Custom Training and Teaching

Increase your skills to analyze your agronomic and environmental data!

Master free tools widely used to process spatialized data (QGIS, Grass, R, GeoFIS….)

Learn about spatial data processing (Geostatistics, Interpolation, Zoning, Filtering, Oriented Sampling…)

We offer two types of training to help you use spatial and temporal data in agriculture:

Geo-localized data are now commonplace in many scientific disciplines, especially in agronomy and environment. With more or less high spatial, temporal or attribute resolution, these data help to better quantify, describe and understand agro-systems. The use of these data nevertheless requires specific skills by the simple fact that they are positioned in space. This training aims to introduce you to the manipulation of these spatial data with the free language R and to allow you to use them in a more or less advanced way.

Keywords: R, Geostatistics, Geomatics, Spatial Analysis, Agronomy, Environment, Mapping

Objectives: To be able to manipulate spatial data in R, initiation to mapping and spatial data analysis in R

Target audience: Academics (Masters, PhD students, Researchers) or private structures wishing to develop Data Science services in Precision Agriculture

Program: The program is given here as an indication, it is likely to evolve.

  1. Discovery of spatial data in R
  • Discovery of spatial data formats and spatial packages
  • Loading and generation of spatial data
  • Management of coordinate systems, reprojection of data
  1. Visualization of spatial data in R
  • Displaying vectors and rasters in R
  • Management of styles and colors, display of cartographic backgrounds…
  • Introduction to several mapping packages: spplot, ggplot2, leaflet…
  1. Handling of spatial data in R
  • Handling of geoprocessing functions (buffers, overlaps, slices, merges…)
  • Management of neighborhood relations between observations
  • Implementation of advanced processing chains
  1. Exploitation and analysis of spatial data in R
  • Introduction to geostatistics (spatial autocorrelation, variographic analysis…)
  • Spatial autocorrelation tests and spatial variability characterization indices, spatial data classification and zoning, spatial sampling, spatial interpolation in R (TIN, IDW, kriging…)
  • Generalized linear models, taking into account spatial auto-correlation phenomena
  • Collaboration of R with other free tools (QGIS, GRASS, Python…)
    Test data will be provided. Participants will have time to work with their own data.

Pre-requisites:

Be autonomous in R (loading data and libraries, simple vector manipulation, be able to write a simple computer program…).
Need to work with spatialized data.
Skills acquired at the end of the training: Exploitation and analysis of spatial data in R (manipulation of vectors and rasters, implementation of geoprocessing chains, geostatistics)

Duration of the training in hours: Between 25 and 30 hours (3 to 4 days)

Geo-localized data are now commonplace in agriculture. Farmers, Advisors, Technicians, Chambers of Agriculture, Cooperatives, Technical Institutes; you all have to handle and exploit spatialized data. Whether it is simple GPS surveys or high spatial resolution vegetation data, new skills and competences are required to be able to integrate these information sources to your expertise to improve your advice and services. This training aims to make you handle QGIS by focusing on your business applications and needs.

Keywords: QGIS, Precision Agriculture, Agronomy, Experimentation, Discovery, Remote Sensing

Objectives: Be able to manipulate spatial data in QGIS

Target audience: Structures or operational field personnel wishing to increase their skills and gain independence in handling geographic data.

Program : The training contains modules (some are independent) adapted to different uses of QGIS

  • QGIS – Digital Transformation: for users who want to digitize and map their data
  • QGIS – Precision Agriculture – Field Experimentation: for users wishing to facilitate the exploitation and analysis of their experimentation data
  • QGIS – Precision Agriculture – Remote Sensing: for users who want to access and use satellite imagery on their production systems
  • QGIS – Precision Agriculture – Spatial Analysis: for users who want to learn about geoprocessing of their data
  • QGIS – Precision Agriculture – Processing Chain / Automation: for users wishing to industrialize geoprocessing on their work plots.

Prerequisite:

  • Be sensitive to the use of spatialized data.
  • Need to work with spatialized data.

Skills acquired at the end of the training: Handling and exploitation of different sources of information in QGIS

Duration of the training in hours: 1/2 to 1 day per module