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Lake Chad, situated in the semi-arid region of African Sahel, plays a vital role in hydrogeological balance of regional ecosystems. It presents an essential water source and provides a habitat for rare wildlife species including migrating waterbirds. However, the lake has shrunk significantly since the 1960s and has continued to reduce in size and extent during recent decades. Trends in drying and shrinking of Lake Chad are caused by environmental factors and changed climate. The desiccation of the lake is threatening environmental sustainability. This study focused on identification of changes in the Chad Lake area, wetland extent, and associated land cover types. The methods include the Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS) for remote sensing data classification. The maximum likelihood discriminant analysis classifier was applied for analysis of multispectral Landsat 8–9 OLI/TIRS images in 2013, 2017, and 2022. Detected changes in land cover types reflect variations in water balance and wetland area and extent around Lake Chad over recent decades. Cartographic scripting tools of GRASS GIS provide an efficient method of digital image processing for monitoring endorheic lakes of Central Africa. GRASS GIS methods provide an opportunity to automatically classify Earth observation data with cartographic scripts for environmental monitoring.

Evaluating the subground properties during the initial stage of a construction of building is important in order to estimate the suitability of soil quality to the technical requirements of bearing capacity, resistance to stress, and strength. This study presented the evaluation of the geotechnical properties of soil intended for the construction of Max IV facility of Lund University, performed in fieldwork and laboratory. The in situ methods included drilling boreholes, core sampling and assessment, crosshole measurements, and borehole logging. The laboratory-based measurements were performed at Swedish Geotechnical Institute and combined seismic measurements of drill cores, determination of the uniaxial compressive strength (UCS), and examination of material property: sieve analysis and natural moisture content. UCS was evaluated with regard to velocities of elastic P-waves. The synchronous light test by X-ray diffraction was performed for qualitative analysis of mineral composition of samples. The study applied integrated approach of the diverse geophysical methods to solve practical tasks on the evaluation of foundation strength and geotechnical parameters. This study demonstrated the benefits of integrated seismic and geophysical methods applied to soil exploration in civil engineering for testing quality of foundation materials.

This study is aimed at evaluating the strength of stabilised soil collected from the Port of Norvik, Stockholm, Sweden, where 350,000 m3 of clay had to be stabilized. The tests were performed in the laboratory of the Swedish Geotechnical Institute (SGI). The soil was stabilised by binder mixtures using Portland cement clinker (PCC) and lime and lime kiln dust (LKD). Accelerators (X-seed 100 BASF, PCC, LKD and salt) were added to the soil samples for quicker stabilization. The strength of the stabilised soil was assessed using resonance frequency measurements of seismic P-waves by an ICP accelerometer in order to estimate the shear strength of the soil and to evaluate the effects from the accelerators, binder ratios, and the curing temperature on the gains in stabilization and strength. Various proportions of the binders were tested, i.e.: 50/50 cement/lime and 50/50 PCC/lime. The temperature was measured using a calorimeter in double experiments. The results showed that the accelerators improve the strength in the stabilized specimens and enhance the soil performance for engineering construction work.

Clay soils can cause significant distress in road construction due to their low strength. Stabilizing such soil improve with binder agents prior to the geotechnical works can significantly its performance and ensure safety and stability of roads while exploitation. This research envisaged the use of five different binders (lime, energy fly ash, bio fly ash, slag, cement) as an additive stabilizing agents to improve the strength parameters of soil as required in engineering industry standards. The variations of strength was assessed using measurements of P-wave velocity of the elastic waves propagating through soil specimens stabilized by different combination of binders. Measurements were performed on 28th day of soil treatment. The best effects of added binders were noted in the following combinations: cement / energy fly ash / bio fly ash (P-waves >3100 m/s), followed by combination lime / energy fly ash / GGBFS (P-waves >2800 m/s) and cement / lime / energy fly ash (P-waves >2700 m/s). Adding lime is effective due to its fixation and chemical bond with particles. The study contributes to the industrial tests on soil strength for constructing roadbed.

