The Experts below are selected from a list of 116442 Experts worldwide ranked by ideXlab platform
Roland Masson - One of the best experts on this subject based on the ideXlab platform.
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Mathematical and numerical analysis of a stratigraphic model
ESAIM: Mathematical Modelling and Numerical Analysis, 2004Co-Authors: Véronique Gervais, Roland MassonAbstract:In this paper, we consider a multi-Lithology diffusion model used in stratigraphic modelling to simulate large scale transport processes of sediments described as a mixture of L lithologies. This model is a simplified one for which the surficial fluxes are proportional to the slope of the topography and to a Lithology fraction with unitary diffusion coefficients. The main unknowns of the system are the sediment thickness h , the L surface concentrations in Lithology i of the sediments at the top of the basin, and the L concentrations c i in Lithology i of the sediments inside the basin. For this simplified model, the sediment thickness decouples from the other unknowns and satisfies a linear parabolic equation. The remaining equations account for the mass conservation of the lithologies, and couple, for each Lithology, a first order linear equation for with a linear advection equation for c i for which appears as an input boundary condition. For this coupled system, a weak formulation is introduced which is shown to have a unique solution. An implicit finite volume scheme is derived for which we show stability estimates and the convergence to the weak solution of the problem.
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Existence and Uniqueness of a Weak Solution to a Stratigraphic Model
Numerical Mathematics and Advanced Applications, 2004Co-Authors: Robert Eymard, Thierry Gallouët, Véronique Gervais, Roland MassonAbstract:In this paper, we study a multi-Lithology diffusion model used to simulate the evolution through time of a sedimentary basin composed of several lithologies such as sand or shale. It is a simplified model for which the surficial flux in Lithology i is taken proportional to the slope and to a Lithology fraction c i s in Lithology i at the top of the basin with a unitary diffusion coefficient. Thus, the sediment thickness variable satisfies a linear parabolic problem and decouples from the other unknowns. The remaining equations couple, for each Lithology, a first order linear equation for the surface concentration c i s with a linear advection equation for the basin concentration, for which c i s appears as an input boundary condition at the top of the basin in case of sedimentation. The existence and uniqueness of a weak solution in L ∞ is proved for this problem.
Niu Rui-qing - One of the best experts on this subject based on the ideXlab platform.
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Spatial Distribution Rule Mining of Lithology in Three Gorges
Computer Science, 2009Co-Authors: Niu Rui-qingAbstract:In the south area of china,there covers thick soil and flourish vegetation on the top of the rocks,so there is little research on Lithology analysis by remote sensing in the south area,and there is also no mature methods on this aspect.Three Gorges is the south area which is thickly covered by vegetation and the Lithology analysis is very difficult.Three Gorges possesses the characters of complicated terrain,frequent geologic disasters and full-grown vegetation and soil.We mined the spatial distribution rules of Lithology aiming at the area of Three Gorges.We piled the remote sensing image with the geological graph,chose the pixel points on the edges of various stratums,analyzed the Lithology in the adjacent 9 directions and based on the algorithm of concept grid mined the adjacent rules and spatial distribution rules of the Lithology in the stratums of Jia Second Section Jia Ling River Group T1j2,Jia Third Section Jia Ling River Group T1j3,Ba First Section Ba Dong Group T2b1,Ba Second Section Ba Dong Group T2b2 and Da Ye Group T1d.
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Association rule mining of Lithology and vegetation in Three Gorges
Computer Engineering and Applications, 2008Co-Authors: Niu Rui-qingAbstract:Three Gorges is the south area in which there covers thick soil and flourish vegetation on the top of the rocks,and the Lithology analysis is very difficult.There are also no mature methods on this aspect.The key of Lithology analysis in Three Gorges lies in analyzing the relation between the vegetation on the surface layer and the Lithology and searching for the method which can eliminate the influence of the vegetation and directly extract the Lithology information.In the paper we mined the association rules of the vegetation and Lithology aiming at the area of Three Gorges.The authors pile the remote sensing image with the geological graph,compute the vegetation index image NDVI,choose the points in each stratum,analyze the relation between the NDVI value and the Lithology in each point and based on the algorithm of concept grid mine the association rules of vegetation and Lithology in the stratums of T1j2,T1j3,T2b1,T2b2 and T1d in Three Gorges.
