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.

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

Members

Projects

Remote Sensing for Smart Agriculture

AHSPECT

Remote Sensing for Smart Agriculture

Olive growth monitoring based on LiDAR remote sensing

Remote Sensing for Smart Agriculture

PHC-UTIQUE 2017: Monitoring of olive trees in the Sfax region by inversion of LiDAR IceSat-2 waveforms and Sentinel-2 images

Remote Sensing for Smart Agriculture

INFOTEL-3