Coursebooks 2017-2018

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Exploratory data analysis and geovisualization

ENV-444

Lecturer(s) :

Joost Stéphane

Language:

English

Summary

This course teaches how to apply spatial exploratory approaches and processing methods and to apply them to georeferenced datasets relevant to the fields of environmental engineering, urban planning and spatial epidemiology.

Content

This course consists of a theoretical and of a practical part. Each week 45 minutes of ex-catedra teaching are used to present the history of the discipline (exploratory data analysis - EDA), of the main theoretical framework and of the main software used.
The theory is followed by 1h30 of practical work during which the notions covered by the theory are implemented in the computer lab. The data used are provided by current research case studies (e.g. spatial epidemiology in urban environments, landscape genetics). Data exploration, geovisualization, geocomputation, communication (semiology of graphics) and representation (thematic mapping) are implemented in the context of exercises. In parallel, the data provided and the approaches taught have to be used to write scientific papers (1 short and 1 regular).

Keywords

Exploratory spatial data analysis; Geocomputation; EDA; ESDA; Geovisualization; GIS; Geoda; Thematic mapping; Semiology of graphics; Spatial statistics; Scientific paper writing

Learning Prerequisites

Recommended courses

Important concepts to start the course

Statistics; Geographic Information Systems;

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

Expected student activities

Attend and participate in theoretical courses, apply the instructions proposed during the practicals, write short articles, present a project orally, show initiative

Assessment methods

Continuous control during the semester:

Supervision

Office hours Yes
Assistants Yes
Forum Yes

Resources

Virtual desktop infrastructure (VDI)

No

Bibliography

Ressources en bibliothèque
Notes/Handbook

Lecture notes are gradually distributed to students during the semester.

Websites
Moodle Link

In the programs

  • Digital Humanities, 2017-2018, Master semester 1
    • Semester
      Fall
    • Exam form
      Oral
    • Credits
      4
    • Subject examined
      Exploratory data analysis and geovisualization
    • Lecture
      1 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Environmental Sciences and Engineering, 2017-2018, Master semester 1
    • Semester
      Fall
    • Exam form
      Oral
    • Credits
      4
    • Subject examined
      Exploratory data analysis and geovisualization
    • Lecture
      1 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Environmental Sciences and Engineering, 2017-2018, Master semester 3
    • Semester
      Fall
    • Exam form
      Oral
    • Credits
      4
    • Subject examined
      Exploratory data analysis and geovisualization
    • Lecture
      1 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Mineur STAS Russie, 2017-2018, Autumn semester
    • Semester
      Fall
    • Exam form
      Oral
    • Credits
      4
    • Subject examined
      Exploratory data analysis and geovisualization
    • Lecture
      1 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks

Reference week

MoTuWeThFr
8-9
9-10
10-11
11-12
12-13
13-14
14-15 MXG110
15-16 MXG110
16-17
17-18
18-19
19-20
20-21
21-22
Lecture
Exercise, TP
Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German