Digital elevation models derived from airborne laser scanning point clouds: appropriate spatial resolutions for multi‐temporal characterization and quantification of geomorphological processes

Digital terrain models (DTMs) are a standard data source for a variety of applications. DTM differencing is also widely used for detection and quantification of topographic changes. While several investigations have been made on the accuracy of DTMs, calculated from different kinds of input data, little has been published on the error of DTM differencing, specifically for the quantification of geomorphological processes. In this study, an extensive, multi‐temporal set of airborne laser scanning (ALS) data is used to investigate the accuracy of topographic change calculations in a high alpine environment, caused by different geomorphic processes. Differences from DTMs with cell sizes ranging from 0.25 m to 10 m were calculated and compared to very accurate point‐to‐point calculations for a variety of processes and in nearby stable areas which show no significant surface changes. The representativeness of the DTM differences is then compared to the terrain slope and surface roughness of the investigated areas to show the influence of these parameters on the errors in the differences. Those errors are then taken into account for analyses of the applicability of different cell sizes for the investigation of geomorphic processes with different magnitudes and over different time periods. The analyses show that the error of DTM differences increases with lower point densities and higher roughness and slope values. The higher the error, the greater the differences between two elevation datasets have to be in order to quantify certain morphodynamic processes. Lower point densities and higher roughness and slope values require greater process rates or longer time intervals in order to obtain valid results. Copyright © 2013 John Wiley & Sons, Ltd.     

Camera system considerations for geomorphic applications of SfM photogrammetry

The availability of high‐resolution, multi‐temporal, remotely sensed topographic data is revolutionizing geomorphic analysis. Three‐dimensional topographic point measurements acquired from structure‐from‐motion (SfM) photogrammetry have been shown to be highly accurate and cost‐effective compared to laser‐based alternatives in some environments. Use of consumer‐grade digital cameras to generate terrain models and derivatives is becoming prevalent within the geomorphic community despite the details of these instruments being largely overlooked in current SfM literature. A practical discussion of camera system selection, configuration, and image acquisition is presented. The hypothesis that optimizing source imagery can increase digital terrain model (DTM) accuracy is tested by evaluating accuracies of four SfM datasets conducted over multiple years of a gravel bed river floodplain using independent ground check points with the purpose of comparing morphological sediment budgets computed from SfM‐ and LiDAR‐derived DTMs. Case study results are compared to existing SfM validation studies in an attempt to deconstruct the principle components of an SfM error budget. Greater information capacity of source imagery was found to increase pixel matching quality, which produced eight times greater point density and six times greater accuracy. When propagated through volumetric change analysis, individual DTM accuracy (6–37 cm) was sufficient to detect moderate geomorphic change (order 100 000 m³) on an unvegetated fluvial surface; change detection determined from repeat LiDAR and SfM surveys differed by about 10%. Simple camera selection criteria increased accuracy by 64%; configuration settings or image post‐processing techniques increased point density by 5–25% and decreased processing time by 10–30%. Regression analysis of 67 reviewed datasets revealed that the best explanatory variable to predict accuracy of SfM data is photographic scale. Despite the prevalent use of object distance ratios to describe scale, nominal ground sample distance is shown to be a superior metric, explaining 68% of the variability in mean absolute vertical error. Published 2016. This article is a U.S. Government work and is in the public domain in the USA     

Application of a multi‐temporal,LiDAR‐derived,digital terrain model in a landslide‐volume estimation

