Topology, homogeneity and scale factors for object detection: application of eCognition software for urban mapping using multispectral satellite image

The research scope of this paper is to apply spatial object based image analysis (OBIA) method for processing panchromatic multispectral image covering study area of Brussels for urban mapping. The aim is to map different land cover types and more specifically, built-up areas from the very high resolution (VHR) satellite image using OBIA approach. A case study covers urban landscapes in the eastern areas of the city of Brussels, Belgium. Technically, this research was performed in eCognition raster processing software demonstrating excellent results of image segmentation and classification. The tools embedded in eCognition enabled to perform image segmentation and objects classification processes in a semi-automated regime, which is useful for the city planning, spatial analysis and urban growth analysis. The combination of the OBIA method together with technical tools of the eCognition demonstrated applicability of this method for urban mapping in densely populated areas, e.g. in megapolis and capital cities. The methodology included multiresolution segmentation and classification of the created objects.Comment: 6 pages, 12 figures, INSO2015, Ed. by A. Girgvliani et al. Akaki Tsereteli State University, Kutaisi (Imereti), Georgi

Computing and Plotting Correlograms by Python and R Libraries for Correlation Analysis of the Environmental Data in Marine Geomorphology

International audienceThe geomorphology of the Mariana Trench, the deepest ocean trench on the Earth, has a complex character: its transverse profile is asymmetric, the slopes are higher on the side of the Mariana island arc. The shape of the Mariana Trench is a strongly elongated, arched in plan and lesser rectilinear depression. The slopes of the trench are dissected by deep underwater canyons with various narrow steps on the slopes of various shapes and sizes, caused by active tectonic and sedimentation processes. Understanding of factors that may affect the shape of the geomorphology of such complex structure requires advanced methods of numerical computing. Current research is focused on the analysis of the geomorphology of the Mariana Trench by application of statistical libraries embedded in Python and R programming languages for the data analysis. Workflow algorithms include processing a data set by analysis, computing and visual plotting of the graphs. The research aims is to understand the environmental interactions affecting submarine geomorphology of the Mariana Trench by statistical data analysis. Technically, used algorithms included libraries of Python (Seaborn, Matplotlib, Pandas, SciPy and NumPy) and libraries of R ({hexbin}, {ggally}, {ggplot2}). Technically, following types of the statistical analysis were tested for computing and plotting: correlograms, histograms, strip plots, ridgeline plots and hexagonal diagrams for the bathymetric and geomorphic analysis. Python, being a high-level language, shown more straightforward approach for the statistical data analysis, while R implies more power in the data visualization. The results of the geospatial data modelling show detected correlation between various factors (geology, bathymetry, tectonics) affecting submarine geomorphology that reveal unevenness in its structure. Both programming languages demonstrated significant functionality for the spatial data analysis. The effective and accurate geospatial data visualization demonstrated by Python and R proves high potential of their application in the geomorphological studies

K-means Clustering in R Libraries {cluster} and {factoextra} for Grouping Oceanographic Data

International audienceCluster analysis by k-means algorithm by R programming applied for the geological data analysis is the scope of the presented paper. The research object is the Mariana Trench, a hadal trench located in west Pacific Ocean. The study evaluates the similarity of the geological data by the analysis of their attributes. The original observation data set contained samples varying in parameters: geology (sediment thickness), tectonics (locations on the tectonic plates), volcanism (igneous volcanic areas), bathymetry (depth ranges) and geomorphology (slope steepness and aspect). The data pool was divided to the clusters using k-means algorithm with aim to detect similarities. Clustering was chosen as a main statistical method, since it enables detecting similar groups within the original data set by unsupervised classification. Technically, the research was performed using R language and its statistical libraries. The main R libraries include {cluster}, {factoextra}; minor libraries include {ggplot2}, {FactoMiner}, {openxlsx}, {carData}, {rio}, {car} and {flashClust}. Several clusters were tested from two to seven, the optimal number is defined as five. The results show visualized computations: correlation matrix of the factors; comparison of the bi-factors showing pairwise correlation; pairwise comparative analysis showing influence of the variables as bi-factors: sediment thickness correlating with slope angles ; correlation of the volcanic igneous areas with slope angles and aspect degree. Four variables affect geomorphology: slope angle, sediment thickness, aspect degree, bathymetry and volcanism. The paper includes listings of R programming codes for repeatability of the algorithms in similar research

