High-quality Digital Elevation Models Research Articles

Assessment of Glacier Volume Change Using ASTER-Based Surface Matching of Historical Photography

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Glaciated regions are known to be particularly sensitive to climate change. Historical archives of glacier volume change are important, as they provide context for present-day changes. Although photogrammetric archives exist for many regions, their usefulness is often limited by a lack of contemporary ground control. High quality digital elevation models (DEMs) underpin a range of change analysis activities. This paper presents a cost-effective solution which utilizes Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEMs as control for the scaling and orientation of archival data sets. Instead of relying upon ground-control points, a robust surface matching algorithm is employed to automatically determine the transformation required to register two overlapping DEMs. Through application to the Slakbreen glacier system in Svalbard, Norway, the strategy is assessed by first matching an ASTER DEM to a fixed lidar reference surface. This demonstrates that ASTER DEMs are effectively correct in scale, supporting their use as a control surface. The second stage of the research implements this by matching an aerial photogrammetric DEM to an ASTER reference surface. Resultant volumetric and annual elevation change rates are compared to those derived from lidar data, which are considered in this paper as a truth data set. ASTER-based matching produced a mean annual elevation change rate of <formula formulatype="inline"><tex Notation="TeX">$-4.12\ \hbox{ma}^{-1}$ </tex></formula>, compared to a value of <formula formulatype="inline"><tex Notation="TeX">$-4.11\ \hbox{ma}^{-1}$</tex></formula> derived from the lidar data. In volumetric terms, this equates to a difference of 0.6%. A major advantage of this approach is the near-global coverage offered by ASTER data and the opportunity that this presents for remote glacial change analysis over regional extents. </para>

A hierarchical approach coupled with coarse DEM information for improving the efficiency and accuracy of forest mapping over very rugged terrains

Forest mapping over mountainous terrains is difficult because of high relief. Although digital elevation models (DEMs) are often useful to improve mapping accuracy, high quality DEMs are seldom available over large areas, especially in developing countries. In this study, a hierarchical approach coupled with topographic information derived from coarse DEM was developed to improve the efficiency and accuracy of forest mapping over mountainous areas. The overall idea of increasing mapping accuracy over large mountainous areas is to reduce spectral variety over areas to be mapped. The approach consists of three major steps. The first step is to partition a large mountainous area into several small mapping zones. Forest mapping is then conducted in each zone independently. At the second step, forest areas are separated from non-forest areas through a semi-automatic binary classification procedure. At the third step, forested areas are then further classified into detailed forest types by coupling Landsat ETM+ imagery and two topographic variables derived from a coarse DEM (extracted from 1:250,000 digital elevation contour layer, which are readily available). This hierarchical approach was illustrated and evaluated through a case study in Northwest Yunnan, China, a very rugged terrain in the world. Forests and non-forests were separated accurately and efficiently (the overall accuracy is 0.97 and Khat value is 0.94 of whole area). It was found that the inclusion of the coarse topographic data improved the mapping accuracy significantly (overall accuracy from 0.74 to 0.84, from 0.76 to 0.89, from 0.78 to 0.84 in three test areas, respectively), and that the difference in accuracy between the use of coarse DEM data and the use of fine DEM data for the study area is not significant (overall accuracy from 0.84 to 0.86). The results indicate that the hierarchical approach, coupled with coarse DEM information, is effective in increasing the accuracy of forest mapping over very rugged terrains when high quality digital elevation models are not available.

Effects of DEM Source and Resolution on WEPP Hydrologic and Erosion Simulation: A Case Study of Two Forest Watersheds in Northern Idaho

