Olive growth monitoring based on LiDAR remote sensing
Overview of the project
Stochastic inversion of the DART simulator model
Laser remote sensing named LiDAR, acronym of light detection and ranging, is a remote sensing technology using optical measures allowing the analysis of the beams backscattered in the sensor direction. The major advantage of the LiDAR is its capability to sound at high sampling rate the foliage density vertical profile, with an important penetration depth encompassing the Radar system performances. In this work, we propose to use the LiDAR to estimate the olive structure in the Sfax region. It will be therefore possible to monitor the growth, the productivity as well as the behavior of the different spacies in face of the climate change.
The work is composed of three axes:
- LiDAR signal modeling tacking into account the laser light polarization, the proposed solution will be integrated on the 3-D radiative transfer model DART simulator,
- Inversion of the proposed model in order to estimate the tree properties,
- Propose a pre-processing technique to deconvolve the LiDAR signal.