Geostatistical Analysis of the Data Sets on the Mariana Trench, Pacific Ocean

DoctoralPresentation reports current progress of the PhD research. Specifically, it shows an application of R programming language for geostatistical data processing and other methods (QGIS, Python, etc) for Mariana Trench modelling and cartographic mapping. The impact of the geographic location and geological factors on its geomorphology has been studied by methods of statistical analysis and data visualization using R libraries. Research aim is to identify main impact factors affecting variations in the geomorphology of the Mariana Trench: steepness angle and structure of the sediment compression. Research focus is upon understanding variability of factors responsible for the deep ocean trench formation and comparative analysis of its geomorphic structure. It contributes towards investigations of the geology of the Pacific Ocean and the interplay between geomorphic, geological, tectonic and volcanic factors affecting submarine landform formation

Mapping Earthquakes in Malawi Using Incorporated Research Institutions for Seismology (IRIS) Catalogue for 1972–2021

Cartographic data visualization is crucial for geological mapping in seismically active areas of Malawi. Representation of the datasets from IRIS database is beneficial for hazard risk assessment, forecasting and damage mitigation, especially for mapping the distribution and magnitude of earthquakes. Scripting cartography using Generic Mapping Tools (GMT) was used to map seismicity in Malawi Rift Zone based on IRIS catalogue for 1972–2021. The maps show relations among the elevation heights, distribution of seismic events and volcanos in the north of the Malawi Lake. The results show correlation between elevations and seismicity with local topographic depressions. Seismic data show variability of the seismicity level with more earthquakes recorded in the north of the country. This paper contributes to the regional studies of Malawi for risk assessment and geological hazard analysis

Geomorfologia Rowu Puerto Rico i Rowu Kajmańskiego w kontekście ewolucji geologicznej Morza Karaibskiego

