Public thesis defense of Jean BOUCHAT

"Maize green area index retrieval from multistatic and multi-frequency SAR data"

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Abstract

Climate change and a rapidly growing world population are placing an ever-increasing pressure on the agricultural sector. In this context, green area index (GAI) monitoring plays an essential role in assessing the status and health of crops, making it a key source of information for farmers and decision-makers alike. Current operational methods for GAI monitoring rely mainly on optical imagery, and are therefore hampered by the recurring presence of clouds. Synthetic aperture radars (SARs) present a promising alternative for collecting data in almost all weather conditions. The main objective of this thesis is to improve the retrieval of the GAI in maize crops using SAR remote sensing, with a perspective towards near real-time, large scale crop monitoring. To this end, the potential of multistatic and multi-frequency SAR for crop monitoring is assessed using experimental data, and methods are developed for GAI retrieval from SAR data, both alone and in conjunction with optical imagery. The results of these investigations suggest that further efforts should be made to integrate SAR remote sensing, either as a complement or entirely on its own, into current crop monitoring systems to improve their temporal resolution, timeliness, and overall reliability, thereby contributing to food security.

Jury Members

Prof. Pierre DEFOURNY (UCLouvain, Belgium), supervisor

Prof. Marnik VANCLOOSTER (UCLouvain, Belgium), chairperson

Prof. Xavier DRAYE (UCLouvain, Belgium), secretary

Dr. Dominique DERAUW (Liège space centre, Belgium)

Prof. Leila GUERRIERO (Tor Vergata University of Rome, Italy)