Modeling alpine geomorphology using laser altimetry data

Geomorphologic Mapping of Tete Municipality, Mozambique

Geomorphological mapping consists of a set of techniques used to map landforms and the processes acting on the Earth's surface. It is a combination of techniques used in the representation of landforms and a useful tool to support information for integrated environmental analyses, territorial management, and geo-environmental risk assessment. Despite its importance and widespread use in several countries, including Brazil, most African countries do not conduct this type of mapping in their territories. This article aims to present the geomorphological mapping of the municipality of Tete in Mozambique. The methodology employed included the use of a Digital Elevation Model (DEM), high-resolution optical images, and fieldwork. The definition and classification of landforms followed the system proposed by Latrubesse and Carvalho (2006), which is nationally recognized and adaptable to different environments. The results indicate that the municipality's area is dominated by denudational units (~208 km²), which have sculpted large Receding Erosion Zones and Planation Surfaces, exhibiting different evolutionary stages. The aggradational units (~85 km²), in turn, are associated with the current and past dynamics of the Zambezi and Revúboè river systems. This study represents a pioneering product in the region and aims to provide support information for urban planning, environmental management, and hydrogeomorphological risk mitigation actions in the municipality of Tete.

Land cover mapping from orthorectified Neo-Pleiades imagery via Object-Based methods

Abstract. Posidonia oceanica is one of the most important seagrass species in the Mediterranean Sea, providing essential ecosystem services such as carbon sequestration, coastal protection and acting as a habitat and nursery ground for numerous marine species. These meadows have experienced significant decline in recent decades due to increasing anthropogenic pressures and environmental changes. Accurate and efficient mapping techniques are therefore essential for monitoring their spatial distribution and supporting conservation efforts. This study investigates the potential of very high-resolution Neo-Pléiades satellite imagery for mapping P. oceanica meadows along the northeastern coast of Sardinia (Italy). Two satellite acquisitions from 2021 and 2022 were orthorectified in PCI Catalyst (v.2023.0.0) using a Rational Polynomial Coefficient (RPC) model. Subsequently, a water column correction based on the Lyzenga depth-invariant index was applied to reduce depth-related spectral variability. The images were then classified using an object-based image analysis approach implemented in eCognition Developer (v.10.5), comparing three supervised algorithms: Nearest Neighbor (NN), Support Vector Machines (SVM), and Random Tree (RT). Accuracy assessment based on confusion matrices showed high classification performance, with overall accuracies up to 0.97 and Kappa values up to 0.96. Additional spatial validation using manually delineated reference areas confirmed classification reliability, although slightly lower agreement values were observed compared to confusion matrix estimates. The results highlight the strong potential of integrating high-resolution satellite imagery, water column correction, and object-based classification for mapping and monitoring P. oceanica habitats.

Geomorphological monitoring of erosion on restored slopes through the integration of drones, GIS, and LiDAR

Abstract. Mining is a strategic driver of economic development, yet it generates substantial impacts on landscape structure, soil integrity, and water systems. During ecological restoration, slope erosion remains a critical challenge for ensuring long-term geomorphological stability and ecosystem recovery. This study evaluates erosion dynamics on restored mining slopes by integrating Geographic Information Systems (GIS) and Unmanned Aerial Systems (UAS) for high-resolution terrain monitoring and quantification of soil loss. Research was conducted at the Lázaro quarry (Tarragona, Spain) using a fixed-wing UAS equipped with a multispectral camera to produce detailed orthophotos and Digital Elevation Models (DEMs), which were compared with historical LiDAR data. Height Difference Models (HDMs) and volumetric calculations were applied to quantify erosion and deposition. Statistical assessment included descriptive indicators, error metrics (ME, MAE, RMSE), distribution parameters (median, IQR, skewness), and spatial autocorrelation (Moran’s I). Three modelling approaches were developed and compared: a ridge-derived DEM (DEMp), a filtered DEM (DEMf), and a LiDAR-based DEM (DEMl). Their performance was evaluated in terms of accuracy, spatial resolution, and capacity to represent erosional microtopography. Results indicate that DEMp provides the most reliable volume estimates and best preserves pre-erosion morphology. In contrast, DEMf smooths surface detail, whereas DEMl provides an overview representation due to its lower spatial resolution. Overall, the integration of UAS photogrammetry and geospatial analysis proves effective for monitoring restored slopes, supporting precise erosion quantification and improved environmental management toward long-term landscape stability.

