Tunisia

Project Overview

  1. Crop identification and Crop Area Estimation
    Crops types are discriminated using multitemporal NDVI data. A decision tree algorithm have been implemented for each year, we intend to develop a more general and robust method. Information about land cover type is required to parameterize the models used (ET, Biomass, etc.).
     
  2. Crop Condition/Stress

    Our main goal is to monitor crop consumption and irrigation requirements using the coupling of FAO-56 method and NDVI time series (see results section). Crop water budget is useful operational information at plot scale (farmers) and at perimeter scale (irrigation managers). This type of products is also a valuable input for watershed integrated modelling, aimed at basins scale management, including groundwater.

    Crop water stress is monitored using thermal image processing, and the results are aimed at being assimilated in the crop water budget model (PhD student).

  3. Soil Moisture
    Soil moisture is the primary objective tackled using microwave data, relying on ground measurements for cal/val purpose. This type of information may also be input in the crop water budget model (A new PhD is currently on this topic by using Sentinel-1 and Sentinel-2 satellites data).
     
  4. Yield Prediction and Forecasting
    Based on NDVI relationships and vegetation model.
     
  5. Crop Residue, Tillage and Crop Cover Mapping
    We don’t study yet residues nor tillage (this will be done in 2017). Crop cover mapping is related to the first point.
©2015 Joint Experiment for Crop Assessment and Monitoring
© HER MAJESTY THE QUEEN IN RIGHT OF CANADA SA MAJESTE LA REINE DU CHEF DU CANADA (2015)