In this paper we propose a new technique of soil stabilization for road construction based on using new alternative binders. The project aims to evaluate the effects of alternative additive materials in soil stabilization contexts for road construction. The alternative binders (slag, energy ash and bio ash as new alternative road construction material) have been used to complement the traditional binders (cement and lime). The project used five binders and evaluated their effects on soil strength. The proposed method comprises advantages of using the alternative binders which are the residual products contributing to a lower environmental impact. The results have shown that only slag has significant effects on the strength of the stabilized soil, while bio ash and energy ash make a marginal contribution to the increase of strength. This is caused by the twofold reasons. First, the effects of the amount of ashes that should reach a certain threshold with respect to the total amount of binder that must be exceeded to have the effect of the soil mixture. Second, the bio fly ash was stored and it was not completely fresh which may have contributed to the carbonation during the storage period and results in a lower hardening ability. Based on the results of the study we recommend the use of bio fly ash as a supply material andfor its amount to be adjusted so the storage period is not too long. This study verified the effects of slag, cement and lime on stabilization of soil for road construction.

The strength of soil can significantly increase by stabilisation with binders. Adding binders in correct proportions to improve soil parameters is of paramount importance for earthworks. In this article, we presented a framework to explore strength characteristics of soil stabilised by several binders and evaluated using applied geophysical methods by estimated P-wave velocities. The core of our work is a systematic assessment of the effects on clay stabilisation from various binders on shear and compressive strength. The binders were combined from four stabilising agents: (i) CEM II/A, a Portland limestone cement; (ii) burnt lime; (iii) lime kiln dust (LKD) limited up to 50%; and (iv) cement kiln dust (CKD). Shear strength has shown a nonlinear dependence as an exponential curve with P-waves. Natural frequency analysis was modelled to simulate resonant frequencies as eigen values. Variations in strength proved that CEM II/A-M (Recipe A, 100% CEM II) has the best performance for weak soil stabilisation followed by the combinations: Recipe B (70% CEM II/A-M, 30% LKD), Recipe C with added 80% CEM II/A-M and 20% CKD, and Recipe D (70% CEM II/A-M 30% CKD). Recipe B has shown high values with maximum uniaxial compressive strength (UCS) at 13.8 MPa. The Recipe C was less effective with the highest value of UCS as 8.8 MPa. The least strength was shown in Recipe D, where UCS has maximal values of 3.7 MPa. The specimens stabilised by Recipe B demonstrated the highest P-wave velocity at 2,350 m/s, while Recipe C and Recipe D showed the highest P-wave velocity at 1,900 and 1,550 m/s. All specimens shown a gain of UCS with sharply increased P-wave speed during the 3 days of curing. The study contributes to the development of methods of soil testing in civil engineering.

In this study, the stabilization process is introduced to a clayey expansive soil collected in southern Sweden. The tests examined strength parameters of expansive soil stabilized by different binders using combination of both traditional binders (cement and lime) and alternative materials (slag Merit 5000, fly ash from SCA Lilla Edet and fly ash from coal combustion, ISO certified). The practical goal was to find a binder mixture that is optimized for soil stabilization with respect to technical properties of stabilizing agent as an inert ballast material. The strength of soil stabilized by various binders was examined by velocity of the P-waves propagating through specimens. The results show that introducing slag Merit 5000 as an admixture to cement and lime is an effective approach in enhancing strength properties in weak soil, which increases bearing capacity of soil for planned construction works. The results also shown that a mixture of lime and bio ash yields a better effect in the stabilization of a clay. Soil stabilized with cement, cement/slag and lime/slag becomes resistant to freeze-thaw cycles, which is crucial for construction of roads and building foundations.

