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     

Variations in multiscale curvature distribution and signatures of LiDAR DTM errors

The development of high resolution LiDAR digital terrain models (DTMs) has enabled the exploration of the statistical signature of morphology on curvature distributions. This work analyzes Minimum Curvature distributions to identify the statistical signature of two types of LiDAR‐DTM errors (outliers and striping artifacts) in the derived estimates, rather than morphology itself. The analysis shows the importance of modeling these errors correctly, in relation to the scale of analysis and DTM resolution, in order to have reliable curvature estimates. Nine DTMs of different morphological areas are considered, and grouped into a training dataset (without errors) and a test dataset (with errors). In the training dataset, the original DTMs are considered as true values; errors are then applied to these data. Minimum Curvature is computed at multiple scales from each DTM: changes in curvature distributions due only to morphology and scale are characterized from the original data; error effects are then identified from the datasets with simulated errors, and validated against the test dataset. The analysis shows that outliers and striping artifacts can be realistically simulated by heavily left tailed distributions. For DTMs without errors, the scale‐dependent change in curvature distribution is primarily controlled by real morphology. When DTMs include errors, curvature distributions become controlled by these errors, whose propagation depends on error distribution, error spatial correlation, and the scale of analysis. This study shows that the curvature distributions are impacted upon differently by striping artifacts and outliers, and that these are clearly distinguishable from the signal of morphological features: a scale‐dependent change in curvature distribution can therefore be interpreted as the signature of these specific errors, rather than morphology. Copyright © 2012 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.     

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.     

Could surface roughness be a poor proxy for landslide age? Results from the Swabian Alb,Germany

The potential of surface roughness to quantify geomorphological landforms and processes has been enhanced with the availability of high‐resolution digital terrain models (DTM). Recent studies that attempt to identify landslide features with surface roughness have suggested that this measure of topographic heterogeneity may also be applied to estimate the relative age of landslides. This is a provisional study that explores the potential of this relationship by assessing the ability of surface roughness to act as a proxy for relative landslide age. The surface roughness for a set of 12 dated landslides in the Swabian Alb that occurred between 1789 and 1985 was calculated from a 1 m² spatial resolution LiDAR DTM with three algorithms: root‐mean‐square‐height (RMSH), standard deviation of slope (SDS), and direction cosine eigenvalue ratios (DCE). Scale‐dependence was analysed by calculating surface roughness for a range of moving window sizes (3 × 3, 5 × 5, 9 × 9 and 15 × 15), and surface roughness for each landslide was summarized by the median and upper quartile. Only weak correlations (best Spearman's rho 0.58) were present between landslide age and surface roughness. This correlation becomes weaker with increasing moving window size. Given weak observed associations and discussed challenges pertaining to the complexities of landslide morphology change over time, we currently find that surface roughness alone may not be justifiable to act as a proxy for landslide age for our study region. Furthermore, we recommend future studies should focus on addressing possible natural and anthropogenic factors such as land use change that may alter surface roughness. These studies may focus on one of the three roughness measures used here as they are strongly correlated. Copyright © 2014 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.     

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.     

Improving the computation of the gravitational terrain effect close to ground stations in the GTE software

The precise computation of the vertical gravitational attraction of the topographic masses (terrain correction) is still being studied both for geodetic and geophysical applications. In fact, it is essential in high precision geoid estimation by means of the well-known remove-compute-restore technique, which is used to isolate the gravitational effects of anomalous masses in exploration geophysics. The terrain correction can be evaluated exploiting a Digital Terrain Model (DTM) in different ways, such as classical numerical integration, prisms, tesseroids, polyhedrons, and/or Fast Fourier Transform techniques. The increasing resolution of recently developed DTMs, the increasing number of observation points, and the increasing accuracy of gravity data represent, nowadays, major challenges for the terrain correction computation. Classical point mass approximation and prism based-algorithms are indeed too slow, while Fourier-based algorithms are usually too much approximate when compared to the required accuracy. In this work, we improve the Gravity Terrain Effects (GTE) algorithm, the innovative tool that exploits a combined prism-Fast Fourier Transform approach especially developed for airborne gravimetry, to compute the terrain correction on the surface of the DTM (i.e. corresponding to the ground stations and/or its vicinity). This required development of a proper adjustment of the algorithms implemented within the GTE software and also to define and implement a procedure to overcome the problems of the computation of the gravitational effects due to the actual slope of the terrain close to the stations. The latter problem is thoroughly discussed and solved by testing different solutions like concentric cylindrical rings, triangulated polyhedrons, or ultra-high resolution squared prisms. Finally, numerical tests to prove the temporal efficiency and the computational performances of the improved GTE software to compute terrain correction for ground stations are also presented.     

