Deep learning methods applied to digital elevation models: state of the art

Deep Learning (DL) has a wide variety of applications in various thematic domains, including spatial information. Although with limitations, it is also starting to be considered in operations related to Digital Elevation Models (DEMs). This study aims to review the methods of DL applied in the field of altimetric spatial information in general, and DEMs in particular. Void Filling (VF), Super-Resolution (SR), landform classification and hydrography extraction are just some of the operations where traditional methods are being replaced by DL methods. Our review concludes that although these methods have great potential, there are aspects that need to be improved. More appropriate terrain information or algorithm parameterisation are some of the challenges that this methodology still needs to face.Functional Quality of Digital Elevation Models in Engineering’ of the State Agency Research of SpainPID2019-106195RB- I00/AEI/10.13039/50110001103

Semi-automated geomorphological mapping applied to landslide hazard analysis

Computer-assisted three-dimensional (3D) mapping using stereo and multi-image (“softcopy”) photogrammetry is shown to enhance the visual interpretation of geomorphology in steep terrain with the direct benefit of greater locational accuracy than traditional manual mapping. This would benefit multi-parameter correlations between terrain attributes and landslide distribution in both direct and indirect forms of landslide hazard assessment. Case studies involve synthetic models of a landslide, and field studies of a rock slope and steep undeveloped hillsides with both recently formed and partly degraded, old landslide scars. Diagnostic 3D morphology was generated semi-automatically both using a terrain-following cursor under stereo-viewing and from high resolution digital elevation models created using area-based image correlation, further processed with curvature algorithms. Laboratory-based studies quantify limitations of area-based image correlation for measurement of 3D points on planar surfaces with varying camera orientations. The accuracy of point measurement is shown to be non-linear with limiting conditions created by both narrow and wide camera angles and moderate obliquity of the target plane. Analysis of the results with the planar surface highlighted problems with the controlling parameters of the area-based image correlation process when used for generating DEMs from images obtained with a low-cost digital camera. Although the specific cause of the phase-wrapped image artefacts identified was not found, the procedure would form a suitable method for testing image correlation software, as these artefacts may not be obvious in DEMs of non-planar surfaces.Modelling of synthetic landslides shows that Fast Fourier Transforms are an efficient method for removing noise, as produced by errors in measurement of individual DEM points, enabling diagnostic morphological terrain elements to be extracted. Component landforms within landslides are complex entities and conversion of the automatically-defined morphology into geomorphology was only achieved with manual interpretation; however, this interpretation was facilitated by softcopy-driven stereo viewing of the morphological entities across the hillsides.In the final case study of a large landslide within a man-made slope, landslide displacements were measured using a photogrammetric model consisting of 79 images captured with a helicopter-borne, hand-held, small format digital camera. Displacement vectors and a thematic geomorphological map were superimposed over an animated, 3D photo-textured model to aid non-stereo visualisation and communication of results

Modelling the spatial distribution of DEM Error

Assessment of a DEM’s quality is usually undertaken by deriving a measure of DEM accuracy – how close the DEM’s elevation values are to the true elevation. Measures such as Root Mean Squared Error and standard deviation of the error are frequently used. These measures summarise elevation errors in a DEM as a single value. A more detailed description of DEM accuracy would allow better understanding of DEM quality and the consequent uncertainty associated with using DEMs in analytical applications. The research presented addresses the limitations of using a single root mean squared error (RMSE) value to represent the uncertainty associated with a DEM by developing a new technique for creating a spatially distributed model of DEM quality – an accuracy surface. The technique is based on the hypothesis that the distribution and scale of elevation error within a DEM are at least partly related to morphometric characteristics of the terrain. The technique involves generating a set of terrain parameters to characterise terrain morphometry and developing regression models to define the relationship between DEM error and morphometric character. The regression models form the basis for creating standard deviation surfaces to represent DEM accuracy. The hypothesis is shown to be true and reliable accuracy surfaces are successfully created. These accuracy surfaces provide more detailed information about DEM accuracy than a single global estimate of RMSE

