## 5 Conclusions  
The European Commission (EC) requires each Member State to monitor the proper use of funds and is considering the use of satellite imagery and Earth Observation (EO) techniques to monitor the condition of crops [44]. Thus, using EO data for the requirements related to the emission of direct payments represents a consistent improvement in cost effectiveness [7]. In this framework, the present work develops a Proof of Concept for an automated processing chain based on TerraSAR-X and Sentinel 2 data to retrieve vegetation biomass and vertical structure and to monitor agricultural practices. Two classification maps were produced and compared, the first based only on S2 data and the second based on the integration between optical and radar sensors (TSX + S2). Integrating two sensors for crop identification provided evidence of improved accuracy. The novelty consists of investigating the multi-temporal pattern of radiometric indices and radar backscatter to detect the different phenological stages of each crop, identifying the Day of the Year (DoY) in which the classes showed greater separability. The processing chain prototype should aim at demonstrating the technical operational feasibility toward a more automated approach in the provision of EO data processing and pre-operational and operational products, so it can complement and broaden the currently available panoply of existing products and be a benchmark for the development of future operational service for agricultural management. Paying agencies and national institutions can benefit from this operational service to easily monitor the use of Common Agricultural Policy (CAP) funds. To develop an automatized processing chain, it is necessary to continuously acquire the required input data over time. For these reasons, this work also contributes to defining mission requirements for upcoming and future constellations (e.g., IRIDE) focusing precisely on the synergistic use of different sensors, which is an added value to obtain a more consistent automatized downstream service. Conceptualization, A.T., E.V. and E.S. ; methodology, S.S. and E.V. ; formal analysis, S.S. and B.M. ; investigation, E.V. and S.S.; resources, A.T. and E.S. ; writing--original draft preparation, S.S.; writing--review and editing, A.T., E.V., M.R. and E.S. ; supervision, A.T., E.V. and E.S. ; funding acquisition, A.T. All authors have read and agreed to the published version of the manuscript. This study has been partially funded by the project NOCTUA \"Landscape Monitoring. For Everyone. From Space,\" funded under the Regional Operative Program (FOR) of Lombardy Region 2014-2020, call hub innovation and research (Project ID: 1179775) and by Italian National Resilience and Recovery Plan (PNRR) M1C2-25--Investment 4.1.2: Satellite Technology and Spatial Economy,Financed by the European Union--NextGenerationEU, Purchase Order N. 5001035211 (Call for Views on the EO PNRR System And/Or Element Architecture). **Data Availability Statement**: Sentinel-2 data were obtained from ESA and are freely available from the Copernicus Open Access Hub portal ([[https://scihub.copernicus.eu](https://scihub.copernicus.eu)]([https://scihub.copernicus.eu](https://scihub.copernicus.eu)), accessed on 21 September 2021), and from Theia catalogue ([[https://www.theia-land.fr/](https://www.theia-land.fr/)]([https://www.theia-land.fr/](https://www.theia-land.fr/)), accessed on 20 October 2021. TerraSAR-X data were obtained from DLR and are available from the EOWEB GeoPortal ([[https://eoweb.dlr.de/egp/](https://eoweb.dlr.de/egp/)]([https://eoweb.dlr.de/egp/](https://eoweb.dlr.de/egp/)), accessed on 7 October 2021) with the permission of DLR. Copernicus products were obtained from the Copernicus Land Monitoring Service ([[https://land.copernicus.eu/en/products](https://land.copernicus.eu/en/products)]([https://land.copernicus.eu/en/products](https://land.copernicus.eu/en/products)), accessed on 20 October 2021).