Polina Lemenkova

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

Keywords: Project mindmap: methods, concepts, approaches and tools

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction -I

Mariana Trench is one of the 37 known deep-water trenches of the World Ocean, 28 of which located in the margin areas of the tectonic plates of the Pacific Ocean. It forms the peripheral framing, of which five are located in the Atlantic [START_REF] Bogdanov | Gidrotermal'nye rudoprojavlenija riftov Sredinno-Atlanticheskogo hrebta (Hydrothermal deposits of rift in the Mid-Atlantic ridge)[END_REF] and four in Indian Ocean [START_REF] Lisicyn | Gidrotermal'nye obrazovanija riftovyh zon okeana (Hydrothermal formation of rift zones of the ocean)[END_REF]. Mariana Trench creates a complex of the deeply interrelated factors, determinants and processes. Factors

Introduction -II

The seafloor of the Mariana Trench is a background, on which all the processes occurring in the Mariana Trench are reflected [START_REF] Dic | Jevoljucija kontinentov i okeanicheskih basseinov kak rezul'tat spredinga okeanicheskogo dna[END_REF]:

The hydrosphere influence on the Mariana Trench is reflected by deep ocean currents bringing sediments to the trench bottom and contributing towards accumulation of the sedimental thickness layer [START_REF] Horleston | Constraining sediment subduction: A converted phase study of the Aleutians and Marianas[END_REF].

The impact of lithosphere is illustrated by a constant exchange of matter and energy between the submarine volcanoes located nearby [START_REF] Hussong | Tectonic process and the history of the Mariana Arc: A synthesis of the results of deep sea drilling project leg 60[END_REF].

The structure of the Mariana Trench and the nature of its relief are greatly complicated by the multiple secondary tectonic disturbances, i.e. by the occurrence of faults and displacements on of grabens, horsts and lateral geologic shifts.

Among other trenches, Mariana Trench is distinct for its edge type associated with the marginal tectonic plate subduction processes [START_REF] Boutelier | Trench-parallel shortening in the forearc caused by subduction along a seaward-concave plate boundary: Insights from analogue modelling experiments[END_REF].

Study area: Mariana Trench: the deepest place of the Earth, located in the west Pacific Ocean. Mariana Trench is a long and narrow topographic depression of the sea floor, the deepest among all hadal trenches, 200 km to the east of the Mariana Islands, eastwards of the Philippine Islands.

.

Mariana Trench: Geological characteristics Bathymetry -transverse profile is strongly asymmetric: the slopes are higher on the side of the island arc. The slopes are dissected by deep underwater canyons. Various narrow steps are often found on the slopes of the trench.

Geomorphology

-complicated steps of various shapes and sizes, caused by active tectonic and sedimental processes. Hence, it is the largest structural trap located in the continental margins of the Pacific Ocean.

Sediments

-the sediments are being carrying by the ocean waves in a clockwise direction, passing through the trenches on the west of the Pacific, i.e. the Kermadec Trench, Tonga Trench, Samoan Passage. The formation of the Mariana Trench is caused by complex and diverse geomorphic factors. Mariana Trench presents a complex system with highly interconnected factors:

Tectonics -II

The system of the Mariana trench is complicated and consists of the interrelated factors forming its tectonic structure:

The main part of the seabed of the Mariana Trench is composed by the oceanic crust forming rift zones of the mid-ocean ridges with a capacity of 5 to 10 km [START_REF] Morgan | Rises, trenches, great faults, and crustal blocks[END_REF].

The deformations of the trench respond to the coupling between the upper and lower plates relating to the continental slab age-buoyancy [START_REF] Ruff | Seismicity and the subduction process[END_REF],

The back-arc deformation roughly correlate with upper continental tectonic plate velocity [START_REF] Heuret | Plate motions, slab dynamics and back-arc deformation[END_REF].

To study such a complex system as Mariana Trench, an objective method combining various approaches (statistics, R, GIS, descriptive analysis and graphical plotting) was performed. Thus, the methodology includes following steps:

Data capture in GIS, vector thematic data were processed in QGIS: tectonics, bathymetry, geomorphology and geology.

Programming on R language

The methodology includes following steps.

firstly, vector thematic data were processed in QGIS: tectonics, bathymetry, geomorphology and geology.

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 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 GIS part of the research is performed in the QGIS 3.0. Geospatial tasks by QGIS plugins: reading coordinates, crossing profile lines, reading data from attribute table into .csv format. Various geospatial data have been uploaded into the GIS project: bathymetry (depths), sediment thickness, location of igneous volcanic zones, tectonic plates, etc. The GIS project: UTM cartesian coordinate system (square N-55).

L A T E X for bathymetry

L A T E X for bathymetry: 3D plotting

The violin plots show Kernel probability density distribution of the bathymetric observations, as multimodal distributions with multiple peaks. Kernel density distribution plot was created using library {violinmplot} of R in a combined plot, which includes calculated quantiles for 0.25 and 0.75 of the data pool.

Regression Analysis: Enlarged Selected Profiles.

Normalized steepness slope calculation of the cross-section profiles Figure 13: Normalized steepness slope calculation of the cross-section profiles: R library {ggplot}, [START_REF] Team | R: a Language and Environment for Statistical Computing[END_REF]. [START_REF] Lemenkova | R scripting libraries for comparative analysis of the correlation methods to identify factors affecting Mariana Trench formation[END_REF]. Visualization of the plot for normalized steepness: R.

Ranking dot plots by data grouping Python libraries: Matplotlib, Seaborn, Pandas [START_REF] Rossum | Python Tutorial Release 3[END_REF]. [START_REF] Lemenkova | Processing oceanographic data by Python libraries NumPy, SciPy and Pandas[END_REF] Methodology

: Forecast evaluation of the spatial variations in sediment thickness. Modelling methods: OLS (A-F); LML (G); WLS (H); Heteroskedastisity-corrected (I). Plotting: Gretl. [27]

Quantile regression tested by Python library StatsModel. [START_REF] Lemenkova | Testing Linear Regressions by StatsModel Library of Python for Oceanological Data Interpretation[END_REF] quantile regression is tested by Python library StatsModel [START_REF] Rossum | Python Tutorial Release 3[END_REF] for sediment thickness (m) versus geologic parameters [START_REF] Lemenkova | Testing Linear Regressions by StatsModel Library of Python for Oceanological Data Interpretation[END_REF] quantile regression (approach of the linear regression) shows the estimated conditional median and other quantiles of the response geological variables:

Results -I. Bathymetry: north, profiles 1-19

Statistical analysis revealed following findings:

The major depth observation points of the Mariana Trench are located in between the -3000 and -5000 m.

The widths of the confidence intervals are expanding rapidly by the profiles 12 to 15 thus indicating on the large amplitude of the depths variations in this part of the Mariana Trench.

The profile depths are affected by the local geographic features caused by the location on 4 tectonic plates with varying environmental conditions.

Conversely, profiles from 1 to 16 have gradual decrease in absolute depths, which can be noted in outliers sample location.

Results -II. Bathymetry: south, profiles 20-25

Summaries of the variations of the local polynomial regression of the bathymetric depths of the measured samples are presented.

The maximal depths reach up to -10000 in the current dataset: profiles №20, 21, 22 crossing mostly Philippine tectonic plate (t.p.).

The widths of the confidence intervals expand rapidly by the profiles 19 to 22 indicating on the large amplitude of the depths variations in this part of the trench.

Decrease of depth: profiles №23, 24, 25, Caroline t.p.

Results -IV. Angle steepness (1)

Analysis of the angle steepness of the cross-section profiles along Mariana Trench revealed following findings:

The major trend of the trench angles located on the Pacific plate has downward general line trend.

The Philippine tectonic plate, on the contrary, has a minimal peak by profiles № 14-21, and then moving upwards.

The highest value for the trench angle steepness is within Caroline t.p.

Mariana plate has the highest density of depth distribution values, followed by the Philippine plate, then Pacific and Caroline, respectively.

From two multiple panel graphs by groups one can compare the slope angles and depth distributions by tectonic plates.

Results -V. Angle steepness (

A bunch of bathymetric cross-section profiles form a cluster groups with similar geomorphic properties divided into five groups over the study area.

Thus, profiles: 21, 22, 18 and 20 have all strong slope tg°angle degree, which is an average of 0.05.

Similarly, profiles: 15, 19, 16, 17, 14 and 2, belonging to class very strong slope, have an tg°angle of 0.057 to 0.058 (Figure 19).

When compared with third group in the study area, such as class extreme slope (profiles: 1, 11, 4, 5, 10 and 13), the average slope tg°angle fluctuating from 0.060 to 0.070.