This paper concerns the Caribbean Sea submarine geomorphology and bathymetry and especially the Puerto Rico Trench and the Cayman Trough, using thematic mapping, geomorphological modelling and statistical analysis. The technical tools include Generic Mapping Tools (GMT) cartographic scripting toolset. The data include GEBCO digital bathymetric model in grid format, geopotential model of the Earth’s gravity field EGM2008, marine free-air Faye gravity anomalies from a combined GEOS3/SEASAT/GEOSAT altimeter data set, sediment thickness from the GlobSed 5-arc-minute grid model and vector layers of GMT (coastlines, river network, borders). The cross-sectioning was done by the “grdtrack” module. Differences between the form of the Puerto Rico Trench and Cayman Trough presumably result from different structure and geological evolution. The geomorphology of the segment of the Puerto Rico Trench (67.5°W and 19.90°N to 64.1°W and 19.82°N) has a gentle curvature of the slope in plane (about 13° slope steepness). The slopes are steeper in the northern part (about 32°) but higher on the continental slope. The profiles of the Puerto Rico Trench are asymmetric due to the tectonic factors. The seabed of the Cayman Trough is flat at the segment (80.0°W and 17.7°N to 78.5°W and 19.5°N). Its profile is asymmetric: northern part is steep (about 57°), southern part is about 16°. A very large negative Faye free-air gravity anomaly (up to –380 mGal) is seen in the Puerto Rico Trench, south of Cuba as well as in the north-eastern part of the Cayman Trough. The tectonic plate subduction in the Lesser Antilles, Central America and sea floor spreading is reflected in the morphostructure in the Cayman Trough and Puerto Rico Trench. Modeled cross-sectioning profiles show differences both for the Trench and Trough. In contrast with the Puerto Rico Trench with distinct density peak (680 samples for depths –5,200 to –5,400 m), the Cayman Trough has a bimodal data distribution: two peaks correspond to the two intervals: 1) –3,250 m to –1,000 m; and 2) –5,250 to –3,500. The paper contributes to Caribbean Sea geological studies by using GMT for geomorphological modelling.W artykule opisano badania wybranych elementów rzeźby dna Morza Karaibskiego na tle budowy geologicznej, tektoniki oraz wybranych właściwości pola geofizycznego wpływającego na powstawanie rowów głębinowych. Analizę batymetrii wzdłuż Rowu Puerto Rico i Rowu Kajmańskiego wykonano z wykorzystaniem mapowania tematycznego, modelowania geomorfologicznego i analizy statystycznej. Wykorzystano zestaw narzędzi do tworzenia skryptów kartograficznych w środowisku Generic Mapping Tools (GMT). Dane obejmują numeryczny model batymetryczny o strukturze GRID z bazy GEBCO, globalny model geopotencjału EGM2008, anomalie grawitacyjne z uwzględnieniem redukcji wolnopowietrznej (redukcja Faye’a) z połączonego zestawu danych altymetrycznych z misji GEOS3/SEASAT/GEOSAT, numeryczny model miąższości osadów o strukturze GRID i rozdzielczości 5 minut z programu GlobSed oraz warstwy wektorowe w formacie GMT (linie brzegowe, sieć rzeczna, granice). Przekrój został wykonany z wykorzystaniem modułu „grdtrack”. Wyniki pokazały różnice między strukturą Rowu Puerto Rico i Rowu Kajmańskiego, na które wpływ miała ewolucja geologiczna. Średnie nachylenie zboczy rowu Puerto Rico (67,5°W i 19,90°N do 64,1°W i 19,82°N) wynosi 13°. W części północnej zbocza są bardziej strome (32,09°), ale wyższe na zboczu kontynentalnym. Profile Rowu Puerto Rico są asymetryczne dla obu boków z powodu uskoków i ruchów tektonicznych płyty karaibskiej i płyty północnoamerykańskiej. Dno morskie Rowu Kajmańskiego jest płaskie w tym segmencie (80,0°W i 17,70°N do 78,5°W i 19,50°N). Jego profil jest asymetryczny: północna część jest stroma (57°), a południowa jest bardziej łagodna (16°). Bardzo duże ujemne anomalie grawitacyjne Faye’a na wolnym powietrzu (do –380 mGal) widoczne są w Rowie Puerto Rico, na południe od Kuby oraz w północno-wschodniej części Rowu Kajmańskiego. Subdukcja płyt tektonicznych w Małych Antylach, Ameryce Środkowej i na dnie morskim, obejmująca nieckę kajmańską, koreluje ze zmianami falowania geoidy wywołanymi właściwościami skał powodujących anomalie grawitacyjne. Analiza warunków topograficznych na przekroju podłużnym ujawnia różnice dla Rowu i niecki. W przeciwieństwie do Rowu Puerto Rico z wyraźnym pikiem gęstości (680 próbek dla głębokości od –5200 do –5400 m), Rów Kajmański ma bimodalny rozkład danych: dwa szczyty odpowiadają dwóm interwałom: 1) od –3250 m do –1000 m; 2) od –5250 m do –3500 m. Wnioski zawarte w artykule mogą przyczynić się do badań geologicznych Morza Karaibskiego z technicznym zastosowaniem GMT do modelowania geomorfologicznego

Statistical analysis of the Mariana Trench geomorphology using R programming language

This paper introduces an application of R programming language for geostatistical data processing with a case study of the Mariana Trench, Pacific Ocean. The formation of the Mariana Trench, the deepest among all hadal oceanic depth trenches, is caused by complex and diverse geomorphic factors affecting its development. Mariana Trench crosses four tectonic plates: Mariana, Caroline, Pacific and Philippine. The impact of the geographic location and geological factors on its geomorphology has been studied by methods of statistical analysis and data visualization using R libraries. The methodology includes following steps. Firstly, vector thematic data were processed in QGIS: tectonics, bathymetry, geomorphology and geology. Secondly, 25 cross-section profiles were drawn across the trench. The length of each profile is 1000-km. The attribute information has been derived from each profile and stored in a table containing coordinates, depths and thematic information. Finally, this table was processed by methods of the statistical analysis on R. The programming codes and graphical results are presented. The results include geospatial comparative analysis and estimated effects of the data distribution by tectonic plates: slope angle, igneous volcanic areas and depths. The innovativeness of this paper consists in a cross-disciplinary approach combining GIS, statistical analysis and R programming