LiDAR Digital Elevation Model Research Articles

Mapping contemporary magnetic mineral concentrations in peat soils using fine-resolution digital terrain data

Small-scale spatial variability in the concentration of magnetic minerals in peat soils has been explained by differences in the deposition and interception of magnetic minerals at the soil surface and the retention of magnetic minerals within the soil. Each of these processes is controlled by topographic conditions. Recent advances in the field of digital terrain analysis and the availability of fine-resolution digital elevation models means that the relationship between the concentration of magnetic minerals in peat soils and topography can be explored using quantitative methods. Alport Moor is an ombrotrophic peat moorland in the Peak District National Park, UK. 24 peat cores were collected from Alport Moor covering an area of 0.1 km 2. Each core was analysed for mass specific magnetic susceptibility. Three topographic attributes (topographic wetness index, difference from mean elevation and elevation as a percentage of elevation range) were extracted from a high resolution LiDAR digital elevation model of Alport Moor. Stepwise multiple regression analyses show that topographic wetness index and difference from mean elevation are excellent predictors of variation in peak magnetic susceptibility and total magnetic susceptibility inventories for peat soils of this upland area. The results demonstrate that the contemporary concentration of magnetic minerals in the peat soils of Alport Moor is controlled by micro- and local-scale variations in water table position. The results also suggest that the contemporary level of magnetic minerals in the peat soils of Alport Moor is controlled by the retention of such particles in the soil environment. Differences in the deposition and interception of magnetic minerals play a secondary role in controlling magnetic mineral concentrations. Spatial maps of magnetic susceptibility reveal that peat soils adjacent to gully edges at Alport Moor have the highest concentration of magnetic minerals. The mapping approach used in this study could be applied to other peatland environments.

Characterizing the Hsincheng active fault in northern Taiwan using airborne LiDAR data: Detailed geomorphic features and their structural implications

We applied newly acquired high-resolution airborne LiDAR data to study a segment of the Hsincheng fault, a well-known active fault near a large industrial park in northern Taiwan. The Hsincheng fault has received much attention and study in the past; but high spatial resolution digital elevation models have not previously been applied to the study of the fault and its surrounding structures. We processed the acquired LiDAR data and produced 1 m digital elevation models (DEMs) to investigate the active fault adjacent to the densely populated and important infrastructure in Taiwan. Using the LiDAR DEMs, aerial photographs and topographic maps, we show highly detailed geomorphic characteristics around the study area of the Hsincheng fault. Three major characteristics of the study area are defined that include three very well preserved river terraces at varying levels, the fault/fold scarp of the Hsincheng fault, and meandering river systems. Using the LiDAR DEMs, we were able to detect with precision several fault/fold scarps and very gentle NE-trending folding of the river terraces. In general, the LiDAR DEMs have provided unprecedented clarity of landforms for one segment of the Hsincheng fault, which has helped the characterization of subtle but important geomorphic features.

Extracting photogrammetric ground control from lidar DEMs for change detection

AbstractResearch has shown the importance of measuring topography for surface change detection and that the use of remote sensing methods is ideal for this application. A prerequisite for measuring change is a historical data‐set that covers the time period of interest. Many remote methods of topographic data collection such as lidar are relatively recent developments and therefore cannot provide records longer than about a decade. Alternatively, aerial photography has been in common use since the early 20th century and archives upwards of 50 years are therefore not uncommon. While photogrammetry is dependent on well distributed, high quality ground control points (GCPs), such data has been successfully applied retroactively. Therefore, contemporary lidar data, which requires little ground‐truth data, should be an ideal source of GCPs for controlling historical aerial photographs. This study aims to evaluate the success with which GCPs can be extracted from a high‐resolution lidar data‐set for controlling aerial photography for digital elevation model (DEM) production. Using a data‐set collected in Upper Wharfedale, northern England, GCPs were measured both by means of a lidar data‐set and by using traditional field‐based methods. The results showed that while the use of lidar‐derived ground control produced a DEM of inferior quality, increasing the number of GCPs used in the model produced results comparable to the GPS‐controlled DEM. These results are significant especially for surface change detection research in remote areas where high quality ground control is difficult to secure.