The fourth group is class steep slope (profiles: 25, 12, 6, 8 3) with a slope tg°angle values from 0.070 to 0.075.

Finally, the last group is notable for the highest steepness (profiles: 9, 7, 23, 24), with average slope tg°angle degree up to 0.079.

The slope steepness is generally related to the slab subduction (tectonic settings) in the particular area, but may also be associated with other factors: topography, submarine volcanism, geology, oceanology.

Enevenness

As a result of the undertaken study, a strong spatial geomorphic unevenness of the Mariana Trench has been revealed: the middle part (profiles: 14 up to 17) has very strong slopes and roughly equal proportions of the sediment thickness layer, while other parts differ.

Five unique regions across the trench length have been classified.

Applied statistics using R

The impact of various factors (oceanology, geology, submarine volcanism, tectonics) affecting structure and geomorphology of the Mariana Trench were studied by means of R programming language.

Euler-Venn diagrams: 4 and 6 petals

Euler-Venn diagrams: 7 petals

There are both theoretical and practical innovations of the presented research.

The theoretical novelty lies in the comparative geomorphological mapping of the Mariana hadal trench that does not exists in the available literature.

The practical novelty consists in the developed methodology of the sequential technological chain of processes: QGIS plugins, R, Python. Cartographic novelty consists in the developed and presented algorithm of the cross-section profiles digitizing and geomorphic modelling of the hadal trench modelling using QGIS plugins. Other methods include Gretle, SPSS [START_REF] Lemenkova | Numerical Data Modelling and Classification in Marine Geology by the SPSS Statistics[END_REF], GMT [START_REF] Lemenkova | Topographic surface modelling using raster grid datasets by GMT: example of the Kuril-Kamchatka Trench, Pacific Ocean[END_REF], [START_REF] Lemenkova | GMT Based Comparative Analysis and Geomorphological Mapping of the Kermadec and Tonga Trenches, Southwest Pacific Ocean[END_REF].

Hadal trench present a complex system with highly interconnected factors affecting geomorphological structure, formation and development of the trench: slabs and tectonics plates, bathymetry, geographic location, geologic structure of the underlying basement and sediment thickness. Therefore, comparative analysis of the Mariana trench requires advanced methods of data analysis for operating with large data sets, structuring, organizing and managing thematic information in a GIS database, linking data and creating map overlays [START_REF] Lemenkova | Thematic Information Clusters for Integrated GIS Mapping of the Marine Ecosystems[END_REF], [START_REF] Lemenkova | Linking Data Between the Worksheets and GIS Databases for Effective Management of the Environmental Projects[END_REF].

Integrating multi-source data supports verification of the data precision and control. The most important geodata include GEBCO [START_REF] Mayer | The Nippon Foundation -GEBCO Seabed 2030 Project: The Quest to See the Worlds Oceans Completely Mapped by 2030[END_REF]; [START_REF] Monahan | GEBCO: the Second Century[END_REF], SRTM [START_REF] Becker | Global bathymetry and elevation data at 30 arc seconds resolution: SRTM30_PLUS[END_REF], ETOPO1 [START_REF] Amante | ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis[END_REF], Goole Earth [START_REF] Lemenkova | Google Earth web service as a support for GIS mapping in geospatial research at universities[END_REF], CryoSat-2, Envisat, Jason-1 [START_REF] Sandwell | Towards 1 mGal Global Marine Gravity from CryoSat-2, Envisat, and Jason-1[END_REF].

The significance and justification of this works consist in the following:

Although ML has been significantly increased recently, using scripting and ML in cartography still remains lower comparing to the traditional GIS used in geosciences (e.g. [START_REF] Suetova | Geoecological Mapping of the Barents Sea Using GIS[END_REF], [START_REF] Klauo | Land Planning as a Support for Sustainable Development Based on Tourism: A Case Study of Slovak Rural Region[END_REF], [START_REF] Klauo | Determination of ecological significance based on geostatistical assessment: a case study from the Slovak Natura 2000 protected area[END_REF], [START_REF] Klauo | Landscape metrics as indicator for ecological significance: assessment of Sitno Natura 2000 sites, Slovakia[END_REF], [START_REF] Lemenkova | Seagrass Mapping and Monitoring Along the Coasts of Crete, Greece[END_REF], [START_REF] Suetova | Geoinformation mapping of the Barents and Pechora Seas[END_REF], [START_REF] Lemenkova | Economic Assessment of Landslide Risk for the Waidhofen a.d. Ybbs Region, Alpine Foreland, Lower Austria[END_REF], [START_REF] Dumnov | Nacional'nyj Atlas Rossii. Priroda. Jekologija[END_REF], [START_REF] Lemenkova | Mapping Land Cover Changes Using Landsat TM: A Case Study of Yamal Ecosystems, Arctic Russia[END_REF], [START_REF] Lemenkova | Clustering Algorithm in ILWIS GIS for Classification of Landsat TM Scenes: a Case Study of Mecsek Hills Region, Hungary[END_REF]).

Seafloor mapping includes multiple steps in technological process which may include: Hydrosweep DS sonar echo-sounding [START_REF] Lemenkova | Smart Seafloor Mapping in Real Time Regime Using Deep-Sea Multibeam Echosounder Hydrosweep DS[END_REF], CARIS HIPS data processing [START_REF] Gauger | The expedition ANTARKTIS-XXIII/4 of the Res. Vessel 'Polarstern' in 2006[END_REF], ArcGIS/ArcCatalog database management, QGIS data processing.

Accurate digitizing cross-section profiles using QGIS is effective. Modelling is important for accurate geomorphological data analysis and crucial for better understanding of the seafloor landforms.

QGIS-based mapping provides accurate visualization of the seafloor.

QGIS-based mapping provides enables cartographic digitizing.

Efforts in developing methodology in automatization in bathymetric mapping exists [START_REF] Schenke | Zur Frage der Meeresboden-Kartographie: Die Nutzung von AutoTrace Digitizer für die Vektorisierung der Bathymetrischen Daten in der Petschora-See[END_REF].

Conclusion

Precise, correct and up-to-date information about the geomorphology Mariana trench is necessary understanding marine geology, tectonics, seismicity, processes of sedimentation and geodynamic evolution of the seafloor [START_REF] Gohl | Tectonic and Sedimentary Processes of the West Antarctic Margin of the Amundsen Sea Embayment and Pine Island Bay[END_REF], [START_REF] Gohl | Crustal and Sedimentary Structures and Geodynamic Evolution of the West Antarctic Margin and Pine Island Bay[END_REF], [START_REF] Kuhn | The response of quaternary climatic cycles in the South-East Pacific: development of the opal belt and dynamics behavior of the West Antarctic ice sheet[END_REF], [START_REF] Gohl | Deep crustal refraction and reflection seismics. Crustal and sedimentary structure and geodynamic evolution of the West Antarctic continental margin and Pine Island Bay[END_REF].

Submarine geomorphological and bathymetric mapping plays a critical role in analysis of the geological structures of the seafloor, marine benthic habitats, navigation, geological drilling, modelling marine environment and other aspects of geosciences.

Current studies contributed to the methodological testing and technical application of the advanced algorithms for seafloor modelling and mapping and to the geomorphological modelling.

Tested, presented and explained functionality of the several QGIS plugins enables to do automated digitizing of the orthogonal profiles crossing trenches in the perpendicular direction. Through this modelling, the shape of the landforms and steepness gradient of the trenches were visualized, compared and statistically analyzed.

Thanks

The funding for this research has been provided by the China Scholarship Council (CSC), Peoples Republic of China (P.R.C.), Beijing. Grant #2016SOA002.

  affecting formation, geomorphic development and bathymetric patterns of the Mariana Trench are diverse:

Figure 3 :

 3 Figure 3: Mariana Trench: square of the study area

.