Sediments produced by landslides are crucial in the sediment yield of a catchment, debris flow forecasting, and related hazard assessment. On a regional scale, however, it is difficult and time consuming to measure the volumes of such sediment. This paper uses a LiDAR‐derived digital terrain model (DTM) taken in 2005 and 2010 (at 2 m resolution) to accurately obtain landslide‐induced sediment volumes that resulted from a single catastrophic typhoon event in a heavily forested mountainous area of Taiwan. The landslides induced by Typhoon Morakot are mapped by comparison of 25 cm resolution aerial photographs taken before and after the typhoon in an 83.6 km² study area. Each landslide volume is calculated by subtraction of the 2005 DTM from the 2010 DTM, and the scaling relationship between landslide area and its volume are further regressed. The relationship between volume and area are also determined for all the disturbed areas (V_L = 0.452A_L^1.242) and for the crown areas of the landslides (V_L = 2.510A_L^1.206). The uncertainty in estimated volume caused by use of the LiDAR DTMs is discussed, and the error in absolute volume estimation for landslides with an area >10⁵ m² is within 20%. The volume–area relationship obtained in this study is also validated in 11 small to medium‐sized catchments located outside the study area, and there is good agreement between the calculation from DTMs and the regression formula. By comparison of debris volumes estimated in this study with previous work, it is found that a wider volume variation exists that is directly proportional to the landslide area, especially under a higher scaling exponent. Copyright © 2013 John Wiley & Sons, Ltd.     

The topographic data source of digital terrain models as a key element in the accuracy of hydraulic flood modelling

The effects of the topographic data source and resolution on the hydraulic modelling of floods were analysed. Seven digital terrain models (DTMs) were generated from three different altimetric sources: a global positioning system (GPS) survey and bathymetry; high‐resolution laser altimetry data LiDAR (light detection and ranging); and vectorial cartography (1:5000). Hydraulic results were obtained, using the HEC‐RAS one‐dimensional model, for all seven DTMs. The importance of the DTM's accuracy on the hydraulic modelling results was analysed within three different hydraulic contexts: (1) the discharge and water surface elevation results from the hydraulic model; (2) the delineation of the flooded area; and (3) the relative sensitivity of the hydraulic model to changes in the Manning's n roughness coefficient. The contour‐based DTM was the least accurate with a root mean square error (RMSE) of 4·5 m in the determination of the water level and a variation of up to 50 per cent in the estimation of the inundated area of the floodplain. The GPS‐based DTM produced more realistic water surface elevation results and variations of up to 8 per cent in terms of the flooded area. The laser‐based model's RMSE for water level was 0·3 m, with the flooded area varying by less than 1 per cent. The LiDAR data also showed the greatest sensitivity to changes in the Manning's roughness coefficient. An analysis of the effect of mesh resolution indicated an influence on the delineation of the flooded area with variations of up to 7·3 per cent. In addition to determining the accuracy of the hydraulic modelling results produced from each DTM, an analysis of the time–cost ratio of each topographic data source illustrates that airborne laser scanning is a cost‐effective means of developing a DTM of sufficient accuracy, especially over large areas. Copyright © 2006 John Wiley & Sons, Ltd.     

Suitability of LiDAR point density and derived landform curvature maps for channel network extraction

This study uses landform curvature as an approach for channel network extraction. We considered a study area located in the eastern Italian Alps where a high‐quality set of LiDAR data was available and where channel heads and related channel network were mapped in the field. In the analysis, we derived 1‐m DTMs from different ground LiDAR point densities, and we used different smoothing factors for the landscape curvature calculation in order to test the suitability of the LiDAR point density and the derived curvature maps for the recognition of channel network. This methodology is based on threshold values of the curvature calculated as multiples (1–3 times) of the standard deviation of the curvature. Our analyses suggested that (i) the window size for curvature calculations has to be a function of the size of the features to be detected, (ii) a coarse ground LiDAR point density could be as useful as a finer one for the recognition of main channel network features and (iii) rougher curvature maps are not optimal as they do not explore a sufficient range at which features occur, while smoother curvature maps overcome this problem and are more appropriate for the extraction of surveyed channels. Copyright © 2010 John Wiley & Sons, Ltd.     