Innovative analysis and use of high‐resolution DTMs for quantitative interrogation of Earth‐surface processes

This is the era of digital landscapes; the widespread availability of powerful sensing technologies has revolutionized the way it is possible to interrogate landscapes in order to understand the processes sculpting them. Vastly greater areas have now been acquired at ‘high resolution’: currently tens of metres globally to millimetric precision and accuracy locally. This permits geomorphic features to be visualized and analysed across the scales at which Earth‐surface processes operate. Especially exciting is the capturing of process dynamics in repeated surveying, which will only become more important with low‐cost accessible data generation through techniques such as Structure from Motion (SfM). But the key challenge remains; to interpret high resolution Digital Terrain Models (DTMs), particularly by extracting geomorphic features in robust and objective ways and then linking the observed features to the underlying physical processes. In response to the new data and challenges, recent years have seen improved processing of raw data into DTMs, development of data fusion techniques, novel quantitative analysis of topographic data, and innovative geomorphological mapping. The twelve papers collected in this volume sample this progress in interrogating Earth‐surface processes through the analysis of DTMs. They cover a wide range of disciplines and spatio‐temporal scales, from landslide prone landscapes, to agriculturally modified regions, to mountainous landscapes, and coastal zones. They all, however, showcase the quantitative exploitation of information contained in high‐resolution topographic data that we believe will underpin the improvement of our understanding of many elements of Earth‐surface processes. Most of the papers introduced here were first presented in a conference session at the European Geosciences Union General Assembly in 2011. Copyright © 2014 John Wiley & Sons, Ltd.     

How does landscape structure influence catchment transit time across different geomorphic provinces?

Despite an increasing number of empirical investigations of catchment transit times (TTs), virtually all are based on individual catchments and there are few attempts to synthesize understanding across different geographical regions. Uniquely, this paper examines data from 55 catchments in five geomorphic provinces in northern temperate regions (Scotland, United States of America and Sweden). The objective is to understand how the role of catchment topography as a control on the TTs differs in contrasting geographical settings. Catchment inverse transit time proxies (ITTPs) were inferred by a simple metric of isotopic tracer damping, using the ratio of standard deviation of δ¹⁸O in streamwater to the standard deviation of δ¹⁸O in precipitation. Quantitative landscape analysis was undertaken to characterize the catchments according to hydrologically relevant topographic indices that could be readily determined from a digital terrain model (DTM). The nature of topographic controls on transit times varied markedly in different geomorphic regions. In steeper montane regions, there are stronger gravitational influences on hydraulic gradients and TTs tend to be lower in the steepest catchments. In provinces where terrain is more subdued, direct topographic control weakened; in particular, where flatter areas with less permeable soils give rise to overland flow and lower TTs. The steeper slopes within this flatter terrain appear to have a greater coverage of freely draining soils, which increase sub‐surface flow, therefore increasing TTs. Quantitative landscape analysis proved a useful tool for inter‐catchment comparison. However, the critical influence of sub‐surface permeability and connectivity may limit the transferability of predictive tools of hydrological function based on topographic parameters alone. Copyright © 2009 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.     

Hydrological runoff modelling by the use of remote sensing data with reference to the 1993–1994 and 1995 floods in the river Rhine catchment