Figure 4 :

 4 Figure 4: Enlarged map of the Mariana Trench

Figure 5 :

 5 Figure5: Study area. Methodological approach using QGIS: digitizing profiles across the Mariana Trench. Source:[START_REF] Lemenkova | Statistical Analysis of the Mariana Trench Geomorphology Using R Programming Language[END_REF]

Figure 6 :

 6 Figure 6: Digitizing 25 bathymetric profiles across the Mariana Trench.[START_REF] Lemenkova | Statistical Analysis of the Mariana Trench Geomorphology Using R Programming Language[END_REF]

Figure 7 :

 7 Figure7:L AT E X Plotting: two selected profiles, 2D View. Source:[START_REF] Lemenkova | R scripting libraries for comparative analysis of the correlation methods to identify factors affecting Mariana Trench formation[END_REF]

Figure 8 :

 8 Figure 8: L AT E X Plotting: Marina Arc, 3D View. Source:[START_REF] Lemenkova | R scripting libraries for comparative analysis of the correlation methods to identify factors affecting Mariana Trench formation[END_REF]

Figure 9 :

 9 Figure 9: Graphs of the 25 bathymetric profiles,Mariana Trench. Source:[START_REF] Lemenkova | Statistical Analysis of the Mariana Trench Geomorphology Using R Programming Language[END_REF]

Figure 10 :

 10 Figure10: Boxplots of the cross-section profiles: R based statistical analysis.[START_REF] Lemenkova | R scripting libraries for comparative analysis of the correlation methods to identify factors affecting Mariana Trench formation[END_REF]

Figure 11 :

 11 Figure 11: Violin plots of the profiles: R based statistical plotting.[START_REF] Lemenkova | Factor Analysis by R Programming to Assess Variability Among Environmental Determinants of the Mariana Trench[END_REF]

Figure 12 :

 12 Figure12: Regression Analysis: 3 selected profiles. Source:[START_REF] Lemenkova | An Empirical Study of R Applications for Data Analysis in Marine Geology[END_REF]

Figure 14 :

 14 Figure 14: Ranking dot plots by data grouping: Left: distribution of data points by profiles across igneous areas. Right: variation of steepness angles by 25 profiles. R based visualization and statistical analysis, libraries {ggalt} and {ggplot}.[START_REF] Lemenkova | An Empirical Study of R Applications for Data Analysis in Marine Geology[END_REF]

Figure 15 :

 15 Figure 15: Scatterplot matrices.[START_REF] Lemenkova | Scatterplot Matrices of the Geomorphic Structure of the Mariana Trench at Four Tectonic Plates (Pacific, Philippine, Mariana and Caroline): a Geostatistical Analysis by R[END_REF]

Figure 16 :Figure 17 :

 1617 Figure 16: R based dendrogram tree of the 25 profiles. Left: unsorted, right: sorted.[START_REF] Lemenkova | Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean[END_REF]

Figure 18 :

 18 Figure 18: Kernel Density Estimation (KDE) for the profiles bathymetry.Python libraries: Matplotlib, Seaborn, Pandas[START_REF] Rossum | Python Tutorial Release 3[END_REF].[START_REF] Lemenkova | Processing oceanographic data by Python libraries NumPy, SciPy and Pandas[END_REF]

Figure 19 :

 19 Figure 19: Descriptive statistical analysis of the bathymetry in the study area: minimal, mean, median and maximal values (A); box plots of the cross-sectional profiles (B). Plotting: Gretl . Source:[START_REF] Lemenkova | Regression Models by Gretl and R Statistical Packages for Data Analysis in Marine Geology[END_REF]

Figure 20 :

 20 Figure 20: Statistical analysis of the sediment thickness: QQ plot (A), locally-weighted polynomial regression (B); box plots ranked by clusters (C).Source:[START_REF] Lemenkova | Regression Models by Gretl and R Statistical Packages for Data Analysis in Marine Geology[END_REF]

  the upper two rows of the plot show (subplots A, B, C, D) data distribution across tectonic plates: A) Pacific Plate; B) Philippine Plate; C) Mariana Plate; D) Caroline Plate; E) Cumulative sediment thickness; F) Slope angle degree by profiles the lower row of the plot (subplots E, F) shows data distribution for the cumulative sediment thickness and slope angle degree by profiles.

Profiles №23 and 24

 24 demonstrate the deepest depth values. The absolute depths in the profiles 22 to 25 on the Caroline t.p. become shallower than those on Philippine and Pacific t.p. The majority of the observation points: Pacific and Philippine t.p., following by . Sediment thickness The sediment thickness changes notably both within the trench by profiles (1:25) and between four tectonic plates that Mariana Trench crosses: Philippine, Pacific, Mariana and Caroline. Since the tectonic properties and attribute values of them are not identical. The comparative analysis of how the data vary across four distinctive plates revealed that the middle part of the Mariana Trench (profiles: 14 up to 17) has roughly equal proportions of the sediment thickness layer, which indicates that spatial locations and distributions of the volcanic areas and slope angle of the ocean trench are closely interrelated; geographic distributions of the volcanic areas and steepness of the slope angles of the ocean trench affect sedimental thickness.

Figure 22 :

 22 Figure 22: Treemap for impact factors affecting Mariana Trench formation, R visualization. Source:[START_REF] Lemenkova | R scripting libraries for comparative analysis of the correlation methods to identify factors affecting Mariana Trench formation[END_REF]

Figure 23 :

 23 Figure 23: Possible correlations of the impact factors affecting Mariana Trench. Left: four tectonic plates. Right: environmental factors

Figure 24 :

 24 Figure 24: Correlations of the impact factors affecting Mariana Trench, R

  E X macro language code for bathymetric plotting. Example for profile16, 17, 18.

\begin{filecontents*}{MyTab18.csv} ELEV ,y2,x2 145.528246366,47.0433461696,-7800 # bathymetric data here in 3 columns \end{filecontents*} \begin{tikzpicture} \begin{axis}[grid=major,minor x tick num=10,minor y tick num=10, colorbar sampled line,colormap name=bluered, title={Mariana Trench. Bathymetric Profiles Nr.16,17,18}, ylabel={Depth (m)}, legend entries={Profile18,Profile17,Profile16,}, scaled ticks=false, yticklabel style={/pgf/number format/fixed,/pgf/number format/fixed zerofill,}] \addplot+ [scatter,only marks,mark=Mercedes star flipped,colormap name=bluered,] table [x=x, y=d, col sep=comma] {MyTab16.csv}; \addplot+ [scatter, colorbar sampled line,only marks,mark=asterisk,colormap name=bluered,] table [x=long, y=d, col sep=comma] {MyTab17.csv}; \addplot+ [scatter, colorbar sampled line,only marks,mark=10-pointed star,colormap name=bluered,] table [x=y2,y=ELEV, col sep=comma] {MyTab18.csv}; \end{axis} \end{tikzpicture} Methodology

Compiled in LuaL AT E X by Polina Lemenkova for: the Seminar at OUC. Venue: Ocean University of China, Faculty of Marine Geo-science. Location: Qingdao, Shandong, P. R. C. Date: 08/04/2019.

attribute information has been derived from each profile and stored in a table containing coordinates, depths and thematic information. this table was processed


Polina Lemenkova

Vn Vt

N B Sc

Ph Mn

R Pl

Prof. Dr Yonghong Wang

Max Depth

Deep-Sea Trenches of the Pacific Ocean: a Comparative Analysis of the Submarine Geomorphology by Data Modeling Using GMT, QGIS, Python and R Mid-Term PhD Thesis Presentation: Current Research Progress

Keywords: processing, visualization, statistical modelling, cartographic mapping, 3D and 2D simulation models, graphical plotting Tools: Generic Mapping Tools (GMT), QGIS plugins, statistical libraries , grids, vector lines, advanced data visualization

Objective

The impact of the factors (geology, tectonics, seismicity) on its geomorphology studied by methods of the data visualization, modelling and statistical analysis.

Pacific Ocean

The Sea of Okhotsk max depths 3374 m [START_REF] Maiorova | Deep-sea spoon worms (Echiura) from the Sea of Okhotsk and the adjacent T slope of the Kuril-Kamchatka Trench[END_REF] The deepest strait to the NW Pacific Ocean is Bussol (2300m) [START_REF] Brandt | First insights into macrofaunal composition from the SokhoBio expedition T (Sea of Okhotsk, Bussol Strait and northern slope of the Kuril-Kamchatka Trench)[END_REF] MA presents a boundary of the large subduction zone of the Pacific tectonic plate under the Okhotsk tectonic plate [START_REF] Bird | An updated digital model of plate boundaries[END_REF] irregularity in its bathymetric shapes and geomorphic structure together with Aleutian Trench, the KKT presents contiguous complex, area: 254,740 km 2 [START_REF] Harris | Geomorphology of the oceans[END_REF].

The Okhotsk plate represents a region of active grabens lying southwards of a chain of small sedimentary basins in the Cherskii Mnts [START_REF] Savostin | Geology and plate tectonics of the Sea of Okhotsk, Geodynamics of the Western Pacific-Indonesian Region[END_REF].

there is proved radially symmetric coherence between satellite gravity and multibeam bathymetry grids [START_REF] Marks | Radially symmetric coherence between satellite gravity and multibeam bathymetry grids[END_REF] the free-air marine gravity fields map illustrates values (mGal) of the density anomalies at seafloor topography, sediments, crust and mantle [START_REF] Smith | Marine gravity field from declassified Geosat and ERS-1 altimetry[END_REF].

the free-air anomaly is dominated by the short wavelength variations which reflect the density contrast at the seafloor.

the gravity spectrum correlates with the bathymetry of the seafloor.

