Geomorphological Mapping, GIS, Remote Sensing and Modelling


Geomorphological Mapping, GIS, Remote Sensing and Modelling
Conveners: Cenira Cunha, Leonardo Santos, Jean-Philippe Malet, Rui Figueiredo
| Thu, 15 Sep, 09:00–16:30|Room Sala Sofia-C2B
| Attendance Thu, 15 Sep, 10:30–10:45 | Display Thu, 15 Sep, 09:00–Fri, 16 Sep, 19:00|Poster area

Orals: Thu, 15 Sep | Room Sala Sofia-C2B

Chairpersons: Leonardo Santos, Rui Figueiredo
GIS, remote sensing, modelling and others
Álvaro Gómez-Gutiérrez, Manuel Sánchez-Fernández, José Juan de Sanjosé-Blasco, and Francisco Lavado-Contador

Geomorphic systems face significant changes of climate, land uses, vegetation cover and socio-demographic characteristics. In this context, the accurate monitoring of geomorphological features may be a relevant tool to understand the consequences and the risks of these changes. At the same time, monitoring some geomorphic systems (for instance a coastal cliff) may be challenging, difficult and dangerous. The direct georeferencing techniques, which do not require acquiring Ground Control Points (GCP), recently integrated into new platforms (mainly Unmanned Aerial Systems or UAS) and sensors (photographic or laser) facilitate this task. Here we test the accuracy of direct georeferencing approaches for two UAS: a DJI Phantom 4RTK (P4) and a MD4-1000 LIDAR. Two flights were carried out to capture images with the P4 over a beach and a coastal cliff in Cantabria (N Spain): a) in Real Time Kinematic (RTK) mode receiving NTRIP corrections and b) without real time corrections to later process the data using a Post Processing Kinematic (PPK) approach with simultaneously registered data at permanent GNSS stations. The PPK approach for the P4 dataset was carried out using Redcatch software and three permanent stations located at different distances of the study area to analyse the influence of the baseline. The P4 datasets were processed by the Pix4Dmapper Pro photogrammetric software to produce 3D models. The same study area was surveyed by the MD4-1000 LIDAR UAS that performs in PPK mode and produces a 3D model. The MD4-1000 LIDAR dataset was processed using PosPac UAV and mdLIDAR processing software packages. Two datasets were used to test the accuracy of the resulting 3D models: a set of 18 check control points established in the study area and surveyed using a GNSS instrument in RTK mode and a 3D model surveyed by a Terrestrial Laser Scanner placed at 5 locations (23.4·106 points with a registration error of 7 mm).

The P4 RTK approach showed a Root Mean Square Error (RMSE) for the Z coordinate of 0.12 m against 0.02 m obtained for the PPK approach. The MD4-1000 LIDAR showed a RMSE for the XY coordinates of 0.03 m and 0.06 for the Z coordinate. These figures were corroborated by the 3D distances between each resulting model and the TLS 3D model. In terms of point density and coverage the P4 resulting point clouds outperformed that obtained by the MD4-1000 LIDAR system, except in vegetated surfaces, where the photogrammetric technique completely failed to reconstruct the surface (i.e. to calibrate the images). These results and figures may be useful for geomorphologists and surveyors interested on monitoring features without the need for GCPs.

How to cite: Gómez-Gutiérrez, Á., Sánchez-Fernández, M., de Sanjosé-Blasco, J. J., and Lavado-Contador, F.: Accuracy of direct georeferencing strategies to monitor geomorphological features, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-91, https://doi.org/10.5194/icg2022-91, 2022.

Zayd Abid-Waheed, Neil Entwistle, and George Heritage

River restoration projects have long relied on the use of modelling in both 1D and 2D to simulate the changes to flow hydraulics and flood extent that alterations to a river and floodplain will have caused. These methods have grown more accurate with increasing computing power and more complex software. However, despite the developments in modelling, a significant gap remains in the usage and accuracy of sediment modelling to identify arguably one of the most important metrics of river restoration: Geomorphic Change. Therefore, this paper attempts to address this by investigating the accuracy of high-resolution sediment modelling to identify geomorphic change on Blaze Beck in Cumbria, a high energy wandering river system that has recently been restored. Comparisons have been made between the impacts of a simulated flood event created using HEC-RAS 6.1 modelling software and a real-life flood event on October the 27th 2021, to compare changes to geomorphology and identify the degree of accuracy of the 2D change modelling compared to change measured using drone-based photogrammetry. The results appear generally accurate, predicting locations of head cutting and more general low-level erosion and deposition. Bar formation, splay deposition and general bed raising are all predicted. The model is, however, very sensitive to the gradation of sediment it has been trained with and this can skew the ratio and pattern of deposition and erosion depending on the sample data used to simulate real life conditions. The model, once refined and iterated to best simulate potential change, is functional even in a high energy hydraulically diverse environment like Blaze Beck, and will have significant value in predicting the degree to which geomorphic change will occur because of restorative or other changes to a river reach.

How to cite: Abid-Waheed, Z., Entwistle, N., and Heritage, G.: Using 2D Sediment Modelling to Simulate Geomorphic Change for River Restoration Initiatives, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-63, https://doi.org/10.5194/icg2022-63, 2022.

Petra Gostinčar, Manja Žebre, Petra Jamšek Rupnik, Eva Mencin Gale, Jernej Jež, Uroš Stepišnik, Jure Atanackov, and Miloš Bavec

On a global scale, inventories and databases are gaining value and there is a demand for openly accessible and reusable data. Here presented GIS database of glacial geomorphological evidence is a compilation of all available glacial and other relevant data in the South-Eastern Alps and the Northern Dinaric Mountains in Slovenia, Italy and Croatia. The database contains the following elements: glacial landforms (e.g., moraines, cirques, erratic fields, kame terraces), non-glacial landforms relevant for the interpretation of the glacial environment (e.g., alluvial fans, alluvial terraces, rock glaciers, protalus ramparts, talus cones), outcrop locations, geochronological data, and data on geophysical exploration. The accompanying attribute tables contains some basic information for each feature, such as type and description of a landform, assumed age, reference, etc. In the first step of database creation, the data were digitised, georeferenced (if not already done by the authors themselves) and cited accordingly. In the second step, the input data were revised in the field and topographically adjusted using a high-resolution lidar-based digital elevation model. The GIS database of glacial geomorphological data was used to develop the web map viewer, which also displays empirically reconstructed ice limits for different time spans during the last glacial cycle (130-0 ka). The data stored in the GIS database is available as ESRI shapefile format. Both the GIS database and the map viewer are open access. Disseminating the results of past and ongoing studies on glacial geomorphological evidence in the Alps-Dinarides junction will improve the availability and accessibility of data, build on previous findings and potentially prevent unnecessary repetition of work already done. Improved accessibility of data also offers greater potential for further research in large-scale studies in the area.


This work was funded by the Past climate change and glaciation at the Alps-Dinarides junction project (J1-2479) supported by the Slovenian Research Agency.

How to cite: Gostinčar, P., Žebre, M., Jamšek Rupnik, P., Mencin Gale, E., Jež, J., Stepišnik, U., Atanackov, J., and Bavec, M.: Towards a comprehensive overview of glaciation at the Alps-Dinarides junction: compilation of a GIS database and creation of a web map viewer, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-227, https://doi.org/10.5194/icg2022-227, 2022.

Benedict Collings, Murray Ford, and Mark Dickson

Satellite earth observation data has been frequently applied to monitor shoreline change at very large geographic scales. Techniques focus on the extraction of the instantaneous waterline boundary, a shoreline proxy that can be extracted from publicly available multispectral satellite data with sub-pixel accuracy. Interpreting coastal change through this proxy can be uncertain as the position of the waterline is dynamic, a function of beach gradient and constantly fluctuating marine processes, and might not capture information of the full spectrum of drivers influencing change for a given section of coast.

Satellite data is acquired in raster format and there is useful information stored in each pixel across the entire coastal zone. Applying per-pixel change detection techniques could offer further insights to the role of drivers of coastal change beyond a vectorised land-water boundary. This paper describes a new method for monitoring coastal change at large geographic scales with public satellite remote sensing data through pixel-based change detection. The first step is the classification of pixels into specific coastal landcover classes. This is challenging at large scales owing to complex and diverse physical environmental characteristics. A methodology was developed and applied to New Zealand’s coastline, identifying 9 landcover types including sedimentary coast. A combination of Sentinel multispectral and synthetic-aperture-radar data were used to derive composite imagery for 2019 using Google Earth Engine cloud computing platform. This was classified using a set of hierarchal rules and machine learning in a Python programming environment. This was validated nationally against high-resolution aerial photography and commercial satellite imagery. This produced a coastal specific landcover classification from which per-pixel change detection techniques can be applied. Overall accuracy was 86.38% and exceeded 90% when normalised by class area.

The outputs and code are available, and the framework has been designed to work with a range of earth observation datasets and can be applied to other regions around the world. Ongoing work includes implementing a framework to assess long-term change, at the coast in New Zealand. By investigating how specific coastal landcover types are changing, useful information can be acquired to better interpret drivers of coastal change and the impacts on coastal geomorphology at large geographic scales.


Keywords: Satellite Remote Sensing, Multispectral, Synthetic Aperture Radar, Landcover classification, Change detection, Coastal change.

How to cite: Collings, B., Ford, M., and Dickson, M.: Pixel-based coastal change detection, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-382, https://doi.org/10.5194/icg2022-382, 2022.

Sebastiano Trevisani

The first aim of this work is to introduce a new geostatistical-based algorithm that permits to detect specific aspects of short-range surface roughness (or of image texture) which does not require user defined choices, except for the radius of the search window, and provides a high interpretability of the results.  In particular, differently from usual geostatistical approaches, this algorithm does not require the derivation of a residual digital elevation model. The new proposed algorithm, despite its simplicity, permits to detect relevant aspects of surface texture, including anisotropy. Moreover, adopting approaches based of digital elevation model smoothing it can also be applied in the context of multiscale analysis. A second aim, functional to the introduction of the new algorithm, is to furnish a general overview of the key aspects of the geostatistical methodologies, highlighting analogies and differences with other approaches. In presenting the algorithm, a comparison with the roughness computed by means of dispersion of vectors normal to surface is performed.


ATKINSON, P.M. and LEWIS, P., 2000. Geostatistical classification for remote sensing: An introduction. Computers and Geosciences, 26(4), pp. 361-371.

BALAGUER, A., RUIZ, L.A., HERMOSILLA, T. and RECIO, J.A., 2010. Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification. Computers and Geosciences, 36(2), pp. 231-240.

