Manuel joined the Environmental Science group in October 2020, under the ESA funded project: AI-Ready Earth Observation Training Datasets (AIREO).
Manuel has an extensive career in both private and public sectors. Manuel has been working as a consultant for European Commission’s DG Joint Research Centre (JRC) at Space, Security and Migration directorate under the Disaster Risk and Management Unit. There, Manuel has been working for different projects such Global Crisis Atlas (GCA) and Urban Analysis Network Syria (UrbAN-S) carrying out GIS and Remote Sensing tasks such a study of Agricultural patterns during Syria’s civil war and to map different conflicts worldwide.
Before joining JRC, Manuel worked at University of Azores (UAc), Cartographic and Geologic Institute of Catalonia (ICGC) among other institutions. Lately, he has been working in 4Site networks carrying out GIS developer tasks.
After receiving his BSc in Topographic engineering at Polytechnic University of Catalonia (UPC), Manuel studied his MSc in GIS for the same University. Nowadays is carrying out his part- time PhD research in Remote Sensing on "Identification and rapid assessment of agricultural areas in developing countries using Remote Sensing and Machine Learning" meanwhile he is working.
- McKinstry, A., Boydell, O., Le, Q., Preet, I., Hanafin, J., Fernandez, M., Warde, A., Kannan, V., and Griffiths, P.: AI-Ready Training Datasets for Earth Observation: Enabling FAIR data principles for EO training data., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12384, https://doi.org/10.5194/egusphereegu21-12384, 2021.
- Fernandez Urrutia, Manuel; Madruga, Joao; Gil , Artur. Using Google Earth Engine and Free Satellite Data for Forest Mapping, Assessment and Monitoring in S. Miguel Island (Archipelago of the Azores, Portugal). (2019). Digital Earth Observation, 44. Retrieved from http://symposium.earsel.org/39th-symposium-Salzburg/wp-content/uploads/2019/07/EARSeL-2019-Bookof-Abstracts-Print.pdf
- Gil A., Fernández-Urrutia M., Tiago F., & Borges-Tiago M.T. (2020) Using Open Remote Sensing and Geographic Data for SMART Monitoring of Nature-based TOURISM in the Azores Islands Natural Parks: towards (more) Sustainability. In: S. Nativi, C. Wang, G. Landgraf, M.A. Liberti, P. Mazzetti, Z.S. Mohamed-Ghouse (Eds.) Proceedings of the 11th International Symposium on Digital Earth (ISDE 11), 24-27 September 2019, Florence - Italy. IOP Conf. Series: Earth and Environmental Science 509 (2020) 012019, IOP Publishing (https://iopscience.iop.org/issue/1755-1315/509/1). DOI:10.1088/1755-1315/509/1/012019.
Available online at https://iopscience.iop.org/article/10.1088/1755-1315/509/1/012019/pdf
- Gil A., Fernández-Urrutia M., Isidoro A., Medeiros V., & Pacheco J.L. (2018) Sentinel-based Azores Regional Forest Inventory. pp102-103. In: NEREUS, European Space Agency & European Commission (2018) "The Ever Growing use of Copernicus across Europe’s Regions: a selection of 99 user stories by local and regional authorities”.
- Halkia, M., Louvrier, C., Caravaggi, I., Tagliacozzo, S., Fernandez, M. and De Girolamo, L., Global Crisis Atlas: mapping for situational awareness, Joint Research Centre, Ispra, 2018, JRC114119 . DOI: 10.2760/123189
- Fernández-Urrutia M., & Gil A. (2022). Resource Communication: ForestAz - Using Google Earth Engine and Sentinel data for forest monitoring in the Azores Islands (Portugal). Forest Systems, 31(2), eRC01. https://doi.org/10.5424/fs/2022312-18929