This paper addresses the problem of mapping land cover types in Senegal and recognition of vegetation systems in the Saloum River Delta on the satellite images. Multi-seasonal landscape dynamics were analyzed using Landsat 8-9 OLI/TIRS images from 2015 to 2023. Two image classification methods were compared, and their performance was evaluated in the GRASS GIS software (version 8.4.0, creator: GRASS Development Team, original location: Champaign, Illinois, USA, currently multinational project) by means of unsupervised classification using the k-means clustering algorithm and supervised classification using the Support Vector Machine (SVM) algorithm. The land cover types were identified using machine learning (ML)-based analysis of the spectral reflectance of the multispectral images. The results based on the processed multispectral images indicated a decrease in savannas, an increase in croplands and agricultural lands, a decline in forests, and changes to coastal wetlands, including mangroves with high biodiversity. The practical aim is to describe a novel method of creating land cover maps using RS data for each class and to improve accuracy. We accomplish this by calculating the areas occupied by 10 land cover classes within the target area for six consecutive years. Our results indicate that, in comparing the performance of the algorithms, the SVM classification approach increased the accuracy, with 98% of pixels being stable, which shows qualitative improvements in image classification. This paper contributes to the natural resource management and environmental monitoring of Senegal, West Africa, through advanced cartographic methods applied to remote sensing of Earth observation data. [ABSTRACT FROM AUTHOR]

This paper describes a scripting cartographic techniques that automatically generate maps from open source spatial data using syntax of General Mapping Tools (GMT) and R. A case study present mapping East Africa with a focus on Malawi. In this study, two different approaches of scripting cartography using R programming language and GMT were studied for geophysical analysis aimed to visualize a series of eight new maps in Malawi: topography based on the GEBCO data, seismicity, geomorphometric modeling based on SRTM-90 m (slope, aspect, hillshade and elevation) and geophysical fields: geoid based on EGM-2008 and free-air Faye's gravity based on satellite derived gravity data from CryoSat-2 and Jason-1. In contrast to previous maps of Malawi, a scripting approach was introduced as a console-based cartographic mapping developed for plotting a series of thematic maps based on the high-resolution data. The maps demonstrate correlations between the topography and tectonic faults (Malawi Rift Zone) and earthquakes in the Malawi Lake and extent of landforms. The results demonstrate strong correspondence between the topography and geophysical fields (geoid and gravity): negative values of geoid (-15 to -20) are notable over the Malawi (Nyasa) Lake which corresponds with local topographic depressions. Free-air gravity fields reach the lowest values (-50 to -100) over the Malawi Lake. Local heights in gravity are compared with topographic mountain ranges in the NW and SW of the country on the borders with Zambia and Mozambique. The location of earthquakes vary with the majority located in the north. The geomorphological landforms demonstrate variability in slope steepness and aspect orientation shown on histogram. The techniques of scripts can be used to automatically map spatial data using raster datasets for geophysical visualization, and this paper demonstrated this through a variety of map from the presented thematic series of geophysical maps of Malawi. Full scripts used for mapping are available on the author's public GitHub repository with provided link to her open access codes.

Marine sediments can be stabilized by ultra high-strength binders: cement, Cement Kiln Dust (CKD) and slag. The properties of the stabilized soil indicate potential to their reuse. This study investigated the performance of the unconfined compressive strength (UCS) in the marine sediments stabilized by binder (cement, CKD, slag), tested by ultrasonic P-waves. Materials include 194 specimens collected from the port of Gothenborg. The experiment was performed in Swedish Geotechnical Institute (SGI). The UCS of specimens stabilized by different ratio of binders (cement, CKD, slag) was tested by resonance frequencies of the elastic P-waves. The significant increase in the UCS (>1500 kPa) was recorded for the highest values of CKD and cement, and low values of slag. The correlation profiles of low water/high binder (LW/HB) cement/slag (40/60%) were controlled by curing time. The slag–cement–CKD simplex tests demonstrated UCS of samples with low/high water content and various binder ratio of cement (kg/m3). The ratio of cement binder and curing time play a critical role in the increase of UCS followed by mechanical properties of specimens and intensity of stress. The highest values exceed 1000 m/s in P-waves. The results shown high accuracy (97%) and non-contacting approach for testing UCS of sediments. Seismic methods can be applied to test the UCS of the stabilized sediments, and also in-situ via seismic CPT, surface testing or cross hole seismic testing.

