Review and critical analysis on digital elevation models

Nowadays, digital elevation model (DEM) acts as an inevitable component in the field of remote sensing and GIS. DEM reflects the physical surface of the earth helps to understand the nature of terrain by means of interpreting the landscape using modern techniques and high-resolution satellite images. To understand and analyze the nature of the terrain, DEM is required in many fields in the improvement of developing the product and decision making, mapping purpose, preparing 3D simulations, estimating river channel and creating contour maps to extract the elevation and so on. DEM in various applications will be useful to replicate the overall importance of the availability of worldwide, consistent, high-quality digital elevation models. The present article represents the overall review of DEMs, its generation, development using various techniques derived from topographic maps and high-resolution satellite images over a decade to present. It is useful to understand the nature of topography, address the practical problems and fix them by applying innovative ideas, upcoming high-resolution satellite images and techniques.Danas, digitalni model uzdizanja (DEM) djeluje kao neizbježna komponenta u području daljinskog istraživanja i GIS-a. DEM reflektira fizičku površinu zemlje pomaže pri razumijevanju prirode terena pomoću tumačenja krajolika pomoću suvremenih tehnika i satelitskih slika visoke razlučivosti. Za razumijevanje i analizu prirode terena, DEM je potreban u mnogim područjima poboljšanja razvoja proizvoda i odlučivanja, svrhe mapiranja, pripreme 3D simulacija, procjene riječnog kanala i stvaranja konturnih karata za izdvajanje visine i tako dalje. DEM u raznim aplikacijama bit će korisno za repliciranje sveukupne važnosti dostupnosti svjetskih, dosljednih i visokokvalitetnih modela digitalnih elevacija. Ovaj članak predstavlja cjelokupni pregled DEM-ova, njegovog stvaranja, razvoja pomoću različitih tehnika izvedenih iz topografskih karata i satelitskih snimaka visoke razlučivosti tijekom desetljeća do danas. Korisno je razumjeti prirodu topografije, rješavati praktične probleme i popraviti ih primjenom inovativnih ideja, nadolazećih satelitskih slika i tehnika visoke razlučivosti

DEM generation and hydrologic modelling using LiDAR data

Communities and governments in flood prone areas around the globe seek to prevent the disastrous effects of major floods. There are plenty of examples of such events in the 21st century occurring around the globe. A particular event of significance to southeast Queensland is the floods of December 2010 and January 2011 which did much damage to communities in affected regions of the state. Airborne LiDAR has provided a sophisticated method of capturing data for digital elevation models (DEM) which provides a basis for flood flow and inundation predictions to inform the design of future developments and mitigation measures to reduce the consequences of major floods. This dissertation investigated the use of Airborne LiDAR for hydrologic modelling, the accuracy of LiDAR data, its use as a tool for terrain change analysis and its effectiveness for basic flood extent modelling. LiDAR data captured in 2010 and 2012 covering the East Creek catchment in Toowoomba was obtained for this project. Hydrologic models were created and results were compared between the 2010 and 2012 LiDAR datasets. It was found that hydrologic flow lines and watershed boundaries varied on side streams. This variation was also found to be less in undeveloped areas than in developed areas. A conventional field survey was carried out over a small area on East Creek to validate the LiDAR datasets and it was found that both LiDAR datasets were within the specified accuracies overall, though there was a tendency to overestimate elevations in areas covered by vegetation. The datasets and validation analysis were used to search for terrain changes between the periods of data capture and several areas of definite probable terrain change were found. The results highlighted the potential of LiDAR data for this application. A basic flood surface extent analysis was done in the same area and LiDAR was found to perform well with minor effects of elevation overestimation errors due to vegetation. This dissertation shows some of the capabilities and limitations of LiDAR. Future research should make use of more sophisticated hydraulic modelling software and techniques. However the use of two independent LiDAR datasets provided a useful independent check which would be helpful for future studies of a similar topic

Uncertainties in Digital Elevation Models: Evaluation and Effects on Landform and Soil Type Classification

