With this ITT ESA aims to start a project addressing scientific priorities and user needs related to agriculture.
The focus is on monitoring of multiple stressors with a particular focus on crop pests and diseases. It aims at exploring and exploiting the huge synergistic opportunities offered by the increasing European EO capacity from space together with in situ observations, advanced models and novel technologies (AI, ICT, cloud computing and HPC) to increase scientific understanding of crop responses to multiple abiotic and biotic stress factors with a focus on pests and diseases.
A main objective is to enhance methods, tools, monitoring systems and platforms for monitoring crops under multiple stressors with focus on identification, assessment and monitoring of pest and diseases. The project will contribute to the ESA-EC joint Earth System Science Initiative (ESSI). In this context the project aims at linking with relevant Horizon Europe projects, e.g. plant-health-related ESSI projects CERBERUS, STELLA and SYLVA, as well as infrastructure/scaling-related projects ScaleAgData and AgriDataValue. Synergies will be sought e.g. through two-ways sharing of input and output data, developed methods, processors, tools, measurement devices and data collection technology, benefiting from and complementing results, strengthening specific components of other projects, and comparison/benchmarking of results.
The study aims at Exploiting new EO techniques for monitoring different kind of stressors, including pests and diseases:
- Exploiting new EO techniques for monitoring different kind of stressors, including pests and diseases
- Improving our understanding of crop response to multiple stressors;
- Improving our understanding of the mechanisms of cascading stressors;
- Improving capacity to detect crop impact from pests and diseases;
- Improving capacity to monitor abiotic stressors and to exclude them as source of detected crop anomalies;
- Improving capacity to attribute detected crop impact to pests/diseases;
- Improving capacity for crop pest and disease monitoring and for predicting pest/disease spreading.
To address these objectives the project will design and implement a set of “integrated experiments” combining the use of EO data with advanced in-situ technology, advanced modelling and data driven, AI and/or hybrid methods. Test cases will include different crops, e.g. olive groves, citrus orchards, vineyards, tomatoes, potatoes or other crop types. The project will also maximise the potential offered by novel EO data with special focus on FLEX assuming that data become available during the project.
Learn more about this Invitation To Tender on the esa-star Publication page.