Lei Jiang - One of the best experts on this subject based on the ideXlab platform.
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Lithology mapping of a mixed siliciclastic carbonate evaporite system using 3d seismic and well data lower triassic jialingjiang formation sichuan basin southwestern china
Marine and Petroleum Geology, 2018Co-Authors: Wenzhi Zhao, Hongliu Zeng, Wei Liu, Shuyuan Shi, Lu Wang, Lei JiangAbstract:Abstract High-quality three-dimensional (3D) seismic data acquired in the central Sichuan Basin, southwestern China, offer an opportunity to map complex lithologies in a mixed siliciclastic–carbonate–evaporite system in the Lower Triassic Jialingjiang (T1j) Formation. The formation consists of siliciclastics, limestone, dolostone, anhydrite, and salt. The lithologies consist several source-reservoir-cap assemblages in the area. Lithologies in the T1j Formation change rapidly in the vertical direction, forming different interbed patterns in thin layers. In the mean time, the lateral extend of each Lithology is complex. This vertical and lateral distribution makes it difficult to predict Lithology by single seismic attribute. Therefore, principle component analysis (PCA) was applied to tens of seismic attributes to extract useful information. The first three components contain most (83.02–99.85%) of the Lithology information preserved in seismic attributes, which were used to correlate with Lithology content calculated by core-calibrated wireline logs. Correlation coefficients of the three seismic components with lithologies are significantly higher (0.37–0.79) than those of individual seismic attributes (near zero to 0.58). Different assemblies of end-member lithologies were selected from anhydrite, siliciclastics, tight dolostone, limestone, and salt to perform PCA in different sequences. Lithologic content distribution of individual end members was shown by color-blending method to map the Lithology mixture. Sedimentary history in the T1j Formation was reconstructed based on Lithology-mixture maps and regional geology background in the study area. Eight 4th-order sequences were interpreted in the T1j Formation. Only the second sequence was influenced by siliciclastic input, forming a complete mixed siliciclastic–carbonate–evaporite system. Open platform and/or restricted evaporative environment dominated the other seven sequences, forming a mixed carbonate–evaporite system.
Wouters Sébastien - One of the best experts on this subject based on the ideXlab platform.
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StratigrapheR: making and using lithologs in R
2020Co-Authors: Devleeschouwer Xavier, Da Silva Anne-christine, Boulvain Frédéric, Wouters SébastienAbstract:StratigrapheR is an open-source integrated stratigraphy package. It is available in the free software environment R (https://CRAN.R-project.org/package=StratigrapheR) and is designed to generate lithologs in a semi-automated way, to process stratigraphical information, and to visualize any plot along the lithologs in the R environment. The basic graphical principle behind StratigrapheR is the incremental addition of elements to a drawing: a plot is opened, and graphical elements are successively added. This allows compartmentalisation of the drawing process, as well as the superposition of different plots for comparison. For instance a litholog of a single section can be written as a single function including all the drawing sub-functions, and be integrated in a larger plot, for instance to be correlated to other sections or to show proxy data. The StratigrapheR package is designed for efficient work, and minimum coding, while still allowing versatility. The lithological information of beds (upper and lower boundary, hardness, Lithology, etc.) is converted into polygons. All polygons are drawn together using a single function, and each polygon can have its personalised symbology allowing to distinguish lithologies. A similar workflow can be used for plotting proxies while distinguishing each sample by their Lithology. Vector graphics can be imported as SVG files, and precisely drawn with the lithologs to serve as symbols or complex elements. Every type of symbol is plotted by calling one single function which repeats the drawing for each occurrence of the represented feature. This illustrates that the amount of work invested to make lithologs using StratigrapheR is related to their complexity rather than their length: a long but monotonous litholog (e.g. of marl-limestone alternations) only takes a few lines of code to generate. The StratigrapheR package also provides a set of functions to deal with selected stratigraphic intervals (for instance in the [0,1[ form): they allow simplification, merging, inversion and visualisation of intervals, as well as identifying the samples included in the given intervals, and characterising the relation of the intervals with each other (overlap, neighbouring, etc.). StratigrapheR includes PDF and SVG generation of plots, of any dimension. The generated PDF can even store multiple plots in a single file (each plot on a different page) to document data processing comprehensively