GUTH, P.L., 2001. Quantifying terrain fabric in digital elevation models. GSA Reviews in Engineering Geology, 14, pp. 13-25.

HERZFELD, U.C. and HIGGINSON, C.A., 1996. Automated geostatistical seafloor classification - Principles, parameters, feature vectors, and discrimination criteria. Computers and Geosciences, 22(1), pp. 35-41.

TREVISANI, S., CAVALLI, M. and MARCHI, L., 2009. Variogram maps from LiDAR data as fingerprints of surface morphology on scree slopes. Natural Hazards and Earth System Science, 9(1), pp. 129-133.

TREVISANI, S., CAVALLI, M. and MARCHI, L., 2012. Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin. Geomorphology, 161-162, pp. 26-39.

TREVISANI, S. and ROCCA, M., 2015. MAD: Robust image texture analysis for applications in high resolution geomorphometry. Computers and Geosciences, 81, pp. 78-92.

TREVISANI, S. and CAVALLI, M., 2016. Topography-based flow-directional roughness: Potential and challenges. Earth Surface Dynamics, 4(2), pp. 343-358.


How to cite: Trevisani, S.: Introducing a new and simplified geostatistical-based roughness algorithm, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-384, https://doi.org/10.5194/icg2022-384, 2022.

Takashi Oguchi, Hiroyuki Yamauchi, Jiali Song, Takuro Ogura, Yuichi Hayakawa, Ken'ichi Tsuruoka, and Kotaro Iizuka

Effective geomorphological education for young students such as university undergraduates and high school students is crucial for fostering future geomorphologists and the long-term development of Geomorphology. As an outreach activity, geomorphological education for common people is also meaningful. Especially, education related to geomorphological hazards for citizens will lead to disaster risk reduction. We have been developing materials and curricula for geomorphological education using GIS, Internet technology, close-range remote sensing, and virtual reality, and have applied them to practical courses in high school classes and social events in Japan and China. The developed materials include: 1) online resources for learning GIS operations including geomorphometric analysis, 2) Web-based online GIS for a better understanding of flood hazard maps in relation to landforms, 3) explanatory materials of typical landforms in Japan based on photographs and topographic data obtained by Unmanned Aerial Vehicles (UAVs), and 4) visual contents for virtual tours of geomorphological sites such as a coastal cliff and an underground cave. This presentation introduces the main points of our educational activities and discusses their implications to provide future perspectives.

How to cite: Oguchi, T., Yamauchi, H., Song, J., Ogura, T., Hayakawa, Y., Tsuruoka, K., and Iizuka, K.: Applications of GIS, Internet technology, close-range remote sensing, and virtual reality to develop geomorphological education, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-389, https://doi.org/10.5194/icg2022-389, 2022.

Coffee break and poster session
Chairpersons: Leonardo Santos, Rui Figueiredo
GIS, remote sensing, modelling and others
Joanna Ewa Szafraniec

Thanks to the modern development of technology, for the morphometric analysis of landforms, we can use accurate data from, for example, laser scanning or UAVs. However, these methods require access to quite expensive equipment, and the available public domain data does not always meet our accuracy requirements. The aim is to present how to obtain high-resolution DTM of small landforms using the photogrammetric Structure from Motion (SfM) technique and open source software available on the web.

In obtaining data, the first stage of fieldwork can be distinguished, where the necessary simple tools are, e.g. stakes and a tape measure/ rangefinder, used to scale or build local coordinate systems of landforms and analyse height and distance errors. However, the essential tool is a digital camera, which, based on the rules of acquiring stereoscopic models (appropriate coverage of adjacent photos), will allow filming the object/ landform from all sides. This principle and image recognition techniques are the basis of the SfM method. The next stages of the work use open-source software to extract the right frames from the movie (e.g. one frame per second), adjust them by combining identical control points, generate a point cloud, rectify it and generate digital elevation models. The last stage is the creation of high-resolution DTM using appropriate interpolation methods in a geoinformation environment.

The above operation scheme allows obtaining DEM with very dense coverage of about 1 point per 1 cm2, having one film frame per second. The resolution of 0.05–0.1 m of the created DTM is a good and optimal value. The accuracy of the model can be increased by increasing the sampling of film frames. The results also show that the values of basic morphometric parameters on models with a resolution of, e.g. 2 m are significantly overestimated. It is possible to examine the minimum size of the landforms for which models with a resolution of 1–2 m will be optimal for the needs of morphometric analyses.

The described method is a cheap, simple and attractive alternative to commercial techniques and software and can be used directly in geomorphological studies, e.g. in the case of documentation of rapid changes in the topography under the influence of extreme events caused by climate change. The method can also be widely applied in many other fields, e.g., archaeology, palaeontology, architecture, and forensics.

How to cite: Szafraniec, J. E.: Structure from Motion technique and open-source software in obtaining high-resolution DTM, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-403, https://doi.org/10.5194/icg2022-403, 2022.

Brian Owain Nieuwenhuis, Fabio Marchese, and Francesca Benzoni

Shallow coral reefs are biodiverse ecosystems currently severely at risk from anthropogenic disturbance and climate change. To ensure their survival through the Anthropocene, ecologically informative maps of these areas, that can guide ecosystem-based management, are necessary. In recent years, Unmanned Aerial Vehicles (UAVs) have emerged as a new tool to obtain spatially explicit data of the benthic community in very shallow habitats (<3.5 m deep), where acoustic survey techniques used in deeper water become challenging or unfeasible. Structure-from-Motion (SfM) processing allows the conversion of separate images into high-resolution orthomosaics and Digital Elevation Models (DEM), spanning several hundred metres. The orthomosaic is commonly used to create a habitat map. Object-Based Image Analysis (OBIA), in which an image is first segmented into homogeneous segments before classification, provides an effective method to work with such high-resolution data. In this study we investigated the possibilities to enhance habitat classification by also using the DEM in the OBIA. Therefore, we surveyed three shallow reef areas on the central Saudi-Arabian coast with a consumer-grade UAV and processed the imagery with SfM. We then separately assessed the impact of adding the DEM’s three-dimensional information on the image segmentation and automatic classification steps in the OBIA. Integrating both the 3D model and spectral information into the segmentation greatly reduced the amount of oversegmentation. The addition of DEM-derived variables into a Random Forest classifier increased overall classification accuracy up to 11%. Thus, this study demonstrates the previously untapped potential of a drone’s DEM to improve the accuracy of semi-automated OBIA for habitat mapping in shallow tropical marine ecosystems.

How to cite: Nieuwenhuis, B. O., Marchese, F., and Benzoni, F.: Integrating a drone’s DEM and orthomosaic enhances performance of Object-Based Image Analysis for habitat mapping of shallow coral reefs, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-439, https://doi.org/10.5194/icg2022-439, 2022.

Marta Andrea Ezeta Watts, Fabio Marchese, and Francesca Benzoni

Remote sensing studies based on satellite and aerial imagery have generated a good understanding of the distribution of several shallow reefs found along the Arabian coast (Bruckner et al., 2011, Rowlands et al., 2012, Rowlands et al., 2016). However, data concerning the deeper benthic assemblages' spatial distribution, type, and conditions are missing, especially in the central Red Sea. Using high-resolution MBES and video collection, we aim to map, describe and classify the reefs found in Thuwal's coastal area, filling the information gap by producing the first benthic habitat map of this area.

High-resolution bathymetric data were collected using the Norbit iWBMS Multibeam Echosounder, which allowed us to classify the reefs in 12 morphotypes. From those morphotypes, 28 areas were selected for ground-truthing examination using a BlueROV2 equipped with a 4K camera and USBL positioning system to characterize the benthic community.

With the information obtained from the bathymetry data and the ROV video transects, a benthic habitat map for Thuwal's reefs was created, where 23 benthic habitat types were observed.

This research uncovered previously poorly studied reef morphologies in the Red Sea and their benthic composition, demonstrating how different reef communities express a different three-dimensional morphological structure. Moreover, this work will help us improve the understanding of the spatial distribution and condition of benthic communities located on Thuwal's coastline, giving a baseline with the potential to provide fundamental information that can be used for management, conservation, and future research in Saudi Arabia.

How to cite: Ezeta Watts, M. A., Marchese, F., and Benzoni, F.: Reef morphotype characterization as an effective tool for benthic habitat description: a case study from the Red Sea., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-516, https://doi.org/10.5194/icg2022-516, 2022.

Christian Depraetere and Serge Riazanoff

Present terrestrial landforms result from hydrogeomorphological processes during geological times that could be deciphered with DEM with specific algorithms. DEM could be considered as a "footprint" with two folds: the "downprint" referring to a tessellation of catchment basins organized according to lowest points and the "upprint" as a topographical splitting in relation to highest points.
Specific algorithms allow the extraction of both "prints" that must be analyzed with ad hoc geostatistical methods. For the downprint, various algorithms have been been developed since the 1980ties to extract of catchments according to the steepest descent downstream lines (I.e. D8 method or variant of it); for the upprint, the previous algorithms must be modified to fit with the specific topological properties of steepest ascent morphological lines with stepwise iterations to delineate humps, hills and mountain ranges of embedded (or enshrined?) magnitudes.
This geomorphometrical approach is applied to DEM SRTM 1 arc second (About 30 meters resolution) on the Sao Miguel and the Pico volcanic islands for comparison purposes. The results pinpoint the valuable contribution of the combined geostatistical analysis of both downprint and upprint to unravel the intricate patterns of hydrological and lithological entities so to say Steepest descent hydrological units (SDHU) and Steepest ascent morphological units (SAMU).
The SDHU delineated from DEM correspond to catchment basins and specific algorithms are implemented in many GIS for hydrological and other types of modeling. This is not the case for SAMU which need to be explained; each unit will be called "massif" and refers to all steepest ascent lines converging to one and only one summit for elementary SAMU (order 0) and the limits between them are related to thalwegs and saddle points; at higher orders, the progressive merging of the elementary massifs creates hierarchical sets (orders 1 to n) of larger massifs with several summits. The result delineates morphological units such as major volcanic mountains and also smaller adventives volcanoes in the case of both islands of San Miguel and Pico. SAMU are then mostly related to lithological and tectonic features and are complementary to SDHU which are hydrological functional units.
The comparative geostatistical analysis (area-number Korcak method) of SDHU and SAMU of the two islands suggests that they have different downprints and upprints despite that there are in the same morphotectonic and climatologic contexts. The discrepancies between the two islands may be because the volcanic geology of San Miguel is older than the one of the island of Pico.


