Funding Organization: General Secretariat for Research and Technology (GSRT)
Funding Instrument: Business Partnerships with Research Organizations
Start Date:
Duration: 36 months
Total Budget: 919.100,00 EUR
ITI Budget: 200.000,00 EUR

ARTEMIS aims at the development of a multi-modal service for the processing of satellite, terrestrial and available spatial data and the generation of products related to the quality, health and sustainable development of economic forests, with emphasis on chestnut forests. These products will be distributed through a dynamic and user-friendly online platform, which will support basic and specialized operations in order to facilitate monitoring and improvement of chestnut production and enhance actions for biodiversity protection against climate change.

It is known that the Mediterranean chestnut forests in the region of Thessaly have been “degraded” despite the fact these are considered as productive forests. Moreover, the long-term lack of planning for alternative crops and the insufficient policies for supporting economic growth of mountain populations have hindered substantially production of chestnuts, and especially in the forests of Mouzaki. Therefore, there is a need for development of modern practices and technologies that will support the continuous monitoring of natural and managed ecosystems and that will promote, in the long-term, the growth of primary production while preserving biodiversity.

The project will mainly address the existing forest health threats in selected areas, which are mainly caused by biotic factors (insects, diseases, etc.), thus resulting in gradual degradation and destruction of production. As many studies focus mainly on assessment of damage driven by abiotic agents (fires, droughts) in forests, it is worth investigating and proposing solutions for the timely evaluation and management of early symptoms of decline, as well as the mitigation of further damage. ARTEMIS project aims to fill this gap, by proposing an innovative forest health monitoring methodology with the use of high and very-high spatial resolution remote sensing data. In order to achieve this, advanced techniques in the scientific fields of image processing, and mechanical learning, combined with collaborative exploitation of freely distributed satellite datasets (Landsat, Sentinel-1, Sentinel-2) will be exploited. The proposed methodology will be applicable not only on the targeted chestnut forests but also to similar forest ecosystems that are potentially threatened by different agents of degradation.

The current consortium, comprising research bodies and medium enterprises, is expected to contribute to an integrated and seamless implementation of the final service-solution, while the commercialization of the innovative technological products will aim at the preservation of the newly created vacancies beyond the end of the project.


  • Aristotle University of Thessaloniki
  • Bank of Karditsa
  • Centre for Research and Technology Hellas / Information Technologies Institute