Digital elevation models (DEMs) are a widely used source for the digital representation of the Earth's surface in a wide range of scientific, industrial and military applications. Since many processes on Earth are influenced by the shape of the relief, a variety of different applications rely on accurate information about the topography. For instance, DEMs are used for the prediction of geohazards, climate modelling, or planning-relevant issues, such as the identification of suitable locations for renewable energies. Nowadays, DEMs can be acquired with a high geometric resolution and over large areas using various remote sensing techniques, such as photogrammetry, RADAR, or laser scanning (LiDAR). However, they are subject to uncertainties and may contain erroneous representations of the terrain. The quality and accuracy of the topographic representation in the DEM is crucial, as the use of an inaccurate dataset can negatively affect further results, such as the underestimation of landslide hazards due to a too flat representation of relief in the elevation model. Therefore, it is important for users to gain more knowledge about the accuracy of a terrain model to better assess the negative consequences of DEM uncertainties on further analysis results of a certain research application. A proper assessment of whether the purchase or acquisition of a highly accurate DEM is necessary or the use of an already existing and freely available DEM is sufficient to achieve accurate results is of great qualitative and economic importance. In this context, the first part of this thesis focuses on extending knowledge about the behaviour and presence of uncertainties in DEMs concerning terrain and land cover. Thus, the first two studies of this dissertation provide a comprehensive vertical accuracy analysis of twelve DEMs acquired from space with spatial resolutions ranging from 5 m to 90 m. The accuracy of these DEMs was investigated in two different regions of the world that are substantially different in terms of relief and land cover. The first study was conducted in the hyperarid Chilean Atacama Desert in northern Chile, with very sparse land cover and high elevation differences. The second case study was conducted in a mid-latitude region, the Rur catchment in the western part of Germany. This area has a predominantly flat to hilly terrain with relatively diverse and dense vegetation and land cover. The DEMs in both studies were evaluated with particular attention to the influence of relief and land cover on vertical accuracy. The change of error due to changing slope and land cover was quantified to determine an average loss of accuracy as a function of slope for each DEM. Additionally, these values were used to derive relief-adjusted error values for different land cover classes. The second part of this dissertation addresses the consequences that different spatial resolutions and accuracies in DEMs have on specific applications. These implications were examined in two exemplary case studies. In a geomorphometric case study, several DEMs were used to classify landforms by different approaches. The results were subsequently compared and the accuracy of the classification results with different DEMs was analysed. The second case study is settled within the field of digital soil mapping. Various soil types were predicted with machine learning algorithms (random forest and artificial neural networks) using numerous relief parameters derived from DEMs of different spatial resolutions. Subsequently, the influence of high and low resolution DEMs with the respectively derived land surface parameters on the prediction results was evaluated. The results on the vertical accuracy show that uncertainties in DEMs can have diverse reasons. Besides the spatial resolution, the acquisition technique and the degree of improvements made to the dataset significantly impact the occurrence of errors in a DEM. Furthermore, the relief and physical objects on the surface play a major role for uncertainties in DEMs. Overall, the results in steeper areas show that the loss of vertical accuracy is two to three times higher for a 90 m DEM than for DEMs of higher spatial resolutions. While very high resolution DEMs of 12 m spatial resolution or higher only lose about 1 m accuracy per 10° increase in slope steepness, 30 m DEMs lose about 2 m on average, and 90 m DEMs lose more than 3 m up to 6 m accuracy. However, the results also show significant differences for DEMs of identical spatial resolution depending on relief and land cover. With regard to different land cover classes, it can be stated that mid-latitude forested and water areas cause uncertainties in DEMs of about 6 m on average. Other tested land cover classes produced minor errors of about 1 – 2 m on average. The results of the second part of this contribution prove that a careful selection of an appropriate DEM is more crucial for certain applications than for others. The choice of different DEMs greatly impacted the landform classification results. Results from medium resolution DEMs (30 m) achieved up to 30 % lower overall accuracies than results from high resolution DEMs with a spatial resolution of 5 m. In contrast to the landform classification results, the predicted soil types in the second case study showed only minor accuracy differences of less than 2 % between the usage of a spatial high resolution DEM (15 m) and a low resolution 90 m DEM. Finally, the results of these two case studies were compared and discussed with other results from the literature in other application areas. A summary and assessment of the current state of knowledge about the impact of a particular chosen terrain model on the results of different applications was made. In summary, the vertical accuracy measures obtained for each DEM are a first attempt to determine individual error values for each DEM that can be interpreted independently of relief and land cover and can be better applied to other regions. This may help users in the future to better estimate the accuracy of a tested DEM in a particular landscape. The consequences of elevation model selection on further results are highly dependent on the topic of the study and the study area's level of detail. The current state of knowledge on the impact of uncertainties in DEMs on various applications could be established. However, the results of this work can be seen as a first step and more work is needed in the future to extend the knowledge of the effects of DEM uncertainties on further topics that have not been investigated to date