High‐resolution topography and anthropogenic feature extraction: testing geomorphometric parameters in floodplains

In floodplains, anthropogenic features such as levees or road scarps, control and influence flows. An up‐to‐date and accurate digital data about these features are deeply needed for irrigation and flood mitigation purposes. Nowadays, LiDAR Digital Terrain Models (DTMs) covering large areas are available for public authorities, and there is a widespread interest in the application of such models for the automatic or semiautomatic recognition of features. The automatic recognition of levees and road scarps from these models can offer a quick and accurate method to improve topographic databases for large‐scale applications. In mountainous contexts, geomorphometric indicators derived from DTMs have been proven to be reliable for feasible applications, and the use of statistical operators as thresholds showed a high reliability to identify features. The goal of this research is to test if similar approaches can be feasible also in floodplains. Three different parameters are tested at different scales on LiDAR DTM. The boxplot is applied to identify an objective threshold for feature extraction, and a filtering procedure is proposed to improve the quality of the extractions. This analysis, in line with other works for different environments, underlined (1) how statistical parameters can offer an objective threshold to identify features with varying shapes, size and height; (2) that the effectiveness of topographic parameters to identify anthropogenic features is related to the dimension of the investigated areas. The analysis also showed that the shape of the investigated area has not much influence on the quality of the results. While the effectiveness of residual topography had already been proven, the proposed study underlined how the use of entropy can anyway provide good extractions, with an overall quality comparable to the one offered by residual topography, and with the only limitation that the extracted features are slightly wider than the investigated one. Copyright © 2013 John Wiley & Sons, Ltd.     

Investigation of topographic reductions and aliasing effects on gravity and the geoid over Greece based on various digital terrain models

The reduction of gravity-field related quantities (e.g., gravity anomalies, geoid heights) due to the topography plays a crucial role in both geodetic and geophysical applications, since in the former it is an intermediate step towards geoid prediction and in the latter it reveals lateral as well as radial density contrasts and infers the geology of the area under study. The computations are usually carried out by employing a DTM and/or a DBM, which describe the topography and bathymetry, respectively. Errors in these DTMs/DBMs will introduce errors in the computed topographic effects, while poor spatial resolution of the topography and bathymetry models will result in aliasing effects to both gravity anomalies and geoid heights, both influencing the accuracy of the estimated solutions. The scope of this work is twofold. First, a validation and accuracy assessment of the SRTM 3″ (90 m) DTM over Greece is performed through comparisons with existing global models as well as with the Greek 450 m national DTMs. Whenever a misrepresentation of the topography is identified in the SRTM data, it is “corrected” using the local 450 m DTM. This process resulted in an improved SRTM DTM called SRTMGr, which was then used to determine terrain effects to gravity field quantities. From the fine-resolution SRTMGr DTMs, coarser models of 15″, 30″, 1′, 2′ and 5′ have been determined in order to investigate aliasing effects on both gravity anomalies and geoid heights by computing terrain effects at variable spatial resolutions. From the results acquired in two test areas, it was concluded that SRTMGr provides similar results to the local DTM making the use of other older global DTMs obsolete. The study for terrain aliasing effects proved that when high-resolution and accuracy gravity and geoid models are needed, then the highest possible resolution DTM should be employed to compute the respective terrain effects. Based on the results acquired from two the test areas a corrected SRTMGr DTM has been compiled for the entire Greek territory towards the development of a new gravimetric geoid model. Results from that analysis are presented based on the well-known remove-compute-restore method, employing land and marine gravity data, EGM08 as a reference geopotential model and the SRTMGr DTM for the computation of the RTM effects.     

