Digital Geomorphological Mapping Research Articles

Physically-based digital geomorphological mapping: Case study of glacial and karst topography

Digital geomorphological mapping is considered here as a semi-automated procedure of division the land surface into genetically meaningful objects. The basis is automatic segmentation into elementary forms, the smallest and indivisible elements of the land surface, should be geometrically clearly identifiable, with maximal internal homogeneity and clear discontinuities at their boundaries. These elements can then be combined into more complex genetically homogeneous composite forms. Given the crucial role of gravitational energy in landform formation, it should also be considered in elementary land surface segmentation . This research builds on the theoretical foundation of physical geomorphometry, which explores the relationship between gravitational energy and geomorphometric variables. Specifically, we apply the recently published algorithm for physically-based elementary land surface segmentation by Minár et al. (2024), which utilizes dynamic least squares (DLS) generalization within a GEOBIA framework. The algorithm was initially tested in structurally fluvial hilly terrain using nine physically interpretable gravity-specific point-based variables (elevation, slope aspect and gradient, three basic curvatures, and three changes in curvature). In this study, we extend the application of this algorithm to two different areas of the Western Carpathians: the glacial topography of its highest part and a karst plateau. By using a slightly simplified and specifically modified version of the physically-based algorithm, we achieved plausible and genetically interpretable results in both case studies, which confirms the value of physical geomorphometry in geomorphological mapping. Additionally, a novel concept of physical-geomorphometric signature was applied in both case studies as a support for the physical-geomorphometric analysis. The physical-geomorphometric signature is very helpful in the quantitative comparison between various genetic groups of landforms.

Digital Geomorphological Mapping of Sabkhas in the Western Gulf of Suez, Egypt

Digital Geomorphological Mapping of Sabkhas in the Western Gulf of Suez, Egypt

Explanation of the influence of geomorphometric variables on the landform classification based on selected areas in Poland

In recent years, automatic image classification methods have significantly progressed, notably black box algorithms such as machine learning and deep learning. Unfortunately, such efforts only focused on improving performance, rather than attempting to explain and interpret how classification models actually operate. This article compares three state-of-the-art algorithms incorporating random forests, gradient boosting and convolutional neural networks for geomorphological mapping. It also attempts to explain how the most effective classifier makes decisions by evaluating which of the geomorphometric variables are most important for automatic mapping and how they affect the classification results using one of the explainable artificial intelligence techniques, namely accumulated local effects (ALE). This method allows us to understand the relationship between predictors and the model’s outcome. For these purposes, eight sheets of the digital geomorphological map of Poland on the scale of 1:100,000 were used as the reference material. The classification results were validated using the holdout method and cross-validation for individual sheets representing different morphogenetic zones. The terrain elevation entropy, absolute elevation, aggregated median elevation and standard deviation of elevation had the greatest impact on the classification results among the 15 geomorphometric variables considered. The ALE analysis was conducted for the XGBoost classifier, which achieved the highest accuracy of 92.8%, ahead of Random Forests at 84% and LightGBM at 73.7% and U-Net at 59.8%. We conclude that automatic classification can support geomorphological mapping only if the geomorphological characteristics in the predicted area are similar to those in the training dataset. The ALE plots allow us to analyze the relationship between geomorphometric variables and landform membership, which helps clarify their role in the classification process.

Named Landforms of the World: A Geomorphological and Physiographic Compilation

Prior to the current era of digital geomorphological mapping, global and regional-scale land surface characterization was advanced by qualitative interpretations that relied on human visualization aided by disciplinary knowledge of geophysical processes combined with extensive field study. In the early twentieth century, Fenneman proposed to devise systematic physiographic divisions of the United States and in 1916 produced what is still regarded as an authoritative map of these divisions. His physiographic regions were developed to provide context when describing land surface characteristics of smaller areas using well-known regional characteristics and descriptors. In 1968, geographer Richard E. Murphy published a large-format map of the “Landforms of the World” to fill a gap in the suite of standard classroom maps. In 1990, the British geomorphologist E. M. Bridges published World Geomorphology, providing the first global treatment and description of divisions, provinces, and sections—the same hierarchical land partitioning concepts that Fenneman used decades earlier. In the twenty-first century, geographic information systems (GIS) technologies are nearly ubiquitous, yet neither Murphy’s nor Bridges’s work existed as GIS data. To further illuminate their pioneering work, we (1) recompiled Murphy’s landforms as a spatial combination of modern existing data layers, and (2) used the recompiled Murphy’s landforms as a basis for the boundaries of the divisions, provinces, and sections described by Bridges. Our aggregation yields a new resource, Named Landforms of the World, version 2.0, which provides a reference-level, basemap-quality data layer that can significantly facilitate mapping, assessing, and understanding Earth surface features.

