High-resolution Digital Terrain Models Research Articles (Page 1)

BankfullMapper: a semi-automated MATLAB tool on high-resolution digital terrain models for spatio-temporal monitoring of bankfull geometry and discharge

ABSTRACT The aim of this study is to evaluate the suitability of very high-resolution satellite stereo-imagery data for creating forest fire-related fuel load maps in the boreal region. We acquired stereo imagery from the GeoEye-1 (GE-1) satellite, which has a ground sampling distance of 50 cm. The images were acquired in August 2021 and 2023 (hence leaf-on). Our study area was centred around the Hiidenportti national park in central Finland, dominated by natural boreal forests. The ground reference was a field dataset consisting of measurements from 33 forested plots, each of 15 m radius. The dominant height (m), foliage biomass (t ha-1) and canopy base height (m) were predicted using multivariate linear regression models, while the understory presence (categorical; present/absent) was predicted using logistic regression analysis. Prediction models using area-based metrics based on airborne laser scanning (ALS) data had the smallest associated root mean square error (RMSE) (between 2.6% and 23.9%). Meanwhile, similar type of area-based metrics of stereo satellite data combined with an ALS-based digital terrain model (DTM) resulted in RMSEs of 6.6–30.3%. We also formulated models suitable for the case when only satellite data is available (i.e. high-quality DTM is absent), such as in remote locations of the boreal forest region. In this case, the models involved several canopy texture metrics and point cloud height and colour intensity-based metrics as predictors. The associated relative RMSEs were in the range of 11–30%. Dominant height, an important global vegetation metric, was predicted with an RMSE of 2.6 m, which compares well with other model predictions under similar circumstances. Our findings suggests that very high-resolution stereo satellite image data is promising for the generation and updating of wall-to-wall boreal forest fuel load maps, including remote areas lacking high resolution DTM data.

Small landslides, though frequent, are often overlooked despite their significant potential impact on human-affected areas. This study presents an analysis of the Bella Orxeta landslide in Alicante, Spain, a rotational landslide event that occurred in March 2017 following intense and continued rainfall. Utilizing multitemporal datasets, including LiDAR from 2009 and 2016 and drone-based photogrammetry from 2021 and 2023, we generated high-resolution digital terrain models (DTMs) to assess morphological changes, estimate displaced volumes of approximately 3500 cubic meters, and monitor slope activity. Our analysis revealed substantial mass movement between 2016 and 2021, followed by relatively minor changes between 2021 and 2023, primarily related to fluvial erosion. This study demonstrates the effectiveness of UAV and DTM differencing techniques for landslide detection, volumetric analysis, and long-term monitoring in urbanized settings. Beyond its scientific contributions, the Bella Orxeta case offers pedagogical value across academic disciplines, supporting practical training in geomorphology, geotechnical assessment, GIS, and risk planning. It also highlights policy gaps in existing territorial risk plans, particularly regarding the integration of modern monitoring tools for small-scale but recurrent geohazards. Given climate change projections indicating more frequent high-intensity rainfall events in Mediterranean areas, the paper advocates for the systematic documentation of local landslide cases to improve hazard preparedness, urban resilience, and geoscience education.