In hydrological modelling of runoff processes, including water balance, various input data and parameters can be acquired or estimated by the use of remote sensing (RS) techniques.The acquisition and use of synoptic RS areal information rather than traditional point information is an important issue in hydrology. Hydrological models allow runoff/water balance in catchments to be calculated and flow routing within flow channels to be done. For runoff and water balance computations land use, soil moisture, detection of snow and ice, digital terrain models (DTM), as well as hydrometeorological information and discharge are important. For flow routing, water level information, geometric–topographic information such as cross-sections for normal and flood conditions, coefficient of roughness and velocity of flow and its cross-sectional distribution are required. In addition, water level information (lower and upper level) is needed for shipping and for design purposes. In the German part of the River Rhine catchment, several focus areas in the December 1993–January 1994 and January 1995 floods were covered with RS data [ERS-1 and airborne SAR, both C-band VV, passive microwave (18·7, 36·5, 89 GHz), TIR, UV, aerial photographs (b/w PAN, b/w NIR)], giving a good opportunity for a comparison of methods. Evaluation is still continuing. The importance of soil saturation for flood generation and, therefore, for flood monitoring, was shown on this occasion. The use of ERS SAR data for soil moisture estimation is currently being investigated by the Federal Institute of Hydrology. Also, the need for emergency schemes for data acquisition and easy, quick and affordable RS data dissemination was demonstrated. The assimilation of RS data with GIS information such as DTMs, including relevant topographic features like dams, which is omitted in currently available raster digital elevation models, is promising. RS altimetry techniques can be a step towards high resolution DTMs for hydrological purposes. Ground truth reference data are still needed. © 1997 John Wiley & Sons, Ltd.     

Long‐range terrestrial laser scanning for geomorphological change detection in alpine terrain – handling uncertainties

Long‐range terrestrial laser scanning (TLS) is an emerging method for the monitoring of alpine slopes in the vicinity of infrastructure. Nevertheless, deformation monitoring of alpine natural terrain is difficult and becomes even more challenging with larger scan distances. In this study we present approaches for the handling of spatially variable measurement uncertainties in the context of geomorphological change detection using multi‐temporal data sets. A robust distance measurement is developed, which deals with surface roughness and areas of lower point densities. The level of detection (LOD), i.e. the threshold distinguishing between real surface change and data noise, is based on a confidence interval considering the spatial variability of TLS errors caused by large laser footprints, low incidence angles and surface roughness. Spatially variable positional uncertainties are modelled for each point according to its range and the object geometry hit. The local point cloud roughness is estimated in the distance calculation process from the variance of least‐squares fitted planes. Distance calculation and LOD assessment are applied in two study areas in the Eastern Alps (Austria) using multi‐temporal laser scanning data sets of slopes surrounding reservoir lakes. At Finstertal, two TLS point clouds of high alpine terrain and scanned from ranges between 300 and 1800 m are compared. At Gepatsch, the comparison is done between an airborne laser scanning (ALS) and a TLS point cloud of a vegetated mountain slope scanned from ranges between 600 and 3600 m. Although these data sets feature different conditions regarding the scan setup and the surface conditions, the presented approach makes it possible to reliably analyse the geomorphological activity. This includes the automatic detection of rock glacier movement, rockfall and debris slides, even in areas where a difference in vegetation cover could be observed. Copyright © 2016 John Wiley & Sons, Ltd.     

Drone photogrammetry and KMeans point cloud filtering to create high resolution topographic and inundation models of coastal sediment archives

Coastal areas are vulnerable to the impacts of tropical cyclones (TC), tsunamis and other water super‐elevation events, but the frequency of these events is often poorly represented by conventional records. Coastal overwash deposits (including washover fans) can provide a longer‐term archive of event frequency. Because of their low‐gradient geomorphic form, washover fans require high accuracy (centimetre‐resolution) topographic models to understand patterns of connectivity and dynamics that control archive formation. Using images collected by a remotely piloted aircraft system (RPAS, or ‘drone’) and Structure‐from‐Motion (SfM) photogrammetry techniques, we apply a novel point‐cloud filtering technique based on KMeans classification of the R‐G‐B colour of each X‐Y‐Z point to remove vegetation and create a centimetre‐resolution and accuracy bare‐earth digital terrain model (DTM) of a washover fan in Exmouth Gulf (Western Australia). Using the RPAS‐SfM orphophoto and DEM data, supported by ground‐penetrating radar (GPR) and field stratigraphic analysis, we show how this approach can be applied to understand dynamics controlling low‐gradient geomorphic landforms, using an example of a washover fan sedimentary archive in northwestern Australia created by extreme overwash events. Our approach reveals the likely role of backflooding and terrestrial runoff in creating backwater environment for sub‐aqueous deposition and good sediment preservation and identifies key areas to target for detailed dating and stratigraphic analysis of a potentially decadal to sub‐millennial resolution sediment archive of TC activity. Copyright © 2018 John Wiley & Sons, Ltd.     