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StratigrapheR: making and using lithologs in R
2020Co-Authors: Devleeschouwer Xavier, Da Silva Anne-christine, Boulvain Frédéric, Wouters SébastienAbstract:audience: researcherStratigrapheR is an open-source integrated stratigraphy package. It is available in the free software environment R (https://CRAN.R-project.org/package=StratigrapheR) and is designed to generate lithologs in a semi-automated way, to process stratigraphical information, and to visualize any plot along the lithologs in the R environment. The basic graphical principle behind StratigrapheR is the incremental addition of elements to a drawing: a plot is opened, and graphical elements are successively added. This allows compartmentalisation of the drawing process, as well as the superposition of different plots for comparison. For instance a litholog of a single section can be written as a single function including all the drawing sub-functions, and be integrated in a larger plot, for instance to be correlated to other sections or to show proxy data. The StratigrapheR package is designed for efficient work, and minimum coding, while still allowing versatility. The lithological information of beds (upper and lower boundary, hardness, Lithology, etc.) is converted into polygons. All polygons are drawn together using a single function, and each polygon can have its personalised symbology allowing to distinguish lithologies. A similar workflow can be used for plotting proxies while distinguishing each sample by their Lithology. Vector graphics can be imported as SVG files, and precisely drawn with the lithologs to serve as symbols or complex elements. Every type of symbol is plotted by calling one single function which repeats the drawing for each occurrence of the represented feature. This illustrates that the amount of work invested to make lithologs using StratigrapheR is related to their complexity rather than their length: a long but monotonous litholog (e.g. of marl-limestone alternations) only takes a few lines of code to generate. The StratigrapheR package also provides a set of functions to deal with selected stratigraphic intervals (for instance in the [0,1[ form): they allow simplification, merging, inversion and visualisation of intervals, as well as identifying the samples included in the given intervals, and characterising the relation of the intervals with each other (overlap, neighbouring, etc.). StratigrapheR includes PDF and SVG generation of plots, of any dimension. The generated PDF can even store multiple plots in a single file (each plot on a different page) to document data processing comprehensively
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StratigrapheR: an R package for integrated stratigraphy
2019Co-Authors: Wouters Sébastien, Boulvain Frédéric, Da Silva Anne-christine, Devleeschouwer XavierAbstract:StratigrapheR is an open-source integrated stratigraphy package. It is available in the free software environment R (https://CRAN.R-project.org/package=StratigrapheR) and is designed to manage the large amount of data needed to perform cyclostratigraphy. As this discipline can be carried out by visual analysis on lithological observations and by time-series analyses, StratigrapheR endeavours to link the two by allowing the semi-automated generation of lithologs, the processing of stratigraphical information, and the visualisation of any plot along the lithologs in the R environment. The basic graphical principle behind StratigrapheR is the incremental addition of elements to a drawing: a plot is opened, and graphical elements are successively added. This allows compartmentalisation of the drawing process, as well as the superposition of different plots for comparison. For instance a litholog of a single section can be written as a single function including all the drawing sub-functions, and be integrated in a larger plot, for instance to be correlated to other sections or to show proxy data. The StratigrapheR package is designed for efficient work, and minimum coding, while still allowing versatility. The lithological information of beds (upper and lower boundary, hardness, Lithology, etc.) is converted into polygons. All polygons are drawn together using a single function, and each polygon can have its personalised symbology allowing to distinguish lithologies. A similar workflow can be used for plotting proxies while