The topographic signature of a major typhoon

In August 2009, the typhoon Morakot, characterized by a cumulative rainfall up to 2884 mm in about three days, triggered thousands of landslides in Taiwan. The availability of LiDAR surveys before (2005) and after (2010) this event offers a unique opportunity to investigate the topographic signatures of a major typhoon. The analysis considers the comparison of slope–area relationships derived by LiDAR digital terrain models (DTMs). This approach has been successfully used to distinguish hillslope from channelized processes, as a basis to develop landscape evolution models and theories, and understand the linkages between landscape morphology and tectonics, climate, and geology. We considered six catchments affected by a different degree of erosion: three affected by shallow and deep‐seated landslides, and three not affected by erosion. For each of these catchments, 2 m DTMs were derived from LiDAR data. The scaling regimes of local slope versus drainage area suggested that for the catchments affected by landslides: (i) the hillslope‐to‐valley transitions morphology, for a given value of drainage area, is shifted towards higher value of slopes, thus indicating a likely migration of the channelized processes and erosion toward the catchment boundary (the catchment head becomes steeper because of erosion); (ii) the topographic gradient along valley profiles tends to decrease progressively (the valley profile becomes gentler because of sediment deposition after the typhoon). The catchments without any landslides present a statistically indistinguishable slope–area scaling regime. These results are interesting since for the first time, using multi‐temporal high‐resolution topography derived by LiDAR, we demonstrated that a single climate event is able to cause significant major geomorphic changes on the landscape, detectable using slope–area scaling analysis. This provides new insights about landscape evolution under major climate forcing. Copyright © 2015 John Wiley & Sons, Ltd.     

Remote measurement of river morphology via fusion of LiDAR topography and spectrally based bathymetry

This study developed and evaluated a hybrid approach to remote measurement of river morphology that combines LiDAR topography with spectrally based bathymetry. Comparison of filtered LiDAR point clouds with surveyed cross‐sections indicated that subtle features on low‐relief floodplains were accurately resolved by LiDAR but that submerged areas could not be detected due to strong absorption of near‐infrared laser pulses by water. The reduced number of returns made the active channel evident in a LiDAR point density map. A second dataset suggested that pulse intensity also could be used to discriminate land from water via a threshold‐based masking procedure. Fusion of LiDAR and optical data required accurate co‐registration of images to the LiDAR, and we developed an object‐oriented procedure for achieving this alignment. Information on flow depths was derived by correlating pixel values with field measurements of depth. Highly turbid conditions dictated a positive relation between green band radiance and flow depth and contributed to under‐prediction of pool depths. Water surface elevations extracted from the LiDAR along the water's edge were used to produce a continuous water surface that preserved along‐channel variations in slope. Subtracting local flow depths from this surface yielded estimates of the bed elevation that were then combined with LiDAR topography for exposed areas to create a composite representation of the riverine terrain. The accuracy of this terrain model was assessed via comparison with detailed field surveys. A map of elevation residuals showed that the greatest errors were associated with underestimation of pool depths and failure to capture cross‐stream differences in water surface elevation. Nevertheless, fusion of LiDAR and passive optical image data provided an efficient means of characterizing river morphology that would not have been possible if either dataset had been used in isolation. Copyright © 2011 John Wiley & Sons, Ltd.     

DTM resolution controls the accuracy of estimating surface runoff indicators in flat,lowland landscapes

Surface runoff plays an important role in contaminant transport, nutrient loss, soil erosion and peak discharges in streams and rivers. Because it is the result of a variety of complex hydrological processes, estimating surface runoff using physically based hydrological models is challenging. Upscaling of physical soil properties is necessary to cope with the limits of computational power in surface runoff modelling. In flat landscapes, the (micro)topographic surface controls the onset and progression of surface runoff on saturated soils during rain events. Therefore, its proper representation is crucial when attempting to model and predict surface runoff. In this study, the influence of microtopography (centimetre scale) on estimations of maximum depression storage (MDS), random roughness (RR) and the connectivity threshold (CT) is explored. These properties are selected because they often serve as surface runoff indicators in hydrological modelling. To characterize microtopography, a terrestrial laser scanner (TLS) is used to generate a digital terrain model (DTM) of the study site with a horizontal spatial resolution of 5 cm. MDS, RR and CT are then calculated and compared to the values generated from the publicly available Dutch national DTM dataset with a resolution of 50 cm. Our results show considerable differences in MDS, RR and CT when calculated for the different input resolution datasets. Using DTMs that do not sufficiently capture microtopography leads to underestimation of MDS and RR, and to overestimation of CT. Our findings indicate that surface runoff indicators, and thereby the surface runoff response of a saturated surface to rainfall events, are defined at scales smaller than the scales of typically available DTMs. Understanding surface runoff through modelling studies therefore requires a framework that accounts for this lack of information arising from using coarser resolution DTMs. We demonstrate a linear relationship between MDS values generated from the different resolution DTMs. This opens the possibility of using empirical scaling relationships between high- and lower-resolution DTMs to account for microtopography. Repetition of our measurements on similar surfaces would contribute to establishing such empirical scaling relationships. Our results should be seen as indicative of flat landscapes and surfaces where centimetre scale microtopography is relevant.     