Depraetere C., Riazanoff S. (2004). « The new Digital Elevation Model data set from the Shuttle Radar Topography Mission : Hydrogeomorphological applications in the Ohrid region (Albania, Greece and Macedonia) ». Conference on Water Observation and Information System for the Balkans Countries BALWOIS, Ohrid, Northern Macedonia, 25-29 May 2004.

Depraetere C., Riazanoff S. (2021). « A Stepwise Massif Partitioning Algorithm Based On Steepest Ascent Method From DEM: Application To Potential Prospection of new archaeological sites ». Extended abstract, 17th International Conference of Computational Methods in Sciences and Engineering ICCMSE 2021 conference, Heraklio, Greece, 4-7 September 2021.


How to cite: Depraetere, C. and Riazanoff, S.: Downprint and upprint of landforms from DEM: the case of the volcanic Acores islands., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-631, https://doi.org/10.5194/icg2022-631, 2022.

Geomorphological process
George Olivier, Marco Van De Wiel, and Willem De Clercq

Gully erosion affects land and water resources, resulting in serious environmental and socio-economic consequences. To aid mitigation and rehabilitation efforts, gully susceptibility mapping of broader gully-prone regions should be augmented by the rapid detection of existing gully features. Numerous works have been published on (semi-)automated approaches to detect gully erosion, most recently incorporating machine learning. However, upscaling and transferability capabilities of these approaches are rarely investigated. Establishing algorithms that are scalable and transferrable will constrain uncertainties when conducting quantitative analysis, allowing comparable results at different landscape scales and/or geo-environmental settings. Here, we aim to develop and apply a semi-automated approach based on Object-Based Image Analysis (OBIA) with low data needs, at different scales and geo-environmental regions. The segmentation process is underpinned by two gully morphological properties: 1) Height Above Nearest Drainage (HAND) and normalised slope, calculated from a Digital Elevation Model (DEM) with a spatial resolution of 2 m, with 93% coverage of South Africa’s 1.22 million km2 expanse. HAND is a terrain model that normalises topography according to local relative heights above a drainage channel (herein, a gully channel). While this has been implemented in flood mapping studies for river systems, it remains unused in gully detection algorithms. Slope, which is often used as a gully predictor variable, is used to confine HAND and implemented here as a normalised slope input, calculated by subtracting a convolved mean slope value with a designated filter size from the DEM-derived slope. Detected gully features are refined using expert knowledge, merging, and pixel-based growing and shrinking. Preliminary development at a local gully scale suggests good performance, with an overall accuracy of 82.3% (includes a user accuracy of 65.5% of gully and 99.0% for non-gullied areas, and a producer accuracy of 98.5% for gully and 74.2% for non-gullied areas) and a kappa index of 0.65. We also discuss the broader performance of our approach when upscaling and implemented in other geo-environmental settings covered by the 2 m-DEM. 

How to cite: Olivier, G., Van De Wiel, M., and De Clercq, W.: Giving gully detection a HAND, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-102, https://doi.org/10.5194/icg2022-102, 2022.

Romanus Udegbunam Ayadiuno, Dominic Chukwuka Ndulue, and Arinze Tagbo Mozie

Landslides are major hydro-geological and anthropogenic hazards that affect not only the mountains areas but also gullies, mining areas, plateau terrain, river banks, coastal areas, and offshore as undersea slides. Slides occur as a result of ground movement, rock falls, and failure of unstable slopes; sand and debris flow on slopes which can cause lots of damage with direct and indirect impacts on human settlements and physical infrastructures. The study used secondary data that consist of other literature from which the likely triggering factors – slope angle, land use land cover change (LULCC), aspect, soil texture and type, curvature, drainage density, elevation, lineament density, normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), geology, topographic wetness index (TWI), geomorphology, rainfall, temperature, wind speed, wind pressure, settlements, rivers and roads construction were extracted, and satellite imageries (SRTM and Landsat 8 OLI-TIRS) data obtained from USGS Earth Explorer, processed and mapped based on the triggering factors using ArcGIS v10.4 and validation visit was made to confirm results. Microsoft excel 2007 was used to compute and assigned weights to the factors while weighted overlay methods in spatial analyst tool of ArcGIS v10.4 were applied in mapping the landslide vulnerable areas in the study area. The study recommended the use of laws to secure and regulate land use activities in the vulnerable areas, educating inhabitants of such areas about the dangers associated with certain land use activities and the need to avoid them, providing alternative means of livelihood that will discourage mining, deforestation, forest fire, and overgrazing, and encourage sustainable resource use and management that will not expose the areas to the triggering factors of landslide.


Keywords: GIS-Remote Sensing, Assessment, Mapping, Landslide Vulnerability Areas, South East

How to cite: Ayadiuno, R. U., Ndulue, D. C., and Mozie, A. T.: GIS-Remote Sensing Integrated Based Assessment and Mapping of Landslide Vulnerability Areas in South East, Nigeria, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-399, https://doi.org/10.5194/icg2022-399, 2022.

Lunch break
Chairpersons: Rui Figueiredo, Leonardo Santos
Geomorphological process
Sanja Bernat Gazibara, Marko Sinčić, Martin Krkač, Petra Jagodnik, Željko Arbanas, and Snježana Mihalić Arbanas

The Istrian Peninsula, in the western part of Croatia, belongs to an undeformed part of the Adriatic Plate. The central part of Istria is the area of the Eocene flysch basin, i.e. “Gray Istria“, which is prone to weathering and active geomorphological processes. The siliciclastic rocks of the basin are homogeneous hemipelagic marls (Globigerina marls with a maximal thickness of 150 m) overlain by gravity-flow deposits or flysch-type rocks. The high erodibility of the Istrian marls led to the formation of steep barren slopes and badlands exceptionally susceptible to slope movements. This research presents the application of Light Detection and Ranging (LiDAR) data for the landslide and erosion inventory mapping at a large scale. Airborne laser scanning (ALS) was taken in March 2020 for the pilot area in the City of Buzet. Based on the characteristics of the acquired LiDAR Point Cloud, a bare-earth digital elevation model (DEM) with 30 cm resolution was created. Different topographic derivative datasets such as slope, hillshade, contour lines, roughness, curvature, flow accumulation and stream power index maps were created to interpret the LiDAR data. Visual identification and mapping of landform features were done on the study area (20 km2) at a large scale (1:500) to produce detailed landslide and erosion maps for implementation in the spatial planning system. After preliminary visual interpretation of LiDAR DTM and field verifications, it was concluded that three types of landforms could be mapped, i.e. badlands, unstable slopes and landslides. Badlands were first identified on the digital orthophoto maps 1:5.000 as areas with sparse or no vegetation, and then the boundary of the entire affected slope was mapped in detail on the LiDAR DTM morphometric derivatives. Additional field checking showed that badland boundaries based on digital orthophoto images and LiDAR DTM have significant deviations. Badlands dominantly appears in the form of plane forms on steep slopes and less often as linear forms such as erosion gullies or torrent beds. Unstable slopes were categorised as areas with dense sliding where the exact landslide boundaries could not be mapped due to the coalescence of landslides or poor contrast between affected and unaffected areas due to the intense erosion. Landslide identification on the LIDAR DTM morphometric derivatives is based on recognising landslide features (e.g., concave main scarps, hummocky landslide bodies and convex landslide toes). A digital orthophoto map from 2020 was used during landslide identification to check the morphological forms along roads and buildings, such as artificial fills and cuts, which can have a similar appearance to landslides on DTM derivatives. Sliding is most often along contacts between weathered and fresh flysch-type rock, especially at places with concentrated surface runoff (e.g., near roads), which typically cause small and shallow landslides. The final result of the visual interpretation of LiDAR DTM derivatives is multi-hazard inventory map which can be implemented in the spatial planning system of the city of Buzet.

How to cite: Bernat Gazibara, S., Sinčić, M., Krkač, M., Jagodnik, P., Arbanas, Ž., and Mihalić Arbanas, S.: Landslide and erosion inventory mapping based on LiDAR data: A case study from Istria (Croatia), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-408, https://doi.org/10.5194/icg2022-408, 2022.

Gonzalo Fernández-Olloqui, Jorge Lorenzo-Lacruz, Noemí Lana-Renault, and Fernando Pérez-Cabello

Wall collapses, sometimes accompanied by mass movements, is one of the main degradation processes in long-abandoned agricultural terraces and critically affects the hydrological and geomorphological behaviour of terraced hillslopes (e.g., development of new sediment sources, increasing soil erosion, increasing hydrological connectivity, re-establishment of natural drainage pathways). An efficient monitoring of the spatial and temporal dynamics of wall collapses is fundamental to understand all these processes. However, the identification of terrace wall collapses in the field is a time-consuming task with spatial limitations. In this study, Object Based Image Analysis (OBIA) applied on High-Resolution Topography was used (and evaluated) for detecting wall collapses in terraced hillslopes. The approach, which includes image segmentation and Support Vector Machine classification, was implemented in the Cidacos Valley (Iberian Range, Spain), extensively affected by the abandonment and degradation of agricultural terraces. Point clouds extracted from three different remote data sources (airborne LiDAR, terrestrial LiDAR and airborne photogrammetry) were used to obtain three different digital terrain models (DTM). The low spatial resolution of the DTM derived from airborne LiDAR (1 m pixel size) was not sufficient to detect any terrace wall collapse, which had a median size of 10 m2. The results showed that slope, Sky-View factor, topographic openness and curvature DTM-derivatives produced the best segmentations. Field inventories of wall collapses were used to train the classification algorithm (Support Vector Machine) and validate the results of the OBIA approach. Terrace wall collapses were identified with an Overall Accuracy of 0.80 and a Producer Accuracy of 0.50. The results of the approach and further improvements are discussed. Although promising, the detection of wall collapses in terraced hillslopes using OBIA is challenging, especially when it is compared to the detection of larger scale hillslope geomorphological processes (e.g.: landslides).

How to cite: Fernández-Olloqui, G., Lorenzo-Lacruz, J., Lana-Renault, N., and Pérez-Cabello, F.: Identification of wall collapses in abandoned agricultural terraces using Object Based Image Analysis and High-Resolution Topography, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-536, https://doi.org/10.5194/icg2022-536, 2022.