MA PC H Ps K southern part is deeper reaching -8,200 m depth while northern part has -7,800 at maximal records.

at a southern segment, the seafloor depths increase with increasing latitude gradually while moving southwards.

the profiles located in in the northern segment are shallower variations illustrates tectonic and geological local variations and different sedimentation of the northern and southern part of the trench.

These are the results of the comparative analysis of the two distinct parts of the trench located north-and southwards from the Bussol Strait. The seafloor of the AT is constantly experiencing deformations under the impact of the plate tectonic processes.

Various factors affect its formation, among which, tectonics plates movement, subduction of the underlying slab into the deep mantle, seismic activities in the study area, e.g. submarine earthquakes [START_REF] Shepard | Submarine Geology[END_REF]. The profiles plotted in an automated regime are located with a distance of 20 km between each pair, spaced every 2 km along the profiles itself and have a total length of 400 km, that is 200 km to both sides from the trench. depths with ranges between -5600 and -5400 m have occurrence of 1106 (8%); depths with ranges between -5400 and -5200 m have occurrence of 846 (7%); depths with ranges between -4900 and -5200 m have occurrence of 1297 (11%).

Aleutian Trench

The topography in the study area ranges between -8000/2000 m. According to the statistical histogram modelling, the most often depth value in the study area is -4800 with frequency 1722. The highest values demonstrated values of -4900 and -4700 with 1722 occurrences (13,2%). Significantly low values demonstrated shallow areas with depth ranges between -4500 and -3000 m with occurrence of below 200 (all of then less than 2,5%). CP is young oceanic tectonic plate, beneath the Pacific Ocean off the coast of the Central America continent [START_REF] Morgan | Rises, trenches, great faults, and crustal blocks[END_REF] CP was created as a results of the break of Farallon Plate into Nazca and CP [START_REF] Turcotte | Geodynamics[END_REF] CP is bounded by: North American, Caribbean, Pacific and Nazca plates [START_REF] Guzmán-Speziale | Seismic strain rate along the Middle America Trench reveals significant differences between Cocos-North America and Cocos-Caribbean convergence[END_REF] MA Middle America Trench Key points on the Middle America Trench:

The neotectonic MAT consists of two distinct parts with varying features of the oceanic plate and geology in either: northern and southern The division between the both parts goes by the Tehuantepec Ridge [START_REF] Aubouin | The Middle America Trench in the Geological Framework of Central America[END_REF] The northern part of MAT, off Mexico, a.k.a. Acapulco Trench: a minor hadal trench, a part of the East Pacific Rise, from Jalisco to Tehuantepec Ridge. processes in the oceanic fracture zones in PCT area are affected by high degree of hydration in the crust and upper mantle is discussed by [START_REF] Contreras-Reyes | Upper lithospheric structure of the subduction zone offshore southern Arauco Peninsula, Chile at 38 • S[END_REF].

according to the sedimentation conditions, the Peru-Chile Trench can be divided into two main provinces: the main sediment-free province extending 8 Over 50% of the world's deep-sea trenches are 'sediment starved' or 'partly sediment filled' [START_REF] Geersen | Submarine Geomorphology[END_REF].

N part of PCT, (Peruvian segment), is 'sediment starved', while S part (Chilean segment) is 'partly sediment filled' [START_REF] Geersen | Sediment-starved trenches and rough subducting plates are conducive to T tsunami earthquakes[END_REF].

As a response of sediment loading at the trench, the downward deflection determines its sediments capacity (amount of subducted sediments)

Weak and hot oceanic plates has larger space for sediment subduction [START_REF] Contreras-Reyes | Lithospheric flexure modeling seaward of the Chile trench: implications for oceanic plate weakening in the Trench Outer Rise region[END_REF].

Downward deflection of the plate is larger along the Chiloé segment comparing to Maule segment [START_REF] Contreras-Reyes | Sediment loading at the southern Chilean Trench and its tectonic implications[END_REF] The margin off Isla de Chiloé is characterized by a largely sedimented segment of the Peru-ChileTrench. This is caused by the extension of turbidite deposits seaward reaching 250 km from the trench axis [START_REF] Contreras-Reyes | Alteration of the subducting oceanic lithosphere at the southern central Chile trench-outer rise[END_REF].

The region close to the Taitao Triple Junction is devoid of sediments and has rapid narrowing of the forearc region [START_REF] Behrmann | Tectonics and geology of spreading ridge subduction at the Chile Triple Junction: A synthesis of results from Leg 141 of the Ocean Drilling Program[END_REF].

Peru-Chile Trench the highest frequency of the data for both segments, the following findings are notable: the Peruvian segment has the majority of the data (23%) reaching 1,410 (-4,500 to -4,700m are the most frequent values for the Peruvian segment).

this peak shows steep pattern in data distribution, while other data in the neighbor diapason are significantly lower: 559 (-4,700 to -5,000 m) and 807 (-4,200 to -4,400 m) for the Peruvian segment.

the Chilean segment has more even shape with unified data distribution for the depths -6,000 to -7,000 m. KT is the 5 th world's deepest trench, max depth 10,177 m, length 1500 km [START_REF] Jamieson | Bait-attending fauna of the Kermadec Trench, SW Pacific Ocean: Evidence for an ecotone across the abyssal-hadal transition zone[END_REF] KT and TT closeness to the Antarctic => among the world's coldest trenches [START_REF] Belyaev | Deep-Sea Ocean Trenches and Their Fauna[END_REF] KT runs parallel to the Kermadec Ridge with geomorphology of V-shape formed by tectonic subduction of the Pacific Plate under the Indo-Australian Plate [START_REF] Leduc | Nematode communities in sediments of the Kermadec Trench, Southwest Pacific Ocean[END_REF] KT extends from ca. 26 • to 36 • S near the NE tip of New Zealand's North Island.

MA PC H Ps K T Vn Vt NB SC Ph Mn R Pl Y MT IB JT Con
The specific tectonic setting is the subduction of the PP at a rapid rate beneath the Indo-Australian Plate along the TT and KT A convergence at max rate (ca. 249 mm/yr) along the TK arc system => one of the world's most seismically active subduction zones [START_REF] Bevis | Geodetic observations of very rapid convergence and back-arc extension at the Tonga arc[END_REF] TT is 2 nd deepest trench in the world (max depths of 10,882 m) [START_REF] Blankenship | Vertical zonation patterns of scavenging amphipods from the Hadal zone of the Tonga and Kermadec Trenches[END_REF].

KT and TT belongs to the South Pacific Subtropical Gyre (SPSG) biogeochemical province, has the same primary productivity rate of 87 g C m-2 y-1 [START_REF] Xu | Biogeochemistry of hadal trenches: Recent developments and future perspectives[END_REF] Both trench axes have roughly 30 • slight from the longitude line. TT has shallower depths on the eastern part along but KT has more abrupt shape with 2,641 depth records s from -6,600 to -6,800m.

TT geomorphology has steeper gradient slope on the western flank.

TT deepest values > 9, 000m: 320 observation samples KT deepest values > 9, 000m: 251 samples => TT is deeper than KT.

KT has more values in this range: 6167 samples. For the TT, the same range gives 4803.

KT has more gentle slope shape form and shallower depths of the western slope off Tonga Ridge.

Variations of the seafloor depths at range from -6,000 to -5,000.

Variation between KT and TT illustrates tectonic and geological local settings => different sedimentation of the KT and TT => different geomorphic shape despite close location Vn has more V-form classic shape for the trench with gentle shapes on both western and eastern slopes.

Vt has shallower depths with maximal not exceeding -5,000 m while Vn is more deep with -6,000 m.

The surrounding relief of the Vn & Vt varies: Vt has the flat neighboring surface;

Vn is surrounded by complex submarine relief of North Fiji Basin (its eastern flank) and its western flank The NBT (a.k.a. Bougainville Trench) is defined by the 6,000 m isoline [START_REF] Mammerickx | Bathymetry of the South Pacific[END_REF] It is a narrow, 50-75 km wide trench extending NE from the E end of the Huon Gulf along the S coast of New Britain [START_REF] Mammerickx | Bathymetry of the South Pacific[END_REF] Its name is derived from the New Britain Island from the New Britain arc Its W extension are: north-dipping Ramu-Markham fault zone, West Bismarck arc [START_REF] Abbott | Structural evolution of a modern arc-continent collision in Papua New Guinea[END_REF] The northern part is characterized by the Bismark Sea back-arc basin where active rifting and seafloor spreading take place [START_REF] Lindley | New Britain Trench, Papua New Guinea: An extensional element in a regional sinistral strike-slip system[END_REF] The Bismark Sea back-arc basin comprises the South and North Bismarck microplates separated by the Bismarck Sea fault [START_REF] Taylor | Bismarck Sea: evolution of a back-arc basin[END_REF] The The increase in depth by NBT is more gentle: in 50km segment it reaches 2000 m depths (from -7,000 to -5,000)

MA PC H Ps K T Vn Vt NB SC Ph Mn R Pl Y MT
The increase for the SCT is more abrupt: for the same distance (50 km) the depths rise from -8,000 to -5,200 m (that is, ca 3000 m).