Mapping Mountain Landforms and Its Dynamics: Study Cases in Tropical Environments

High mountain areas are critical for water security and natural hazard dynamics, as well as glacier and ecosystem conservation in a warming world. We present a brief account of the methodological steps for geomorphological mapping in mountain areas, including the required scale, the legends, technology, and software. We analyze the best imagery sources and their combination with fieldwork and geographical information systems (GIS), in performing accurate cartography. In addition, we present two case studies in which we apply several methods described previously. Firstly, we carried out a classical and digital geomorphological mapping of Cerro Chirripó (Talamanca Range). Secondly, we studied the Reserva Biológica Alberto Manuel Brenes (Central Volcanic Range), where we used UAVs to map high-resolution fluvial geomorphology. This methodological framework is suitable for future geomorphological surveys in mountain areas worldwide. Moreover, the case studies can give ideas on the application of these approaches to different mountainous environments.

Hierarchical geomorphological mapping in mountainous areas

ABSTRACT We present a method of digital geomorphological mapping of mountainous areas with a legend consisting of a three-tiered nested hierarchy using two case study areas from Vorarlberg, Austria. Users can easily visualize maps in a geographical information system (GIS) at the finest level with a legend of 33 morphogenetic domains. Reclassification of the morphogenetic classes in an automated GIS-workflow generates the medium and high levels of hierarchy, and each tier is accompanied by suggested scale ranges for visualization. A variety of high-resolution input data (LiDAR-derived data, geomorphological and geological raster maps) supports the mapping method, which also strongly benefits from field knowledge. The method facilitates analysis, interpretation, visualization and application of geomorphological data at a large range of scales and corresponding information densities within one database. The structure of the legend allows for inclusion of additional morphogenetic classes and for application and adaptation in other environments.

Geomorphology of the Sulden River basin (Italian Alps) with a focus on sediment connectivity

ABSTRACT An area-wide digital geomorphological map consisting of 12,180 non-overlapping polygons was created for the Sulden river basin (South Tyrol, Italian Alps) with the purpose to carry out a GIS-based sediment connectivity analysis. Thirty-one landform types were defined with respect to their role within sediment cascades. As such, the classification and the related symbology partly differ from a traditional geomorphological map where several areal objects are frequently represented by scaled and rotated point symbols. The catchment (∼130 km²), exhibits a high geomorphological variability as well as relatively large glacierized areas. We used the geomorphological map for a first qualitative estimate of the main differences between the two major sub-basins concerning the components of the sediment cascades: while the Trafoi sub-catchment exhibits a high number of small landslides and debris flow channels (i.e. source and transport landforms), the Sulden sub-catchment is rather characterized by large proglacial and talus landforms (i.e. temporary storage landforms).

Geomorphometric tool associated with soil types and properties spatial variability at watersheds under tropical conditions

