IN A NUTSHELL
ERMES aims to develop a prototype of downstream services based on the assimilation of EO and in situ data within crop modeling solutions. Two services are foreseen: Regional Rice Service (RRS) customised for providing public authorities with an agro-monitoring system for crop mapping, yield estimating and risk forecast and Local Rice Service (LRS) for the private sector (farmers, agro-services) providing added value information on yield variability, risk alert and crop damage at farm scale.
The project received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration (FP7/2007-2013) and will last three years (2014 – 2017).
The project is coordinated by CNR-IREA (Institute on Electromagnetic Sensing of Environment), and involves partners of four European countries (Greece, Spain, Italy, Switzerland) with strong expertise in different scientific domains, such as: Remote Sensing, Crop Modeling, Agronomy and Information and Communication Technology.
The agricultural sector in Europe is facing the challenge to maintain and improve its competitiveness by reducing production costs and minimizing environmental impact of agricultural practices. ERMES will contribute to achieve the objective of sustainable agriculture needs by developing operational methods able to monitor crop status during the season and to capture within field spatial variability of the production.
ERMES aims to create added-value information for the agro-sector by integrating in crop models operational Copernicus core products, maps derived from SAR and optical data processing and in situ observations. Two services will be created for regional authorities and local agro-business. Advanced smart technologies will be used to collect in-situ observations and return customized information to end-users.
ERMES takes advantage from Copernicus Land services and proposes innovative approach for the integration of optical and SAR data in view of fully exploitation of Sentinel missions. Such high temporal/spatial resolution satellite products and in-situ observations, acquired by smart technologies, are assimilated into crop yield model to provide added value information customized to public and private stakeholders of the agro-sector.