GEOMORPHOLOGICAL MAPPING OF PART OF THE NIGER DELTA, NIGERIA USING DEM AND MULTISPECTRAL IMAGERY

This study utilised geo-information technology to carry out a geomorphological mapping of a part of the Niger Delta. Satellite image analysis was based on bi-annual seasonal approach using a combination of visual analysis of the geometry, site, situation, colour, and season for analysis of the non-topographic features. The study also utilised virtual and onsite fieldworks and existing geomorphologic information to interpret and analyse topographic and bathymetric features. First-order topographic features (elevation) and second level features including slope, aspect, curvature and mathematically exaggerated shaded relief were extracted from DEM. Relief classification was based on average elevation differences, hill shade, slope, and aspect. Three main non-topographic landforms were identified; the permanent rivers with stable meanders, perennially-active systems of creeks and fluvial landforms including scroll bars and oxbows. With the exception of higher elevation values towards the north-western fringe, the elevation ranges between mean sea level and 1 metre above sea level thus establishing a somewhat flat terrain. These areas were filled with meandering streams, sinuous creeks and watercourses flanked by mangrove vegetation.  In the north-western area, elevation rose close to approximately 4 metres in most of the area with a peak of 10 metres.  Generally, the cumulative area-slope analysis yielded a deltaic plain with generalised slope ≤ 20. Overall two elevation-based geographically differentiated morphological units were identified; tidal mudflats and saltmarshes. The study recommends that to provide needed information for resource planning and management, further investigation should be carried out with a view to modelling probable ecological and geomorphological changes in the entire Niger Delta.   &nbsp

Remote sensing of geomorphodiversity linked to biodiversity — part III: traits, processes and remote sensing characteristics

Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well as the constraints of monitoring the diversity of geomorphology using RS, are discussed. RS-aided techniques that can be used for monitoring geomorphodiversity in regimes with changing land-use intensity are presented. Further, new approaches of geomorphic traits that enable the monitoring of geomorphodiversity through the valorisation of RS data from multiple missions are discussed as well as the ecosystem integrity approach. Likewise, the approach of monitoring the five characteristics of geomorphodiversity recording with RS is discussed, as are existing approaches for recording spectral geomorhic traits/ trait variation approach and indicators, along with approaches for assessing geomorphodiversity. It is shown that there is no comparable approach with which to define and record the five characteristics of geomorphodiversity using only RS data in the literature. Finally, the importance of the digitization process and the use of data science for research in the field of geomorphology in the 21st century is elucidated and discussed

Analysis of the efficacy of LiDAR data as a tool for archaeological prospection at the Highland Valley Copper Mine

As heritage resource management and Indigenous heritage stewardship moves into the forefront of project design and operational planning in British Columbia, researchers look for innovative ways to foster impact assessment efficiency without sacrificing quality. In this study I explore methods for employing LiDAR-derived digital elevation models as a tool for archaeological prospection within the Highland Valley Copper Mine. A review of contemporary and formative LiDAR-analysis archaeological prospection research was conducted to identify the most appropriate visualization techniques and data management workflow. Specific methods for the identification of microtopographic relief with the potential to contain archaeological resources were developed. The efficacy of LiDAR-based topographic analysis using manual feature extraction is validated through comparison with georeferenced survey and ground-truthing data provided by my research partners at the Nlaka’pamux Nation Tribal Council. The LiDAR analysis method identified a high percentage of recorded archaeological sites and meets provincial requirements for a moderately effective predictive model. Results of LiDAR analysis are presented along with recommendations for improved performance using best practices and an interpolation workflow. An analysis of the cost implications of incorporating LiDAR-survey into the heritage management workflow in the study area identified a significant benefit during survey. These savings would allow for redistribution of resources and potentially a greater focus on mitigative systematic data recovery. The use of remote sensing technologies and methods can have a positive impact on heritage resource management industry in BC by decreasing program costs while maintaining quality

Remote sensing of subglacial bedforms from the British Ice Sheet using an Unmanned Aerial System (UAS): Problems and Potential.

