Courses

The short courses that have been confirmed are as follows:

Young Scientist Course

In the scope of IAMG2017, there will be a course specifically targeting the early career researchers and postgraduate students. The course aims at contributing to the early career researchers’ professional career. The courses that will be available are as follows:

  • How to write and publish effective papers
Introduction to compositional data analysis by Prof Vera Pawlowsky-Glahn and Prof Juan José Egozcue

Compositional data are vectors showing the relative importance of the parts of a whole. Typical examples are data in percentages, ppm, ppb, molar composition, or the like, common in many fields of science, particularly in the geosciences. The classical statistical analysis of this data type suffers from many problems, including spurious correlation. As a solution to these problems, J. Aitchison introduced the log-ratio approach in the eighties. Since then, progress has been made in understanding the geometry of the sample space, the D part simplex. This course provides an introduction to the theory and practice of statistical analysis of compositional data aspects, as well as a forum for informal discussion on more advanced topics. It also provides an introduction to available software, which includes Codapack and some packages in R. Codapack is freeware (http://imae.udg.edu/codapack/) specifically developed for the statistical analysis of compositional data. It is an easy to use tool for elementary exploratory analysis and is used in most course activities. For the treatment of zeros the R package zCompositions is used, and for some more demanding statistical techniques, other R packages (compositions, robCompositions) are introduced. 

Course Outline:

  1. Hypothesis underlying any statistical analysis (sample space, scale operations).
  2. The Aitchison geometry of the simplex.
  3. Representation in coordinates; distributions in the simplex.
  4. Exploratory analysis (centre, variation matrix, biplot, dendrogram, balances).
  5. Irregular data: zeroes, outliers, missing data.
  6. Random compositions. Normal distribution in the simplex.
  7. Methods of multivariate analysis with compositional data: regression, MANOVA, discriminant analysis and cluster analysis.
  8. Compositional processes.

Course Schedule:

  • Morning: Lectures
  • Afternoon: Practicals using participants own data

Course dates: Monday 28 August – Friday 1 September 2017 (5 days)
Venue: TBA
Participants: Minimum 8, Maximum 20

Course Instructors:

Juan José EgozcueJuan José Egozcue studied Physics, oriented to Geophysics and Meteorology, at the University of Barcelona (Spain). He obtained his PhD in the same university with a dissertation on maximum entropy spectral analysis (1982). He taught several topics of Applied Mathematics and Probability and Statistics at the Civil Engineering School in the Universidad Politécnica de Cataluña (UPC, Barcelona, Spain). He became Full Professor in 1989, at the UPC, and he retired on February 1st 2016. He is now Emeritus professor of UPC.  His research activities are presently centered in two lines: estimation of natural hazards using Bayesian methods, and statistical analysis of compositional data, with special emphasis in the geometry of the sample space, the simplex.  He has been leader of several research projects. Most of them on hazard and vulnerability of coastal and port structuresunder action of severe ocean-waves. At present, he participates actively in a project on compositional data analysis. Research contributions have been published in many journal articles and most important results are summarized in the book “Modeling and Analysis of Compositional Data” (Wiley 2015), co-authored by V. Pawlowsky-Glahn and R. Tolosana-Delgado.

Prof Vera Pawlowsky-Glahn 200x230Dr. Pawlowsky-Glahn is professor at the University of Girona, Department of Computer Science, Applied Mathematics, and Statistics. She studied Mathematics at the University of Barcelona, Spain, and obtained her PhD (doctor rerum naturam) from the Free University of Berlin, Germany. Before going to Girona, she was professor in the School of Civil Engineering at the Technical University of Catalonia (UPC) in Barcelona. Her main research topic since 1982 has been the statistical analysis of compositional data. The results obtained over the years have been published in multiple articles, proceedings and books. Together with A. Buccianti she has acted as editor of a book in honour of J. Aitchison in 2011 published by Wiley, who has also published in 2015 a textbook on modelling and analysis of compositional data, co-authored with J.J. Egozcue and R. Tolosana-Delgado. Until 2008, she was the leader of a research group on this topic involving professors from different Spanish universities. The group organises every two years a workshop on compositional data analysis, known as CoDaWork, and their research has received regularly financial support from the Spanish Ministry for Education and Science and from the University Department of the Catalan Government. Prof. Dr. Pawlowsky-Glahn has been vice-chancellor at UPC from 1990 to 1994, head of the Department of Computer Science and Applied Mathematics at the University of Girona in 2004-05, and dean of the Graduate School of the University of Girona in 2005-06. She received in 2006 the William Christian Krumbein Medal of IAMG, was nominated Distinguished Lecturer of IAMG in 2007, and received the J.C. Griffiths Teaching Award in 2008. From 2008 to 2012 she was President of IAMG and is Past-President for the period 2012-2016. From 2015 to 2017 she is President of the Association for Compositional Analysis, founded in L’Escala (Spain) in June 2015.

Uncertainty in 3D Geological Modelling by Prof Mark Jessell

More details to follow

Resource and Reserve Classification through JORC and VALMIN Codes by Dr Jacqui Coombes

More details to follow

Mathematical Morphology in Interpolations and Extrapolations by Prof B. S. Daya Sagar

Data available at multiple spatial / spectral / temporal scales pose numerous challenges to the data scientists. Of late researchers paid wide attention to handle such data acquired through various sensing mechanisms to address intertwined topics—like pattern retrieval, pattern analysis, quantitative reasoning, and simulation and modelling—for better understanding spatiotemporal behaviours of several terrestrial phenomena and processes. Various original algorithms and techniques that are mainly based on mathematical morphology (Matheron 1975, Serra 1982, Soille 2010, Sagar 2010, 2013) have been developed and demonstrated. This course that presents fundamentals of mathematical morphology and their involvement in interpolations and extrapolations with applications in geosciences and geoinformatics would be useful for those with research interests in image processing and analysis, remote sensing and geosciences, geographical information sciences, spatial statistics and mathematical morphology, mapping of earth-like planetary surfaces, etc. This course will be offered in two parts on 03-09-2017. In the morning shift all the fundamental morphological transformations would be covered. The applications of those transformations, covered in the first shift, to understand the morphological interpolations and extrapolations would be covered with several case studies in the second shift.