José Eduardo Bonini, Bianca Carvalho Vieira, and Tiago Damas Martins

In the last two decades several studies have applied automatic and semiautomatic methods to produce landslide inventories using high resolution Earth Observation products such as satellite imagery and Digital Elevation Models (DEMs). In Brazil, inventory maps for large areas are not systematic and the application of automated and semiautomated methods for landslide detection is unusual. In January 2014 intense rainstorms (200mm/2h) occurred in the Ribeira de Iguape river Valley (São Paulo State, Southeast Brazil), triggering landslides and a debris flows that caused 25 deaths and damage to urban, transportation and energy infrastructures. In the following years, a few event-based inventories were produced for small subbasins affected in 2014, by the means of empirical methods and freely available images. To the best of our knowledge there are no large-scale event-based inventories for the whole area affected by landslides in the 2014 event. In this study, we tested a combination of unsupervised classification of high-resolution orbital images, visual interpretation and DEM analysis to map landslides triggered in 2014 event. The landslide inventory was produced for an area of 110 km². The ISODATA algorithm from SAGA GIS was used to clusterize a NDVI difference layer derived from RapidEye (5m) pre-event and post-event orhorectified mosaics. The resulting clusters were checked and corrected through visual interpretation. Finally, we used a TanDEM-X DEM (12m) to identify valley bottoms and separate the inventory in two classes: landslide scars and landslide deposits. Our results shows that an area of 5.48 km² (approximately 5% of the total area) was affected by landslides in 2014, with 4.04 km² classified as landslide scars and 1.44 km² as landslide deposits. A total of 2089 landslide scars were detected, with mean area of 1.926 m², minimum of 25 m², maximum of 91.100m² and median of 800 m². Given the scarcity of detailed geographical information about the landslides in the area, the inventory presented here may improve future susceptibility and hazard studies, especially regional scale statistically based models. This inventory can also be used as labeled sample for the application of Machine Learning and Deep Learning algorithms aiming to detect landslide scars and the timing of ruptures using satellite imagery time series, as well to launch a systematic mapping of such phenomena in Brazil.

How to cite: Bonini, J. E., Vieira, B. C., and Martins, T. D.: Semiautomatic inventory of the landslides triggered in the 2014 event in Ribeira Valley using Remote Sensing Data, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-664, https://doi.org/10.5194/icg2022-664, 2022.

Geomorphological map
Valerija Butorac, Andrija Krtalić, and Nenad Buzjak

In mountainous regions such as mountainous Croatia, natural and semi-natural landscapes are most common and are changing due to climate change and more intense economic activities. Due to these changes, there is a need of inventarisation and valorisation of mountainous landscapes in order to manage and preserve them. In Croatia, there is no inventory that would provide us with a zero status of mountain landscapes. On the other hand, the mountainous environment and the size of the area ​present an obstacle for landscape mapping. The use of Sentinel-2a imagery and a digital relief model allow ​a fast, inexpensive, and accurate mapping of landscapes in large areas such as mountainous Croatia. Orthophoto images were used to increase the accuracy of sampling and thus the accuracy of the final classification. Remote sensing techniques, GIS analysis and field validation were used to create an inventory of the landscapes types. This type of landscape mapping, which includes geological, geomorphological and land cover data, provides a better understanding of the composition and configuration of mountain landscapes, leading to knowledge-based management and landscape-level protection.

How to cite: Butorac, V., Krtalić, A., and Buzjak, N.: Sentinel 2a in mountain landscape mapping – region of mountainous Croatia, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-207, https://doi.org/10.5194/icg2022-207, 2022.

Fábio Luiz Macao Campos and André Luiz Nascentes Coelho

Geomorphometry is an interdisciplinary science that aims to quantify the earth's surface landforms. This science techniques have supported the development of several knowledge fields, including geomorphology, in which the relationship between landforms and processes can be better understood and used in practical applications. In order to evaluate the use of geomorphometric techniques for structural best management practices (BMPs) placement in basin scale and what spatial resolution can provide better results, a morphological mapping methodology has been developed and 3 different digital elevation models (DEM) have been evaluated as data sources (SRTM – 30 m; ALOS/PALSAR – 12.5 m; GEOBASES – 2 m). The methodology has been applied in a small watershed in Espírito Santo state (Brazil) using 3 DEMs with different spatial resolutions. In such basin, slope segments previously defined as priorities for the BMP placement has been mapped using the Qgis software and the SAGA tools, for the 3 DEMs. The landforms mapped have been compared to the landforms observed in a field work. The results show the differences between the DEMs related to the mapping of relief units (summit, slope, valley) as well as the curvature of the slope segments (concave, straight, convex). Different results in terms of mapping priority areas for BMP placement have been noticed. The SRTM and Alos/Palsar DEMs are proven to be great options for carrying out morphological mapping for BMP placement purpose. Both DEMs have produced very similar results compared to the field work, while the 2-meters spatial resolution DEM was not able to map the features satisfactorily due misrepresentation of landforms and slope segments.

How to cite: Macao Campos, F. L. and Nascentes Coelho, A. L.: Relief mapping to best management practices placement purpose: an evaluation of different Digital Elevation Models, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-264, https://doi.org/10.5194/icg2022-264, 2022.

Efthimios Karymbalis, Konstantinos Tsanakas, Diamantina Griva, Dimitrios-Vasileios Batzakis, and Kanella Valkanou

The present study is a geomorphological overview of Greece on a scale of 1:1,000,000. It is the first attempt of a cartographic synthesis that aims to bring together and interpret the geological and geomorphological factors that contributed to the landscape formation and evolution of Greece on a national scale. The production of the geomorphological map was based on a literature review of previous geomorphological studies of the greek terrestrial and coastal area at different scales as well as on the application of semi-automated, GIS techniques. High resolution topography obtained from the Hellenic Cadastre as well as the geological maps of Greece at a scale of 1:50,000 obtained from the Institute of Geology and Mineral Exploration of Greece were used as initial inputs in a spatial geodatabase for the production of a series of secondary layers. These layers, which included a hillshade map, a slope-aspect map, and a red relief image map, were combined with Google Earth Imagery to delineate small- and large scale landform across the Greek territory. The final map incorporates landforms of both endogenic and exogenic origin. It was organized genetically including structural landforms, landforms due to fluvial erosional and depositional processes, gravity induced landforms as well as coastal, karst, volcanic, glacial and periglacial landforms and anthropogenic facilities. A series of accompanying maps and tables were also produced, providing topographic parameters as well as information about the geotectonic setting and the climatic regime of Greece. The results show that the greek territory comprises a landscape with heterogeneous geomorphological environments, the formation and evolution of which, is the result of primarily active tectonics, and exogenic processes. The map reflects the extent of recent developments of geomorphology of Greece and can be used as a management tool for stakeholders, as well as a reference for further interdisciplinary research.

How to cite: Karymbalis, E., Tsanakas, K., Griva, D., Batzakis, D.-V., and Valkanou, K.: Geomorphological map of Greece, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-367, https://doi.org/10.5194/icg2022-367, 2022.

Askoa Ibisate, J. Horacio García, Alfredo Ollero, Josu Ortiz, Alvaro Gómez-Gutierrez, and Ana Sáenz de Olazagoitia

Ephemeral rivers (IRES – Intermittent Rivers and Ephemeral Streams) differ from perennial rivers in that they do not have a base flow, therefore, when direct flow stop, they dry up. This condition is spatially accentuated in the ephemeral streams of arid and semi-arid environments (SAES – Semi-arid Ephemeral Streams). Much of the East of the Iberian Peninsula has a climate and lithological conditions that favour the presence of SAES.

The hydrogeomorphological dynamics of these rivers are controlled by flash-floods, with marked rises inflow, short delay times, and on numerous occasions, a significant sediment load. These characteristics that define them, added to the urban development of recent decades, mean that SAES is not usually part of restoration plans. In addition to the technical-administrative “forgetting”, there is scarce appreciation and lack of social sensitivity towards the SAES.

In this project (CCAMICEM Project from Spanish Research National Plan) we focus on the cartographic development of ephemeral rivers with the aim of knowing the geomorphological evolution of several reaches, and between different dates, as a geoindicator of global change using historical and UAVs images. A diachronic geomorphological mapping has been carried out in six reaches distributed throughout the Ebro River Basin (Tudela, Reajo, Alpartir, Cariñena, Sosa and Seco). The timeframe covers 65 years, from 1956-57 (American Flight B) to 2021 through images taken with an unmanned aerial vehicle (UAV). As intermediate years, images were taken from the mid-1980s, and the latest official orthoimage available (2017). The official images belong to the National Geographic Institute (IGN). An altimetric correction has been made in the first two images.

The categories identified have been active channel, main channel and secondary channel, sediment bars (which can be vegetated, scant vegetated and non-active paleo-bars), the deposits coming from bank failures or tributaries, rocky areas, exhumed old sediment areas, and consolidated or unconsolidated granular bed. The categories were mapped at different scales according to the quality of the image, that is, from a scale ≤1/300 of the UAV to another scale ≤1/1000 of the American Flight B. The results achieved are allowing geomorphological changes and basin processes to be related to global change.

How to cite: Ibisate, A., García, J. H., Ollero, A., Ortiz, J., Gómez-Gutierrez, A., and Sáenz de Olazagoitia, A.: Ephemeral rivers, geomorfphological evolution and mapping. A case study in NE Iberian Peninsula, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-483, https://doi.org/10.5194/icg2022-483, 2022.

Miguel Inácio, Ana Cunha, Maria da Conceição Freitas, Vera Lopes, Manel Leira, and César Andrade

Salt marshes are highly valued coastal environments for different services: coastline protection, biodiversity, and carbon storage (blue carbon). However, they are vulnerable to climate changes, particularly sea-level rise (SLR). For this reason, it is essential to project the evolution of marsh areas until the end of the century. This work presents the results of applying a reduced complexity two-dimensional rule-based model developed by the authors: SMRM (Simplified Marsh Response Model). The model requires four parameters: a high-resolution digital terrain model (DTM) (LiDAR survey from 2011), local tidal levels (modeled from Setúbal-Tróia tide gauge), at least one SLR scenario (IPCC RCP4.5, FCUL MOD.FC_2b and NOAA Extreme were used) and accretion rates (determined through the analysis of 210Pb and 137Cs isotopic activity from a core in one of the studied marshes). Furthermore, additional parameters such as the error of the DTM (RMSE) or the acceleration of SLR and accretion rates can be added. The process is done through a MATLAB script and the output is a Geotiff file. The presented results are for the estuarine margin of the Tróia sandspit salt marshes (Sado estuary, Portugal – 40 km south of Lisbon), where six marsh patches(Caldeira de Tróia (CT-N (North) and CT-S (South)), Malha da Costa (MC-N and MC-S) and Comporta (Cmp-N and Cmp-S)) are present, totalizing an area of 109 ha.