Photogrammetry can be applied to the results of UAS (Unmanned Aerial Systems) based photographic surveys to produce high resolution DEMs (Digital Elevation Models) of small areas (c. 1 km2). However, this method has not been widely used in academia due to photogrammetric programmes working poorly with the ill constrained intrinsic and extrinsic properties that often accompany UAS based photographs. In this study a PAMS (Personal Aerial Mapping System) SmartOne B UAS was used to provide image sets for testing a number of different photogrammetry packages; LPS, Bundler, PhotoSynth and PhotoScan, with the aim of producing sub-metric accuracy DEMs with a low complexity methodology and without significant financial investment. To demonstrate the potential use of a UAS photogrammetric survey methodology it was applied here to an investigation into scale dependant remote sensing of glacial geomorphology. Subglacial bedforms, landforms produced by the flow of ice over land, are thought to ‘seed’ with a minimum horizontal dimension of 100 m. This hypothesis is based on surveys of bedforms across the UK and Ireland using NEXTMap DEMs with 1 m accuracy and 5 m resolution. Here we test that hypothesis using sub-metric accuracy DEMs produced via photogrammetry of an area in the Eden Valley drumlin field, NW England. The UAS was found to be suitable for this type of survey, but only one of the four photogrammetry programmes provided an effective and low complexity methodology. This programme, PhotoScan, was shown to require minimal user training and could produce DEMs from the survey imagery on the day of flying with a standard high performance computer at a resolution of 0.12 m2. The DEM produced was down sampled and validated against pre-existing 1 m LiDAR (Light Detection And Ranging) data of the same area. It showed poor absolute accuracy due to a systematic parabolic error introduced during processing that made quantification of the DEM error problematic. However, estimates of the error additional to this systematic error put it at around 0.5 m which makes the DEM suitable for mapping low amplitude bedforms. Use of the DEM for mapping subglacial bedforms yielded ambiguous results. 17 additional linear ridges were identified that were not visible on the NEXTMap DEM. Their dimensions were not remarkably shorter than the 100 m limit, with only 6 measuring <100 m, but their width was much narrower than those mapped previously. However, whilst these dimensions could suggest that bedforms do not ‘seed’ at a certain size and may fine into smaller features such as flutes, there was no way to demonstrate that they were in fact glacial in origin. This highlighted that whilst sub-metric resolution DEMs are undoubtedly highly useful tools in the survey of glacial bedforms, they may require additional data from field investigations in order for robust conclusions to be drawn due to the numerous processes capable of produce geomorphic features at a sub-metric vertical scale

Derivation of Soil Roughness Using Multi-Temporal Laser Scanning Point Clouds

The present paper deals with the derivation of roughness parameters of soil from laser scanning point clouds, allowing to draw conclusions about properties of the soil (e. g. soil aggregation, soil sealing) and related to this its vulnerability to soil erosion. For this purpose, soil erosion scenes with agricultural cultivation are acquired in five measuring epochs under field conditions. For geo-referencing of the acquired time series of point clouds, a target-based and a data-driven approach are compared. In order to derive roughness parameters, the point clouds are cleaned of vegetation and then modelled to reduce the measurement noise. For this purpose, a collocation-based approach is used, in which a trend surface roughly approximates the point clouds. Remaining systematic deviations, which are caused by the insufficient functional approximation, are caught with the help of a stochastic signal, the variances and correlations lengths of which simultaneously provide information about the soil’s roughness

