Context and objectives
Red Palm Weevil (RPW) is considered as a key pest of palms with immense economic and environmental impacts, with consequences on food security and rural community livelihood in date palm oases. Adult weevils colonize the palms as they fly between them, while transnational infestations are due to the trade of infested plants. Direct losses due to RPW can be attributed to the value of the destroyed palms and, for date palms, the consecutive loss of date production, in addition to the high cost of the management programs, notwithstanding the expenses incurred on the removal and disposal of infested palms. It is clear that for a proper monitoring of RPW, it is essential to work on the complete set of contextual, structural, spatial, spectral and temporal information available from remote sensing. Spatially detailed multidate observations are rare, while they can provide information on the phenology and might significantly improve the accuracy and time of the RPW detection throughout the season. Furthermore, the spatial distribution of pest abundance and damage can be mapped without a large number of samples and provide spatial approaches for pest control.
The PALMWATCH project will investigate whether detection of red palm weevil infestation is feasible using airborne and spaceborne remote sensing (RS) techniques. An assessment will be made at what stage of the infestation a confident RPW detection can be provided, and which RS data is needed for this purpose.
An evaluation of the current remote sensing technologies, both airborne and spaceborne, for the monitoring of RPW infestations will be made.
An evaluation will be made on the need of high temporal resolution to monitor the development of the disease over time, the spatial resolution to monitor individual trees and even leaves in detail, as well as the spectral resolution to detect subtle changes due to RPW. An innovative RS monitoring system will be set-up for a non destructive, effective detection of RPW infestations, bearing in mind an operational service resulting from this project.
Considering the missing links and future recommendations from literature, we believe that the PALMWATCH project could accomplish a major step forward in the realization of a RPW detection system. Timeseries of Pleiades, Sentinel 1 (S1) and 2 (S2) satellite images will be used to evaluate their potential for RPW detection. An integrated multi-sensor RS monitoring system will be set-up in order to find the most optimal RPW detection system, focusing on timely RPW detection and more generally on the adequate identification and localization of infested palms.
Expected scientific results
- New insights into the disease-plant interaction mechanism. PALMWATCH will have a major impact on our understanding of what we can monitor with remote sensing and which spatial, spectral and temporal characteristics are needed for an early RPW detection. Our approach spans from the identification of the infested plants by RPW experts, through disease characterization by very detailed imagery to general spatial distribution monitoring. Combined, this approach will enable an unprecedented understanding of key disease processes that can be monitored by RS.
- Delivering a processing chain for non-destructive and effective RPW detection. PALMWATCH will generate new research tools, such as improved classification and segmentation techniques including the combination of different sensors, different time steps, contextual and morphological information to better identify RPW. Our resulting RS system will be defended at FAO by dr. Ferry. With their global reach, FAO can setup, deliver, manage and introduce platforms at the national, regional & global levels. National training, support & capacity building can be offered.
Expected products and services
Delivering a visualization platform indicating infestation probabilities. Maps will be generated with indication of the presence probability of RPW and will be accessible through an online visualization platform. FAO is urgently looking for these kind of applications.
Date farm companies, FAO, Biobest, Koppert, Smart Farm Sensing, UP42
|Project leader(s):||VITO - Remote Sensing - Teledetectie en aardobservatieprocessen|