Projections indicate that a significant reduction in the marsh area is expected until 2100, that will be transformed in tidal flats/subtidal areas. Depending on the chosen SLR scenario, the losses will be between 6 (IPCC RCP4.5) and 84 % (NOAA Extreme) in area. If sea-level rises around 1 m until the end of the century (FCUL MOD.FC_2b), a loss of 36 % in global area is expected. The evolution will not be similar along the sandspit. The most mature marshes (MC-S, TC-N and TC-S) will be more resilient to SLR. These projections consider that the surrounding areas will not be occupied until the end of the century, reducing the probability of these areas disappearing in the future. In fact, limited saltmarsh displacement to inland will occur (between 4 and 35 ha – from IPCC RCP4.5 to NOAA Extreme) to adjacent areas with low slopes.

The influence of each parameter was also evaluated in this work through a sensitivity analysis. The results indicate that SLR is the most significant parameter to consider, followed by accretion rates and the error of the DTM. The main conclusion is that the studied salt marshes could be resilient to conservative SLR scenarios but not to more severe projections, even if they have space landwards to expand.

This research was funded by Portuguese Foundation for Science and Technology, I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 + PTDC/CTA-GEO/28412/2017 and Ph.D. Grants PD/BD/142781/2018 + PD/BD/106074/2015.

How to cite: Inácio, M., Cunha, A., Freitas, M. D. C., Lopes, V., Leira, M., and Andrade, C.: Tróia sandspit (Sado estuary, Portugal) salt marshes' evolution until the end of the 21st century, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-436, https://doi.org/10.5194/icg2022-436, 2022.

Display time: Thu, 15 Sep 09:00–Fri, 16 Sep 19:00

Poster: Thu, 15 Sep, 10:30–10:45 | Poster area

Chairpersons: Leonardo Santos, Rui Figueiredo
Eliomara Leite Meira Gomes, Rubson Pinheiro Maia, Anna Sabrina Vidal de Souza, and Ana Beatriz da Silva Barbosa

Geoconservation is an instrument of Geodiversity, and encompasses a set of actions from inventorying and characterization of geosites to their conservation and management, in addition to enabling the appropriate use of its scientific, educational, cultural, touristic, and economic values. The inventory, characterization, and representation of geosites from a geopark is essential for recognition of its scientific importance and collaborates to verification of potential conservation and its different forms of use for geopatrimony. The geomorphological mapping as an instrument of this representation permits the users to visualize the landscape elements and makes them understand why such an area is a site and a geopatrimony. This work aims to describe the geomorphological heritage of an area designated for the creation of the Sertao Monunmental Geopark, in central Ceara, Northeastern Brazil, using geomorphological mapping, to represent the landforms and to discuss landscape dynamics.  In this regard, different cartographic products are necessary, such as geological maps, clinographic and hypsometric, pedological, hydrographic network and sub-basins, and geomorphological maps in detail and semi-detail scales in which the main geographic accidents, residual reliefs, planed surfaces, and slopes will be presented. The methodology of the landform classification will be made in accordance with Ross (1991; 1992), Santos et al. (2006), Dantas (2016), Diniz (2017), and IBGE (2009), among others that categorize the relief in taxonomic units. These are the following morphostructural units (1st taxon), morphosculptural units (2nd taxon), morphological units or similar patterns of forms (3rd taxon), types, and forms of relief (4th taxon). For the representation of relief patterns, it is assumed to consult the technical documents with standards and representations of geomorphological aspects. This work will be based, on geoprocessing techniques with GIS, mostly using QGIS software, and satellite and radar image processing for scales 1/250,000 and 1/100,000, and high-resolution imaging for more detailed scales (1/10,000 and 1/25,000). It is expected that this geomorphological mapping contributes to understanding the spatial setting of landforms in the study area providing an interpretation of the geomorphological facts and supporting different activities in the region, such as the orientation of visits and planning projects.

How to cite: Leite Meira Gomes, E., Pinheiro Maia, R., Vidal de Souza, A. S., and da Silva Barbosa, A. B.: Geomorphological mapping as an instrument for Geoheritage and Geoconservation - a study of geosites in granite terrains of Northeastern Brazil, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-188, https://doi.org/10.5194/icg2022-188, 2022.

Filip Duszyński, Kacper Jancewicz, Wioleta Porębna, Piotr Migoń, Jarosław Waroszewski, and Markus Egli

Rock materials on slope surfaces, derived from upslope segments and transported by gravity, are a carrier of important geomorphic information. They can be causally linked to processes operating on hillslopes and hence, help to recognize mechanisms involved in slope retreat and lowering, related to both weathering and mass movements. Moreover, these materials and landforms built of them are part of the memory of a hillslope geomorphic system and allow us to infer past events, such as transport mechanisms that are no longer operating. In this way, pathways of slope evolution over time can be reconstructed, and differences between neighbouring slope segments be evaluated.

Only a few studies have attempted to explain the origin of boulder mantles in tablelands, where they usually occur on the sub-caprock slopes. These mantles were variously hypothesized to result from rockfalls, toppling, landslides or in situ disintegration. There have hardly been any studies focussing on the quantification of such boulder mantles. This stands in contrast to the voluminous literature on scree where an informal protocol how to characterize these deposits exists and various morphometric features of scree slopes are used to infer processes involved in their built-up and re-modelling.

In this study, our primary intention is to develop a set of approaches and indices which would help to characterize boulder mantles quantitatively and more objectively, opening the way to comparative studies based on a common protocol. They are based on field observations and measurements, as well as on geomorphometric analyses of high-resolution (1 m × 1 m) LiDAR DEMs. The study focuses on two localities; on boulder-mantled hillslopes of two sandstone-capped mesas in Central Europe, the Szczeliniec Wielki in south-west Poland and Pfaffenstein in east Germany. Additionally, sandstone samples were collected from boulders and the adjacent cliff-lines at Szczeliniec Wielki for dating purposes (exposure dating using cosmogenic 10Be). In this case, the goal was to identify whether the exposure ages of boulder-covers follow any patterns in the downslope direction, which might be interpreted in terms of involved geomorphic processes.

The results show that derivatives of airborne LiDAR DEMs can be a useful source of information, allowing to study the patterns of boulder distribution within the sub-caprock slopes. Yet, it is strongly recommended to precede any morphometric analyses by field reconnaissance and semi-manual DEM upgrades on the basis of point cloud data as it turned out that automatic filtration algorithms removed a large amount of boulders, resulting in a picture that does not reflect the actual morphological situation. With the issue of DEM quality being solved, surface roughness indices enable overall quantification of spatial distribution of boulders. It should be underlined, however, that field measurements across slope longitudinal profiles are of considerable added value, helping to determine the azimuth of boulders’ longer axis or the details of boulder dimensions. This information, together with DEM-based analysis, can be used to hypothesize processes that are involved in boulder accumulation and their diversity in space.

This study has been financially supported by the National Science Centre, Poland (project no. 2020/39/D/ST10/00861).

How to cite: Duszyński, F., Jancewicz, K., Porębna, W., Migoń, P., Waroszewski, J., and Egli, M.: Quantyfiying boulder covers on caprock-crowned hillslopes – a means to decipher the patterns of escarpment retreat?, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-198, https://doi.org/10.5194/icg2022-198, 2022.

Jorge Lorenzo-Lacruz, Celso Garcia, Enrique Morán-Tejeda, Antoni Capó, Christian Mestre-Runge, and Aaron Ortega-Mclear

Subsidence is a highly destructive natural hazard, which can be caused by both natural and anthropogenic causes. Its impacts include a decrease in storage capacity of aquifer systems, the creation of cracks and fissures, damages to buildings and infrastructures, and an increase of the susceptibility to flooding. In this study, Persistent Scattered Interferometry (PSI) has been used to process Synthetic Aperture Radar (SAR) images, for the detection and analysis of ground deformation and subsidence processes in the island of Mallorca. The study database is composed of 120 images captured by the Sentinel 1A and 1B satellites (between May 2016 and December 2019), from which we derived a map of accumulated displacement rates occurred during a 3 years and a half period. The results show important subsidence processes of up to 3 cm per year in large areas of the sedimentary basin of Palma, and of lesser magnitude (between 1 and 2 cm per year) in locations of the Inca basin and in small basins in the Tramuntana Range. A significant relationship has been observed between the thickness of the Quaternary sediment and the observed subsidence rates. The results highlight the high degree of geomorphological dynamism at very short time scales that characterizes Mallorca, and the vulnerability of certain urban areas, such as the city of Palma (400000 inhabitants), and agricultural areas, such as the Central Depression, facing the risk of subsidence and associated damages.

How to cite: Lorenzo-Lacruz, J., Garcia, C., Morán-Tejeda, E., Capó, A., Mestre-Runge, C., and Ortega-Mclear, A.: Subsidence mapping in Mallorca (Spain) via Sentinel-1 imagery and links with sedimentary basin characteristics, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-206, https://doi.org/10.5194/icg2022-206, 2022.

Christian Mestre-Runge, Jorge Lorenzo-Lacruz, Aaron Ortega-Mclear, and Celso Garcia

The availability of high spatial resolution historical remote sensing products and advances in Structure from Motion (SfM), Multi-View Stereopsis (MVS) and LiDAR (Light Detection And Ranging) techniques offer a wide range of applications to understand landscape evolution and to monitor geomorphological changes. In this work, we apply an optimised SfM-MVS workflow based on minimising georeferencing error on black and white and colour historical photographs acquired in 1945 (American flight series A), 1979 (Spanish Interministerial Order), 1991 (Spanish Coastal Directorate General) and 2006 (PNOA flights) to generate 3D point clouds, Digital Elevation Models (DEM) and orthomosaics at 1 m resolution for the beach-dune system and coastal area of Es Trenc (southern Mallorca). In addition, we applied LiDAR techniques on the Airborne Laser Scanning (ALS) point clouds collected by the PNOA LiDAR flights in 2014 and 2019 to generate DEMs. The use of these products in multi-temporal analysis requires quality control of their spatial accuracy due to the diversity of sources and technologies used. The first quality control was based on evaluating the SfM sparse cloud optimisation process in the orthomosaic georeferencing step by calculating the RMSE between the Ground Validation Points (GVP) surveyed with Global Navigation Satellite System (GNSS) readings and the predicted height values at the closest point of each SfM sparse cloud. The second quality control was based on systematically assessing the vertical accuracy of the dense MVS and ALS clouds as a step prior to point interpolation to generate DEMs at 1 m resolution. The height errors of these clouds were estimated by calculating the RMSE between the Ground Test Points (GTP) read by GNSS on the ground and the predicted values at the respective nearest point for each of the MVS and ALS cloud series. Preliminary results show that the optimised SfM-MVS method applied on historical imagery can generate high-resolution orthomosaics and DEMs with acceptable accuracy: RMSE in z ranges from 0.2 to 10 m, with the lower accuracy obtained for the 1945 DEM, due to the lower resolution and coarse grain size (texture) of the photographs used. Overall, these products in combination with current LiDAR-derived DEMs have great potential for monitoring historical landscape evolution in coastal ecosystems.