This research focuses on the 2D and 3D geospatial analysis of the Ryukyu Trench, a deep-sea trench located in the western Pacific Ocean between Japan and Taiwan. The aim of the research is to visualize regional differences in the topography of the southern (S) and northern (N) parts of the trench. Technically, the methodology is based on using the Generic Mapping Tools (GMT) scripting toolset, for modelling the General Bathymetric Chart of the Oceans (GEBCO), and Earth Topography and Bathymetry dataset (ETOPO1) raster grids. The results demonstrated topographic differences in the two segments. The most frequent depths lie between −5,000 and −6,000 m. The N part has steeper gradient slopes and deeper bathymetry. Of the depth differences >−6,000 m, S has nine values with depths >−6,800 m while N shows 123 records (max −7,460 m). The submarine terraces of S have gentler slopes compared with the N segment. The technical approach presents GMT-based 2D and 3D cartographic modelling aimed at visualizing regional variations of the seafloor topography.

The study presents a comparative analysis of eight Vegetation Indices (VIs) used to examine vegetation greenness over the northern coasts of Iceland. The geographical extent of the study area is set by the coordinates of the two fjords, Eyjafjörður and Skagafjörður, notable for their agricultural significance. Vegetation in Iceland is fragile due to the harsh climate, climate change, overgrazing and volcanic activity, which increase soil erosion. The study was conducted on a Landsat TM image using SAGA GIS as a technical tool for raster bands calculations. The NDVI dataset shows a range from -0.56 to 0.24, with 0 indicating ‘no vegetation’, and negative values – ‘other surfaces’ (e.g. rocks, open terrain). The DVI, compared to the NDVI, shows statistically non-normalized values ranging from -112 to 0, with extreme negative values while the coastal vegetation areas are badly distinguished from the water areas. The NRVI shows an extent from -0.24 to 0.48 with higher values for vegetation. The NRVI reduces topographic, solar and atmospheric effects and creates a normal data distribution. RVI shows a range in a dataset from 0.2 to 3.2 with vegetation in the river valleys clearly visible and depicted, while the water areas have values 0.8 to 1.0. The CTVI shows corrected TVI, in a data range -0.10 to 1.10, as the dataset of NDVI were negative. The TVI dataset ranges from 0.44 to 0.80 with the ice-covered areas and glaciers distinguishable and water values within a range from 0.60 to 0.64 and the vegetation from 0.60 to 0.44. The TTVI dataset ranges from 0.40 to 0.80 performing similarly to the TVI, but more refined with vegetation values 0.64 to 0.68. SAVI dataset ranges from -0.80 to 0.30 with minimized effects of soil on the vegetation through a constant soil adjustment factor added into the NDVI formula. The paper presents a comparison of eight VIs for Arctic vegetation monitoring. The overall behavior of SAGA GIS in calculation and mapping of the VIs is effective in terms of their use for vegetation mapping of the region.

The paper presents technical application of TeX high-level, descriptive markup language for processing geological dataset from soil laboratory. Geotechnical measurements included equivalent soil cohesion, absolute and absolute deformation index, soil compressibility coefficient by time of immersion depth, exposure time to compressive strength to samples and physical and mechanical properties (humidity, density). Dataset was received from laboratory based experimental tests of the physical and mechanical properties of soils. Data were converted to csv table and processed by LaTeX. Methodology is based on LaTeX packages: {tikz}, {tikz-3dplot}, {tikzpicture}, {pgfplot}, {filecontetns}, {spy} for 3D plotting showing correlation in variables and descriptive statistical analysis based on the data array processing. Results demonstrated LaTeX scripts and graphics: 2D and 3D scatterplots, ternaries, bar charts, boxplots, zooming techniques detailing fragment of the plot, flowchart. Research novelty consists in technical approach of TeX language application for geo- logical data processing and graphical visualization. Engineering graphics by TeX was demonstrated with screenshots of the codes used for plotting.

