Remote Sensing for Smart Agriculture

  • Head: Abdelaziz Kallel
  • Field: Optical Remote sensing
  • Theme: Vegetation property modeling, estimation, monitoring and assimilation

Team presentation

Well developed forests as well as cultivated plants need water and nutrients to grow. They are also sensitive to extreme weather events, diseases and predators. In this context, remote sensing can provide very useful data to identify and monitor forests and crops on a global or local scale using different spatial and temporal resolutions.

Research activities

  • Radiative transfer theory application on light scattering within vegetation medium in order to simulate different optical sensors: 
    • Multipsectral sensor
    • Light polarization 
    • Full waveform LiDAR
  • Monitoring the growth of cultivated plants and trees using LiDAR and Optical sensorson broad of satellite
  • Precision Agriculture using Multispectral and LiDAR sensonrs on broad of drones
  • Satellite image resolution improvement using downscaling and pansharpening techniques
  • Correction of optical images time series: gap feeling and cloudy pixel removal using Baysian approach


Remote sensing Radiative transfer Forward modeling Backward modeling 1-D & 3-D modeling Monte Carlo Simulation Vegetaion cover monitoring Forest inventory Growth monitoring Vegetation phenology Precision agriculture Satellite image processing Pansharpening Satellite image time series correction

Current projects

Team members

  • Dr. Abdelaziz KALLEL, Assosiate Pr, CRNS
  • Dr. Sihem CHAABOUNI, Assisntant Pr, ENET’Com
  • Dr. Rima GUIDARA, Assisntant Pr, ENET’Com
  • Dr. Sonia Ben HASSEN, Assisntant Pr, ENET’Com
  • Dr. Tijani DALLEJI, Assisntant Pr, Military Commander
  • PhD student Sahar Ben HAMIDA, CRNS
  • PhD student Hana ABDELMOULA, CRNS
  • Master student Amir DHOUIB, CRNS/ENET'Com