Scientific computing and applications

Acquire the basic concepts of scientific computing and its applications, including data analysis, data visualization and imaging, necessary for the analysis of physical, hydrogeological and environmental phenomena. In addition to classical (procedural) scientific programming, OOP (Object-Oriented Programming) will also be introduced to enable the development of more complex scientific computing applications, particularly in visualization. These concepts will be applied to a variety of problems in hydrology, geology, geochemistry, remote sensing and geophysics, using the scientific computing and programming tool matlab. Beginners, intermediate and advanced scientific programming groups will be set up at the start of the course. A project involving polluted sites and soils is planned at the end of the module.
Minimum skills to be acquired: Mastery of the theoretical bases and scientific calculation tools used in geo-environment.

1. Scientific computing applied to earth sciences (S. Boukir, L. Fallot and N. Chehata, 22h)

Procedural programming and data analysis (SBetNC, 16h): review of basic scientific programming concepts, control structures, scripts, functions, data access (common formats such as text files, excel files, images). These concepts will be addressed through the implementation of classic data analysis methods, in particular PCA and SFM (covered in ENS1). Application to environmental data analysis
Object-oriented programming (LFetNC, 10h): notions of class and object, class properties and methods, notions of inheritance and encapsulation, manipulation of graphical objects. These concepts will be applied to visualization (part 3)

2. Imaging applied to earth sciences (S. Boukir, 12h)

Image enhancement for photo-interpretation: mathematical operations (logarithmic, power, piecewise linear transformations), histogram manipulation (spreading, equalization), spatial filtering (noise attenuation, contrast enhancement, blur attenuation). Application to land-use mapping
Frequency filtering: 1D and 2D Fourier transforms, low-pass, high-pass, band-pass filtering. Applications in geophysics
Global binary thresholding (simple, adaptive). Applications in microscopic reservoir imaging

3. Visualization applied to earth sciences (L. Fallot and O. Atteia, 12h)

Data import and export
Visualization of 2D vector fields (example: spatial gradient)
Visualization of 3D vector fields: contours, isocontours, surfaces and meshes, cones, flows and isosurfaces, 2D slices (with filtering and contrast enhancement), viewpoint control, time series
Volume visualization (example: tomography)
Project (red thread principle): polluted sites and soils