The recent modification of the Water Erosion Prediction Project (WEPP) model has improved its applicability to hydrology and erosion modeling in forest watersheds. To generate reliable topographic and hydrologic inputs for the WEPP model, carefully selecting digital elevation models (DEMs) with appropriate resolution and accuracy is essential because topography is a major factor controlling water erosion. Light detection and ranging (LIDAR) provides an alternative technology to photogrammetry for generating fine-resolution and high-quality DEMs. In this study, WEPP (v2006.201) was applied to hydrological and erosion simulation for two small forest watersheds in northern Idaho. Data on stream flow and total suspended solids (TSS) in these watersheds were collected and processed. A total of six DEMs from the National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and LIDAR at three resolutions (30 m, 10 m, and 4 m) were obtained and used to calculate topographic parameters as inputs to the WEPP model. WEPP-simulated hydrologic and erosion results using the six DEMs were contrasted and then compared with field observations. For the study watersheds, DEMs with different resolutions and sources generated varied topographic and hydrologic attributes, which in turn led to significantly different erosion simulations. WEPP v2006.201 using the 10 m LIDAR DEM (vs. using other DEMs) produced a total amount of as well as seasonal patterns of watershed discharge and sediment yield that were closest to field observations.

On the Use of High-Resolution Topographic Data as a Proxy for Seismic Site Conditions (VS30)

An alternative method has recently been proposed for evaluating global seismic site conditions, or the average shear velocity to 30 m depth ( V S 30), from the Shuttle Radar Topography Mission (SRTM) 30 arcsec digital elevation models (DEMs). The basic premise of the method is that the topographic slope can be used as a reliable proxy for V S 30 in the absence of geologically and geotechnically based site-condition maps through correlations between V S 30 measurements and topographic gradient. Here we evaluate the use of higher-resolution (3 and 9 arcsec) DEMs to examine whether we are able to resolve V S 30 in more detail than can be achieved using the lower-resolution SRTM data. High-quality DEMs at resolutions greater than 30 arcsec are not uniformly available at the global scale. However, in many regions where such data exist, they may be employed to resolve finer-scale variations in topographic gradient, and consequently, V S 30. We use the U.S. Geological Survey Earth Resources Observation and Science (EROS) Data Center’s National Elevation Dataset (NED) to investigate the use of high-resolution DEMs for estimating V S 30 in several regions across the United States, including the San Francisco Bay area in California, Los Angeles, California, and St. Louis, Missouri. We compare these results with an example from Taipei, Taiwan, that uses 9 arcsec SRTM data, which are globally available. The use of higher-resolution NED data recovers finer-scale variations in topographic gradient, which better correlate to geological and geomorphic features, in particular, at the transition between hills and basins, warranting their use over 30 arcsec SRTM data where available. However, statistical analyses indicate little to no improvement over lower-resolution topography when compared to V S 30 measurements, suggesting that some topographic smoothing may provide more stable V S 30 estimates. Furthermore, we find that elevation variability in canopy-based SRTM measurements at resolutions greater than 30 arcsec are too large to resolve reliable slopes, particularly in low-gradient sedimentary basins.

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 digital elevation model (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 high-density 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.

A photogrammetric digital elevation model of the Bødalen valley saw-tooth moraine complex, western Norway

Please click here to download the map associated with this article. Thorough geomorphological and geophysical investigations rely on high quality digital elevation models (DEM). Many areas in the developed world are covered by DEMs through national ordnance surveys or similar organizations. However, these DEMs are often of quite low resolution and do not allow detailed geomorphological investigations. One way to overcome this problem is to photogrammetically generate a bespoke DEM based on aerial photographs and ground control points. The glacier foreland of the Bødalsbreen glacier, emanating from the Jostedalsbreen icefield in western Norway, is characterized by a set of distinct and morphologically interesting moraine ridges. Existing topographic data of the valley was not of sufficient quality for detailed investigations. We therefore constructed a photogrammetric DEM covering the glacier foreland. The resulting map is presented in this paper (Map A) and it is our hope that it will be used for further studies on glacial geomorphology in the area.

Visualisations of the Human Impacts on the Earth’s Surface

The objective is to discuss the human impacts to the changing of the landscape surface. The study surface is mainly karstic part of Slovenia. The primary data sources are digital elevation models (DEMs) as continuous surface data, supported with aerial photographs, satellite images and older topographic maps. This study is supplemented with textual information about of historical surfaces. Geomorphologically high quality DEM of Slovenia with 12.5 m resolution uncovered many human impacts to the terrain surface, which could not be perceived before using any classical surveying techniques. Particularly on the karstic areas, changes of the surface as a consequence of highway constructions and developing of the stone quarries are well seen. Additionally is involved a database of natural (ridges, valleys, peaks, sinkholes) and antropogenic features (stone and gravel quarries, standing waters, different types of roads and railways) on the current terrain surface. Even more surface changes were found on the LIDAR-based DEM of 1 m resolution. Some human impacts to the surface changes from prehistory until today were analysed with many visual techniques and confirmed with objective numerical methods. The results show that is the human impact on the Earth’s surface important factor that grows exponentially with time.