In situ characterization of grain‐scale fluvial morphology using Terrestrial Laser Scanning

The grain‐scale morphology of fluvial sediments is an important control on the character and dynamics of river systems; however current understanding of its role is limited by the difficulties of robustly quantifying field surface morphology. Terrestrial Laser Scanning (TLS) offers a new methodology for the rapid acquisition of high‐resolution and high‐precision surface elevation data from in situ sediments. To date, most environmental and fluvial applications of TLS have focused on large‐scale systems, capturing macroscale morphologies. Application of this new technology at scales necessary to characterize the complexity of grain‐scale fluvial sediments therefore requires a robust assessment of the quality and sources of errors in close‐range TLS data. This paper describes both laboratory and field experiments designed to evaluate close‐range TLS for sedimentological applications and to develop protocols for data acquisition. In the former, controlled experiments comprising high‐resolution scans of white, grey and black planes and a sphere were used to quantify the magnitude and source of three‐dimensional (3D) point errors resulting from a combination of surface geometry, reflectivity effects and inherent instrument precision. Subsequently, a methodology for the collection and processing of grain‐scale TLS data is described through an application to a coarse grained gravel system, the River Feshie (D₅₀ 32 to 63 mm). This stepwise strategy incorporates averaging repeat scans and filtering scan artefact and non‐surface points using local 3D search algorithms. The sensitivity of the results to the filter parameter values are assessed by careful internal validation of Digital Terrain Models (DTMs) created from the resulting point cloud data. The transferability of this methodology is assessed through application to a second river, Bury Green Brook, dominated by finer gravel (D₅₀ 18 to 33 mm). The factor limiting the resolution of DTMs created from this second dataset was found to be the relative sizes of the laser footprint and smallest grains. Copyright © 2009 John Wiley & Sons, Ltd.     

Urban flood modelling combining top-view LiDAR data with ground-view SfM observations

Remote Sensing technologies are capable of providing high-resolution spatial data needed to set up advanced flood simulation models. Amongst them, aerial Light Detection and Ranging (LiDAR) surveys or Airborne Laser Scanner (ALS) systems have long been used to provide digital topographic maps. Nowadays, Remote Sensing data are commonly used to create Digital Terrain Models (DTMs) for detailed urban-flood modelling. However, the difficulty of relying on top-view LiDAR data only is that it cannot detect whether passages for floodwaters are hidden underneath vegetated areas or beneath overarching structures such as roads, railroads, and bridges. Such (hidden) small urban features can play an important role in urban flood propagation. In this paper, a complex urban area of Kuala Lumpur, Malaysia was chosen as a study area to simulate the extreme flooding event that occurred in 2003. Three different DTMs were generated and used as input for a two-dimensional (2D) urban flood model. A top-view LiDAR approach was used to create two DTMs: (i) a standard LiDAR-DTM and (ii) a Filtered LiDAR-DTM taking into account specific ground-view features. In addition, a Structure from Motion (SfM) approach was used to detect hidden urban features from a sequence of ground-view images; these ground-view SfM data were then combined with top-view Filtered LiDAR data to create (iii) a novel Multidimensional Fusion of Views-Digital Terrain Model (MFV-DTM). These DTMs were then used as a basis for the 2D urban flood model. The resulting dynamic flood maps are compared with observations at six measurement locations. It was found that when applying only top-view DTMs as input data, the flood simulation results appear to have mismatches in both floodwater depths and flood propagation patterns. In contrast, when employing the top-ground-view fusion approach (MFV-DTM), the results not only show a good agreement in floodwater depth, but also simulate more correctly the floodwater dynamics around small urban feature. Overall, the new multi-view approach of combining top-view LiDAR data with ground-view SfM observations shows a good potential for creating an accurate digital terrain map which can be then used as an input for a numerical urban flood model.     