NBT has gentle slope on the Solomon Sea side. NBT is markedly asymmetric in the landward slope and has an arc form in E. Geologically, the area of NBT and SCT belongs to one of the most prospective for intrusion-related mineral deposits there is distinct variability in depths by samples in two trenches.

The SCT is generally deeper reaching -9,000m while median for NBT <-7,000m.

The gradient slope of SCT is more symmetric with accurate 'V' form.

In a cross-section graph, the NBT landward slope is markedly asymmetric U-shaped form and has crescent form in the east.

The NBT slope dips westwards with 35 • eastward, and 41 • westward, while SCT slope has 33 • oceanwards and 33,69 • landwards.

The differences between the trenches are explained by the context of the historic and actual geomorphic and sedimentary processes affected their formation and structure.

Key points on the QGIS digitizing:

The 1.000 km long profiles were drawn along the trench using 'Add Line Feature' tool from the Digitizing Toolbar.

The intersections between the lines and the bathymetry was done using 'Vector / Analysis Tools / Lines Intersection' command. This resulted in the array of the points along each profile. Each point has now a bathymetry depth value and a point reference number.

Lat/lon coordinates were added to the attribute table of each intersection line of the profiles using plugin 'Lat Lon Tools / Conversion / Point layer to fields'.

This added the 25 layer's latitude, longitude (Y, X) and copied into the text fields in the new layers.

The topography was plotted using 'ProfileFromPoints' plugin, along a profiles centerline using elevation Z (depths).

The attribute tables were exported from the QGIS she files ('Export / Save Features As') to csv format for each of the profiles.

The results are shown left.

The csv table was then further processed by Python and SPSS. MA

Key points on the regression analysis by R:

For the assessment of the variation in the geomorphology of the trench, it is of significant advantage to visualize the data set using regression analysis (Fig. left).

Regression analysis determines the range, general trend in data distribution and scale of the changes in the observed bathymetry by analyzing changes in the values of the elevation.

The algorithms and approaches for the performed regression analysis use existing methods and embedded in {ggplot} library of R.

Advantages of plotting a facetted graph consists in visualizing a stream of the data at one look. topographic analysis by statistical plotting of data using the high-low charts, SPSS, [START_REF] Lemenkova | Numerical Data Modelling and Classification in Marine Geology by the SPSS Statistics[END_REF] shows analysis of the depth ranges: summaries of variables by 25 profiles PT geology: sequences of serpentinized peridotite, basalts, limestones, block of coral-reef limestones (4,900 to 6,500m) [START_REF] Kobayashi | Why is the Palau Trench so Deep? Deep-Sea Trench without Plate Convergence[END_REF] PT is connected with the Kyushu-Palau Ridge (N) and Ayu Trough (S). YT has the greatest depth at 8,292 m, is 700km long and 50km wide [START_REF] Sato | Seismic observations at the Yap Islands and the northern Yap Trench[END_REF].

YT stretches from the trench axis to Yap islands arc with a characteristic 'J' form [START_REF] Lee | Deformation from the convergence of oceanic lithosphere into Yap trench and its implications for early-stage subduction[END_REF].

YT is morphologically divided into the N and S parts with the the boundary between the two at 8 • 26 N [START_REF] Fujiwara | Morphology and tectonics of the Yap Trenches[END_REF].

YT and PT are distinguished from the flat-bottomed Ayu Trough by their V shape. Such complex tectonic structure of the region is reflected in notable heterogeneity of the crustal and upper mantle velocity structures beneath the PSP [START_REF] Oda | Regional variation in surface wave group velocities in the Philippine Sea[END_REF].

Necessarily, it affects the submarine seafloor topography and its geomorphology.

The Yap-Palau subduction zone lies S off the Mariana arc-trench system.

PT and YT are formed in the place of the PSP subduction and oceanic lithosphere sinking to the mantle.

As the sinking PSP moves deeper into the mantle, the fluids are released from the mantle rock => melting of the the overlying mantle.

The new magma rises to the surface and erupts violently forming volcanoes and arcs of islands along the convergent tectonic plate boundary. Attribute table content: XY coordinates, Z (m), thematic data box plot & violit plot graphically displays summary on the statistical distribution of depths: frequencies, range and quartiles of samples across profiles plots shows: x-axis is measured variable (profiles); y-axis is frequency/count on depths method: R libraries {stat} and {violinmplot} [START_REF] Team | R: a Language and Environment for Statistical Computing[END_REF].

Quantile regression tested by Python library StatsModel. [START_REF] Lemenkova | Testing Linear Regressions by StatsModel Library of Python for Oceanological Data Interpretation[END_REF] quantile regression is tested by Python library StatsModel [START_REF] Rossum | Python Tutorial Release 3[END_REF] for sediment thickness (m) versus geologic parameters [START_REF] Lemenkova | Testing Linear Regressions by StatsModel Library of Python for Oceanological Data Interpretation[END_REF] quantile regression (approach of the linear regression) shows the estimated conditional median and other quantiles of the response geological variables: The Izu-Bonin Trench is boarded on the east by the Ogasawara Plateau [START_REF] Nishizawa | Crustal structure of the ocean-island arc transition at the mid Izu-Ogasawara (Bonin) arc margin[END_REF] Longitudinally, it extends from near Tokyo, Japan to Guam [START_REF] Barnes | Chorine stable isotope variations in Izu Bonin tephra: Implications for serpentinite subduction[END_REF] In its structure, IBT continues the JT. The Izu-Bonin Trench is formed in the area of active tectonic subduction of the Cretaceous (135 Ma) PP beneath the PSP [START_REF] Sano | Progressive enrichment of arc magmas caused by the subduction of seamounts under Nishinoshima volcano, Izu-Bonin Arc, Japan[END_REF] As a consequence of this subduction the following structured are formed (volcanic arc of the on the Izu-Bonin-Mariana Arc system):

Izu Island Bonin Islands Shikoku Basin as a backarc basin

Key points on the cross-sectioned profiles visualized at two IBT segments: S segment is deeper and has more accurate V-form with a steeper gradient slope on both slopes N segment has asymmetric shape of the slope with notable submarine terrace on the W part and more straight shape on the oceanwards side S segment of the trench has Bonin Ridge distinguishable on the graph.

Comparison of the oceanward flank of the both segments of the Izu-Bonin Trench show similar geomorphic shape but seamounts on the N

The Japan Trench is located in W part of the Pacific Ocean, E off Japan. Geologic and tectonic settings are strongly influenced by subduction of the PP beneath Japan and NAP along JT [START_REF] Huene | Tectonic erosion along the Japan and Peru convergent margins[END_REF].

Key points on the Japan Trench (JT):

JT region is a convergent zone associated with earthquakes [START_REF] Yoshii | Detailed cross-section of the deep seismic zone beneath northeastern Honshu, Japan[END_REF].

JT belongs to circum-Pacific seismic belt 'Ring of Fire' => large earthquakes are in sedimentation area on upper forearc slopes [START_REF] Arai | Episodic subsidence and active deformation of the forearc slope along the Japan Trench near the epicenter of the 2011 Tohoku Earthquake[END_REF].

JT structure is a typical arc-trench system [START_REF] Ludwig | Sediments and structure of Japan Trench[END_REF].

JT arc-trench system is a type of the mobile belts with bathymetric and topographic relief formed under the impact of tectonic plates subduction, active volcanism, repetitive earthquakes and orogenesis.

Geological complexity of the JT results in the highly seismicity [START_REF] Huene | Tectonic erosion at the front of the Japan Trench convergent margin[END_REF]; [START_REF] Lin | Distribution of stress state in the Nankai subduction zone, southwest Japan and a comparison with Japan Trench[END_REF]; [START_REF] Boston | Forearc slope deformation above the Japan Trench megathrust: Implications for subduction erosion[END_REF].

MA S shows more gentle slope on the Honshu Island.

