Katerina Trepekli
Gæsteforsker
Energy flux parametrization as an opportunity to get Urban Heat Island insights: The case of Athens, Greece (Thermopolis 2009 Campaign)
Loupa, G., Rapsomanikis, S., Trepekli, Aikaterini & Kourtidis, K., 2016, I: Science of the Total Environment. 542, s. 136-143 8 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Deep learning based 3D point cloud regression for estimating forest biomass
Oehmcke, Stefan, Li, Lei, Caballer Revenga, Jaime, Nord-Larsen, Thomas, Trepekli, Aikaterini, Gieseke, F. & Igel, Christian, 1 nov. 2022, 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2022. Renz, M., Sarwat, M., Nascimento, M. A., Shekhar, S. & Xie, X. (red.). Association for Computing Machinery, Inc., s. 1-4 38Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR
Oehmcke, Stefan, Li, Lei, Trepekli, Aikaterini, Caballer Revenga, Jaime, Nord-Larsen, Thomas, Gieseke, Fabian Cristian & Igel, Christian, 2024, I: Remote Sensing of Environment. 302, 21 s., 113968.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Fluxes of gaseous elemental mercury on a Mediterranean coastal grassland
Polyzou, C., Loupa, G., Trepekli, Aikaterini & Rapsomanikis, S., 1 sep. 2019, I: Atmosphere. 10, 9, 15 s., 485.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Vertical Energy and Momentum Fluxes in the Centre of Athens, Greece During a Heatwave Period (Thermopolis 2009 Campaign)
Rapsomanikis, S., Trepekli, Aikaterini, Loupa, G. & Polyzou, C., 2014, I: Boundary-Layer Meteorology. 154, 3, s. 497-512 16 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods
Caballer Revenga, Jaime, Trepekli, Aikaterini, Oehmcke, Stefan, Jensen, Rasmus, Li, Lei, Igel, Christian, Gieseke, Fabian Cristian & Friborg, Thomas, 2022, I: Remote Sensing. 14, 16, 22 s., 3912.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Prediction of above ground biomass and C-stocks based on UAV-LiDAR,multispectral imagery and machine learning methods.
Caballer Revenga, Jaime, Trepekli, Aikaterini, Oehmcke, Stefan, Gieseke, Fabian Cristian, Jensen, Rasmus & Friborg, Thomas, 2021. 1 s.Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › fagfællebedømt
Seasonal evapotranspiration, energy fluxes and turbulence variance characteristics of a Mediterranean coastal grassland
Trepekli, Aikaterini, Loupa, G. & Rapsomanikis, S., 2016, I: Agricultural and Forest Meteorology. 226-227, s. 13-27 15 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Methods for processing and analyzing UAV-retrieved Lidar and RGB data covering selected areas in Accra
Trepekli, Aikaterini, Fog, Bjarne & Møller-Jensen, Lasse, 16 feb. 2021, Department of Geography & Geology, University of Copenhagen. 18 s.Publikation: Bog/antologi/afhandling/rapport › Rapport › Forskning
- Udgivet
Plant Structure and Carbon Storage Assessment Utilizing Drone-Borne Lidar and Deep Learning Technologies in a Danish Agricultural Expanse.
Trepekli, Aikaterini, Caballer Revenga, Jaime, Oehmcke, Stefan, Gieseke, Fabian Cristian, Jensen, Rasmus & Friborg, Thomas, 2021. 12 s.Publikation: Konferencebidrag › Paper › Forskning
ID: 196033191
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Influence Of Climate Change On The Future Precipitation Pattern In The Region Of Ghana: Climate change resilience in urban mobility
Publikation: Bog/antologi/afhandling/rapport › Rapport › Forskning
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Fluxes of gaseous elemental mercury on a Mediterranean coastal grassland
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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69
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Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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