Interactive simulations and immersive environments offer a powerful means of enhancing education by replicating real-world challenges in virtual settings. In the context of space exploration, these tools provide learners with opportunities to engage in mission-relevant tasks, fostering exploration, problem-solving and experimentation. This paper presents SOL977: Ingenious Revival, a simulation-based game developed with the Unity game engine and 3D modeling tools such as Blender. The Martian environment is constructed using, among other sources, high-resolution Digital Terrain Models (DTMs) of Mars to support realism and immersion. The simulation places players in the role of a field technician responsible for restoring the functionality of NASA’s Ingenuity drone after it sustains damage. The main goal is to replace a broken rotor blade in order to restore the vehicle’s flight capability. This scenario is inspired by a real malfunction that occurred on Mars in January 2024. The player interacts with mechanical and electronic components by carrying out realistic maintenance procedures. They complete a series of mission-specific tasks including terrain navigation and equipment repairs within a simulated Martian environment. The repair process reflects authentic workflows with each action needing to be carried out in a specific order and under defined conditions. The player must use the right tools, follow written procedures and demonstrate a high level of attention to detail. This structure supports the development of critical thinking, problem-solving abilities and technical reasoning within a STEM-focused educational context. Preliminary evaluation that was conducted with high school students suggested that the game increased motivation, deepened conceptual understanding of STEM subjects and promoted interest in space-related careers. This project highlights the educational potential of interactive simulations to bridge theoretical knowledge with hands-on problem-solving, supporting more meaningful and applied STEM learning. It also demonstrates the transformative potential of interactive simulations in STEM education, bridging the gap between theoretical knowledge and practical experience. It finally showcases how simulation-based games can engage students and foster a deeper understanding of complex concepts, while also sparking interest in space exploration and technical careers.

The extent of the Rhine Glacier in eastern Upper Swabia (southern Germany) at the height of the Last Glacial Maximum: new morphological constraints from high-resolution digital terrain models

Assessing land use changes and agricultural practices in highland valley-bottom wetlands in Taita Hills, Kenya.

Abstract. This work demonstrates the potential of exploiting LiDAR-based high resolution Digital Terrain Models (DTMs) to estimate water volume proxies by the mean of standard GIS tools, in a river stretch. Such approach may result profitable to integrate rapid analyses and reach timely information about the quantity of water contained in a river portion. This paper addresses the case study of Po River, in Italy, leveraging official databases to recover necessary data. Cross-sections are extracted from several DTMs and are used, in combination with hydrometric records collected along the river stretch, to estimate water volumes. Among the analyzed models, LiDAR-based DTMs, such as the 2x2 m resolution DTM used in this study, provided particularly accurate reconstructions of riverbed morphology. The findings show a substantial coherence with the river's seasonal variations and the volume trends reflect the environmental conditions faced by the Po River in the period of reference, ranging from severe drought to flood events. Furthermore, noticeable correlation between the estimated volumes and water surface extent evaluated in a previous work (Conversi et al., 2024) are shown.

Extreme sea levels (ESLs) induce significant risks to Hong Kong. With climate change, the risks will be amplified, while existing studies have not provided fine-grained simulations of Hong Kong’s future ESL exposure and its socio-economic risks. Employing a GIS-based coastal flood inundation model, this research integrates a high-resolution Digital Terrain Model (DTM) with datasets of ESL forecasts, demography, economy, infrastructure, and land use to estimate the future ESL risks posed on Hong Kong for 2050 and 2100 under two Representative Concentration Pathways (RCPs): RCP4.5 and RCP8.5. The projections indicate that, under RCP4.5, over 27.66% of the population and 39.52% of the Gross Domestic Product (GDP) will be exposed to ESL after 2050. Under RCP8.5 scenario, the exposed population may surpass 31.21%, with economic exposure estimated at 40.98% of GDP after 2050. Under both RCPs, Hong Kong’s ESL-threatened area may range from 8.23 to 11.41%, exposing over 16.09% of the infrastructure to ESL after 2050. Regions in the northwestern Yuen Long, Tuen Mun River Estuary, Rambler Channel coast, Victoria Harbor coast, Shing Mun River, and Tai Po Waterfront have particularly high ESL risks. The findings highlight the need for resilient infrastructure to counteract the long-term risks ESL poses in Hong Kong.