The application of quantitative methods to digital soil and geomorphological mapping is becoming an increasing trend. One of these methods, Geomorphons, was developed to identify the ten most common landforms based on digital elevation models. This study aimed to make a quantitative assessment of the relationships between Geomorphons units, determined at three spatial resolutions and nine radii, and soil types and properties of two watersheds with different soil-landscape relationships in Brazil to help soil surveying and mapping under tropical conditions. The study was conducted at Lavrinha Creek (LCW) and Marcela Creek (MCW) watersheds, located in the state of Minas Gerais, Brazil. Spatial resolutions of 10, 20 and 30 m were the basis for generating Geomorphons at 9 radii of calculation for the watersheds. They were overlapped to detailed soil maps of the watersheds and a chi-square test was carried out to assess their relationship with soil types. Observation points were compared with the most highly correlated Geomorphons to also assess relationships with soil properties. Geomorphons with resolution of 30-m and radii of 20 and 50 cells, respectively for LCW and MCW, were more highly correlated with the variability of soil types, in accordance with the terrain features of these watersheds. The majority of observation points for each soil type was located in the same Geomorphon unit that was dominant when analyzing soil maps. There was less variability in soil properties between Geomorphon units, which was probably due to the highly weathered-leached stage of soils. Geomorphons can help to improve soil maps in tropical conditions when assessing soil variability due to its high correlation with tropical soil types variability.

Spatial distribution of erosion and deposition during a glacier surge: Brúarjökull, Iceland

Time-series of digital elevation models (DEMs) of the forefield of the Brúarjökull surge-type glacier in Iceland were used to quantify the volume of material that was mobilized by the 1963–1964 surge. The DEMs were produced by stereophotogrammetry on aerial photographs from before the surge (1961) and after (1988 and 2003). The analysis was performed on two DEMs of Difference (DoDs), i.e., a 1961–2003 DoD documenting the impact of the surge and a 1988–2003 DoD documenting the post-surge modification of the juvenile surging glacier landsystem. Combined with a digital geomorphological map, the DoDs allow us to quantify the impact of the surge on a landsystem scale down to individual landforms. A total of 34.2±11.3×106m3 of material was mobilized in the 30.7-km2 study area as a result of the most recent surge event. Of these, 17.4±6.6×106m3 of the material were eroded and 16.8±4.7×106m3 were deposited. More than half of the deposited volume was ice-cored landforms. This study demonstrates that although the total mobilized mass volume is high, the net volume gain of ice and sediment deposited as landforms in the forefield caused by the surge is low. Furthermore, deposition of new dead-ice from the 1963–1964 surge constitutes as much as 64% of the volume gain in the forefield. The 1988–2003 DoD is used to quantify the melt-out of this dead-ice and other paraglacial modification of the recently deglaciated forefield of Brúarjökull.

Digital geomorphological map of Poland

The paper presents the Digital Geomorphological Map of Poland (DGM) on which work started in 2013. Background is provided on the history of geomorphological mapping and the digital adaptation of analoguegeomorphological maps. The legend (key symbols) of the DGM and the construction of its database are introduced. The test sheets prepared on the basis of the DGM assumptions are demonstrated.

Applications of high-resolution images and DTMs for detailed geomorphological analysis of mountain and plain areas of NW Italy

Detailed analysis of Digital Terrain Models (DTMs), digital imagery, and a discussion of their various applications and derived geothematic products are presented for study areas in two different geological and geomorphological contexts of North West (NW) of Italy. In both cases it has been proposed an integrated approach for geomorphological analysis that put in evidence many advantages of using these new geomatics tools.In the first context, digital geomorphological mapping of high altitude areas of the Aosta Valley (Gran Paradiso and Gran San Bernardo) have been carried out by using photogrammetry and remote sensing on airborne laser scanner data (LiDAR derived DTM) and orthophotos. Suitable results have been obtained for areas of difficult accessibility, with reduced costs and work time compared to traditional field techniques.In the second geomorphological context, high-resolution images of the present topography of the high Piedmont plain (Turin, Asti and Cuneo Provinces) have been used to perform GIS mapping and analysis. Evidences of Quaternary modifications in the hydrographic network have been enhanced, suggesting new geomorphological elements for the reconstruction of the recent geodynamic history of the area.