distinguishing each sample by their Lithology. Vector graphics can be imported as SVG files, and precisely drawn with the lithologs to serve as symbols or complex elements. Every type of symbol is plotted by calling one single function which repeats the drawing for each occurrence of the represented feature. This illustrates that the amount of work invested to make lithologs using StratigrapheR is related to their complexity rather than their length: a long but monotonous litholog (e.g. of marl-limestone alternations) only takes a few lines of code to generate. The StratigrapheR package also allows basic visualisation and processing of oriented data used for magnetostratigraphy: efficient functions are provided for stereographic projections, Zijderveld plots, conversion between data conventions and reorientation (sample correction, bedding correction, rotation). It also provides a set of functions to deal with selected stratigraphic intervals (for instance in the [0,1[ form): they allow simplification, merging, inversion and visualisation of intervals, as well as identifying the samples included in the given intervals, and characterising the relation of the intervals with each other (overlap, neighbouring, etc.). StratigrapheR includes PDF and SVG generation of plots, of any dimension. The generated PDF can even store multiple plots in a single file (each plot on a different page) to document data processing comprehensively
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StratigrapheR: an R package for integrated stratigraphy
2019Co-Authors: Wouters Sébastien, Boulvain Frédéric, Da Silva Anne-christine, Devleeschouwer XavierAbstract:StratigrapheR is an open-source integrated stratigraphy package. It is available in the free software environment R (https://CRAN.R-project.org/package=StratigrapheR) and is designed to manage the large amount of data needed to perform cyclostratigraphy. As this discipline can be carried out by visual analysis on lithological observations and by time-series analyses, StratigrapheR endeavours to link the two by allowing the semi-automated generation of lithologs, the processing of stratigraphical information, and the visualisation of any plot along the lithologs in the R environment. The basic graphical principle behind StratigrapheR is the incremental addition of elements to a drawing: a plot is opened, and graphical elements are successively added. This allows compartmentalisation of the drawing process, as well as the superposition of different plots for comparison. For instance a litholog of a single section can be written as a single function including all the drawing sub-functions, and be integrated in a larger plot, for instance to be correlated to other sections or to show proxy data. The StratigrapheR package is designed for efficient work, and minimum coding, while still allowing versatility. The lithological information of beds (upper and lower boundary, hardness, Lithology, etc.) is converted into polygons. All polygons are drawn together using a single function, and each polygon can have its personalised symbology allowing to distinguish lithologies. A similar workflow can be used for plotting proxies while distinguishing each sample by their Lithology. Vector graphics can be imported as SVG files, and precisely drawn with the lithologs to serve as symbols or complex elements. Every type of symbol is plotted by calling one single function which repeats the drawing for each occurrence of the represented feature. This illustrates that the amount of work invested to make lithologs using StratigrapheR is related to their complexity rather than their length: a long but monotonous litholog (e.g. of marl-limestone alternations) only takes a few lines of code to generate. The StratigrapheR package also allows basic visualisation and processing of oriented data used for magnetostratigraphy: efficient functions are provided for stereographic projections, Zijderveld plots, conversion between data conventions and reorientation (sample correction, bedding correction, rotation). It also provides a set of functions to deal with selected stratigraphic intervals (for instance in the [0,1[ form): they allow simplification, merging, inversion and visualisation of intervals, as well as identifying the samples included in the given intervals, and characterising the relation of the intervals with each other (overlap, neighbouring, etc.). StratigrapheR includes PDF and SVG generation of plots, of any dimension. The generated PDF can even store multiple plots in a single file (each plot on a different page) to document data processing comprehensively.Assessment of the reproducibility of cyclostratigraphy during the Hauterivia
Devleeschouwer Xavier - One of the best experts on this subject based on the ideXlab platform.