Course Date: 3rd September 2017
Venue Details: TBA
Course Duration: 1 day
Logistics: Morning Session: Introduction to Mathematical Morphology: (i) Binary Mathematical Morphology, (ii) Grayscale Mathematical Morphology, (iii) Geodesic and Graph Morphology. Afternoon Session: Mathematical Morphology in Spatial Interpolations and Extrapolations: (i) Conversion of point-data into polygonal map via SKIZ and WSKIZ, (ii) Visualisation of spatiotemporal behaviour of discrete maps via generation of recursive median elements, (iii) Morphing of grayscale DEMs via morphological interpolations, and (iv) Ranks for pairs of spatial fields via metric based on grayscale morphological distances

Course Instructor: Prof B. S. Daya Sagar
Picture1B. S. Daya Sagar is a full Professor of the Systems Science and Informatics Unit (SSIU) at the Indian Statistical Institute. Sagar received the M.Sc and Ph.D de-grees from the Faculty of Engineering, Andhra University, Visakhapatnam, India, in 1991 and 1994 respectively. He is also the first Head of the SSIU. Earlier, he worked in College of Engineering, Andhra University, and Centre for Remote Imaging Sensing and Processing (CRISP), The National University of Singapore in various positions during 1992-2001. He served as Associate Professor and Researcher in the Faculty of Engineering & Technology (FET), Multimedia University, Malaysia during 2001-07. His research interests include mathematical morphology, GISci, digital image pro-cessing, fractals and multifractals their applications in extraction, analyses, and modeling of geophysical patterns. He has published over 75 papers in journals, and has authored and/or guest edited 9 books and/or special theme issues for journals. He recently authored a book entitled “Mathematical Morphology in Geomorphology and GISci,” CRC Press: Boca Raton, 2013, p. 546. He recently co-edited a special issue on “Filtering and Segmentation with Mathematical Morphology” for IEEE Journal on Selected Topics in Signal Processing (v. 6, no. 7, p. 737-886, 2012). He is an elected Fellow of Royal Geographical Society (1999), Indian Geophysical Union (2011), and was a member of New York Academy of Science during 1995-96. He received Dr. Balakrishna Memorial Award from Andhra Pradesh Akademi of Sciences in 1995, Krishnan Gold Medal from Indian Geophysical Union in 2002, and ‘Georges Matheron Award-2011 (with Lecturership)” of International Association for Mathematical Geosciences. He is the Founding Chairman of Bangalore Section IEEE GRSS Chapter. He is on the Editorial Boards of Computers & Geosciences, and Frontiers: Environmental Informatics. More details about him can be seen at http://www.isibang.ac.in/~bsdsagar

Practical Stratigraphic Forward Modelling by Dr. Cedric M. Griffiths

Stratigraphy is the scale-independent preserved record of many interacting erosion, transport and depositional processes and events. Numerical stratigraphic forward modelling (SFM) attempts to simulate the physical, chemical and biological processes that have been, are, and will be responsible for stratal architecture over time scales from seconds to millions of years. We can only demonstrate that we understand these processes by making quantitative predictions about stratal architecture and rock properties, away from observations, at all scales and time intervals from the Pre-Cambrian to the future. Using this technology earth scientists can develop quantitative multiple working hypotheses of basin fill and the response of depositional systems to future climate change. The course will focus on hands-on use of the Sedsim SFM software, and the workflow needed to develop and test depositional and stratigraphic understanding at a variety of scales. The treatment of theory will be limited and there is a strong emphasis on using SFM programs in real-world settings such that their capabilities and limitations are well understood. A range of practical applications from flume tank to continental scales will be discussed.  Copies of the latest trial version of Sedsim and documentation will be provided beforehand together with exercises and test data sets.  Participants will be expected to have their own lap-top computer and pre-load the Trial-Sedsim software and Exercises.

Course Date: 8th September 2017
Venue Details: TBA
Course Duration: 1-Day
Course outline:  Morning Session:   Introduction to Stratigraphic Forward Modelling: Historical review, current status, trend and future: Sedsim (algorithm, parameters, problem identification and specification):  Use of Trial-Sedsim and discussion of the input files. Simple worked class exercise. Afternoon Session: Carbonate and organic exercises: Digital flume tank exercises: Basin Scale Exercise: Constraint and Verification: Summary.

Course Instructor: Dr. Cedric M. Griffiths
Cedric GriffithsCedric Griffiths is Director of StrataMod and Adjunct Professor at Curtin University. He has held positions as Nordic Council Research Professor in Petrophysics at NTNU, Trondheim, and the South Australian Chair of Petroleum Geology at the University of Adelaide. He has worked for BP Research and Sintef, in Norway, and CSIRO in Australia on various aspects of quantitative stratigraphic modelling. Cedric holds a PhD from Newcastle University in the UK, is an Associate Editor of Terra Nova, and over the past 30 years has published numerous peer‐reviewed papers in the fields of quantitative stratigraphy, stratigraphic forward modelling, petroleum geology, coastal process modelling and petrophysics.

We welcome offers of short courses and workshops from other participants, please contact the conference organisers. 

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Ph: +61 2 9265 0700
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iamg2017@arinex.com.au