HODNOCENÍ RIZIK DOPADU PROJEKTŮ TĚŽBY UHLÍ NA RELIÉF MORAVSKO-SLEZSKÝCH KARPAT V ČESKÉ REPUBLICE: PŘÍPADOVÁ INŽENÝRSKO-GEOMORFOLOGICKÁ STUDIE DOBÝVACÍHO PROSTORU TROJANOVICE

The aim of the paper is prediction and estimation of risks of planned hard coal deep mining in Trojanovice mining area below sensitive young terrain of the Moravian-Silesian Carpathians and impact of mining activities on the relief. The authors carried out detailed geomorphological mapping of the area, compiled digital geomorphological map and 3-D model of geomorphological hazards. The engineering-geomorphological analysis has shown that planned underground mining activities will accelerate geodynamic processes in the area and cause substantial changes of mountain and highland relief.

Geospatial technologies and digital geomorphological mapping: Concepts, issues and research

Geomorphological mapping plays an essential role in understanding Earth surface processes, geochronology, natural resources, natural hazards and landscape evolution. It involves the partitioning of the terrain into conceptual spatial entities based upon criteria that include morphology (form), genetics (process), composition and structure, chronology, environmental system associations (land cover, soils, ecology), as well as spatial topological relationships of surface features (landforms). Historically, the power of human visualization was primarily relied upon for analysis, introducing subjectivity and biases with respect to selection of criteria for terrain segmentation and placement of boundaries. This paper reviews new spatio-temporal data and geocomputational approaches that now permit Earth scientists to go far beyond traditional mapping, permitting quantitative characterization of landscape morphology and the integration of varied landscape thematic information. Numerous conceptual, theoretical, and information-technology issues are at the heart of digital geomorphological mapping (DGM), and scientific progress has not kept pace with new and rapidly evolving geospatial technologies. Consequently, new capabilities exist but numerous issues have not been adequately addressed. Therefore, this paper discusses conceptual foundations and illustrates how geomorphometry and mapping approaches can be used to produce geomorphological information related to the land surface and landforms, process rates, process–form relationships, and geomorphic systems.

A morphological, sedimentological and geophysical investigation of the Woore Moraine, Shropshire, England

The Bar Hill–Whitchurch–Wrexham Morainic Complex is a large-scale glacial landform thought to represent either the maximum extent or the re-advance of the British–Irish Ice Sheet during the Late Devensian. The origin of the moraine remains uncertain as its key characteristics have not been studied in detail due to a lack of exposures from which its large-scale structure can be determined. The development of new technologies has enabled detailed examination of the topography and internal structure of such large-scale landforms. This paper describes a multi-disciplinary approach involving digital geomorphological mapping using enhanced resolution NextMAP™ digital surface models, geophysical imaging (electrical resistivity tomography) and conventional sedimentological analyses. This combination of techniques is useful for elucidating the origin of a large glacial landform in a region of poor exposure. Digital elevation models such as NextMAP™ offer an efficient and accurate method for landform-mapping, whilst electrical resistivity tomography was able to map the major constituent sediments of the moraine, which had in turn been identified in the single exposure available. Additional geophysical techniques should however be applied to provide further structural data and thereby enable a more detailed interpretation of the moraine's internal structure. Preliminary findings indicate that the moraine is a glaciotectonic landform composed of diamicton and glaciofluvial sediments, an origin consistent with recent suggestions that the Cheshire Plain contained an active ice lobe during the last glacial maximum.

Digital geomorphological landslide hazard mapping of the Alpago area, Italy

Large-scale geomorphological maps of mountainous areas are traditionally made using complex symbol-based legends. They can serve as excellent “geomorphological databases”, from which an experienced geomorphologist can extract a large amount of information for hazard mapping. However, these maps are not designed to be used in combination with a GIS, due to their complex cartographic structure. In this paper, two methods are presented for digital geomorphological mapping at large scales using GIS and digital cartographic software. The methods are applied to an area with a complex geomorphological setting on the Borsoia catchment, located in the Alpago region, near Belluno in the Italian Alps. The GIS database set-up is presented with an overview of the data layers that have been generated and how they are interrelated. The GIS database was also converted into a paper map, using a digital cartographic package. The resulting largescale geomorphological hazard map is attached. The resulting GIS database and cartographic product can be used to analyse the hazard type and hazard degree for each polygon, and to find the reasons for the hazard classification.

Baselevel, Grade and Peneplain

Baselevel, Grade and Peneplain