Sensitivity of channel mapping techniques to uncertainty in digital elevation data

Digital elevation data are now commonly used to map channel networks automatically. This paper evaluates the sensitivity of six methods of extracting channel networks from digital elevation models (DEMs) to elevation error. As such, the robustness of channel mapping techniques against noisy data was evaluated and not the accuracy of DEM extracted channel networks. Stochastic simulations were used in combination with a fine‐resolution LiDAR DEM of a small upland catchment to assess the robustness of each of the channel mapping algorithms. Findings showed that the four tested methods that were based on identifying patterns or positions in the surface morphology were more sensitive to elevation error than the two methods that were based on simulating overland flow and channelization processes, particularly at lower error magnitudes. While the morphology‐based channel‐mapping methods were highly sensitive to the degree of spatial autocorrelation in elevation error fields, the channelization based methods were relatively insensitive. Drainage network extent and the geometry of exterior stream channels were both found to be greatly influenced by low to moderate degrees of topographic error. Although LiDAR data were found to provide a sufficient resolution for mapping fine‐scale headwater channels, the greater surface roughness did present challenges for automated channel‐mapping techniques.

An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling

Identification and removal of surface depressions is a critical step for automated modelling of surface rainfall runoff based on Digital Elevation Models (DEMs). At present, nearly all GIS and hydrologic software packages employ Jenson and Domingue's method for preparing depressionless DEMs for hydrologic analysis. This conventional method is computationally intensive and time‐consuming. With the growing availability of high‐resolution DEMs produced by airborne LIDAR and InSAR techniques, GIS‐based hydrologic applications often need to handle larger geographic areas at finer resolutions. In the face of high‐resolution DEMs, the conventional method becomes inadequate and deficient. In this paper, we present a new method for efficiently identifying and filling surface depressions in DEMs. This method can simultaneously determine flow paths and spatial partition of watersheds with one pass of processing. A novel concept of spill elevation and the least‐cost search for optimal flow paths are the two cornerstones of our method. The time complexity of our method is in O(Nlog N). It has been implemented using C++ programming language and successfully applied to USGS DEMs and LIDAR DEMs of various sizes. Experiments show that our method outperforms the conventional method by a factor of over 30, in terms of running time.

The application of lidar-derived digital elevation model analysis to geological mapping: an example from the Fundy Basin, Nova Scotia, Canada

High-resolution laser altimetry (lidar) is applied to geological problems such as bedrock and surficial mapping and the relationship to earth surface processes in the Fundy Basin of Nova Scotia. A "bald earth" lidar digital elevation model (DEM) is used in conjunction with field observations to map three flow units of the Jurassic North Mountain Basalt (NMB) based on contrasting terrain characteristics (slope, smoothness, and relief). The variable resistance of the flow units to erosion, documented by shatterbox experiments and down-core fracture density data, has a measurable control on incision by post-glacial consequent streams. In catchments where till cover is thick, greater surface runoff and weaker infiltration increase incision by as much as 43% for a given flow unit. Interpretation of field, petrologic, and digital topography data indicates previously unrecognized craters in the lower flow unit are the result of interaction between partially solidified lava and surface water or groundwater. Two new sets of surficial landforms have been identified that indicate ice was directed northwestward into the Bay of Fundy during the late stages of glaciation. Twice as many wave-cut terraces have been identified in the lidar DEM than previously mapped, and elevations have been extracted and compared with published values that are related to higher sea-levels at 12–14 ka. This paper demonstrates through a range of examples that the precision and enhanced resolution of lidar can improve our understanding of how landscapes form and evolve.

Using airborne lidar to assess the influence of glacier downwasting on water resources in the Canadian Rocky Mountains

Knowledge of the changing dimensions of alpine glacier surfaces is critical from both a water resources and climate change indication perspective. With the development of airborne light detection and ranging (lidar) technologies with the capability to rapidly map large areas of topography at high resolutions, there is a need to assess the utility of this technology for glacier surface change detection and water resources assessment. The study presented here compares two lidar digital elevation models (DEMs) collected 23 months apart in 2000 and 2002 over Peyto Glacier, Canadian Rocky Mountains, for the purposes of intensity image feature recognition and surface downwasting assessment. The 2002 DEM was subtracted from the 2000 DEM to quantify the total and spatial variability in surface downwasting (or growth) within the glacial and periglacial environments. It was found that there was a reduction in volume totaling 33 × 106 m3 over the Peyto Glacier surface and surrounding ice-cored moraines. This downwasting was estimated to be equivalent to approximately 22 × 106 m3 of water volume and, after extrapolation, 16% of total basin runoff. The water-equivalent contribution from ice-cored moraines was estimated to be 6% of the total glacier runoff contribution, highlighting the importance of monitoring this component of glacial melt.