A method for estimating sediment budgets of washover deposits using digital terrain models

Washover fans are located on small barriers in fetch-limited micro-tidal coastal environments in Denmark. These washover fans are formed during high-energy storm events and we present a method to quantify their volumes and to estimate sediment exchanges between washover fans and their adjacent morphologies. We use high resolution digital terrain models (DTMs) based on light detection and ranging (LiDAR) data. We have delineated landforms using known methods of scale analysis and geomorphometric classification. We quantified volumes of the delineated landforms and estimated the related sediment budgets. These computed volumes were compared using different pre-depositional surfaces. Finally, we assessed the sediment exchange and associated sources of sediments of the washover fans. We applied a scale analysis to determine suitable DTM resolution and focal statistics window size as input to a geomorphometric classification analysis. Landform areas and landforms were delineated using morphometric threshold values, and volumes and sediment budgets of the delineated landforms were computed using different assumptions to define the pre-depositional surface. Resulting washover fan volumes were validated against digital elevation model (DEM) of difference (DoD) derived volumes. Sediment budgets were derived from representative volumes of the washover fans and adjacent berms. We show that quantification of washover features derived from DTMs, using geomorphometric analysis is feasible and that the presented approach provides estimates of washover deposit volumes with an accuracy between 1% and 28% compared to control volumes. © 2021 John Wiley & Sons, Ltd.     

An optimized use of limited ground based topographic data for river applications

A prime requirement for hydrological applications,such as sediment budgeting or numerical modelling,is that produced Digital Terrain Models(DTMs)accurately represent the shape of landforms,especially for river reaches where data are not homogeneous.DTM error is a function of data point measurement accuracy and density and also of the field survey strategy when limited amounts of data will be acquired.This paper aims to advance the importance of the field survey strategy for the specific,but common cases,where only limited topographic data will be available.This methodology is based on the idea that any feature can be properly described by a set of cross sections and breaklines describing both main and secondary directions of the flow.Then,a longitudinal linear interpolation can be applied to the defined homogeneous zones.This morphologically oriented(MO)method that includes data acquisition strategy and interpolation,was validated using a reference DTM derived from LiDAR measurements.An estimation of the uncertainties also is suggested based on the distance of the nearest point and the local slope using a geographically weighted regression.The proposed MO method is typically applicable to Alpine river reaches characterized by multiple channels that may always be underwater and not navigable such as an alternate bar system with secondary and transverse channels.     

Investigating the geomorphological potential of freely available and accessible structure‐from‐motion photogrammetry using a smartphone

We test the acquisition of high‐resolution topographic and terrain data using hand‐held smartphone technology, where the acquired images can be processed using technology freely available to the research community. This is achieved by evaluating the quality of digital terrain models (DTM) of a river bank and an Alpine alluvial fan generated with a fully automated, free‐to‐use, structure‐from‐motion package and a smartphone integrated camera (5 megapixels) with terrestrial laser scanning (TLS) data used to provide a benchmark. To evaluate this approach a 16.2‐megapixel digital camera and an established, commercial, close‐range and semi‐automated software are also employed, and the product of the four combinations of the two types of cameras and software are compared. Results for the river bank survey demonstrate that centimetre‐precision DTMs can be achieved at close range (10 m or less), using a smartphone camera and a fully automated package. Results improve to sub‐centimetre precision with either higher‐resolution images or by applying specific post‐processing techniques to the smartphone DTMs. Application to an entire Alpine alluvial fan system shows the degradation of precision scales linearly with image scale, but that (i) the expected level of precision remains and (ii) difficulties in separating vegetation and sediment cover within the results are similar to those typically found when using other photo‐based techniques and laser scanning systems. Copyright © 2014 John Wiley & Sons, Ltd.     

