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Author(s) Organisation(s) Contribution Title
Naemi, VahidVienna University of Technology (TU Wien), Vienna, AustriaTowards a global high resolution wetland inventory based on optical and radar imagery
Nafría, David A.Agricultural Technological Institute of Castile and Leon, Regional Ministry of Agriculture, Junta de Castilla y León, SpainCastile and Leon Crops and Natural Land Map
Nagler, ThomasENVEO IT GmbH, Austria;
Environmental Earth Observation IT GmbH, Innsbruck, Austria
The Chilly Zones Of The Land Cover Mapped By Means Of Sentinel-2
The Regional Distribution of Permafrost on Tröllaskagi peninsula, Northern Iceland
Napiorkowska, MilenaDeimos Space UK, United KingdomDeep Learning for Land Classification and Palm Tree Counting for the United Arab Emirates
Nemec, JohannaENVEO IT GmbH, AustriaThe Chilly Zones Of The Land Cover Mapped By Means Of Sentinel-2
Ngumindoga, WebsterUniversity of ZimbabweGIS-based Estimation of Soil Erosion Potential and its Implications to Water Resources of City of Kinshasa, D.R. Congo
Nicholson, LindseyInstitute of Atmospheric and Cryospheric Sciences, University of Innsbruck, AustriaMonitoring of Glacier Surface Properties with optical Satellite Data – Examples from the Eastern Alps (Austria and Italy) and the Khumbu-Himal (Nepal)
Nicola, LaurentiuCS-Romania, RomaniaSentinel-2 for Agriculture: Synergy of Sentinel-2 and Landsat 8 for supporting operational national and global crop monitoring
Nicolas, BellemansUCLouvain-Geomatics, BelgiumLarge Scale decametric Cropland Mapping from Sentinel-2 and Validation: Lessons Learned from 2016 nationwide Demonstration for different Countries
Nicolas, MattonUCLouvain-Geomatics, BelgiumLarge Scale decametric Cropland Mapping from Sentinel-2 and Validation: Lessons Learned from 2016 nationwide Demonstration for different Countries
Nistor, ConstantinUniversity of Bucharest, Faculty of Geography, RomaniaThe synergy of Sentinels and Corona imagery to assess urban land cover change over 5 decades in Bucharest, Romania
Nita, MihaiFaculty of Forestry, University of Transylvania, Brasov, RomaniaGlobal Land Cover Products Validation and Inter-comparison in South Central and Eastern Europe
Nolasco, Miguel MartínUniversidad Nacional de Córdoba (Argentina), Argentine RepublicCrop mapping in the Pampas, Argentina. A comparison between Maximum Likelihood and Machine Learning approaches.
Nosavan, JulienCNES, FranceSPOT World Heritage : images from the past for time series
Novikov, AlexeiNational Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”Large Scale Crop Classification Using Deep Learning Approach
Nowakowski, ArturSpace Research Centre (CBK PAN), Poland;
Space Research Centre of Polish Academy of Science, Poland
A Sampling Approach for Advanced Multi-Temporal Classification of Sentinel-2 Data
Towards Automatic Global Land Cover Classification On Sentinel-2 Data
Nunes, PauloEuropean Union Satellite Centre, SpainLand Cover data to support a Change Detection system for the Space and Security community