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StratigrapheR: making and using lithologs in R
2020Co-Authors: Devleeschouwer Xavier, Da Silva Anne-christine, Boulvain Frédéric, Wouters SébastienAbstract:StratigrapheR is an open-source integrated stratigraphy package. It is available in the free software environment R (https://CRAN.R-project.org/package=StratigrapheR) and is designed to generate lithologs in a semi-automated way, to process stratigraphical information, and to visualize any plot along the lithologs in the R environment. The basic graphical principle behind StratigrapheR is the incremental addition of elements to a drawing: a plot is opened, and graphical elements are successively added. This allows compartmentalisation of the drawing process, as well as the superposition of different plots for comparison. For instance a litholog of a single section can be written as a single function including all the drawing sub-functions, and be integrated in a larger plot, for instance to be correlated to other sections or to show proxy data. The StratigrapheR package is designed for efficient work, and minimum coding, while still allowing versatility. The lithological information of beds (upper and lower boundary, hardness, Lithology, etc.) is converted into polygons. All polygons are drawn together using a single function, and each polygon can have its personalised symbology allowing to distinguish lithologies. A similar workflow can be used for plotting proxies while distinguishing each sample by their Lithology. Vector graphics can be imported as SVG files, and precisely drawn with the lithologs to serve as symbols or complex elements. Every type of symbol is plotted by calling one single function which repeats the drawing for each occurrence of the represented feature. This illustrates that the amount of work invested to make lithologs using StratigrapheR is related to their complexity rather than their length: a long but monotonous litholog (e.g. of marl-limestone alternations) only takes a few lines of code to generate. The StratigrapheR package also provides a set of functions to deal with selected stratigraphic intervals (for instance in the [0,1[ form): they allow simplification, merging, inversion and visualisation of intervals, as well as identifying the samples included in the given intervals, and characterising the relation of the intervals with each other (overlap, neighbouring, etc.). StratigrapheR includes PDF and SVG generation of plots, of any dimension. The generated PDF can even store multiple plots in a single file (each plot on a different page) to document data processing comprehensively
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StratigrapheR: making and using lithologs in R
2020Co-Authors: Devleeschouwer Xavier, Da Silva Anne-christine, Boulvain Frédéric, Wouters SébastienAbstract:audience: researcherStratigrapheR is an open-source integrated stratigraphy package. It is available in the free software environment R (https://CRAN.R-project.org/package=StratigrapheR) and is designed to generate lithologs in a semi-automated way, to process stratigraphical information, and to visualize any plot along the lithologs in the R environment. The basic graphical principle behind StratigrapheR is the incremental addition of elements to a drawing: a plot is opened, and graphical elements are successively added. This allows compartmentalisation of the drawing process, as well as the superposition of different plots for comparison. For instance a litholog of a single section can be written as a single function including all the drawing sub-functions, and be integrated in a larger plot, for instance to be correlated to other sections or to show proxy data. The StratigrapheR package is designed for efficient work, and minimum coding, while still allowing versatility. The lithological information of beds (upper and lower boundary, hardness, Lithology, etc.) is converted into polygons. All polygons are drawn together using a single function, and each polygon can have its personalised symbology allowing to distinguish lithologies. A similar workflow can be used for plotting proxies while distinguishing each sample by their Lithology. Vector graphics can be imported as SVG files, and precisely drawn with the lithologs to serve as symbols or complex elements. Every type of symbol is plotted by calling one single function which repeats the drawing for each occurrence of the represented feature. This illustrates that the amount of work invested to make lithologs using StratigrapheR is related to their complexity rather than their length: a long but monotonous litholog (e.g. of marl-limestone alternations) only takes a few lines of code to generate. The StratigrapheR package also provides a set of functions to deal with selected stratigraphic intervals (for instance in the [0,1[ form): they allow simplification, merging, inversion and visualisation of intervals, as well as identifying the samples included in the given intervals, and characterising the relation of the intervals with each other (overlap, neighbouring, etc.). StratigrapheR includes PDF and SVG generation of plots, of any dimension. The generated PDF can even store multiple plots in a single file (each plot on a different page) to document data processing comprehensively
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StratigrapheR: an R package for integrated stratigraphy