This paper evaluates the potential of using artificial intelligence (AI) and machine learning (ML) approaches for classification of Landsat satellite imagery for environmental coastal mapping. The aim is to identify changes in patterns of land cover types in a coastal area around Cheetham Wetlands, Port Phillip Bay, Australia. The scripting approach of the Geographic Resources Analysis Support System (GRASS) geographic information system (GIS) uses AI-based methods of image analysis to accurately discriminate land cover types. Four ML algorithms are applied, tested and compared for supervised classification. Technical approaches are based on using the 'r.learn.train' module, which employs the scikit-learn library of Python. The methodology includes the following algorithms: (1) random forest (RF), (2) support vector machine (SVM), (3) an ANN-based approach using a multi-layer perceptron (MLP) classifier, and (4) a decision tree classifier (DTC). The tested methods using AI demonstrated robust results for image classification, with the highest overall accuracy exceeding 98% and reached by the SVM and RF models. The presented scripting approach for GRASS GIS accurately detected changes in land cover types in southern Victoria over the period of 2013–2024. From our findings, the use of AI and ML algorithms offers effective solutions for coastal monitoring by analysis of change detection using multi-temporal RS data. The demonstrated methods have potential applications in coastal and wetland monitoring, environmental analysis and urban planning based on Earth observation data. [ABSTRACT FROM AUTHOR]

This paper presents the application of the scripting algorithm GRASS GIS for calculation and visualization of vegetation indices using satellite data. The data include satellite images Landsat-8 OLI/TIRS covering tropical rainforests of central Angola. The images were acquired in July 2013 and July 2023. The methodology is based on using module 'i.vi' of GRASS GIS which automatically calculated 10 vegetation indices: DVI, NDVI, ARVI, EVI, GEMI, MSAVI2, NDWI, PVI, GARI and IPVI. The algorithms of data processing and calculation of vegetation indices are presented in the scripts. The results include the extracted information on distribution of bright green vegetation compared with other land cover types: tropical forests and coastal areas distinguished from artificial surfaces and urban areas, soils and coastal shores. The results indicated landscape dynamics in Angola with decline in tropical forests since 2013 until 2023. The machine-based workflow increases computational efficiency through fast processing of satellite data. The use of scripts demonstrated that programming method of automated information extraction from satellite images is effective for environmental monitoring of tropical African landscapes in rainforests. [ABSTRACT FROM AUTHOR]

Scripting cartographic technique is a new method of geospatial data visualization - especially with thematic mapping such as geomorphological models. The purpose of this study was to explore the use of Generic Mapping Tools (GMT) and R for geomorphological and topographic mapping of Serbia using free open datasets (DEM, SRTM/ GEBCO, OpenStreetMap). Current trend in education and research of distance-based and online-based education suggests that application of free high-resolution data for modelling and mapping by open source cartographic toolsets are more likely to result in deep geospatial analysis of the geomorphology of Balkans with associated geographic phenomena: hydrology, soils, vegetation, geology. Presented fragments of scripts aim to demonstrate the technical usage of R and GMT coding in cartographic workflow with a case study on Serbia. Using qualitative descriptive cartographic approach to visualize the slope, aspect and terrain elevations over the country and the ‘raster’ package provided by R, it was found that the geomorphology of Serbia spatially differs in southern and northern parts of the country resulting in regional geologic evolution and tectonic dynamics of the Balkan formation. The presented maps portrayed general distribution of the landforms in Serbian region of Balkans. The research contributes to the methodological development and testing of the cartographic techniques as well as geomorphological and environmental studies of Serbia.

This paper presents using GDAL utilities and GRASS GIS for topographic analysis of the raster grids based on GEBCO DEM as NetCDF file at 15 arc-second intervals. The focus study area encompasses the area around Okinawa Trough, Ryukyu trench-arc system, southern Japan, East China Sea and the Philippine Sea, West Pacific Ocean. Several GDAL utilities were applied for data processing: gdaldem, gdalwarp, gdalinfo, gdal_translate. The data were imported to GRASS GIS via r.in.gdal. Data visualization highlighted high resolution and accuracy of GEBCO grid, enabling topographic modelling at the advanced level. The algorithm of DEM processing, implemented in GDAL utility gdaldem, was used for generating multi-purpose topographic models: aspect, hillshade, roughness and topographic indices, such as Topographic Position Index (TPI), Terrain Ruggedness Index (TRI). Thematic maps (topography, geoid, marine free-air gravity) were visualized using GRASS GIS modules for raster (d.rast, r.colors, r.contour) and vector (d.vect, v.in.region, d.legend) data processing. The results demonstrated smoother bathymetry in the East China Sea and rugged relief in the Philippine Sea which corresponds to their different geological and geophysical settings. The presented methodology of the topographic analysis based on DEM demonstrated technical aspects of GDAL and GRASS as scripting approach of advanced cartography.