Mine Subsidence Monitoring Using Multi-source Satellite SAR Images

Ground subsidence due to underground mining has posed a constant threat to the safety of surface infrastructure such as motorways, railways, power lines, and telecommunications cables. Traditional monitoring techniques like using levels, total stations and GPS can only measure on a point-by-point basis and hence are costly and time-consuming. Differential interferometric synthetic aperture radar (DINSAR) together with GPS and GIS have been studied as a complementary alternative by exploiting multi-source satellite SAR images over a mining site southwest of Sydney. Digital elevation models (DEMs) derived from ERS-1 and ERS-2 tandem images, photogrammetry, airborne laser scanning, and the Shuttle Radar Topography Mission were assessed based on ground survey data using levelling as well as GPS-RTK. The identified high quality DEM was then used in the DINSAR analysis. Repeat-pass acquisitions by the ERS-1, ERS-2, JERS-1, RADARSAT-1 and ENVISAT satellites were used to monitor mine subsidence in the region with seven active mine collieries. Sub-centimeter accuracy has been demonstrated by comparing DINSAR results against ground survey profiles. The ERS tandem DINSAR results revealed mm-level resolution.

LiDAR-Derived High Quality Ground Control Information and DEM for Image Orthorectification

Orthophotos (or orthoimages if in digital form) have long been recognised as a supplement or alternative to standard maps. The increasing applications of orthoimages require efforts to ensure the accuracy of produced orthoimages. As digital photogrammetry technology has reached a stage of relative maturity and stability, the availability of high quality ground control points (GCPs) and digital elevation models (DEMs) becomes the central issue for successfully implementing an image orthorectification project. Concerns with the impacts of the quality of GCPs and DEMs on the quality of orthoimages inspire researchers to look for more reliable approaches to acquire high quality GCPs and DEMs for orthorectification. Light Detection and Ranging (LiDAR), an emerging technology, offers capability of capturing high density three dimensional points and generating high accuracy DEMs in a fast and cost-effective way. Nowadays, highly developed computer technologies enable rapid processing of huge volumes of LiDAR data. This leads to a great potential to use LiDAR data to get high quality GCPs and DEMs to improve the accuracy of orthoimages. This paper presents methods for utilizing LiDAR intensity images to collect high accuracy ground coordinates of GCPs and for utilizing LiDAR data to generate a high quality DEM for digital photogrammetry and orthorectification processes. A comparative analysis is also presented to assess the performance of proposed methods. The results demonstrated the feasibility of using LiDAR intensity image-based GCPs and the LiDAR-derived DEM to produce high quality orthoimages.

Investigations on intra-annual elevation changes using multi-temporal airborne laser scanning data: case study Engabreen, Norway

AbstractKey issues of glacier monitoring are changes in glacier geometry and glacier mass. As accurate direct measurements are costly and time-consuming, the use of various remote-sensing data for glacier monitoring is explored. One technology used and described here is airborne laser scanning. The method enables the derivation of high-quality digital elevation models (DEMs) with a vertical and horizontal accuracy in the sub-metre range. Between September 2001 and August 2002, three laser scanner data acquisition flights were carried out, covering the whole area of Engabreen, Norway, and corresponding well to the measurement dates for the mass-balance year 2001/02. The data quality of the DEMs is assessed (e.g. by comparing the values with a control area which has been surveyed independently or GPS ground profiles measured during the flights). For the whole glacier, surface elevation change and consequently volume change is calculated, quantified and compared with traditional mass-balance data for the same time interval. For the winter term, emergence/submergence velocity is determined from laser scanner data and snow-depth data and is compared with velocity measurements at stakes. The investigations reveal the high potential of airborne laser scanning for measuring the extent and the topography of glaciers as well as changes in geometry (Δarea, Δvolume).