12 profiles were drawn for the southern segment and 14 profiles for the northern one. Therefore, comparative analysis of the trenches of the Pacific Ocean requires advanced methods of data analysis for operating with large data sets, structuring, organizing and managing thematic information in a GIS database, linking data and creating map overlays [START_REF] Lemenkova | Thematic Information Clusters for Integrated GIS Mapping of the Marine Ecosystems[END_REF], [START_REF] Lemenkova | Linking Data Between the Worksheets and GIS Databases for Effective Management of the Environmental Projects[END_REF].

Integrating multi-source data supports verification of the data precision and control. The most important geodata include GEBCO [START_REF] Mayer | The Nippon Foundation -GEBCO Seabed 2030 Project: The Quest to See the World's Oceans Completely Mapped by 2030[END_REF]; [START_REF] Monahan | GEBCO: the Second Century[END_REF], SRTM [START_REF] Becker | Global bathymetry and elevation data at 30 arc seconds resolution: SRTM30_PLUS[END_REF], ETOPO1 [START_REF] Amante | ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis[END_REF], Goole Earth [START_REF] Lemenkova | Google Earth web service as a support for GIS mapping in geospatial research at universities[END_REF], CryoSat-2, Envisat, Jason-1 [START_REF] Sandwell | Towards 1 mGal Global Marine Gravity from CryoSat-2, Envisat, and Jason-1[END_REF].

MA Research Significance and Justification The significance and justification of this works consist in the following: Although ML has been significantly increased recently, using scripting and ML in cartography still remains lower comparing to the traditional GIS used in geosciences (e.g. [START_REF] Suetova | Geoecological Mapping of the Barents Sea Using GIS[END_REF], [START_REF] Klaučo | Land Planning as a Support for Sustainable Development Based on Tourism: A Case Study of Slovak Rural Region[END_REF], [START_REF] Klaučo | Determination of ecological significance based on geostatistical assessment: a case study from the Slovak Natura 2000 protected area[END_REF], [START_REF] Klaučo | Landscape metrics as indicator for ecological significance: assessment of Sitno Natura 2000 sites, Slovakia[END_REF], [START_REF] Lemenkova | Seagrass Mapping and Monitoring Along the Coasts of Crete, Greece[END_REF], [START_REF] Suetova | Geoinformation mapping of the Barents and Pechora Seas[END_REF], [START_REF] Lemenkova | Economic Assessment of Landslide Risk for the Waidhofen a.d. Ybbs Region, Alpine Foreland, Lower Austria[END_REF], [START_REF] Dumnov | Nacional'nyj Atlas Rossii. Priroda. Jekologija[END_REF], [START_REF] Lemenkova | Mapping Land Cover Changes Using Landsat TM: A Case Study of Yamal Ecosystems, Arctic Russia[END_REF], [START_REF] Lemenkova | Clustering Algorithm in ILWIS GIS for Classification of Landsat TM Scenes: a Case Study of Mecsek Hills Region, Hungary[END_REF]).

Seafloor mapping includes multiple steps in technological process which may include: Hydrosweep DS sonar echo-sounding [START_REF] Lemenkova | Smart Seafloor Mapping in Real Time Regime Using Deep-Sea Multibeam Echosounder Hydrosweep DS[END_REF], CARIS HIPS data processing [START_REF] Gauger | The expedition ANTARKTIS-XXIII/4 of the Res. Vessel 'Polarstern' in 2006[END_REF], ArcGIS/ArcCatalog database management, GMT data processing [START_REF] Lemenkova | Data Capture for Seafloor Bathymetric Mapping Using Software Caris Hips, GMT and ArcGIS[END_REF]. Accurate digitizing cross-section profiles using ArcGIS is slower comparing to the developed GMT-based automated digitizing. This is important for accurate geomorphological data analysis and crucial for better understanding of the seafloor landforms. GMT-based mapping provides accurate visualization of the seafloor [START_REF] Gauger | The expedition ANTARKTIS-XXIII/4 of the Res. Vessel 'Polarstern' in 2006[END_REF] GMT-based mapping provides faster and preciser cartographic digitizing comparing to the traditional GIS. The traditional handmade (e.g. via QGIS) cartographic digitizing is a tedious monotonous slow-speed routine, might be prone to minor or major errors. Efforts in developing methodology in automatization in bathymetric mapping exists [START_REF] Schenke | Zur Frage der Meeresboden-Kartographie: Die Nutzung von AutoTrace Digitizer für die Vektorisierung der Bathymetrischen Daten in der Petschora-See[END_REF].

The GMT based ML methodology ( [START_REF] Wessel | The Generic Mapping Tools[END_REF], [START_REF] Wessel | The Generic Mapping Tools. Version 4.5.18 Technical Reference and Cookbook[END_REF]) enabled to make further steps in automatization of the cartographic techniques. This significantly improved the speed, precision and quality of the data modelling.

Conclusion

Precise, correct and up-to-date information about the geomorphology hadal trenches in the Pacific Ocean is necessary understanding marine geology, tectonics, seismicity, processes of sedimentation and geodynamic evolution of the seafloor [START_REF] Gohl | Tectonic and Sedimentary Processes of the West Antarctic Margin of the Amundsen Sea Embayment and Pine Island Bay[END_REF], [START_REF] Gohl | Crustal and Sedimentary Structures and Geodynamic Evolution of the West Antarctic Continental Margin and Pine Island Bay[END_REF], [START_REF] Kuhn | The response of quaternary climatic cycles in the South-East Pacific: development of the opal belt and dynamics behavior of the West Antarctic ice sheet[END_REF], [START_REF] Gohl | Deep crustal refraction and reflection seismics. Crustal and sedimentary structure and geodynamic evolution of the West Antarctic continental margin and Pine Island Bay[END_REF].

Submarine geomorphological and bathymetric mapping plays a critical role in analysis of the geological structures of the seafloor, marine benthic habitats, navigation, geological drilling, modelling marine environment and other aspects of geosciences.

Current studies contributed to the methodological testing and technical application of the advanced algorithms for seafloor modelling and mapping and to the geomorphological modelling.

Tested, presented and explained functionality of the several GMT modules enables to do automated digitizing of the orthogonal profiles crossing trenches in the perpendicular direction. Through this modelling, the shape of the landforms and steepness gradient of the trenches were visualized, compared and statistically analyzed.

Figure 1 :

 1 Figure 1: General bathymetric map of the seafloor of the Pacific Ocean, ETOPO1

Figure 2 :

 2 Figure 2: General geologic map of the seafloor of the Pacific Ocean

  Key points on the geologic and tectonic settings of the KKT:

Figure 3 :

 3 Figure3: Cross-section bathymetric profiles across the Kuril-Kamchatka Trench.[START_REF] Lemenkova | Topographic surface modelling using raster grid datasets by GMT: example of the Kuril-Kamchatka Trench, Pacific Ocean[END_REF]

Figure 4 :

 4 Figure 4: Cross-section bathymetric profiles across the Kuril-Kamchatka Trench, Octave

Figure 5 :

 5 Figure 5: Statistical analysis of the cross-section profiles of KKT, GMT

Figure 6 :

 6 Figure 6: Topographic map and location of the Aleutian Trench

Figure 7 :

 7 Figure 7: Cross-section bathymetric profiles across the Aleutian Trench

Figure 8 :

 8 Figure 8: Statistical analysis of the profiles, AT: GMT

Figure 10 :

 10 Figure 10: Geological settings in the region of the Middle America Trench Mid-Term PhD Thesis Presentation of Polina Lemenkova. College of Marine Geo-Sciences, Ocean University of China. Qingdao, 04/11/2019. 25

Figure 13 :

 13 Figure 13: Cross-section profiles of the Peru-Chile Trench

Figure 14 :

 14 Figure 14: Topographic settings of the Hikurangi Trench.

Figure 15 :Figure 16 :Figure 17 :

 151617 Figure 15: Modeled cross-section profiles of the Hikurangi Trench

Figure 18 :

 18 Figure18: Topographic map and location of the Kermadec and Tonga trenches.[START_REF] Lemenkova | GMT Based Comparative Analysis and Geomorphological Mapping of the Kermadec and Tonga Trenches, Southwest Pacific Ocean[END_REF]

Figure 19 :

 19 Figure19: Geologic settings of the Kermadec and Tonga trenches.[START_REF] Lemenkova | GMT Based Comparative Analysis and Geomorphological Mapping of the Kermadec and Tonga Trenches, Southwest Pacific Ocean[END_REF]

Figure 20 :

 20 Figure20: Cross-section profiles of the Tonga and Kermadec trenches.[START_REF] Lemenkova | GMT Based Comparative Analysis and Geomorphological Mapping of the Kermadec and Tonga Trenches, Southwest Pacific Ocean[END_REF]

Figure 21 :