Mine landform design using natural analogues

Current practice for landscape reconstruction following opencast mining relies on topographic reconstruction, adaptive land management and botanical characterisation. Environmental processes may be altered where reconstructed landforms have significant relief. Consequently, environmental outcomes in cases where there is large scale land forming are unpredictable. Moreover, landscape restoration lacks an integrated methodology, and while many mine closures have detailed ecosystem and biodiversity objectives based on natural analogue areas there has been no reliable way to design these objectives into mine landforms. The methods used in landscape restorations to describe reference conditions are based on generalised environmental factors using regional information and incorporating conceptual models. Such models lack the precision and accuracy required to understand and restore hillslope environmental pattern at mine sites. However, methodological integration and statistical inference models underpinning the spatial inference methods in conservation and landscape ecology, and pedology may be applied to solve this problem. These inference models utilise digital terrain models as the core environmental data incorporating ecological theory to predict biodiversity and species distribution. Also, numerical mass balance models such as water and solute balance, which have been applied to understand environmental processes in landscapes, can be used to assess mine landform design. The objective of the work reported here was to investigate environmental variation, with sufficient accuracy and precision, in natural landscapes to design mature mine landforms and to demonstrate the capacity to predict ecological outcomes. This would extend current best practice - designing mine landforms with predictable hydrological and geotechnical outcomes needed to protect off-site environmental conditions – to the on-site environment after closure. The specific aims of this thesis were to: (i) evaluate the predictability of ecosystems based on regional ecological mapping: (ii) develop and evaluate quantitative, site specific environmental mapping and natural analogue selection methodology; (iii) evaluate a trial final landform cover (reconstructed soil) using water balance, water chemistry monitoring; (iv) design and evaluate a conceptual mine landform through the assessment of environmental processes in natural analogue areas; and (v) make valid predictions of revegetation outcomes on the conceptual landform. In meeting these aims, links between ecological theory, landscape analysis and the current practice in mine landform design were identified. The first phase of the thesis involved environmental investigations and surveys of extensive savanna environments on the Tiwi Islands (7320 km-2) and similar environments in the vicinity of Ranger uranium mine (150 km-2) in northern Australia. This first phase, reported in Chapter 3, investigated the reliability of conceptual landscape models used in regional ecological mapping in predicting ecological patterns in terms of vegetation and soil. The Tiwi Islands was selected because of the relatively uniform parent material and its simplified climate. This allowed the study of physiographic control of soil and vegetation patterns. The results identified correlations between vegetation pattern and landform that were confounded by a subjective and complex land unit model of ecosystems. This investigation enabled the development methodological approach to analogue selection and ecological modelling at Ranger uranium mine – a site that will require a restoration approach so as to meet environmental closure objectives. The second phase is the methodological development – involving an initial reconnaissance, is presented in Chapter 4. This phase was aimed at selecting natural analogue areas for mined land restoration. Environmental pattern recognition involving classification, ordination and network analysis was implemented based on methods of conservation ecology. This led to quantitative landscape model to identify natural analogue areas and design ecosystem surveys. This quantitative landscape model incorporated a grid survey of vegetation and soil variation into a nearby analogue landform that matched the area of mine disturbance. This analogue landform encapsulates the entire ecosystem types observed on rocky substrates in the broader reconnaissance survey. The natural analogue selection incorporated a combination of digital terrain analysis and k-means clustering of primary and secondary terrain variables to classify habitat variation on hillslopes. Landscapes with similar extent to the mine landscape were identified from numerical similarity measures (Bray-Curtis) of fine grained habitat variation and summarised using a dendrogram. The range in hillslope ecosystem types were described from stratified environmental surveys of vegetation and soils along environmental gradients in selected analogue landforms. The results show that the mapped environmental factors in close correlation with water and sediment distribution were strongly associated with observed vegetation patterns in analogue areas at Ranger uranium mine. Environmental grain size and landform extent concepts were therefore introduced using landscape ecology theory to integrate different scales of environmental variation in a way that provides direct context with the area impacted by mining. Fine-grained environmental terrain attributes that describe runoff, erosion and sediment deposition were derived from a digital elevation model and classified using non-hierarchical multivariate methods to create a habitat class map. Patch analysis was used to aggregate this fine-grained environmental pattern into a grid that matched the scale of the mine landform. The objective was to identify landforms that were similar in extent to the reconstructed mine landscape. Ecosystem support depends on soil as well as geomorphic factors. An investigation into critical environmental processes, water balance and solute balance, on a waste rock landform at Ranger uranium mine is presented in Chapter 5 to characterise waste rock soils and investigate cover design options that affect environmental support. This involved monitoring of water balance of a reconstructed soil cover on a waste rock landform for four years and the solute loads for two years. A one dimensional water balance model was parameterised and run based on 21 years of rainfall records so as to assess the long-term effects of varying cover thickness and surface compactness on cover performance. The results show that the quality of runoff and seepage water did not improve substantially after two years as large amount of dissolved metal loads persisted. Also, tree roots interacted with the subsoil drainage-limiting layer at one metre below the land surface in just over two years - and thus altering the hydraulic properties of the layer. Further, the results of water balance simulations indicate that increasing the depth to, and thickness of, the drainage-limiting layer would reduce drainage flux. Increasing layer thickness could also limit tree root penetration. It