How to cite: Mestre-Runge, C., Lorenzo-Lacruz, J., Ortega-Mclear, A., and Garcia, C.: Generation of high-resolution digital elevation models and orthomosaics from historical aerial photographs and LiDAR: quality assessment in the coastal beach-dune system of Es Trenc (Mallorca, Spain), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-209, https://doi.org/10.5194/icg2022-209, 2022.

Zarka Mukhtar, Francesco Comiti, and Simone Bizzi

The monitoring of hydro-morphological changes in proglacial rivers is crucial to expand the knowledge of unified river management. Himalayan region in South Asia is one of the extremely glaciated, vulnerable mountainous areas on globe and a source of plenty of rivers. The remoteness of proglacial zones and complexity to have access to the majority of sites for field investigation, highlights the viability of remote sensing data. The main aim of the research is to analyze the recent morphological dynamics in Himalayan proglacial river channels by means of remote sensing techniques. This              investigation is carried out on a number of different multispectral satellite imageries for the duration of 2000 to 2020. For the classification of river channel delineation and monitoring a semi-automated approach is used, based on geographic object based image analysis (GEOBIA). Multispectral satellite data acquired by high resolution Sentinel-2 images is processed to extract the channels and variations over time. Very high resolution (VHR) satellite image WorldView-2 is acquired for the validation of classification method, of overall accuracy obtained by high resolution images. The study is based on remote sensing analysis coupled to river evolutionary trajectories, and to the validation of reliability to free accessible high resolution satellite data for similar results to  VHR images.

How to cite: Mukhtar, Z., Comiti, F., and Bizzi, S.: Monitoring morphological changes in Himalayan proglacial rivers though a semi-automated classification approach, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-239, https://doi.org/10.5194/icg2022-239, 2022.

Joanna Hałys and Anita Bernatek-Jakiel

Soil piping is an important subsurface soil erosion process that accelerates land degradation in many areas around the world, as well as it impacts landscape evolution mainly by developing new gullies. Up to now, several studies have revealed factors controlling this process (such as high silt content, soil dispersion, biological activity of soil biota, and high hydraulic gradient), but most of them are connected with local soil properties and local topography. This study aims to identify the relationships of soil piping with geological structure at regional scale. The study is conducted in the Bieszczady Mts. (SE Poland), which are the westernmost part of the Eastern Carpathians. The Bieszczady Mts. covers more than 2200 km2. They are built of flysch rocks, i.e., sandstones alternated with shales and mudstones, which are diversified in the vertical profile (variable thickness of shale and sandstone layers) and in the horizontal profile (regional variability). Moreover, the Bieszczady Mts. lies in the contact zone of two major tectonic units of the Outer Carpathians (the Dukla and the Silesian Units). The study involves geomorphological mapping of pipe collapses (PCs), which are surface manifestations of soil piping, i.e., pipe roof collapses. PCs are mapped manually by visual inspection using hillshade of LiDAR-based Digital Elevation Model (DEM) with 1 m accuracy, along with the orthophotos. The data are verified in the field. Thanks to the previous study in this area, the geomorphological mapping has been limited to the areas where grasslands/pastures occur and where transition from pastures to forest has been observed (Bernatek-Jakiel and Jakiel, 2021).

First results have shown that PCs are related to geological structure. They develop in the areas where prevails thin- and medium-bedded sandstones with shales, not in the areas with thick-bedded sandstones. These rocks are grouped in the narrow strips of NW–SE direction in the Bieszczady Mts.

Recognition of soil piping relationship with geological structure is an important step to incorporate piping erosion to regional and global soil erosion models. This is of crucial significance in the sustainable soil management.

This research is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952327 and it has been supported by a grant from the Priority Research Area Anthropocene under the Strategic Programme Excellence Initiative at the Jagiellonian University.

How to cite: Hałys, J. and Bernatek-Jakiel, A.: Geomorphological mapping of pipe collapses as a tool to identify the relationships of soil piping and geological structure at regional scale, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-326, https://doi.org/10.5194/icg2022-326, 2022.

Marta Zocchi, Roberta Marini, Claudia Masciulli, Benedetta Antonielli, Francesca Reame, Gianmarco Pantozzi, Francesco Troiani, Paolo Mazzanti, and Gabriele Scarascia Mugnozza

Landslide inventory maps represent a preliminary step toward landslide susceptibility, hazard, and risk assessment. The increasing enhancement of A-DInSAR (Advanced Differential Synthetic Aperture Radar Interferometry) techniques facilitates the detection of Earth’s surface displacements over large or remote areas. Moreover, applying post-processing tools to the measurements retrieved by PS-InSAR analyses (i.e., one of the most common multitemporal A-DinSAR techniques) permits the representation of gravity-driven processes evolution in both spatial and temporal terms. Nevertheless, geometric distortions linked to the orbit and acquisition parameters of the SAR sensors, along with insufficient site coverage and spatial density of the PS-InSAR analyses, may lead to a lack of information, especially in mountainous areas. To address this problem, we processed the data using different InSAR tool packages and exploited the combination of orbital geometries for different satellites at the regional and local scales. These analyses were applied over an area encompassing four regions in the Central Apennines (Italy), within the framework of a broader national project which aims at mapping and updating landslide-prone slopes interacting with urban centers. For each processed dataset, we compared the spatial coverage and the accuracy of the displacements, providing statistical correlation tests to establish the relationship between the different InSAR tool packages. Therefore, we were able to verify the possible underestimation of the velocity and coherency measurements, and then select the best dataset (or the best combination) for further analyses. Based on the comparison between the dataset and through a semi-automatic approach, we then selected several areas that exceeded specific velocity thresholds and were densely covered by PS. In these areas, classified with a high priority level, detailed analyses were performed through a set of post-processing plugins designed for the software QGIS. Spatial and temporal deformation trends of the PSI results, along with subtle surface patterns within the landslide area, were highlighted by the post-processing analyses. Thus, we derived a detailed geomorphological characterization for the high priority phenomena interacting with cities and infrastructures. While at the regional scale findings from our work help the validation and integration of multi-satellite datasets, at the local scale the proposed workflow can also support the prioritization of site-specific monitoring and intervention planning.

How to cite: Zocchi, M., Marini, R., Masciulli, C., Antonielli, B., Reame, F., Pantozzi, G., Troiani, F., Mazzanti, P., and Scarascia Mugnozza, G.: Multi-satellite InSAR combination to support multi-scale analyses of hillslope processes, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-356, https://doi.org/10.5194/icg2022-356, 2022.

Ana Cunha, Miguel Inácio, Maria da Conceição Freitas, and Manel Leira

Saltmarshes are a valuable wildlife habitat and play a key role in shoreline protection; given their potential in carbon sequestration and storage, these areas might also play a significant role within mitigation strategies to climate change. Natural saltmarshes can adapt to various disturbances through a series of feedbacks. However, land use changes and human occupation can alter the marsh natural dynamics diminishing their resilience.

Aerial photographs have been used to study marsh vegetation and map its evolution since the late 70’s and have proven to be a key source of information. This technique facilitates the study of wetlands on a monthly, yearly, or decadal timescales. Historical photographs can be used to identify past trends and support the implementation of monitoring programs on vast wetland areas.

In the region of the Tróia peninsula in the Sado estuary (SW Portugal), historical aerial photographs are available for the past 70 years. Using these photographs, this work attempts to answer the following questions: (1) How have the saltmarshes of Sado estuary change since the 1940’s? (2) How have marsh geomorphology and anthropogenic pressure contributed to these changes? (3) Is the variation of sea level in the Portuguese coast an important factor in marsh evolution?

From the saltmarshes that were studied, only two increase in size; all the other saltmarshes suffer substantial losses in total area. All combined, these saltmarshes shrunk over 30 ha (≈27%) in the past 70 years. Availability of accommodation space and level of protection seem to be the key factors in saltmarsh resilience. There appears to be a link between the rise of the mean sea-level and the colonization of terrestrial areas, as well as with the disappearance of the saltmarsh islands. The effect of direct human action on the saltmarshes can also be observed in some of the studied areas.

While this is a regional study – mostly intended to understand how the marshes of this area have evolve - it also serves a larger purpose, to emphasize the importance of aerial historical photographs as a source of information about this environment. Unlike other countries, in Portugal aerial photographs are used mostly for coastal erosion assessment, having been used only a couple of times to study marshes. Considering how many estuaries exist in Portugal, and the importance of these areas for the future of our coasts, it is essential to start using all the tools available in their study and in the creation of conservation, naturalization and recovery plans.

This research was funded by Portuguese Foundation for Science and Technology, I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 + PTDC/CTA-GEO/28412/2017 and Ph.D. Grants PD/BD/106074/2015 + PD/BD/142781/2018.

How to cite: Cunha, A., Inácio, M., Freitas, M. D. C., and Leira, M.: Use of historical aerial photographs to study the evolution of saltmarshes in the Tróia sandspit, Sado estuary, Portugal, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-431, https://doi.org/10.5194/icg2022-431, 2022.

Osama AlRabayah, Djamil Al-Halbouni, Robert A. Watson, Danu Caus, Harsh Grover, David Nakath, Lars Rüpke, and Tobias Weigel

This research aims at developing and applying a machine learning based algorithm to detect geological structural features at the exposed Dead Sea shoreline. We focus on sinkhole, stream-channel and crack features that appear in different material at the coastlines, and post partly a threat for the local population and infrastructure. We use high resolution orthophotos and satellite images from the last years, as well as derived topographic models to reach an automatic identification and classification of these structures. The aim is to train a convolutional neural network that can identify these structures on recent datasets from satellite images in order to establish an automated detection of hazardous and active zones in the area. Furthermore, we use the algorithms to detect structures in the shallow waters of the lake.

How to cite: AlRabayah, O., Al-Halbouni, D., Watson, R. A., Caus, D., Grover, H., Nakath, D., Rüpke, L., and Weigel, T.: Automatic geological structure recognition at the Dead Sea lakebed, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-460, https://doi.org/10.5194/icg2022-460, 2022.