Monitoring and reconstructing past biogeomorphic succession within fluvial corridors using stereophotogrammetry

Past fluvial biogeomorphic succession dynamics, i.e. reciprocal interactions and adjustments between vegetation growth and fluvial landform construction, were monitored and reconstructed using stereophotogrammetry. The four‐dimensional spatio‐temporal stereophotogrammetric analyses were based on the use of archival analogue and digital aerial photographs. First, we tested the relevance of the technique to produce floodplain digital terrain models (DTMs) and cover height models (CHMs) of the dynamic River Allier, France, and compared the models derived from photogrammetric procedures to field measurements for CHMs and to LiDAR data for DTMs. Automatic photogrammetric procedures tended to create inaccurate digital models with production of outliers, incomplete sectors and areas of confusion especially for analogue stereo‐pairs. Expert correction using stereoscopic viewing improved the vertical accuracy of the digital models, but the vegetation height tended to be underestimated: approximately 0.50 m for vegetation heights less than 10 m, up to 1.50 m for tree heights higher than 25 m. Second, we applied this method to a wooded point bar located on the channelized River Garonne, France. At the scale of the point bar, accurate biogeomorphic maps that show terrain and vegetation height changes in all three spatial dimensions were produced and accurate vegetation growth curves from the early stages of establishment until maturity were extracted. Assuming that a set of conditions is satisfied (e.g. spatial scale of investigation, quality of the photographs), our results show that the photogrammetric method applied in this research can be used operationally to detect and quantify present fluvial biogeomorphic dynamics (i.e. changes of topography and vegetation canopy height) within fluvial corridors of temperate rivers with satisfactory accuracy. Copyright © 2016 John Wiley & Sons, Ltd.     

Use of fused airborne scanning laser altimetry and digital map data for urban flood modelling

Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, digital surface models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub‐metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. This paper describes the development of a LiDAR post‐processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post‐processing produces a digital terrain model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR‐derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ～1 m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a two‐dimensional finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features (such as buildings and roads) and taller vegetation features (such as trees and hedges). This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features. Copyright © 2007 John Wiley & Sons, Ltd.     

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

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. Copyright © 2009 John Wiley & Sons, Ltd.     

Basin‐scale methods for predicting salmonid spawning habitat via grain size and riffle spacing,tested in a California coastal drainage

Basin‐scale predictive geomorphic models for river characteristics, particularly grain size, can aid in salmonid habitat identification. However, these basin‐scale methods are largely untested with actual habitat usage data. Here, we develop and test an approach for predicting grain size distributions from high resolution LiDAR (Light Detection and Ranging)‐derived topographic data for a 77 km² watershed along the central California Coast. This approach improves on previous efforts in that it predicts the full grain size distribution and incorporates an empirically calibrated shear stress partitioning factor. The predicted grain size distributions are used to calculate the fraction of the bed area movable by spawning fish. We then compare the ‘movable fraction’ with 7 years of observed spawning data. We find that predicted movable fraction explains the paucity of spawning in the upper reaches of the study drainage, but does not explain variation along the mainstem. In search of another morphologic characteristic that may help explain the variation within the mainstem, we measure riffle density, a proxy for physical habitat complexity. We find that field surveys of riffle density explain 64% of the variation in spawning in these mainstem reaches, suggesting that within reaches of appropriate sized gravel, spawning density is related to riffle density. Because riffle density varies systematically with channel width, predicting riffle spacing is straightforward with LiDAR data. Taken together, these findings demonstrate the efficacy of basin‐scale spawning habitat predictions made using high‐resolution digital elevation models. Copyright © 2016 John Wiley & Sons, Ltd.