Flood-risk mapping for storm-surge events and sea-level rise using lidar for southeast New Brunswick

Coastal flooding from storm-surge events and sea-level rise is a major issue in Atlantic Canada. Airborne light detection and ranging (lidar) has the spatial density and vertical precision required to map coastal areas at risk of flooding from water levels typically 1–2 m higher than predicted tides during storm surges. In this study, a large section of the New Brunswick coast along Northumberland Strait was surveyed in 2003 and 2004 using two lidar systems. Water levels from a major storm-surge event in January 2000 were surveyed using a global positioning system (GPS) and used as a benchmark for flood-risk maps. Maps of flood depth were also generated for all water levels and used for socioeconomic and ecosystem impact assessment. Flood-risk maps were constructed using standard geographical information system (GIS) processing routines to determine the spatial extent of inundation for a given water level. The high resolution of the lidar digital elevation model (DEM) captured embankments such as raised roadbeds that could prevent flooding inland. Where connectivity was present due to culverts or bridges, the DEM was notched across the roadbed to simulate the connection between the ocean and upstream low-lying areas in the GIS. An automated routine was then used to generate maps of flood extent for water levels at 10 cm increments from 0 to 4 m above mean sea level. Validation of the flood-risk and flood-depth maps for the January 2000 storm-surge water level by field visits indicates that the simulations are generally accurate to within 10–20 cm. The lidar data were also used to evaluate the potential for overtopping and dune erosion on a large coastal spit, La Dune de Bouctouche. This showed a high vulnerability to storm damage for critical habitats on the spit. The lidar-derived maps produced in this study are now available to coastal communities and regional planners for use in the planning process and to assist in development of long-term adaptation strategies.

Removal of artifact depressions from digital elevation models: towards a minimum impact approach

Artifact depressions in digital elevation models (DEMs) interrupt flow paths and alter drainage directions. Techniques for removing depressions should enforce continuous flow paths in a way that requires the least modification of the DEM. Impacts on the spatial and statistical distributions of elevation and its derivatives were assessed for four methods of removing depressions: (1) filling; (2) breaching; (3) a combination of filling and breaching, with breaching constrained to a maximum of two grid cells; (4) a combination of filling and breaching based on an impact reduction approach (IRA). The IRA removes each depression using either filling or breaching, depending on which method has the least impact, in terms of the number of modified cells and the mean absolute difference in the DEM. Analysis of a LiDAR DEM of a landscape on the Canadian Shield showed significant differences in the impacts among the four depression removal methods. Depression filling, a removal method that is widely implemented in geographical information system software, was found to impact terrain attributes most severely. Constrained breaching, which relies heavily on filling for larger depressions, also performed poorly. Both depression breaching and the IRA impacted spatial and statistical distributions of terrain attributes less than depression filling and constrained breaching. The most sensitive landscapes to depression removal were those that contained large (i.e. >10%) flat areas, because of the occurrence of relatively large depressions in these areas. Copyright © 2005 John Wiley & Sons, Ltd.

Assessment of airborne scanning laser altimetry (lidar) in a deltaic wetland environment

The objective of the study was to evaluate the airborne scanning light detection and ranging (lidar) technology for hydrological applications in wetlands, deltas, or other similar areas. A comparison of lidar data with in situ survey data revealed a negative elevation bias of 0.21 m, which was corrected by block adjustment. The evaluation demonstrated that the lidar pulses had difficulties penetrating thick willow cover and dense thatch layers beneath the grasses and sedges (graminoids). After block adjustment, the lidar data achieved a root mean squared error (RMSE) of 0.15 and 0.26 m in graminoid and willow vegetation, respectively. The bare ground points produced an RMSE of 0.07 m. To be useful in hydrologic modelling, elevation data need to be interpolated into an even grid, or a digital elevation model (DEM). Four interpolation algorithms were evaluated for accuracy. The input elevations were best honoured when interpolated into a 0.25 m grid using a kriging algorithm and, thereafter, averaged to a 4 m resolution DEM. The RMSE of the DEM was 0.22 m. Despite some problems in dense vegetation, the lidar DEM provided useful topographic detail in a resolution and accuracy that is acceptable for many hydrologic purposes.