Stefania Cristino de Oliveira, Renan Cassimiro Brito, and Fabiano do Nascimento Pupim

The estimation of suspended sediment concentration (SSC) by remote sensing is a valuable tool because it allows a systematic monitoring in large watersheds and provides information on variations in SCC and its drivers, such as mining and deforestation. Therefore, this work presents a statistical model for estimating SCC in the Upper Paraguay River Basin from the integration of data collected in situ from hydrological stations and remote sensing data over a series of historical data. The method used was based on the premise that the spectral reflectance varies as a function of SCC. The rise of SSC in water leads to an increase in electromagnetic radiation (EMR) backscatter, which is observed as an increase in the reflectance of the water body in Landsat images. Initially, in situ SSC data were obtained from the National Water Agency databases and the Landsat 5 and 7 System Geospatial Dataset (Tier 1 Surface Reflectance) acquired from the Google Earth Engine platform. Then, a filtering of the pixel values ​​was performed to avoid sampling with reflectance values ​​that did not correspond to the changes of sediments on the water surface, such as clouds and cloud shadows. After collecting the in situ and orbital data, the data were calibrated in the RStudio program. For the model implementation, the spectral reflectance measurements of the water must be almost simultaneous to the SCC measurements at fluviometric stations. Thus, images were chosen that coincided within an interval of 6 days with the date of the SCC collection. Multiple regression analysis was the method used to express the relationship between reflected EMR and SCC, which allows the dependent variable (SCC) to be estimated as a function of one or more independent variables, in this case, spectral bands and bands. Thus, the data obtained in situ and the satellite images made it possible to estimate the distribution of suspended sedimentary load into the main rivers of the Upper Rio Paraguay in the period from 1984 to 2021, resulting in a greater distribution of temporal and spatial sampling quickly, with low cost and simple logistics.

How to cite: Cristino de Oliveira, S., Cassimiro Brito, R., and do Nascimento Pupim, F.: Remotely estimation of suspended sediment concentration in the Upper Paraguay River Basin, Brazil., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-484, https://doi.org/10.5194/icg2022-484, 2022.

Water erosion modeling using the SIMWE (Simulated of Water Erosion)
Evandro Daniel, Bianca Carvalho Vieira, and Tiago Damas Martins
Sam Woor, David Thomas, and Ash Parton

Fans form where down-system sediment transfers undergo decreases in confinement, such as when confined mountain stream systems enter open sedimentary basins at mountain fronts. Fans represent fundamental buffers in the sediment cascade (e.g. Harvey, 2011), act as palaeohydrological and palaeoenvironmental archives of their mountain catchments (e.g. Parton et al., 2015) and can pose risks to society through flash flooding (e.g. Gutiérrez et al., 1998).  The morphometric characteristics of fans are often strongly coupled to catchment morphology. Fan-catchment relationships, therefore, allow the principal controls on fan morphometry, evolution and heterogeneity to be understood, as has been shown in numerous studies of arid region fans (e.g. Stokes and Gomes, 2020). The Al-Hajar Mountains in south-east Arabia represent large, well-preserved fan systems the morphometry of which has been understudied. This is despite the opportunity for unique comparisons of fan morphometric controls, with fans ranging across several orders of magnitude (101-104 km2) and terminating in different environments such as the coastline of the Arabian Sea to the east and Rub’al Khali dunefield to the west.

Accurately mapping the extent of the Al-Hajar fans, however, is difficult. This is because they are commonly partly obscured by sand dunes and are becoming increasingly urbanised or disturbed by human activities. To address these issues, we employed multiple remote-sensing datasets to aid the mapping of mountain-front fan systems and their catchments across the Al-Hajar, including Landsat 8 false colour composites, Google Earth historical and modern imagery and spaceborne synthetic aperture radar (SAR). This resulted in the most comprehensive dataset of Al-Hajar mountain-front fan systems produced to date, with c. 400 fans mapped. We then determined numerous morphometric parameters of fans and their catchments. Regression analysis between these variables revealed a significant positive relationship between catchment area and fan area, as well as a significant negative relationship between catchment area and fan gradient, as derived by studies in other arid settings. Analysis of the residuals of these relationships showed that catchment characteristics, such as rock type, as well as base level changes (notably sea level for coastal fans) are important controls on fan morphometry. Comparisons with other arid region fans shows that Al-Hajar fans are both larger and less steep than many other terrestrial fans, potentially making them useful analogues for extra-terrestrial systems.

Gutiérrez, F., Gutiérrez, M. and Sancho, C., 1998. Geomorphological and sedimentological analysis of a catastrophic flash flood in the Arás drainage basin (Central Pyrenees, Spain). Geomorphology, 22(3-4), pp.265-283.

Harvey, A., 2011. Dryland alluvial fans. In Thomas, D.S.G. (ed), 2011. Arid zone geomorphology: Process, form and change in drylands, pp.333-371.

Parton, A., Farrant, A.R., Leng, M.J., Telfer, M.W., Groucutt, H.S., Petraglia, M.D. and Parker, A.G., 2015. Alluvial fan records from southeast Arabia reveal multiple windows for human dispersal. Geology, 43(4), pp.295-298.

Stokes, M. and Gomes, A., 2020. Alluvial fans on volcanic islands: A morphometric perspective (São Vicente, Cape Verde). Geomorphology, 368, p.107356.

How to cite: Woor, S., Thomas, D., and Parton, A.: A multi-method remote sensing study of the morphology and controls of Al-Hajar Mountain alluvial fans, south-east Arabia., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-488, https://doi.org/10.5194/icg2022-488, 2022.

Ana Amaral, Luis Cherem, Renata Momoli, and Pâmela Assis

Digital Elevation Models are numerical representations of the topography in a regular grid of points, which are obtained by vectoring contour lines, as well as aerial and orbital data. From these images it is possible to carry out various analyses, such as the delimitation of hydrographic basins, calculation of flow accumulation, delimiting elevations and depressions in the terrain, as well as performing the geomorphological mapping of the landscape. In view of this, several methodologies emerged with the purpose of identifying specific features on the ground, such as sinkholes. An example of a method used to identify features of this type is the semi-automatic sinkhole identification technique, which consists of calculating the difference between a filled DEM (procedure performed by the Fill tool in ArcGis software) and the original DEM. The difference between these two products generates areas of endorheic flow accumulation, on which morphometric indices and neighborhood criteria are applied, making it possible to identify the location and shape of these probable sinkholes. However, despite the functionality of the method, validation is a fundamental step, and fieldwork is a very expensive solution for the researcher. In view of this, this work aims to propose the alternative validation of data generated by the semiautomatic method through high resolution satellite images. The research had Central Brazil as its study area, more precisely the northwest region of the Tocantins Basin, where the karst relief is expressive and well developed. The image used for the application of the semiautomatic method was the Copernicus DEM (resolution of 30 meters) and for its subsequent validation, images from the SENTINEL 2 satellite (resolution of 10 meters) were used together with Google Earth images. With the application of the semi-automatic sinkhole identification method, 16.712 depressed features were identified in the terrain, in an area of ​​approximately 30,000 km², however, through the visual inspection of the generated data, it was observed that many polygons were more related to the carving of the drainage channel than with karst features. In view of this, the validation of these polygons were carried out through images from the SENTINEL satellite, where, through visual analysis, about 1.332 depressed features remained. The criteria used for validation was the identification of circular features that had water inside them or that indicated they were undergoing processes of rock dissolution. Vegetation was also another criterion, considering that in places with sinkholes, they tend to be more humid and consequently have a greener vegetation. It was concluded with this study that the semiautomatic method presented good results when analyzed together with satellite images, allowing the analysis of large areas in a short period of time and with low costs, being, therefore, a good validation procedure in alternative to field work.

How to cite: Amaral, A., Cherem, L., Momoli, R., and Assis, P.: Identification of karst depressions through Digital Elevation Models and high resolution satellite images, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-502, https://doi.org/10.5194/icg2022-502, 2022.

Marco Cunha, Fernando Lopes, and Pedro Dinis

The usage of Digital Elevation Maps, either from Satellite Altimetric Radar Missions (such as SRTM, Jaxa and others), large scale or high-resolution Lidar surveys and Multibeam bathymetric surveys, small to medium scale photogrammetric surveys, or any other tridimensional surface restitution technique, have been widely used to assess terrain features such as morphostructural, watershed and hydrogeologic features, sometimes involving geomorphologic classification. Commonly, fast DEM analysis highlights abrupt slope change, producing mainly ridge lines and crevices/valleys like features. On applying a first order derivate to the elevation data, easily it is mapped those sudden changes on the terrain morphology.

The following work suggests the conversion of the DEM data to pointcloud, where, with specialized software (like freely distributed open-source CloudCompare), further analysis can be done, allowing fast analysis of big data, and with possible segmentation of the data into families. Depending on the user's objectives and applied analysis, segmented families can be geomorphologic features, morphostructural features, or any other.

CloudCompare allows the fast calculation of geometric features of pointcloud data, such as roughness, curvature, density (surface or volume), 1st order derivate, linearity, planarity, sphericity and others. The desired geometric attribute is then stored to scalar data, that can be split by value (split the original pointcloud to segmented pointclouds), representing families by feature. When existent, other features from pointcloud can also be converted to scalar values, and can also be split by value. Example, from colored pointcloud (commonly Lidar or Photogrammetry), RGB data can be split, revealing to be an extreme valuable tool, for example to extract low height vegetation data from bare ground (green tones from brownish tones), where ground points automatic classification (example, CSF addon on CloudCompare) wasn’t as precise as desired. CloudCompare allows to re-interpolate data by scalar field or by elevation, reproducing a 2.5D elevation raster, that can be reimported to Remote Sense and GIS specialized software, such as QGIS, for further integration or data interpretation, where Remote Sensing common techniques may allow, as example, data integration, weighted-sum composite analysis, automatic or semi-automatic classification, or other.

It is presented the proposed pipeline for this analysis, using large scale Satellite data (Santo António, Benguela, Angola), high-resolution medium scale bathymetric data (multibeam survey in Porto Amboím bay, Angola), and high-resolution Digital Terrain Model from SFM photogrammetric survey (Miradouro da Lua, Belas, Angola).

How to cite: Cunha, M., Lopes, F., and Dinis, P.: On pointcloud analysis for geomorphologic and morphostructural mapping, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-519, https://doi.org/10.5194/icg2022-519, 2022.