was also found that surface compaction was the most effective means of limiting deep drainage, which contained high concentrations of dissolved metals. However, surface compaction creates an ecological desert. Therefore long-term rehabilitation of the cover will be required to allow water to infiltrate for it to be available for ecosystems. A cover that can store and release sufficient water to support native savanna eucalypt woodland may need to be three to five metres deep, including a drainage limiting layer at depth so as to slow vertical water movement and comprise a well graded mix of hard rock and weathered rock to provide water storage and erosion resistance. The resulting waste rock soils would be similar, morphologically to the gradational, gravelly soils found in natural analogue areas. The study then shifted from mined land back to a selected natural analogue landscape at Ranger mine in Chapter 6. The fine grained variation in terrain attributes is described to support a landform design that allowed for mine plan estimates of waste rock volumes and pit void volumes. A process of developing and evaluating the landform design was put forward, in the case of Ranger, that begins with key stakeholder consultation, followed by an independent scientific validation using published landform evolution and integrated, surface-groundwater water balance modelling. The natural analogue and draft final landforms were compared in terms of terrain attributes, landform evolution and eco-hydrological processes to identify where improvements could be required. The results of the independent design reviews are contained in confidential reports to Ranger mine and in conference proceedings that are referenced in Chapter 6. Independent validation will be a key element of an ecological landform design process and the application of published eco-hydrological and landform evolution models at the Ranger mine case study site are presented as an example of current best practice. Also, detailed assessment was made of environmental variation and soil and geomorphic range in the selected analogue landscape to support the landform design process with the mining department. Ecological modelling of the distributions of framework species in the reconstructed landscape is proposed as an additional assessment tool in this thesis to validate an ecological landform design methodology. To this end, a detailed environmental survey is presented in Chapter 6 of the soils and vegetation in a selected natural analogue area of Ranger mine to identify common and abundant plant species and their distribution in a similar landscape context to the mined land. This work supported ecological modelling of species distributions in reconstructed and natural landscapes in the following chapter. The results of species distribution models for reconstructed and natural landscapes at the Ranger mine site are reported in Chapter 7. The aim was to predict the distribution of common and abundant native woodland species across a landscape comprising a sculpted, post mining landform within a natural landscape. Species distribution models were developed from observations of species presence-absence at 102 sites in the grid survey of the natural analogue area that was reported in Chapter 6. Issues related to optimising predictor selection and the range of environmental support were investigated by introducing survey sites from the broad area reconnaissance survey reported in Chapter 4. Added to these are the published species abundance data from an independent regional biodiversity survey of rocky, well drained eucalypt woodlands, used as analogues of mined land. Plant species responses to continuous and discrete measures of environmental variation were then analysed using multivariate detrended correspondence analysis and canonical correspondence analysis to select independent variables and assess the relative merits of abundance versus presence absence observations of species. Then, generalised additive statistical methods were used to predict species distributions from primary and secondary terrain variables across the natural analogue area and a reconstructed post-mining landform. This analysis was completed with an assessment of the effect that survey support has on model formulation and accuracy. The scale of the mine landscape was found to provide important context for the stratified environmental surveys needed to support predictive modelling. Extending the geographic range of survey support did not improve model performance, while survey sites remote from the mine introduced some degree of spatial autocorrelation that could reduce the prediction accuracy of species distributions in the mine landscape. Further work is needed to address uncommon species or species with highly constrained environmental ranges and aspects of landform cover design and land management that affect woodland type and vigour. The combined studies reported in this thesis show that the predictability of mine land restorations is dependent on the landscape models used to characterise the natural analogue areas. It is demonstrated that conceptual ecological models developed for regional land resources survey, commonly used to select natural analogue areas, are subjective, complex and unreliable predictors of vegetation and soil patterns in hillslope environments at particular sites. It was recognised that environmental patterns are subject to terrain and hillslope environmental variation across an extensive areas. The landform model for selecting natural analogues was refined by introducing grain size and ecological extent concepts, used to describe ecological scale in landscape ecology, to address these effects. These refined concepts were adapted to define environmental variation in the context of natural analogue selection for mining restoration, rather than home range habitat conditions for native animals as was their original purpose. It is demonstrated here that the grain size and extent of environmental variation in the natural landscape can be used to select natural analogue landforms, develop ecological design criteria and design field surveys that support the capacity to predict the distributions of common and abundant woodland species in a reconstructed landscape. In conclusion, it is worth noting that an integrated ecological approach to landscape design can be applied to closure planning at mine sites where cultural and ecological objectives are critical to the success of the mine rehabilitation. Furthermore final landform trials could be used to support a restoration approach — providing an understanding of the interactions between critical physical and ecological processes in the soil layers and environmental processes at catchment scales. The accuracy of the inferences made is dependent on the understanding of hydrological processes in natural and constructed landforms. However, the natural analogue approach provides a clear landscape context for these trials. In a world where species extinction resulting from habitat loss is one of the most important global ecological issues, mine rehabilitation offers unique experimental opportunities to develop capability in ecosystem rehabilitation