This research aims to characterize sediment dynamics in the Rupinaro catchment, a uniquely terraced and human-shaped basin in Italy’s Liguria region, employing geomorphometric methods to unravel sediment connectivity in a landscape vulnerable to shallow landslides. Within a scenario-based approach, we utilized high-resolution LiDAR-derived digital terrain models (DTMs) to calculate the Connectivity Index, comparing sediment dynamics between the original terraced landscape and a virtual natural scenario. To reconstruct a pristine slope morphology, we applied a topographic roughness-based skeletonization algorithm that simplifies terraces into linear features to simulate natural hillslope conditions and remove anthropogenic structures. The analysis was carried out considering diverse targets (e.g., hydrographic networks, road networks) and the effect of land use. The results reveal significant differences in sediment connectivity between the anthropogenic and natural morphologies, with implications for erosion and landslide susceptibility. The findings reveal that sediment connectivity is moderately higher in the scenario without terraces, indicating that terraces function as effective barriers to sediment transfer. This highlights their potential role in mitigating landslide susceptibility on steep slopes. Additionally, the results show that roads exert a stronger influence on the Connectivity Index, significantly altering flow paths. These modifications appear to contribute to increased landslide susceptibility in adjacent areas, as reflected by the higher observed landslide density within the study region.

Sea level rise (SLR) and increased urbanisation of coastal areas have exacerbated coastal flood threats, making them even more severe in important cultural sites. In this context, the role of hard coastal defences such as promenades and embankments needs to be carefully assessed. Here, a thorough investigation is conducted in Grado, one of the most significant coastal and historical towns in the Friuli Venezia Giulia region of Italy. Grado is located on a barrier island of the homonymous lagoon, the northernmost of the Adriatic Sea, and is prone to flooding from both the sea and the back lagoon. The mean and maximum sea levels from the historical dataset of Venice (1950–2023) were analysed using the Gumbel-type distribution, allowing for the identification of annual extremes based on their respective return periods (RPs). Grado and Trieste sea level datasets (1991–2023) were used to calibrate the statistics of the extremes and to calculate the local component (subsidence) of relative SLR. The research examined the occurrence of annual exceedance of the minimum threshold water level of 110 cm, indicating Grado’s initial notable marine ingression. The study includes a detailed analysis of flood impacts on the urban fabric, categorised into sectors based on the promenade elevation on the lagoon side, the most vulnerable to flooding. Inundated areas were obtained using a high-resolution digital terrain model through a GIS-based technique, assessing both the magnitude and exposure of the urban environment to flood risk due to storm surges, also considering relative SLR projections for 2050 and 2100. Currently, approximately 42% of Grado’s inhabited area is inundated with a sea level threshold value of 151 cm, which occurs during surge episodes with a 30-year RP. By 2100, with an optimistic forecast (SSP1-2.6) of local SLR of around +53 cm, the same threshold will be met with a surge of ca. 100 cm, which occurs once a year. Thus, extreme levels linked with more catastrophic events with current secular RPs will be achieved with a multi-year frequency, inundating more than 60% of the urbanized area. Grado, like Venice, exemplifies trends that may impact other coastal regions and historically significant towns of national importance. As a result, the generated simulations, as well as detailed analyses of urban sectors where coastal flooding may occur, are critical for medium- to long-term urban planning aimed at adopting proper adaptation measures.

Cold-water coral habitats (Madrepora oculata and Desmophyllum pertusum) were mapped in the Lacaze-Duthiers Canyon, within the “Parc naturel marin du golfe du Lion” (northwestern Mediterranean), to support the creation of a strongly protected area for these vulnerable marine ecosystems (VME). The analyses are based on ROV data, high-resolution digital terrain models (5–10 m), hydrodynamic model simulations (currents, temperature, salinity from SYMPHONIE), and fishing pressure data derived from Vessel Monitoring System (VMS) and Automatic Identification System (AIS) fishing data. Habitat models indicate coral habitats are mainly on the western canyon flank (250 to 600 m depth). Desmophyllum pertusum predominantly colonizes gentle slopes at cliff bases, while M. oculata is found on steeper slopes, and the eastern flank. Some western flank areas support both species. Direct impacts from fishing activities, including lost longlines and nets entangled with corals, were observed. In addition, bottom trawling at the continental shelf edge induces sediment resuspension, potentially smothering the underlying coral ecosystems in the canyon. This study recommends enhancing fishing activity monitoring by increasing VMS positioning transmission frequency across European countries and facilitating the combination of VMS and AIS data to derive higher-resolution fishing effort and footprint assessments. Protection should prioritize canyon flanks and the surrounding continental shelf, not just the canyon itself, to mitigate fishing pressure. Tailored management measures are needed for sensitive habitats. Creating a strongly protected area will require crossborder cooperation (France, Spain) to ensure the effective conservation of these fragile ecosystems.

