and in the majority of current standards of positional accuracy. The three approaches were tested using Monte Carlo simulation for several populations of residuals generated from originally sampled data. Those original grid DEMs, considered as ground data, were collected by means of digital photogrammetric methods from seven areas displaying differing morphology employing a 2 by 2 m sampling interval. The original grid DEMs were subsampled to generate new lower-resolution DEMs. Each of these new DEMs was then interpolated to retrieve its original resolution using two different procedures. Height differences between original and interpolated grid DEMs were calculated to obtain residual populations. One interpolation procedure resulted in slightly non-normal residual populations, whereas the other produced very non-normal residuals with frequent outliers. Monte Carlo simulations allow us to report that the estimating function approach was the most robust and general of those tested. In fact, the other two approaches, especially the Chi-squared method, were clearly affected by the degree of normality of the residual population distribution, producing less reliable results than the estimating functions approach. This last method shows good results when applied to the different datasets, even in the case of more leptokurtic populations. In the worst cases, no more than 64-128 checkpoints were required to construct an estimate of the global error of the DEM with 95% confidence. The approach therefore is an important step towards saving time and money in the evaluation of DEM accuracy using a single average-error statistic. Nevertheless, we must take into account that MSE is essentially a single global measure of deviations, and thus incapable of characterizing the spatial variations of errors over the interpolated surface.

ACCURACY ASSESSMENT OF DIGITAL ELEVATION MODELS OBTAINED FROM DIFFERENT DATA AND METHODS

ACCURACY ASSESSMENT OF DIGITAL ELEVATION MODELS OBTAINED FROM DIFFERENT DATA AND METHODS, 2017

Digital elevation model (DEM) is primarily a way of visualising 2D maps, photographs and images in 3D. Common uses of DEMs are creation of relief maps, rendering of 3D visualizations, rectification of satellites images and aerial photographs, creation of different physical models, etc. DEMs can be produced by different methods. In this study, DEMs are produced by 1:25000 digital topographic maps, Light Detection and Ranging (LIDAR) data, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Shuttle Radar Topographic Mission (SRTM) data, and the accuracy of these models are analysed.