 21 Figure21: Modeled gradient slopes of the profiles of the TT and KT.[START_REF] Lemenkova | GMT Based Comparative Analysis and Geomorphological Mapping of the Kermadec and Tonga Trenches, Southwest Pacific Ocean[END_REF]

Figure 22 :

 22 Figure 22: Topographic map and location of the Vanuatu (New Hebrides) and Vityaz trenches

Figure 23 :

 23 Figure 23: Modeled cross-sections of the Vanuatu (New Hebrides) and Vityaz trenches

Figure 24 :

 24 Figure 24: Geologic map and tectonic setting of the Vanuatu (New Hebrides) and Vityaz trenches

Figure 25 :

 25 Figure 25: Statistical analysis on the digitized cross-sections of the Vanuatu (New Hebrides) and Vityaz trenches Key points on the statistical analysis of the Vt and Vn trenches: Bathymetry of the Vt is shallower: depths <-6,100 m; Vn reaches -7,000 m Vt: 'bell-shape' with 2 peaks: -3,500 to -3,700 m, and -4,800 to -5,000 m Vt: the majority of values are within the range of -5,000 to -3,000 m. Vn: data distribution is even with slight increase of depths at -2,200 to -800 m (total 1,353 samples) Vt: 1605 samples (517, 653 and 435) at the first peak (-3,300 to -4,000) and 839 samples (238, 304, 297) at -4,500 to -5,200 m.

Figure 26 :

 26 Figure 26: Topographic map and location of the New Britain and San Cristobal trenches

  islands of eastern Papua New Guinea and the Solomon Islands are island arc terranes, surrounding New Britain Trench, are formed adjacent to the boundary between the Australia and Pacific plates Woodlark Basin subducts beneath the Solomon Islands arc region, forming a double-sided subduction zone [106]. Mid-Term PhD Thesis Presentation of Polina Lemenkova. College of Marine Geo-Sciences, Ocean University of China. Qingdao, 04/11/2019.

Figure 27 :

 27 Figure 27: Cross-section profiles of the New Britain and San Cristobal trenches

Figure 28 :

 28 Figure 28: Statistical analysis of the cross-section profiles of the NBT and SCT

Figure 29 :

 29 Figure 29: Map of the region of Philippine Trench. Mapping: QGIS.

Figure 30 :Figure 31 :

 3031 Figure 30: Letter-value plot (modified box plot) visualizing descriptive statistics of the topography of the cross-section profiles: mean, median, upper and lower quartiles of the data distribution. Plotting: Python, Matplotlib

Figure 32 :

 32 Figure 32: KDE plots for the 25 profiles crossing the Philippine Trench area. Plotting: Python libraries Matplotlib & Seaborn The Kernel Density Estimation (KDE) analysis shows combining five plots of the bathymetric cross-section profiles. It shows range of the density distribution in the elevations across the Philippine archipelago and Philippine Trench.

Figure 33 :

 33 Figure 33: Distribution of the samples from the cross-section profiles across tectonic plates. Plotting: Python, Matplotlib library and R (subplot in 'D' shows correlation sediment thickness vs slope angles across profiles)

  analysis is done by Graphs/Legacy Dialog menu box plots show the extreme values in the bathymetric and topographic elevations across the Philippine Trench and archipelago [53]. 25 box plots include: min, max, 1 st and 3 rd quartiles, median, error bars Pairwise comparative analysis of sample distribution by two plates Philippine Sea plate max samples (profiles 21, 22 and 23: 765, 681 and 652 samples), SW Philippines [53]. Sunda Plate has lesser samples: max for profile 25 (622). Philippine Trench variation of the data distribution for the geologic classes across 25 profiles qualitative analysis of the geological classes by the multi-plot visualization for comparative analysis graph shows mean values of the observation samples by separate variables (profiles 1:25) [53].

  the comparison between 2 segments of the trench (N and SE): S part of the trench has steeper slope gradient (oceanward) on the contrary, N part is steeper in the continental slope submarine terraces can be noted on the N segment of the trench at -2,000 m. generally, the modelling of the N part shows more steep degree of the oceanward slope. a gradually slanting terrace on the S part of the trench can be seen on the fragment 50-100 of the cross-section at -1,100 to -1,300 m. N part is shallower comparing to the S yet more steep slope on the Luzon Island side. the Trench: RT is 1400 km long, stretches along the SE edge of the Ryukyu Arc, between Taiwan & Kyushu [3]. located to NW of the Ryukyu Arc, a back-arc basin and depression of the Okinawa Trough formed as a result of the subduction of the oceanic crust of the PSP beneath the continental crust of the EP [20]. bathymetry varies in its N and S parts of RT: correlation bw. shape, gradient slope steepness, tectonics N: the subduction of the PSP is notable for shallow depths and steepness, reaches ca. 11 • . on the contrary, S: angle becomes steeper, reaching 70 • below ca. 70 km. the geology: double subduction system of the RT: PP subducts beneath the PSP, which is in turn subducts beneath the EP along the RT [24]. RT reaches depths of 7000 m b.s.l.; forearc slope between the island chain and the RT is 130-160 km wide. N group: Yaku-shima and Tanega-shima and 200 km long Tokara Channel gap between the island groups [84]. tectonics reflects evolutional processes of the building seamounts and the structure of the Earth's crust. variations in the lithological patters, geological conditions of the rocks formation, stratigraphy, sedimentary of the ocean seafloor formation during J, M and C Ryukyu Trench Key result points on the Ryukyu Trench: the median stacked profile on the S shows more gentle slope shape with submarine terraces there are no clear on northern part of the forearc slope At the same time the depth of the forearc slope increases in the N segment of the trench differences in the depth ranges along the Ryukyu Arc: max -5,500 to -5,700 m for N (334 samples). S: comparable values (329 samples) for the same depth range. significant differences for depths >6,000 m. S: has only few values (9 samples) with depths >6,800m while N shows 41, 59 and 23 records, with a max -7,460 m. Moderate to shallow depths with ranges -3,000 to -5,000 m for both N and S with values < 68 samples for N and 42 samples for S. The forearc basin deeper than 2,000 m and shallower than 1,000 m b.s.l.: more samples in the N than in the S. In contrast, a wide terrace with depths < 25 m is generally larger (161 s.) in S. Palau Trench The Islands of Palau located W to the PT, composed of volcanic rocks capped by coral reef limestone => Palau islands were located along the volcanic front. Key points on the Palau Trench: PT is located in the Philippine Sea, N from the Papua-New Guinea and E from the Philippines PT has greatest depth at 8,080 m (S), has straight geometric shape form PT stretches SW to NE, located within a square 133 • -136 • E and 6 • -8 • N, east from the Yap Islands.PT uniqueness: short distance (35 km) between the trench axis and the coast of the Palau Islands W[START_REF] Kobayashi | Why is the Palau Trench so Deep? Deep-Sea Trench without Plate Convergence[END_REF]

  the Trench: YT is located in the Philippine Sea, N from the Papua-New Guinea and E from the Philippines.

  Therefore, earthquakes are common in subduction zone of PSP, YT and PT. Mid-Term PhD Thesis Presentation of Polina Lemenkova. College of Marine Geo-Sciences, Ocean University of China. Qingdao, 04/11/2019.

Figure 34 :

 34 Figure34: Topographic map and location of the Mariana Trench.[START_REF] Lemenkova | K-means Clustering in R Libraries {cluster} and {factoextra} for Grouping Oceanographic Data[END_REF]

Figure 36 :

 36 Figure36: Mariana Trench crossing four tectonic plates.[START_REF] Lemenkova | Regression Models by Gretl and R Statistical Packages for Data Analysis in Marine Geology[END_REF]

Figure 37 :

 37 Figure 37: Digitizing cross-section profiles of the MT: QGIS

Figure 38 :

 38 Figure 38: 4 steps of the QGIS based digitizing of the trench profiles. [50]

Figure 39 :

 39 Figure 39: Cross-section profiles of the Mariana Trench Key points on QGIS methodology of manual digitizing: Manual digitizing of the 25 bathymetric profiles across the trench: length 1000 km, a distance gap of 100 km, 518 sample points in each. Coordinates converted to UTM; reading depths of the samples into csv table.Attribute table content: XY coordinates, Z (m), thematic data

Figure 40 :

 40 Figure 40: Normalized steepness slope calculation of the cross-section profiles: R library {ggplot},[START_REF] Team | R: a Language and Environment for Statistical Computing[END_REF].[START_REF] Lemenkova | R scripting libraries for comparative analysis of the correlation methods to identify factors affecting Mariana Trench formation[END_REF]

Figure 41 :Figure 42 :