Assessment of precision in dems generated using automatic correlation

En este trabajo se muestra una experiencia en la generación de Modelos Digitales de Elevaciones (MDE) a partir de algoritmos de correlación automática propios de una Estación de Fotogrametría Digital (EFD), así como una evaluación sobre la precisión obtenida en función de los datos disponibles y de la metodología empleada. Este estudio se aplica a un espacio singular denominado cerro “Calderico” en el que se ubican los famosos molinos de viento de Don Quijote en Consuegra (Toledo, España), donde se diferencian tres zonas, caracterizadas principalmente por su distinta pendiente. Una vez creados los diferentes MDE para los ámbitos descritos se efectúa un análisis estadístico que nos servirá para hacer una valoración cuantitativa tanto de los modelos como de las ortoimágenes que se obtengan. Los resultados que se aportan indican mayor disparidad en la precisión de los puntos homólogos identificados en cada MDE para las zonas de más desnivel y menor en las zonas con pendiente más suave. Es interesante observar la buena calidad de los puntos controlados mediante GPS diferencial

Quality assessment of DEM derived from topographic maps for geomorphometric purposes

Digital elevation models (DEMs) play a significant role in geomorphological research. For geomorphologists reconstructing landform and drainage structure is frequently as important as elevation accuracy. Consequently, large-scale topographic maps (with contours, height points and watercourses) constitute excellent material for creating models (here called Topo-DEM) in fine resolution. The purpose of the conducted analyses was to assess the quality of Topo-DEM against freely-available globalDEMs and then to compare it with a reference model derived from laser scanning (LiDAR-DEM). The analysis also involved derivative maps of geomorphometric parameters (local relief, slope, curvature, aspect) generated on the basis of Topo-DEM and LiDAR-DEM. Moreover, comparative classification of landforms was carried out. It was indicated that Topo-DEM is characterised by good elevation accuracy (RMSE <2 m) and reflects the topography of the analyzed area surprisingly well. Additionally, statistical and percentage metrics confirm that it is possible to generate a DEM with very good quality parameters on the basis of a large-scale topographic map (1:10,000): elevation differences between Topo-DEM and: 1) topographic map amounted from−1.68 to +2.06 m,MAEis 0.10 m, RMSE 0.16 m; 2) LiDAR-DEM (MAE 1.13 m, RMSE 1.69 m, SD 1.83 m); 3) GPS RTK measurements amounted from−3.6 to +3.01 m, MAE is 0.72 m, RMSE 0.97 m, SD 0.97 m. For an area of several dozen km2 Topo-DEM with 10×10 m resolution proved more efficient than detailed (1×1 m) LiDAR-DEM

Two decades of digital photogrammetry: Revisiting Chandler’s 1999 paper on “Effective application of automated digital photogrammetry for geomorphological research” – a synthesis