Abstract. Analysis of the effect of the resolution and quality of terrain data, as the most sensitive input to 2D hydrodynamic modeling, has been one of the main research areas in flood modeling. However, previous studies have lacked discussion on (1) the limitations of the target area and the data source and (2) the underlying causes of simulation bias due to different resolutions. This study first discusses the performance of a high-resolution digital terrain model (DTM), acquired using a drone, for flood modeling in a mountainous riverine city; analyses the effect of the DTM resolution on the results using grid resolutions from 6 cm to 30 m; and then investigates the root causes of the effect based on topographic attributes. Xuanhan, a riverine city in the mountainous region of Southwestern China, was used as the study area. The Hydrologic Engineering Center's River Analysis System (HEC-RAS) 2D model was used for all simulations, and the results generated using a 6 cm DTM acquired by drone were used as a benchmark. The results indicate that flood characteristic simulations exhibit noticeable stepwise changes as the DTM resolution varies. DTMs with a resolution better than 10 m are more effective with respect to capturing the terrain's undulating features in the study area, which is crucial for accurately modeling the inundation area. However, to accurately capture topographic features related to elevation differences, the resolution should preferably be better than 5 m, as this directly affects the accuracy of flood depth simulation. The analysis of topographic attributes provides theoretical support for determining the optimal resolution to meet simulation requirements.

Pluvial flooding, driven by increasingly impervious surfaces and intense storm events, presents a growing challenge for urban areas worldwide. In Baltimore City, MD, USA, climate change, rapid urbanization, and aging stormwater infrastructure are exacerbating flooding impacts, resulting in significant socio-economic consequences. This study evaluated the effectiveness of a soil profile rehabilitation scenario using a 2D hydrodynamic modeling approach for the Tiffany Run watershed, Baltimore City. This study utilized different extreme storm events, a high-resolution (1 m) LiDAR Digital Terrain Model (DTM), building footprints, and hydrological soil data. These datasets were integrated into a fully coupled 2D hydrodynamic model, the City Catchment Analysis Tool (CityCAT), to simulate urban flood dynamics. The pre-soil rehabilitation simulation revealed a maximum water depth of 3.00 m in most areas, with hydrologic soil groups C and D, especially downstream of the study area. The post-soil rehabilitation simulation was targeted at vacant lots and public parcels, accounting for 33.20% of the total area of the watershed. This resulted in a reduced water depth of 2.50 m. Additionally, the baseline runoff coefficient of 0.49 decreased to 0.47 following the rehabilitation, and the model consistently recorded a peak runoff reduction rate of 4.10 across varying rainfall intensities. The validation using a contingency matrix demonstrated true-positive rates of 0.75, 0.50, 0.64, and 0 for the selected events, confirming the model’s capability at capturing real-world flood occurrences.