The potential of digital filtering of generic topographic data for geomorphological research

High resolution terrain models generated from widely available Interferometric Synthetic Aperture Radar (IfSAR) and digital photogrammetry are an exciting resource for geomorphological research. However, these data contain error, necessitating pre‐processing to improve their quality. We evaluate the ability of digital filters to improve topographic representation, using: (1) a Gaussian noise removal filter; (2) the proprietary filters commonly applied to these datasets; and (3) a terrain sensitive filter, similar to those applied to laser altimetry data. Topographic representation is assessed in terms of both absolute accuracy measured with reference to independent check data and derived geomorphological variables (slope, upslope contributing area, topographic index and landslide failure probability) from a steepland catchment in northern England. Results suggest that proprietary filters often degrade or fail to improve precision. A combination of terrain sensitive and Gaussian filters performs best for both IfSAR and digital photogrammetry datasets, improving the precision of photogrammetry digital elevation models (DEMs) by more than 50 per cent relative to the unfiltered data. High‐frequency noise and high‐magnitude gross errors corrupt geomorphological variables derived from unfiltered photogrammetry DEMs. However, a terrain sensitive filter effectively removes gross errors and noise is minimized using a Gaussian filter. These improvements propagate through derived variables in a landslide prediction model, to reduce the area of predicted instability by up to 29 per cent of the study area. Interferometric Synthetic Aperture Radar is susceptible to removal of topographic detail by oversmoothing and its errors are less sensitive to filtering (maximum improvement in precision of 5 per cent relative to the raw data). Copyright © 2008 John Wiley and Sons, Ltd.     

Geomorphic process signatures reshaping sub-humid Mediterranean badlands: 2. Application to 5-year dataset

Badland landscapes exhibit high erosion rates and represent the main source of fine sediments in some catchments. Advances in high-resolution topographic methods allow analysis of topographic changes at high temporal and spatial scales. We apply the Mapping Geomorphic Processes in the Environment (MaGPiE) algorithm to infer the main geomorphic process signatures operating in two sub-humid badlands with contrasting morphometric attributes located in the Southern Pyrenees. By interrogating a 5-year dataset of seasonal and annual topographic changes, we examine the variability of geomorphic processes at multiple temporal scales. The magnitude of geomorphic processes is linked to landform attributes and meteorological variables. Morphometric differences between both adjacent badlands allow us to analyse the role of landform attributes in the main geomorphic process reshaping landscapes subjected to the same external forcing (i.e. rainfall and temperature). The dominant geomorphic process signatures observed in both badlands are different, despite their close proximity and the same rainfall and temperature regimes. Process signatures determining surface lowering in the gently sloping south-facing badland, characterized by lower connectivity and more vegetation cover, are driven by surface runoff-based processes, both diffuse (causing sheet washing) and concentrated (determining cutting and filling, rilling and gullying). The steeper, more connected north-facing slopes of the other badland are reshaped by means of gravitational processes, with mass wasting dominating topographic changes. In terms of processes determining surface raising, both mass wasting and cutting and filling are most frequently observed in both badlands. There is a clear near-balanced feedback between both surface-raising and -lowering processes that becomes unbalanced at larger temporal scales due to the thresholds overcome, as the volume associated with surface lowering becomes higher than that associated with raising-based processes. Rainfall variables control surface flow processes, while those variables associated with low temperature have a significant relation with mass movement-based processes and other localized processes such as regolith cohesion loss. Finally, our results point out that morphometry (slope and connectivity) together with vegetation cover are key factors determining geomorphic processes and associated topographic changes. © 2020 John Wiley & Sons, Ltd.     

