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Presentation of the module 

This compulsory module presents mathematical methods required for information processing, working techniques of visualisation, image improvement processing, the supervised and non-supervised classification methods, as well as the multitemporary analysis (change detection, analysis of the seasonal cycle and long-term trends), by implementing more relevant algorithms.

In addition to the traditional techniques of classification and regression, it is equipped with advanced computing tools (estimation by neutral networks, regularised inversion methods, temporary series analysis, data fusion, hybrid classification), and the analysis of maps obtained (techniques to quantify the error, analysis of ROC curves and others).

Description of the module

Number of ECTS credits: 10

Temporary unit: First and second semester

Nature: Compulsory


  • Supervised and unsupervised classification
  • Parametric and non-parametric methods
  • Neural networks and decision trees
  • Theory and adjustment of free parameters
  • Regression: parametric and non-parametric methods
  • Training and measures of precision, adjustment and bias
  • Selection and feature extraction
  • Image fusion techniques
  • Change detection analysis
  • Temporary series analysis

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