The advent of geomatic techniques and novel sensors has opened the road to new approaches in mapping, including morphological ones. The evolution of a land portion and its graphical representation constitutes a fundamental aspect for scientific and land planning purposes. In this context, new paradigms for geomorphological mapping, which are useful for modernizing traditional, geomorphological mapping, become necessary for the creation of scalable digital representation of processes and landforms. A fully remote mapping approach, based on multi-source and multi-sensor applications, was implemented for the recognition of landforms and processes. This methodology was applied to a study site located in central Italy, characterized by the presence of ‘calanchi’ (i.e., badlands). Considering primarily the increasing availability of regional LiDAR products, an automated landform classification, i.e., Geomorphons, was adopted to map landforms at the slope scale. Simultaneously, by collecting and digitizing a time-series of historical orthoimages, a multi-temporal analysis was performed. Finally, surveying the area with an unmanned aerial vehicle, exploiting the high-resolution digital terrain model and orthoimage, a local-scale geomorphological map was produced. The proposed approach has proven to be well capable of identifying the variety of processes acting on the pilot area, identifying various genetic types of geomorphic processes with a nested hierarchy, where runoff-associated landforms coexist with gravitational ones. Large ancient mass movement characterizes the upper part of the basin, forming deep-seated gravity deformation, highly remodeled by a set of widespread runoff features forming rills, gullies, and secondary shallow landslides. The extended badlands areas imposed on Plio-Pleistocene clays are typically affected by sheet wash and rill and gully erosion causing high potential of sediment loss and the occurrence of earth- and mudflows, often interfering and affecting agricultural areas and anthropic elements. This approach guarantees a multi-scale and multi-temporal cartographic model for a full-coverage representation of landforms, representing a useful tool for land planning purposes.

Sinkholes are significant geohazards in karst regions that pose risks to landscapes and infrastructure by disrupting geological stability. Usually, sinkholes are mapped by field surveys, which is very cost-intensive with regard to vast coverages. One possible solution to derive sinkholes without entering the area is the use of high-resolution digital terrain models, which are also expensive with respect to remote areas. Therefore, this study focusses on the mapping of sinkholes in arid regions from open-access remote sensing data. The case study involves data from the Sentinel missions over the Mangystau region in Kazakhstan provided by the European Space Agency free of cost. The core of the technique is a multi-scale curvature filter bank that highlights sinkholes (and takyrs) by their very special illumination pattern in Sentinel-2 images. Marginal confusions with vegetation shadows are excluded by consulting the newly developed Combined Vegetation Doline Index based on Sentinel-1 and Sentinel-2. The geospatial analysis reveals distinct spatial correlations among sinkholes, takyrs, vegetation, and possible surface discharge. The generic and, therefore, transferable approach reached an accuracy of 92%. However, extensive reference data or comparable methods are not currently available.

In recent years, Vision-Based Navigation (VBN) techniques have emerged as a fundamental component to enable autonomous spacecraft operations, particularly in challenging environments such as planetary landings, where ground control may be limited or unavailable. Developing and testing VBN algorithms requires the availability of a large number of realistic images of the application scenario; however, these are rarely available. This paper presents a novel rendering software tool to generate accurate synthetic optical images of the lunar surface by leveraging high-resolution Digital Terrain Models (DTMs). Unlike traditional ray-tracing algorithms, the method iteratively propagates camera rays to determine their intersection with the terrain surface defined by a Digital Elevation Model (DEM). The color information is then retrieved from the corresponding Digital Orthophoto Model (DOM) through the knowledge of the ray impact points, bypassing the need for the costly computation of shadows, reflections, and refractions effects. The rendering performance is demonstrated through a comprehensive selection of images of the lunar surface under different illumination conditions and camera orientations.