Mitigating systematic error in topographic models for geomorphic change detection: accuracy,precision and considerations beyond off-nadir imagery

Unmanned aerial vehicles (UAVs) and structure-from-motion photogrammetry enable detailed quantification of geomorphic change. However, rigorous precision-based change detection can be compromised by survey accuracy problems producing systematic topographic error (e.g. ‘doming’), with error magnitudes greatly exceeding precision estimates. Here, we assess survey sensitivity to systematic error, directly correcting topographic data so that error magnitudes align more closely with precision estimates. By simulating conventional grid-style photogrammetric aerial surveys, we quantify the underlying relationships between survey accuracy, camera model parameters, camera inclination, tie point matching precision and topographic relief, and demonstrate a relative insensitivity to image overlap. We show that a current doming-mitigation strategy of using a gently inclined (<15°) camera can reduce accuracy by promoting a previously unconsidered correlation between decentring camera lens distortion parameters and the radial terms known to be responsible for systematic topographic error. This issue is particularly relevant for the wide-angle cameras often integrated into current-generation, accessible UAV systems, frequently used in geomorphic research. Such systems usually perform on-board image pre-processing, including applying generic lens distortion corrections, that subsequently alter parameter interrelationships in photogrammetric processing (e.g. partially correcting radial distortion, which increases the relative importance of decentring distortion in output images). Surveys from two proglacial forefields (Arolla region, Switzerland) showed that results from lower-relief topography with a 10°-inclined camera developed vertical systematic doming errors > 0·3 m, representing accuracy issues an order of magnitude greater than precision-based error estimates. For higher-relief topography, and for nadir-imaging surveys of the lower-relief topography, systematic error was < 0·09 m. Modelling and subtracting the systematic error directly from the topographic data successfully reduced error magnitudes to values consistent with twice the estimated precision. Thus, topographic correction can provide a more robust approach to uncertainty-based detection of event-scale geomorphic change than designing surveys with small off-nadir camera inclinations and, furthermore, can substantially reduce ground control requirements. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd     

Inter‐catchment comparison to assess the influence of topography and soils on catchment transit times in a geomorphic province; the Cairngorm mountains,Scotland

A quantitative, process relevant analysis of ten mesoscale (ca 10–90 km²) catchments in the Cairngorm mountains, Scotland was carried out using 10‐m digital terrain models (DTMs). This analysis produced a range of topographic indices that described differences in the landscape organisation of the catchments in a way that helped explain contrasts in their hydrology. Mean transit time (MTT)—derived from isotopic tracer data—was used as a metric that characterised differences in the hydrological function of the ten catchments. Some topographic indices exhibited significant correlations with MTT. Most notably, the ratio of the median flow path length to the median flow path gradient was negatively correlated with MTT, whilst the median upslope area was positively correlated. However, the relationships exhibited significant scatter which precluded their use as a predictive tool that could be applied to ungauged basins in this region. In contrast, maps of soil hydrological properties could be used to differentiate hydrologically responsive soils (which are dominated by overland flow and shallow sub‐surface storm flow) from free draining soils (that facilitate deeper sub‐surface flows). MTT was negatively correlated with the coverage of responsive soils in catchments. This relationship provided a much better basis for predicting MTT in ungauged catchments in this geomorphic province. In the Cairngorms, the extensive cover of various glacial drift deposits appears to be a first order control on soil distributions and strongly influences the porosity and permeability of the sub‐surface. These catchment characteristics result in soil cover being a much more discerning indicator of hydrological function than topography alone. The study highlights the potential of quantitative landscape analysis in catchment comparison and the need for caution in extrapolating relationships between landscape controls and metrics of hydrological function beyond specific geomorphic provinces. Copyright © 2009 John Wiley & Sons, Ltd.     

复杂地形条件下航空伽玛能谱地形改正方法探讨

应用矩形辐射体航空伽玛辐射场理论,研究应用于复杂地形条件下的航空伽玛能谱资料的地形改正方法,并针对该方法进行验证. 本文利用航空物探测量过程中获得的DTM数据（达到了地形改正所需的地形起伏数据精度）,应用矩形辐射体航空伽玛辐射场理论,根据地面辐射体与航空伽玛场分布之间的正演关系,对航空伽玛能谱解释方法的原理进行了正演分析和反演推导. 探索出一种按影响角进行地形改正的方法. 该方法特点是适合于任意飞行方式(缓地形和水平飞行均可)和任意地形条件航空伽玛能谱的逐点地形改正. 结果表明该地形改正方法能够基本消除航空伽玛能谱测量中的地形起伏产生的影响,经地形修正后的航空伽玛能谱异常能较正确地反映地面辐射体的真实情况.