To propose a set of methods and tools to study complex data (georeferencing, temporal data and so on) in order to predict a variable of interest or identify consistent sub-sets and to represent these results in the form of maps and charts.
The course will combine lectures-seminars, tutorials, interviews and on-site visits and project-based learning.
|Disciplinary Content||Nb of hours|
|Applications : project (tutorials with R, QGIS) and advanced level in R||8|
|Distributed spatial data extraction and management, Databases, Big data, Semantic Networks||20|
|Statistics (Spatial autocorrelation and regression)||18|
|Variogram – Kriging||5|
Books and other reading materials
No books have been ordered for this course. All required readings are available as downloads from the Montpellier SupAgro teaching platform. There is no formal reading packet for this course.
Research Units: UMR MISTEA (L'institut Agro | Montpellier SupAgro & INRAE) and UMR ITAP (L'institut Agro | Montpellier SupAgro & INRAE)