Zambia recently experienced several environmental threats from climate change such as droughts, temperature rise and occasional flooding and they all affect agricultural sustainability and people wellbeing through negative effects on plants and growing crops. This paper is aimed at showing variations in several climate and environmental parameters in Zambia showing spatial variability and trends in different regions of Zambia's key environmental areas (Zambezi River and tributaries), Livingstone near the Victoria Falls and central region with Muchinga Mountains. A series of 10 maps was plotted using data from TerraClimate dataset: precipitation, soil moisture, Palmer Drought Severity Index (PDSI), downward surface shortwave radiation, vapor pressure deficit and anomalies, potential and actual evapotranspiration and wind speed with relation to the topographic distribution of elevations in Zambia plotted using GEBCO/SRTM data. The data range of the PDSI according to the index values ranged from minimum at -5.7 to the maximum at 16.6 and mean at 7.169, with standard deviation at 4.278. The PDSI is effective in quantifying drought in long-term period. Because PDSI index applies temperature data and water balance model, it indicates the effect of climate warming on drought by correlation with potential evapotranspiration. The maximum values for soil moisture of Zambia show minimum at 1 mm/m, maximum at 413 mm/m, mean at 173 mm/m. This study is technically based on using the Generic Mapping Tools (GMT) as cartographic scripting toolset. The paper contributes to the environmental monitoring of Zambia by presenting a series of climate and environmental maps that are beneficial for agricultural mapping of Zambia.

The paper presents the use of the Landsat TM image processed by the ArcGIS Spatial Analyst Tool for environmental mapping of southwestern Iceland, region of Reykjavik. Iceland is one of the most special Arctic regions with unique flora and landscapes. Its environment is presented by vulnerable ecosystems of highlands where vegetation is affected by climate, human or geologic factors: overgrazing, volcanism, annual temperature change. Therefore, mapping land cover types in Iceland contribute to the nature conservation, sustainable development and environmental monitoring purposes. This paper starts by review of the current trends in remote sensing, the importance of Landsat TM imagery for environmental mapping in general and Iceland in particular, and the requirements of GIS specifically for satellite image analysis. This is followed by the extended methodological workflow supported by illustrative print screens and technical description of data processing in ArcGIS. The data used in this research include Landsat TM image which was captured using GloVis and processed in ArcGIS. The methodology includes a workflow involving several technical steps of raster data processing in ArcGIS: 1) coordinate projecting, 2) panchromatic sharpening, 3) inspection of raster statistics, 4) spectral bands combination, 5) calculations, 6) unsupervised classification, 7) mapping. The classification was done by clustering technique using ISO Cluster algorithm and Maximum Likelihood Classification. This paper finally presents the results of the ISO Cluster application for Landsat TM image processing and concludes final remarks on the perspectives of environmental mapping based on Landsat TM image processing in ArcGIS.The results of the classification present landscapes divided into eight distinct land cover classes: 1) bare soils; 2) shrubs and smaller trees in the river valleys, urban areas including green spaces; 3) water areas; 4) forests including the Reykjanesfólkvangur National reserve; 5) ice-covered areas, glaciers and cloudy regions; 6) ravine valleys with a sparse type of the vegetation: rowan, alder, heathland, wetland; 7) rocks; 8) mixed areas. The final remarks include the discussion on the development of machine learning methods and opportunities of their technical applications in GIS-based analysis and Earth Observation data processing in ArcGIS, including image analysis and classification, mapping and visualization, machine learning and environmental applications for decision making in forestry and sustainable development.

The paper presents the cartographic processing of the Landsat TM image by the two unsupervised classification methods of SAGA GIS: ISODATA and K-means clustering. The approaches were tested and compared for land cover type mapping. Vegetation areas were detected and separated from other land cover types in the study area of southwestern Iceland. The number of clusters was set to ten classes. The processing of the satellite image by SAGA GIS was achieved using Imagery Classification tools in the Geoprocessing menu of SAGA GIS. Unsupervised classification performed effectively in the unlabeled pixels for the land cover types using machine learning in GIS. Following an iterative approach of clustering, the pixels were grouped in each step of the algorithm and the clusters were reassigned as centroids. The paper contributes to the technical development of the application of machine learning in cartography by demonstrating the effectiveness of SAGA GIS in remote sensing data processing applied for vegetation and environmental mapping.