Eduardo García-Meléndez, Montserrat Ferrer-Julià, Gonzalo Frías, Elena Colmenero-Hidalgo, Antonio Espin de Gea, Mónica Reyes, Francisca Carreño, Juncal A. Cruz, Arturo Bascones, and Inés Pereira

Imaging spectrometry, also known as Hyperspectral imaging (HSI) or imaging spectroscopy has been established as a robust technology for remotely mapping the distribution of spectrally active materials at the surface of the Earth. The main objective of this work is the application of imaging spectroscopy techniques for the earth surface observation based on landform development related to the presence of clay minerals. The study area is located in the Cenozoic Tagus sedimentary basin in Central Spain, an area particularly interesting because of the presence of clay minerals of economic interest and with the potential to generate expansive soils. This area conforms a landscape characterized by gentle sloping terrains with an almost complete absence of outcrops, except for the staircase structural surfaces conditioned by horizontal bedding and resistance of the alternating lithologies made of gypsum, clays, limestones and dolostones, outcropping in the left margin of the Guatén stream valley extending in a N-S direction. Image processing procedures have been developed aiming to detect mineral associations related to specific landforms with hyperspectral imagery. Spectral Angle Mapping (SAM) algorithm has been applied to the image data set for mineral mapping. Conventional aerial photointerpretation provides the spatial distribution of landform mapping units. GIS overlay operations crossing the mineral and landform units maps depict the relationships between clay minerals and landforms. The results allow the observation of differences in the distribution of minerals depending on the lithology and origin of each landform. Thus, while in the geomorphological units of fluvial origin montmorillonite is the clay mineral that occupies most of their surface, in the relatively steep slopes that articulate the structural surfaces, the spectral response is varies depending on the lithological types. Regarding the landforms of anthropic origin, the mining dumps show an spectral response associated with the mined ore (stenvensite, paligorskite, sepiolite). Lastly, in eluvial formations, their mineral distribution is always linked to their lithological nature.

Acknowledgements: This work has been supported by FEDER/Spanish Ministry of Science and Innovation-Agencia Estatal de Investigación) research project ISGEOMIN-ESP2017-89045-R and HYPOPROCKS (PDC2021-121352-100) by MCIN/AEI/10.13039/501100011033 and the European Union “NextGenerationEU”/PRTR.

How to cite: García-Meléndez, E., Ferrer-Julià, M., Frías, G., Colmenero-Hidalgo, E., Espin de Gea, A., Reyes, M., Carreño, F., Cruz, J. A., Bascones, A., and Pereira, I.: Earth observation from AHS (Airborne Hyperspectral Scanner) data: spectral response of landforms, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-600, https://doi.org/10.5194/icg2022-600, 2022.

Eduardo García-Meléndez, Montserrat Ferrer-Julià, Elena Colmenero-Hidalgo, Antonio Espín de Gea, Mónica Reyes, Francisca Carreño, Juncal A. Cruz, Arturo Báscones, Sara Alcalde-Aparicio, and Inés Pereira

High spatial resolution data recorded by the AHS (Airborne Hyperspectral Scanner) imaging system is evaluated for mapping the mineral composition of low relief landforms. The study area is located in the Cenozoic Tagus sedimentary basin (Central Iberian Peninsula) in geological units made of clay (smectites), evaporitic (gyspsum, anhydrite) and carbonate rocks (limestones and dolostones). The study is based on the spectral response of key minerals such as calcite, gypsum and both Mg and Al-bearing clays in order to map their presence in the flat and gently sloping surfaces of the area located between the Tagus, Tajuña and Jarama rivers. Two mapping techniques were used: image band ratios to enhance diagnostic mineral absorption features and the SAM (Spectral Angle Mapper) algorithm. Both methods show a good discrimination of the above referred minerals, being the best mapped gypsum. For the validation of the results, spectroscopic field and laboratory measurements were used together with the geological map of the study area and conventional aerial photointerpretation, providing the spatial distribution of Landforms mapping units and their differentiated mineral composition grouped in three main domains.

Acknowledgements: this research is supported by FEDER/Spanish Ministry of Science and Innovation-Agencia Estatal de Investigación) research project ISGEOMIN-ESP2017-89045-R and HYPOPROCKS (PDC2021-121352-100) by MCIN/AEI/10.13039/501100011033 and the European Union “NextGenerationEU”/PRTR

How to cite: García-Meléndez, E., Ferrer-Julià, M., Colmenero-Hidalgo, E., Espín de Gea, A., Reyes, M., Carreño, F., Cruz, J. A., Báscones, A., Alcalde-Aparicio, S., and Pereira, I.: Imaging spectroscopy in low relief landforms with airborne AHS images: an example in the Tagus Basin, Central Spain, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-620, https://doi.org/10.5194/icg2022-620, 2022.

Cristian Valeriu Patriche, Rosca Bogdan, Radu Gabriel Pirnau, and Ionut Vasiliniuc

Our study attempts to estimate current and future rill and interrill soil erosion in Romania using RUSLE model in GIS environment. We used the 25 x 25 m resolution EUDEM to derive terrain slope, while the SAGA GIS software was used to derive the slope and slope length (LS) factor. The rainfall erosivity (R) factor was extracted from RUSLE2015 European soil erosion model.  For the computation of the crop and crop management (C) factor we used detailed crop information for arable lands for the year 2021. Soil erodibility (K) factor was computed in four different manners. Therefore, four spatial models of soil erosion were achieved and the optimum one was selected by correlations of estimated erosion with measured erosion values for several locations throughout the country. To estimate the possible future changes in soil erosion rates due to climate change, we extracted monthly rainfall data from CHESLA database for the Romanian territory for two climate change scenarios (RCP 4.5 and 8.5) and two time periods (2014-2060 and 2061-2080) and computed the modified Fournier index. A statistical relationship between rainfall erosivity and the current modified Fournier index was computed and then applied to future Fournier index values in order to estimate future rainfall erosivity values. Our results show that rainfall erosivity is likely to enhance during the 2041-2060 period, especially in the western, south-western and eastern part of the country, causing a corresponding increase in soil erosion rates with 1-2 t ha-1 yr-1 on average. During the 2061-2080 period, rainfall erosivity is likely to decrease in the central and eastern Romania.

How to cite: Patriche, C. V., Bogdan, R., Pirnau, R. G., and Vasiliniuc, I.: Assessment of current and future soil erosion risk in Romania, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-667, https://doi.org/10.5194/icg2022-667, 2022.

Rui Ferreira and Luca Dimuccio

Geomorphometry is a research field focused on surface quantitative analysis and modelling. Due to its characteristics, it is an inherently multidisciplinary area of expertise, incorporating techniques and technology from multiple domains (e.g., geosciences, computer science, mathematics and data science). It is worth to note that the concept of surface is used here in a broad sense so, beside topography, geomorphometry can also be of interesting for study land cover change, soil formation, watershed dynamics, erosion, tectonic uplifts, landform evolution, etc. The use of modern geographic information technologies and the dissemination of digital data were major steps in the evolution of geomorphometry, allowing to go beyond the limited approach associated with quantitative geomorphology. In this work, 3 major objectives where establish: 1) assess the use of LiDAR data to build digital elevation models (DEM); 2) assess the accuracy of topographic surfaces from multiscale DEMs; 3) calculate morphometric parameters to support terrain object identification. The achievement of these objectives is based on the presentation of several examples and applications from selected key-areas in the central region of Portugal, as well as from the Côa Valley region (northeast of Portugal) in the framework of CLIMATE@COA project (COA/CAC/0031/2019).

How to cite: Ferreira, R. and Dimuccio, L.: Using GIS in geomorphometric research: examples from north and central regions of Portugal, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-668, https://doi.org/10.5194/icg2022-668, 2022.

Roger Gonçalves, Franciele Guerra, Isabel Paiva, and Hung K. Chan

Geographic Information Systems and spatial analysis models are constantly being implemented in geomorphological and environmental studies. The recent advances in remote sensing using active and passive sensors brought important techniques and products which improved the spatio-temporal data quality for geological models. Landscape analysis has always been considered an essential step during the construction of conceptual models, and nowadays, it is also relevant in numerical models. As landscape characteristics reflect by any means the geological features and the soils, combined with climatological variations, we can extract valuable proxies that can be used in hydrogeomorphological models. Such models usually combine geological and geomorphological knowledge with at least the understanding of hydrological attributes such as hydrographic patterns, groundwater dynamics, precipitation, evapotranspiration, and land use and land cover changes. Fortunately, several of these elements can currently be analyzed and/or estimated by remote sensing, supported by in situ measurements. Some remote sensing products are essential for Brazilian studies, e.g., the Tropical Rainfall Measuring Mission (TRMM) to estimate precipitation patterns and the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate evapotranspiration, quantify land surface characteristics and monitor atmospheric properties. Besides all these well-known remote sensing products, active sensors such as LiDAR and radar are critical to map and model with a suitable topography on different scales.

Radar products have earned attention with some worldwide surveys, such as the NASA's Shuttle Radar Topography Mission (SRTM) and the JAXA's Advanced Land Observing Satellite-1 (ALOS) with the PALSAR's L-band synthetic aperture radar. In Brazil, we also have a project called TOPODATA (INPE) that produced a topographic/geomorphologic countrywide database based on SRTM data. These data are being successfully implemented in geologic numerical models, especially the tridimensional ones since the model's top layer is often the topography. Considering regions where unconfined aquifers occur, especially with shallow water levels, the watershed delimitation is a key-information to define hydrogeological model boundaries, and usually, there is an essential relation between drainages and aquifers, with the water flowing from one to another. Accordingly, these radar-specific applications are related to the superficial portion of the water system.

On the other hand, active sensors such as radars can be applied to map the bottom boundaries of aquifer systems, especially shallow aquifers, since these limits are usually related to lithological contacts: a more permeable rock type (or soil) and a less permeable (or impermeable) material. The differences in permeability may also follow significant differences in erosion resistance, and in these cases, we may see a distinct slope, usually a steeper terrain. In our study, we assess the use of radar products to map the bottom boundary of a shallow unconfined aquifer (Rio Claro Aquifer, southeastern Brazil) and validate against in situ data, such as outcrops showing the lithological contact and springs revealing the groundwater dynamics that corroborates with the conceptual model. The results show the reliability of using active sensors and slope analysis to support hydrogeological models since the conceptualization of water resource systems to tridimensional numerical modeling.

How to cite: Gonçalves, R., Guerra, F., Paiva, I., and K. Chan, H.: Using active sensors in hydrogeomorphological modeling through landscape analysis in Brazil, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-688, https://doi.org/10.5194/icg2022-688, 2022.