Kinematic Mapping and Geomorphological Analysis of Rock Glaciers in the Pirin Mountains (Bulgaria)

Rock glaciers are critical indicators of periglacial environments and the spatial distribution of mountain permafrost. Given their complex deformation patterns and temporal variability, which may indicate progressive destabilization, a quantitative evaluation of their kinematic activity is critical from both climatological and geohazard perspectives. This study applies Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) to Sentinel-1 radar imagery on both ascending and descending orbits, in order to detect and map moving areas (MA) within the Pirin Mountains (Bulgaria). The primary objective of this study is to update the existing rock glacier inventory (RoGI) by integrating high-resolution Line-of-Sight (LOS) velocity data in accordance with the latest international standards established by the Rock Glacier Inventories and Kinematics (RGIK) standing committee. A secondary objective is to investigate the spatial relationships between the identified moving areas (MAs) and other surrounding geomorphological features (e.g., talus slopes), hence providing a wider context for slope dynamics and landform evolution. The results identified MAs with PSInSAR-derived Line-of-Sight (LOS) velocities reaching up to 10 cm yr−1, which were subsequently classified according to RGIK kinematic categories. A substantial proportion of the detected moving areas occur outside mapped rock glacier boundaries and may reflect a range of geomorphological processes, including permafrost-related creep, talus creep, or other forms of slope deformation. The LOS velocity data were used to assess the activity status of 74 rock glacier units within the regional inventory, classifying 8 as transitional (velocity exceeding 1 cm yr−1) and 66 as relict. Furthermore, we analyse the spatial distribution of these moving areas in relation to primary topographic variables, such as elevation, aspect, and slope. The results highlight the influence of topographic control factors and rock glacier dynamics and provide new insights into the distribution of active periglacial landforms and terrain potentially affected by permafrost in the Balkan Peninsula under changing climatic conditions.

Mapping of multi-scale relief patterns and territorial planning: Applications at the Geological Survey of Brazil

Geomorphological studies conducted by the Geological Survey of Brazil (SGB-CPRM) have evolved since the 1970s, with significant methodological advances over the past two decades in institutional projects. In this context, multiscale mapping of landform patterns has become established as a fundamental approach to terrain characterization and support for territorial planning. Based on the integrated interpretation of remote sensing data, including satellite imagery, drone-derived products, and field validation, the proposed methodology enables landforms to be identified and spatially organized according to their morphology, morphometry, genesis, dynamics, and geological controls at different scales. This article presents the methodological evolution and institutional applications of this approach within the SGB-CPRM, based on a literature review and the experience accumulated through geomorphological mapping projects conducted in different regions of Brazil. The methodology evolved from exploratory surveys at a scale of 1:1,000,000 to progressively more detailed analyses at scales of 1:100,000, 1:25,000, and 1:10,000, enhancing the capacity to represent geomorphological features and processes and their application in studies of geodiversity, susceptibility to natural processes, geotechnics, and municipal geomorphological mapping. As a result of this trajectory, the Multiscale Landform Pattern Library was developed, serving simultaneously as a methodological framework for institutional mapping and as a technical and scientific reference for researchers and professionals in the field. The results demonstrate that this approach produces standardized and consistent geospatial information, constituting an effective tool for territorial planning, environmental management, and disaster risk reduction.

Modeling alpine geomorphology using laser altimetry data