2019Co-Authors: Wouters Sébastien, Boulvain Frédéric, Da Silva Anne-christine, Devleeschouwer XavierAbstract:StratigrapheR is an open-source integrated stratigraphy package. It is available in the free software environment R (https://CRAN.R-project.org/package=StratigrapheR) and is designed to manage the large amount of data needed to perform cyclostratigraphy. As this discipline can be carried out by visual analysis on lithological observations and by time-series analyses, StratigrapheR endeavours to link the two by allowing the semi-automated generation of lithologs, the processing of stratigraphical information, and the visualisation of any plot along the lithologs in the R environment. The basic graphical principle behind StratigrapheR is the incremental addition of elements to a drawing: a plot is opened, and graphical elements are successively added. This allows compartmentalisation of the drawing process, as well as the superposition of different plots for comparison. For instance a litholog of a single section can be written as a single function including all the drawing sub-functions, and be integrated in a larger plot, for instance to be correlated to other sections or to show proxy data. The StratigrapheR package is designed for efficient work, and minimum coding, while still allowing versatility. The lithological information of beds (upper and lower boundary, hardness, Lithology, etc.) is converted into polygons. All polygons are drawn together using a single function, and each polygon can have its personalised symbology allowing to distinguish lithologies. A similar workflow can be used for plotting proxies while distinguishing each sample by their Lithology. Vector graphics can be imported as SVG files, and precisely drawn with the lithologs to serve as symbols or complex elements. Every type of symbol is plotted by calling one single function which repeats the drawing for each occurrence of the represented feature. This illustrates that the amount of work invested to make lithologs using StratigrapheR is related to their complexity rather than their length: a long but monotonous litholog (e.g. of marl-limestone alternations) only takes a few lines of code to generate. The StratigrapheR package also allows basic visualisation and processing of oriented data used for magnetostratigraphy: efficient functions are provided for stereographic projections, Zijderveld plots, conversion between data conventions and reorientation (sample correction, bedding correction, rotation). It also provides a set of functions to deal with selected stratigraphic intervals (for instance in the [0,1[ form): they allow simplification, merging, inversion and visualisation of intervals, as well as identifying the samples included in the given intervals, and characterising the relation of the intervals with each other (overlap, neighbouring, etc.). StratigrapheR includes PDF and SVG generation of plots, of any dimension. The generated PDF can even store multiple plots in a single file (each plot on a different page) to document data processing comprehensively
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StratigrapheR: an R package for integrated stratigraphy
2019Co-Authors: Wouters Sébastien, Boulvain Frédéric, Da Silva Anne-christine, Devleeschouwer XavierAbstract:StratigrapheR is an open-source integrated stratigraphy package. It is available in the free software environment R (https://CRAN.R-project.org/package=StratigrapheR) and is designed to manage the large amount of data needed to perform cyclostratigraphy. As this discipline can be carried out by visual analysis on lithological observations and by time-series analyses, StratigrapheR endeavours to link the two by allowing the semi-automated generation of lithologs, the processing of stratigraphical information, and the visualisation of any plot along the lithologs in the R environment. The basic graphical principle behind StratigrapheR is the incremental addition of elements to a drawing: a plot is opened, and graphical elements are successively added. This allows compartmentalisation of the drawing process, as well as the superposition of different plots for comparison. For instance a litholog of a single section can be written as a single function including all the drawing sub-functions, and be integrated in a larger plot, for instance to be correlated to other sections or to show proxy data. The StratigrapheR package is designed for efficient work, and minimum coding, while still allowing versatility. The lithological information of beds (upper and lower boundary, hardness, Lithology, etc.) is converted into polygons. All polygons are drawn together using a single function, and each polygon can have its personalised symbology allowing to distinguish lithologies. A similar workflow can be used for plotting proxies while distinguishing each sample by their Lithology. Vector graphics can be imported as SVG files, and precisely drawn with the lithologs to serve as symbols or complex elements. Every type of symbol is plotted by calling one single function which repeats the drawing for each occurrence of the represented feature. This illustrates that the amount of work invested to make lithologs using StratigrapheR is related to their complexity rather than their length: a long but monotonous litholog (e.g. of marl-limestone alternations) only takes a few lines of code to generate. The StratigrapheR package also allows basic visualisation and processing of oriented data used for magnetostratigraphy: efficient functions are provided for stereographic projections, Zijderveld plots, conversion between data conventions and reorientation (sample correction, bedding correction, rotation). It also provides a set of functions to deal with selected stratigraphic intervals (for instance in the [0,1[ form): they allow simplification, merging, inversion and visualisation of intervals, as well as identifying the samples included in the given intervals, and characterising the relation of the intervals with each other (overlap, neighbouring, etc.). StratigrapheR includes PDF and SVG generation of plots, of any dimension. The generated PDF can even store multiple plots in a single file (each plot on a different page) to document data processing comprehensively.Assessment of the reproducibility of cyclostratigraphy during the Hauterivia