 4142 Figure41: Boxplots of the cross-section profiles: R based statistical analysis.[START_REF] Lemenkova | R scripting libraries for comparative analysis of the correlation methods to identify factors affecting Mariana Trench formation[END_REF]

Figure 43 :

 43 Figure 43: Scatterplot matrices of the factors affecting Mariana Trench formation: R based statistical analysis,[START_REF] Team | R: a Language and Environment for Statistical Computing[END_REF].[START_REF] Lemenkova | Scatterplot Matrices of the Geomorphic Structure of the Mariana Trench at Four Tectonic Plates (Pacific, Philippine, Mariana and Caroline): a Geostatistical Analysis by R[END_REF]

Figure 44 :Figure 45 :

 4445 Figure 44: R based dendrogram tree of the 25 profiles. Left: unsorted, right: sorted. [61]

Figure 46 :

 46 Figure46: Ranking dot plots by data grouping: R based statistical analysis, libraries {ggalt} and {ggplot}.[START_REF] Lemenkova | An Empirical Study of R Applications for Data Analysis in Marine Geology[END_REF]

  the upper two rows of the plot show (subplots A, B, C, D) data distribution across tectonic plates: A) Pacific Plate; B) Philippine Plate; C) Mariana Plate; D) Caroline Plate; E) Cumulative sediment thickness; F) Slope angle degree by profiles the lower row of the plot (subplots E, F) shows data distribution for the cumulative sediment thickness and slope angle degree by profiles.

Figure 48 :

 48 Figure48: R based ridgeline plots by tectonic plates and bathymetric profiles, library {ggplot}.[START_REF] Lemenkova | Scatterplot Matrices of the Geomorphic Structure of the Mariana Trench at Four Tectonic Plates (Pacific, Philippine, Mariana and Caroline): a Geostatistical Analysis by R[END_REF]

Figure 49 :

 49 Figure 49: R based analysis of the submarine geomorphology if the Mariana Trench (steepness angles): unsorted (left); sorted and grouped (right), libraries {tidyverse} and {ggsignif}. [50]

Figure 50 :

 50 Figure 50: Partial regression analysis for the slope gradient in profiles by tectonic plates. Python library {StatsModels}

Figure 51 :

 51 Figure 51: Data distribution analysis: ranges of the maximal depths. Python library {Matplotlib} The deepest part is in SW and C segments where trench crosses PSP and PP. Moderate depths correlate with MP and the majority of the PSP. The depths ranges higher in the S part than in N. Central part has variations in depth. General trend: increased depths to S Comparing the profiles Nr. 3, 4, 9, 12 (green) to profiles Nr. 18, 16, 15, 13 (orange) => depths increase up to max in the Nr. 20, 21, 19, 14, blue group). Max depths: Nr. 20, 21, 19, 14, min depths: Nr. 24, 23, 22, 10. Profile depth ranged from -10.600m to -3150m

  IBT a.k.a. Izu-Ogasawara Trench is located in west Pacific Ocean, lies south of Japan Key points on the Izu-Bonin Trench (IBT):

  points on the cross-sectioned profiles visualized at two JT segments: rugged geomorphic structure of the median profiles and increased altitude in S-N direction on the N part N more steep slope on the continental slope part beneath the frontal wedge of the North American tectonic plate.

  geological settings and seismicity of the area impact the trench roughness and general geomorphic shape W part of the trench profiles (Honshu Island slope) has steeper slopes comparing to the oceanward slopes for both segments are both theoretical and practical innovations of the presented research. The theoretical novelty lies in the comparative geomorphological mapping of the 20 Pacific hadal trenches that does not exists in the available literature. The practical novelty consists in the developed methodology of the sequential technological chain of processes: GMT, QGIS plugins, Python[START_REF] Rossum | Python Tutorial Release 3[END_REF], Matlab/Octave, AWK and R. Cartographic novelty consists in the developed and presented algorithm of the cross-section profiles digitizing and geomorphic modelling of the hadal trench modelling through the 'grdtrack' (main) GMT module. Hadal trench present a complex system with highly interconnected factors affecting geomorphological structure, formation and development of the trench: slabs and tectonics plates, bathymetry, geographic location, geologic structure of the underlying basement and sediment thickness.

Table 1 :

 1 Data sources, types and precision

	No Data	Origine	Type
	1 ETOPO1	NOAA	1 arc-min GRM grid [2]
	2 ETOPO5	NOAA	5 arc-min GRM grid
	3 GEBCO	BODC	15-sec DEM raster grid
	4 SRTM	NASA	15-sec DEM raster grid [7]
	5 Geology	USGS	Vector layers
	6 Gravity	Scripps IO	CryoSat-2, Jason-1 grid [86]
	7 EGM96	Scripps IO	Geopotential geoid model
	8 ASCII	Scripps IO	Topo tables (xyz format)
	9 GEBCO	IHO-IOC	Geographic gazetteer [38]

Kuril-Kamchatka Trench Kuril-Kamchatka Trench (KKT): depths > 5000 m KKT is located on the border of the Sea of Okhotsk, Far East, NW Pacific KKT continues south-eastwards from the coast of the Kamchatka Peninsula, in parallel to the Kuril Island chain until Hokkaido Island.

  The study area is 94• W-87 • W, 11,5 • N-15 • N

	MA PC H MA PC H MA PC H MA PC H	Ps Ps Ps Ps	K K K K	T T T T	Vn Vt Vn Vt Vn Vt Vn Vt	NB SC Ph Mn R NB SC Ph Mn R NB SC Ph Mn R NB SC Ph Mn R	Pl Pl Pl Pl	Y Y Y Y	MT IB MT IB MT IB MT IB	JT JT JT JT	Con End Bib Con End Bib Con End Bib Con End Bib
	Middle America Trench Middle America Trench Peru-Chile Trench Peru-Chile Trench
	Key points on the topography of Study sample area is a southern part of MAT: Guatemala Trench the Peru-Chile Trench (PCT): Key points on the geology of the Peru-Chile Trench (PCT):
	PCT a.k.a. Atacama Trench, PCT is formed by the subduction of the Nazca and Antarctic plates beneath the the longest Pacific trench South American Plate [9]. (5900 km) specific geologic, geotectonic, geomorphic and climatic characteristics generated PCT stretches from Ecuador between the Chilean-Peru Trench and the Chilean coasts to Chile 6 • S, 81 • 50W to PCT is exposed to a wide variety of hazards: earthquakes, local tsunamis, 39 • S, 75 • W. volcanism, continent-specific hazards (floods, landslides, mass movements) In total length, PCT covers area of ca. 590,000 km 2 . giant earthquakes: Valdivia (Mw=9.5), 1960, Maule (Mw=8.8), 2010.
	The PCT is shallower
	comparing to other Pacific
	trenches (64 km width).

Figure 11: Cross-section profiles of the Middle America Trench Mid-Term PhD Thesis Presentation of Polina Lemenkova. College of Marine Geo-Sciences, Ocean University of China. Qingdao, 04/11/2019.

Figure 12: Statistical analysis of the Middle America Trench Mid-Term PhD Thesis Presentation of Polina Lemenkova. College of Marine Geo-Sciences, Ocean University of China. Qingdao, 04/11/2019.

  • S-32 • S and the sedimentary province extending 33 • S-57 • S [35].

	MA PC H	Ps	K	T	Vn Vt	NB SC Ph Mn R	Pl	Y	MT IB	JT	Con End Bib
	Peru-Chile Trench
	Key points on the sedimentation of the Peru-Chile Trench (PCT):

  NBT is shallower comparing to the SCT : it has median values not exceeding -7,000m (vs -8,000 m median value for the SCT). SCT has 33 • slope oceanwards while 33,69 • landwards increasing in relief more direct on the oceanward side.NBT has more asymmetrical U-shaped cross-section dipping westwards with 35 • eastward slope, and 41 • westward slope

	MA PC H	Ps	K	T	Vn Vt	NB SC Ph Mn R	Pl	Y	MT IB	JT	Con End Bib
	New Britain Trench
	Key points on the New Britain Trench:

  Parece Vela Basin, located in the E side of the PSP).

	MA PC H	Ps	K	T	Vn Vt	NB SC Ph Mn R	Pl	Y	MT IB	JT	Con End Bib
	Yap Trench
	Key points on plate tectonics of the Yap and Palau trenches:
	PT and YT form a typical trench-arc-basin system which includes:
	deep trench,
	island arcs,
	back-arc basin (a

Mid-Term PhD Thesis Presentation of Polina Lemenkova. College of Marine Geo-Sciences, Ocean University of China. Qingdao, 04/11/2019.

(SOA), Marine Scholarship of China, People's Republic of China (P. R. C.), Beijing, Grant #2016SOA002, 2016-2020.