The Cascadia Trench is stretching along the convergent plate boundaries of Pacific Plate, North America Plate and Juan De Fuca Plate. It is an important geomorphological structural feature in the north-east Pacific Ocean. The aim of the paper is to analyse the geomorphology of the Cascadia Trench west of Vancouver Island (Canada and USA) using the GMT cartographic scripting toolset. The unique geomorphological feature of the Cascadia Trench is that the thick sediment layer completely obscures the subduction zone and abyssal hills. This results in the asymmetric profile in the cross-section of the trench. Bathymetric data were extracted from the GEBCO 2019 dataset (15 arc-second grid), sediment thickness by the GlobSed dataset. Due to the dominance of high sedimentary rate and complexity of the tectonic processes and geologic settings, Cascadia Trench develops very specific asymmetric geomorphic shape comparing to the typical V-form. The results of the geomorphic modelling show that eastern side of the trench has a gentle curvature (slope: 35.12°), partially stepped, due to the tectonic movements and faults. The opposite, oceanward side is almost completely leveled. The trench is narrow with maximal depth at the selected segment -3489 m and for the whole dataset -6201 m. The most repetitive depth is in a range -2500 to -2400 m (267 samples) and -2500 to -2600 m (261 samples). The bottom is mostly flat due to the high sedimentation rates indicating the accumulative leveling processes. Marine free-air gravity anomalies along the Cascadia Subduction Zone are characterized by weakly positive values (20 mGal) increasing rapidly in the zone of the continental slope (>200 mGal), which is associated with a decrease in thickness of the Earth’s crust.

The study presents geospatial analysis of the seabed distribution of North Sea sediments. Data include thematic datasets with a high-resolution: GlobSed 5-arc-minute total sediment thickness grid combined with GEBCO regional bathymetric grid and geophysical grids showing EGM2008 geoid undulations and marine free-air gravity. The data have been processed using GMT. The data analysis revealed variations in the occurrence and distribution of sediment materials as well as its relationship with topography and regional geophysical settings, marine free-air gravity and geoid. Analysis of the topographic map was performed to describe the structural features of the seafloor. Ridges, large-scale sandbanks, shallow coastal areas and local depressions illustrate uneven bathymetry with northward increasing depths. The highest recorded value is 12,779.642 m located in the northern ares in the SW coast of Norway. Moderate values of sediment thickness (5,000-6,000 m) stretching in NW direction clearly correlate with the marine gravity anomaly isolines with values 10-20 mGal which points at the local relief forms in central basin of the North Sea. The subsidence of the outer shelf of the North Sea and increase of sediment thickness is notable in the central depressions and northern areas: Faroe Islands and Rockall Plateau. The sediment thickness shows the relationship with the topography increasing toward high latitudes. It is also associated with the isostatic sink of the submarine relief in the peripheral areas of the Arctic Ocean. Topographic compensation for the seafloor subsidence by increasing sediment thickness explains local dislocations connected with submarine geomorphology. This study also demonstrated that accurate GMT-based cartographic visualization of the oceanic seafloor using high-resolution multi-source raster grids is crucial to better understand spatial distribution of the marine sediments in the northern latitudes of the North Atlantic Ocean.

The main purpose of this article is to present the use of R programming language in cartographic visualization demonstrating using machine learning methods in geographic education. Current trends in education technologies are largely influenced by the possibilities of distance-learning, e-learning and selflearning. In view of this, the main tendencies in modern geographic education include active use of open source GIS and publicly available free geospatial datasets that can be used by students for cartographic exercises, data visualization and mapping, both at intermediate and advanced levels. This paper contributes to the development of these methods and is fully based on the datasets and tools available for every student: the R programming language and the free open source datasets. The case study demonstrated in this paper show the examples of both physical geographic mapping (geomorphology) and socio-economic geography (regional mapping) which can be used in the classes and in self-learning. The objective of this research includes geomorphological modelling of the terrain relief in Italy and regional mapping. The data include dem SRTM90 and datasets on regional borders of Italy embedded in R packages 'maps' and 'mapdata'. Modelling references to the characteristics of slope, aspect, hillshade and elevation, their visualization using R packages: 'raster' and 'tmap'. Regional mapping of Italy was made using main package 'ggmap' with the 'ggplot2' as a wrapper. The results present five thematic maps (slope, aspect, hillshade, elevation and regions of Italy) created in R language. Traditionally used in statistical analysis, R is less known as a perfect tool in geographic education. This paper contributes to the development of methods in geographic education by presenting new technologies of the machine learning methods of mapping.