Effect of support size on the accuracy of a distributed rockfall model

It is investigated whether a GIS-based distributed model developed for rockfall assessment at slope scale, which uses data with a support of 2.5×2.5 m, could be used for rockfall assessment at the regional scale, using input data with a support of 25×25 m and of poorer quality. It was anticipated that in the latter case the model error would increase. Three types of simulations were applied to the same model and the outcomes were validated with field data. The first simulation used input data with a support of 2.5×2.5 m and aggregated the output to a support of 25×25 m. The second simulation used the same input data as in the first simulation, but these data were aggregated to a support of 25×25 m before running the model. The third simulation used input data of poorer quality obtained at a support of 25×25 m. The results show that simulating the maximum extent of rockfall runout zones with a distributed model using data with a support of 25×25 m is realistic and feasible. This is also true for data with poorer quality as the third simulation resulted in a slightly larger mean-squared error than the first simulation. Surprisingly, it also gave a smaller error than the second simulation. We investigated the cause of the large error produced by the second simulation and concluded that this was mainly caused by the combination of a high-quality digital elevation model and the loss of spatial structure in the input data due to spatial aggregation.

Estimation of erosion and deposition volumes in a large, gravel‐bed, braided river using synoptic remote sensing

AbstractSystem‐scale detection of erosion and deposition is crucial in order to assess the transferability of findings from scaled laboratory and small field studies to larger spatial scales. Increasingly, synoptic remote sensing has the potential to provide the necessary data. In this paper, we develop a methodology for channel change detection, coupled to the use of synoptic remote sensing, for erosion and deposition estimation, and apply it to a wide, braided, gravel‐bed river. This is based upon construction of digital elevation models (DEMs) using digital photogrammetry, laser altimetry and image processing. DEMs of difference were constructed by subtracting DEM pairs, and a method for propagating error into the DEMs of difference was used under the assumption that each elevation in each surface contains error that is random, independent and Gaussian. Data were acquired for the braided Waimakariri River, South Island, New Zealand. The DEMs had a 1·0 m pixel resolution and covered an area of riverbed that is more than 1 km wide and 3·3 km long. Application of the method showed the need to use survey‐specific estimates of point precision, as project design and manufacturer estimates of precision overestimate a priori point quality. This finding aside, the analysis showed that even after propagation of error it was possible to obtain high quality DEMs of difference for process estimation, over a spatial scale that has not previously been achieved. In particular, there was no difference in the ability to detect erosion and deposition. The estimates of volumes of change, despite being downgraded as compared with traditional cross‐section survey in terms of point precision, produced more reliable erosion and deposition estimates as a result of the large improvement in spatial density that synoptic methods provide. Copyright © 2003 John Wiley &amp; Sons, Ltd.

Parameterization of soil properties for a model of topographic controls on shallow landsliding: application to Rio de Janeiro

A key problem in the use of physically based models of landslide hazards is how to parameterize the representation of soil properties. We applied a physically based model for the topographic control on shallow landsliding (SHALSTAB) to two catchments in Rio de Janeiro to investigate the accuracy of model results in relation to parameterization of soil properties. In so doing, we address the relevance of values derived from laboratory tests to the field problem, as well as the trade-offs inherent in model parameterization. We ran the model for all combinations of reasonable cohesion, bulk density, and friction angle values and compared model predictions to mapped landslides scars. We rank sorted model performance through the proportion of the total area of landslide scars correctly predicted as potentially unstable. Application of the model to an area where soil properties are not well known can be based on either a standard parameterization that emphasizes topographic controls, or on local calibration of soil parameters against a map of known landslide locations. Our analysis suggests that, in general, acquisition of high-quality digital elevation models (DEMs) is more important than generation of spatially detailed soil property values for reconnaissance level assessment of shallow landslide hazards.