Automated analysis and classification of landforms using high-resolution digital elevation data: applications and issues

This paper describes recent efforts to use fine spatial resolution digital elevation model (DEM) data, including, but not limited to, lidar DEM data, for automated analysis and classification of geomorphic and hydrologic terrain features. The example applications presented are based on a 3-m horizontal resolution lidar DEM for a 6 km by 8 km agricultural watershed in Alberta and on a similar 5-m horizontal resolution conventional DEM for two forested areas of 14 km by 12 km in the Cariboo Forest Region of British Columbia. The applications illustrate efforts to produce meaningful classifications of ecological and landform spatial entities and to automatically extract hydrological spatial entities required for input into the WEPP water erosion model. Fine spatial resolution DEMs present some unique problems for which solutions are still lacking or are insufficient. Errors of apparently minor extent or degree can seriously affect some forms of analysis, especially analyses that involve hydrological calculations of paths of surface water flow. A need is recognized for improved methods and tools for interpolating and editing fine spatial resolution DEMs to remove or reduce localized errors.

Comparison and fusion of LIDAR and InSAR digital elevation models over urban areas

In this paper we analyse a multiple sensor dataset corresponding to three-dimensional data coming from interferometric radar (InSAR) or laser ranging (LIDAR) measurements. We consider digital elevation models (DEMs) extracted from a single LIDAR scan plus multiple SAR scans of the same area, downtown Denver, CO, USA. Horizontal resolution for both datasets is 2.5 m, a value allowing good characterization of sparse tall buildings. Fusion of DEMs extracted from InSAR data originated during flights orthogonal to each other allows reduction of layover and shadowing. A novel strategy combining advantages of existing fusion techniques is proposed. Results from individual and combined techniques are presented, compared and discussed. The ability of characterizing buildings allows us to raise the fusion strategy scope from the pixel-level up to the feature level, once 3D features are extracted. Related results are presented and discussed. Finally, fusion of InSAR and LIDAR data is considered. LIDAR can reliably determine building footprints, thus relieving the problem of multiple bouncing radar pulses. Some results show that analysis of combined InSAR and LIDAR data on a small area can provide an improvement in DEMs extracted from a much larger area where only InSAR data are available.

William S. Apple, 1918-1983

High-resolution LiDAR Digital Elevation Model (DEM) data were used to create DEM mosaics and hillshade maps of a large region in North Dakota for better defining and measuring the strandlines of glacial Lake Agassiz. Although many of the strandlines in this region had been identified and named more than a century ago by Warren Upham, LiDAR images clearly reveal their complexity, and identify additional small and low relief ridges not previously mapped. The elevations of the crests of six well-developed strandlines – the Campbell, McCauleyville, lower Blanchard, Emerado, upper Ojata, and lower Ojata beaches – were measured. For each of these strandlines, north–south gradients were calculated, which were produced by differential isostatic rebound. The steepest gradient is on the uppermost (Campbell) beach in the sequence and the gradient on each beach below is progressively lower, confirming that these beaches were deposited in sequence from oldest to youngest as the level of Lake Agassiz declined. Because there were no anomalous beach gradients in this sequence, the Ojata beach formed after 9400 14C (10,630 cal) BP, which is when the higher-elevation Campbell beach was deposited, rather than at ∼10,000 14C (11,480 cal) years ago as some have suggested because of the age of organics below the Ojata beach. Those organics and the subaerial surface on which they lie survived the Moorhead transgression to the Campbell beach, and the Ojata beach must have been deposited over the older organic unit later, as lake level regressed. A simple extrapolation model was used to estimate the ages of beaches in the sequence.