The paper discusses the geomorphology of the Sunda Trench, an oceanic trench located in the eastern Indian Ocean along the Sumatra and Java Islands of the Indonesian archipelago. It analysis difference in depths and variation in slope steepness between the two segments of the trench: southern Java transect (108.8°E 10.10°S - 113.0°E 10.75°S) and northern Sumatra transect (97.5°E 1.1°S - 101.0°E 5.5°S). The maps and geomorphological modelling were plotted using Generic Mapping Tools (GMT). The data include high-resolution grids on topography, geology, geodesy and geophysics: GEBCO, EGM2008 EGM-2008, GlobSed. The results include modelled segments, slope gradients, and cross-section profiles. The geological processes take place in the Indian Ocean at different stages of its evolution and influence the nature of the submarine geomorphology and geomorphology of the trench that differs in two segments. Java segment has a bell-shaped data distribution in contrast to the Sumatra with bimodal pattern. Java segment has the most repetitive depths at -2,500 to -5,200 m. Sumatra transect has two peaks: 1) a classic bell-shaped peak (-4,500 m to -5,500 m); 2) shelf area (0 to -1,750 m). The data at middle depths (-1,750 to -4,500 m) have less than 300 samples. The most frequent bathymetry for the Sumatra segment corresponds to the -4,750 m to -5,000 m. Comparing to the Sumatra segment, the Java segment is deeper. For depths > -6,000 m, there are only 138 samples for Sumatra while 547 samples for Java. Furthermore, Java segment has a more symmetrical geometric shape while Sumatra segment is asymmetric, one-sided. The Sumatra segment has a steepness of 57.86° on its eastern side (facing Sumatra Island) and a contrasting 14.58° on the western part. The Java segment has a steepness of 64.34° on its northern side (facing Java Island) and 24.95° on the southern part (facing the Indian Ocean). The paper contributes to the studies of the submarine geomorphology in Indonesia.

The author presents a geospatial analysis of the Peru-Chile Trench located in the South Pacific Ocean by the Generic Mapping Tool (GMT) scripting toolset used to process and model data sets. The study goal is to perform geomorphological modelling by the comparison of two segments of the trench located in northern (Peruvian) and southern (Chilean) parts. The aim of the study is to perform automatic digitizing profiles using GMT and several scripting modules. Orthogonal cross-section profiles transecting the trench in a perpendicular direction were automatically digitized, and the profiles visualized and compared. The profiles show variations in the geomorphology of the trench in the northern and southern segments. To visualize geological and geophysical settings, a set of the thematic maps was visualized by GMT modules: free-air gravity anomaly, geoid, geology and bathymetry. The results of the descriptive statistical analysis of the bathymetry in both segments show that the most frequent depths for the Peruvian segment of the Peru-Chile Trench range from -4,000 to -4,200 (827 recorded samples) versus the range of -4,500 to -4,700 m for the Peruvian segment (1,410 samples). The Peruvian segment of the trench is deeper and its geomorphology steeper with abrupt slopes compared to the Chilean segment. A comparison of the data distribution for both segments gives the following results. The Peruvian segment has the majority of data (23%) reaching 1,410 (-4,500 m to -4,700 m). This peak shows a steep pattern in data distribution, while other data in the neighbouring diapason are significantly lower: 559 (-4,700 m to -5,000 m) and 807 (-4,200 m to -4,400 m). The Chilean segment has more unified data distribution for depths of -6,000 m to -7,000 m. This paper presents GMT workflow for the cartographic automatic modelling and mapping deep-sea trench geomorphology.