Through‐Water Close Range Digital Photogrammetry in Flume and Field Environments

Measurement of the structure of gravel‐bed river surfaces is crucial for understanding both bed roughness and the sediment entrainment process. This paper describes the use of close range digital photogrammetry to measure and monitor change occurring in submerged river gravel‐beds in both flume and field environments. High‐resolution digital elevation models (DEMs) were obtained and two‐media (through air and water) techniques were used to correct for the e.ects of refraction at the air/water interface. Although suitable refractive models have been developed, the use of proprietary software to generate DEMs automatically introduces the problem of how to re‐establish collinearity. A simple refraction correction algorithm based upon analytical geometry was developed and is described. This algorithm was designed for use after initial DEM acquisition and allows any photogrammetric software package to be used for data acquisition. Application of this algorithm led to improvements in DEM accuracy by reducing the systematic, depth‐dependent bias caused by refractionResearch carried out in a flume environment allowed the algorithm to be tested by measuring a flooded and drained bed surface. Non‐systematic differences between the “dry” and “wet” DEMs arose from reductions in stereomatching success in the two‐media case. This effect was thought to be due to light attenuation and the introduction of residual parallax. Results suggest that close range digital photogrammetry can be used to extract high quality DEMs of submerged topography in both flume and field fluvial environments, which represents a particularly exciting development for fluvial geomorphologists

Broad-scale Spatial Prediction of Areas at Risk from Dryland Salinity

This paper presents a method for predicting areas at risk from dryland salinity using information derived from multi-temporal Landsat Thematic Mapper satellite images combined with land form data derived from high-quality digital elevation models. The method aims to reproduce expert opinion about the future extent of salinity by using decision trees to determine the relationship between salinity risk and variables that describe various aspects of the landscape. Feature selection procedures are used to determine the optimal subset of variables for predicting risk areas. Preliminary studies were conducted in five subcatchments and the model was spatially extrapolated over 30 000 km2 to produce maps of those areas expected to become saline under current management practices.

Self‐organization and scaling relationships of evolving river networks

The power spectra S of linear transects of Earth's topography is often observed to be a power law function of wave number k with exponent close to −2: S(k) ∝ k−2. In addition, river networks are fractal trees that satisfy several power law relationships between their morphologic components. A model equation for the evolution of Earth's topography by transport‐limited erosional processes which produces fractal topography and fractal river networks is presented, and its solutions are compared in detail to real topography. The model is the diffusion equation for sediment transport on hillslopes and channels with the diffusivity constant on hillslopes and proportional to the three‐halves power of discharge in channels. The dependence of diffusivity on discharge is consistent with sediment rating curves. We study the model in two ways. In the first analysis the diffusivity is parameterized as a function of elevation, and a Taylor expansion procedure is carried out to obtain a differential equation for the landform elevation which includes the spatially variable diffusivity to first order in the elevation. The solution to this equation is a self‐affine or fractal surface with linear transects that have power spectra S(k) ∝ k−1.8, independent of the age of the topography, consistent with observations of real topography. The hypsometry produced by the model equation is skewed such that lowlands make up a larger fraction of the total area than highlands as observed in real topography. In the second analysis we include river networks explicitly in a numerical simulation by calculating the discharge at every point. We characterize the morphology of real river basins with five independent scaling relations between six morphometric variables. Scaling exponents are calculated for seven river networks from a variety of tectonic environments using high‐quality digital elevation models. River networks formed in the model match the observed scaling laws and satisfy Tokunaga side‐branching statistics.

Multibaseline InSAR DEM reconstruction: the wavelet approach

Multibaseline synthetic aperture radar (SAR) interferometry can be exploited successfully for high-quality digital elevation model (DEM) reconstruction, provided that both noise and atmospheric effects are taken into account. A weighted combination of many uncorrelated topographic profiles strongly reduces the impact of phase artifacts on the final DEM. The key issue is weights selection. In the present article a wavelet domain approach is proposed. Taking advantage of the particular frequency trend of the atmospheric distortion, it is possible to estimate, directly from the data, noise and atmospheric distortion power for each interferogram. The available DEMs are then combined by means of a weighted average, carried out in the wavelet domain. This new approach provides a valuable tool not only for DEMs combination (improving accuracy), but for data evaluation and selection, since the phase error power is estimated for each interferogram. Results obtained using simulated and real data (ERS-1/2 TANDEM data of a test area around the Etna volcano, Sicily) are presented.