In this paper, the application is investigated of fast Fourier transform filtering (FFT-FR) to high spatial resolution digital terrain models (HR-DTM) derived from LiDAR sensors, assessing its efficacy in identifying genuine relief elements, including both natural geological features and anthropogenic landforms. The suitability of the derived filtered geomorphic references (FGRs) is evaluated through spatial correlation with ground truths (GTs) extracted from the topographical and geological geodatabases of Santander Bay, Northern Spain. In this study, it is revealed that existing artefacts, derived from vegetation or human infrastructures, pose challenges in the units’ construction, and large physiographic units are better represented using low-pass filters, whereas detailed units are more accurately depicted with high-pass filters. The results indicate a propensity of high-frequency filters to detect anthropogenic elements within the DTM. The quality of GTs used for validation proves more critical than the geodatabase scale. Additionally, in this study, it is demonstrated that the footprint of buildings remains uneliminated, indicating that the model is a poorly refined digital surface model (DSM) rather than a true digital terrain model (DTM). Experiments validate the DTM’s capability to highlight contacts and constructions, with water detection showing high precision (≥60%) and varying precision for buildings. Large units are better captured with low filters, whilst high filters effectively detect anthropogenic elements and more detailed units. This facilitates the design of validation and correction procedures for DEMs derived from LiDAR point clouds, enhancing the potential for more accurate and objective Earth surface representation.

Drone photogrammetry is a swift, inexpensive, accurate, and detailed procedure that makes it possible to obtain pictures for the creation of a high spatial resolution Digital Terrain Model (DTM) with enhanced planimetric and altimetric precision. It also provides the possibility of cartographic land use. Study site: the experiment was carried out in a mountain area using a Phantom 4 RTK drone over the road connecting Demnate to Aït Bouguemez in the province of Azilal. The results were processed with Agisoft software running a TIN (Triangulated Irregular Network) based algorithm for a geometric classification (ground vs above ground). This was followed by manual intervention to increase the accuracy of the desired output. Image processing and classification helped to build a Digital Terrain Model with an altimetric RMSE of 5 cm - just 3 cm for planimetric error. This extreme accuracy is valuable when performing tasks that demand great precision, like building a detailed road development plan.Drone photogrammetry excels in the development of roads, highway, and many other tasks mainly thanks to its speed, cost-effectiveness and detail. In this paper, the results show that this technique produces high- fidelity images and can make a DTM with high precision. This higher accuracy leads to informed decisions in the planning and implementation of road work.

The rehabilitation of mine waste dumps is a critical environmental challenge, particularly in areas like Uricani, Romania, where such sites are often characterized by hazardous conditions and poor ecological recovery. This study addresses the need for efficient, low-cost solutions for land reclamation by employing UAV photogrammetry and GIS spatial analysis to assess the potential for afforestation with Robinia pseudoacacia L., a species known for its soil stabilization and ecological benefits. Using UAV technology, high-resolution digital terrain models and orthophotos were generated, with an RMSE of 0.086 m, demonstrating the accuracy and efficiency of this method for large-scale landscape initiatives. GIS spatial analysis was performed to create six key terrain maps and four pedoclimatic factor maps, essential for evaluating the site’s suitability for ecological restoration. The pilot afforestation project, which involved planting R. pseudoacacia, achieved a 75% survival rate after four years, suggesting that the species can thrive under the site’s conditions. The landscape design proposal incorporates recreational spaces aimed at benefiting the local community and attracting tourism, thereby contributing to the area’s economic and cultural revitalization. The interdisciplinary integration of UAV surveying, GIS, and landscape design highlights the cost-effectiveness and interdisciplinary nature of this approach, offering a sustainable model for mine waste dump reclamation and future ecological restoration projects.

Abstract. This study presents a low-cost, multi-sensor monitoring setup for wadi discharge assessment. The system comprises a time-lapse camera gauge and a Raspberry Shake seismograph, both powered by solar energy and integrated with data transmission units for remote monitoring. Optical data, combined with a high-resolution digital terrain model generated via UAV-based photogrammetry, enables semi-automatic discharge estimation. Seismic data complement the optical workflow by capturing flow-induced vibrations, providing a second line of evidence for wadi discharge. Our systems operated successfully, recording several flow events, highlighting the feasibility of low-cost, remote monitoring in ephemeral wadi environments. Key challenges included limited camera accuracy and the need for frequent DTM updates due to morphological changes. Improvements, such as upgrading camera hardware and enhancing automation in data processing, are underway to increase system accuracy and reliability for operational use.