This is the author accepted manuscript. The final version is available from SAGE Publications via the DOI in this record.Digital photogrammetry has experienced rapid development regarding the technology involved and its ease of use over the past two decades. We revisit the work of Jim Chandler who in 1999 published a technical communication seeking to familiarise novice users of photogrammetric methods with important theoretical concepts and practical considerations. In doing so, we assess considerations such as camera calibration and the need for photo-control and check points, as they apply to modern software and workflows, in particular for Structure-from-Motion (SfM) photogrammetry. We also highlight the implications of lightweight drones being the new platform of choice for many photogrammetry-based studies in the geosciences. Finally, we present three examples based on our own work, showing the opportunities that SfM photogrammetry offers at different scales and systems: at the micro-scale for monitoring geomorphological change, and at the meso-scale for hydrological modelling and the reconstruction of vegetation canopies. Our examples showcase developments and applications of photogrammetry which go beyond what was considered feasible 20 years ago and indicate future directions that applications may take. Nevertheless, we demonstrate that, in-line with Chandler’s recommendations, the pre-calibration of consumer-grade cameras, instead of relying entirely on self-calibration by software, can yield palpable benefits in micro-scale applications and that measurements of sufficient control points are still central to generating reproducible, high-accuracy products. With the unprecedented ease of use and wide areas of application, scientists applying photogrammetric methods would do well to remember basic considerations and seek methods for the validation of generated products.European Union’s Horizon 2020 researchMarie Skłodowska-CurieUK Department for Environment, Food and Rural Affair

Kinematics and geomorphological changes of a destabilising rock glacier captured from close-range sensing techniques (Tsarmine rock glacier, Western Swiss Alps)

Accurately assessing landform evolution and quantifying rapid environmental changes are gaining importance in the context of monitoring techniques in alpine environments. In the European Alps, glaciers and rock glaciers are among the most characteristic cryospheric components bearing long and systematic monitoring periods. The acceleration in rock glacier velocities and the onset of destabilization processes, mainly since 1990, have raised several concerns due to the potential effects on the high alpine natural and anthropic environments. This study presents a combination of uncrewed aerial vehicle (UAV) and terrestrial laser scanning (TLS) surveys for monitoring the current changes on the quickly accelerating, destabilised Tsarmine rock glacier in the Arolla Valley, Western Swiss Alps, delivering a considerable volume of debris to a steep torrential gully. High-resolution digital elevation models (DEMs) and orthomosaics are derived from UAV image series combined with structure from motion (SfM) photogrammetry techniques. Multitemporal orthomosaics are employed for measuring spatially continuous rock glacier kinematics using image matching algorithms. Superficial displacements are evaluated with simultaneous in-situ differential global navigation satellite system (GNSS) measurements. Elevation and volume changes are computed from TLS and UAV-derived DEMs at similar periods. Between June 2017 and September 2019, both datasets showed a similar elevation change pattern and surface thinning rates of 0.15 ± 0.04 and 0.16 ± 0.03 m yr−1, respectively. Downward of a rupture zone developing about 150 m above the front, the rock glacier doubled its overall velocity during the study period, from around 5 m yr−1 between October 2016 and June 2017 to more than 10 m yr−1 between June and September 2019. The kinematic information reveals striking differences in the velocity between the lower and upper rock glacier sections. The monitoring approach based on close-sensing techniques provides accurate surface velocity and volume change information, allowing an enhanced description of the current rock glacier dynamics and its surface expression

Integrated Geomatics Surveying and Data Management in the Investigation of Slope and Fluvial Dynamics

In mountain environments, slope and fluvial dynamics often interact, and their relationship can be investigated through an integrated methodological approach. Landslides are a source of supplying sediments into riverbeds and can interact or interrupt the water course. Water courses can trigger or re-activate slope movements. The complexity of investigating the interaction between the two dynamics needs a complementarity of methods and techniques, combining remote and proximal sensing, geotechnical in situ surveys, and repositories and catalogue datasets. This leads to a synergistic use of all the heterogeneous data from different fields and formats. The present paper provides a literature review on the approaches and surveying procedures adopted in the investigation of slope and fluvial dynamics and highlights the need to improve the integrated management of geospatial information complemented by quality information. In this regard, we outline a geodatabase structure capable of handling the variety of geoscientific data available at different spatial and temporal scales, with derived products that are useful in integrated monitoring tasks. Indeed, the future adoption of a shared physical structure would allow the merging and synergistic use of data provided by different surveyors as well as the effective storing and sharing of datasets from a monitoring perspective