Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Session Overview | |
Location: High Bay Poster Session |
Date: Wednesday, 13/Nov/2024 | |
12:00pm - 1:00pm |
Poster Session (Day1) Location: High Bay Poster Session COME-ON-BOARD-PSG!: Optimizing PRISMA Second Generation Acquisitions with Onboard Edge Computing and Machine Learning Algorithms 1: School of Aerospace Engineering, Sapienza University, Rome, Italy; 2: DICEA, Department of Civil, Building and Environmental Engineering, Sapienza University, Rome, Italy; 3: Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy; 4: INGV, National Institute of Geophysics and Vulcanology, Rome, Italy; 5: ASI, Italian Space Agency, Rome, Italy BIODIVERSITY – End-user driven optimization of the SWIR spectral sampling for a future hyperspectral sensor using end-to-end simulations 1: Université de Toulouse, ONERA DOTA, Toulouse, France; 2: Ifremer, DYNECO, LEBCO, 29280 Plouzané, France; 3: Nantes Université, Laboratoire de Planétologie et Géosciences, UMR 6112, Nantes, France; 4: Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Sorbonne Université, Laboratoire Lagrange, Nice, France; 5: Université Lille, CNRS, UMR 8518, LOA, France; 6: Université Paris Cité, Institut de Physique du Globe de Paris, CNRS, Paris, France; 7: Université Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d’Etudes de la Neige, Grenoble, France; 8: Université de Toulouse, INRAE, UMR DYNAFOR, Castanet-Tolosane, France; 9: Université Gustave Eiffel, LASTIG, ENSG, IGN, Saint-Mandé, France; 10: SHOM, Brest, France; 11: CEA/DAM/DIF, Arpajon, France; 12: Université de Toulon, CNRS, SeaTech, LIS laboratory, UMR 7020, Toulon, France; 13: DGA, Paris, France; 14: ACRI-ST, Sophia-Antipolis, France; 15: CNES, Toulouse, France Atmospheric correction of hyperspectral data with the MAGAC toolbox Magellium, France SBG VSWIR Terrestrial Vegetation Algorithm Development Update 1: NASA Jet Propulsion Laboratory, California Institute of Technology, United States of America; 2: NASA Goddard Space Flight Center; 3: University of Wisconsin, Madison; 4: Battelle, National Ecological Observatory Network; 5: Rocky Mountain Biological Laboratory Forest Cover Mapping by a Three-branch Convolutional Neural Network and PRISMA Images 1: Department of Information Engineering and Computer Science, University of Trento, Trento, Italy; 2: CREA Research Centre for Forestry and Wood, Trento, Italy Assessing Sentinel-2 MSI and EnMAP HSI data to retrieve wheat nitrogen content UCLouvain, Belgium Spectral invariants for vegetation mapping VTT Technical Research Centre of Finland, Finland NASA’s PACE Mission – Pretty Applicable to all of Crustal Earth. 1: NASA Goodard Space Flight Center, United States of America; 2: Science Systems and Applications, Inc.; 3: University of Maryland Baltimore County; 4: Morgan State University Tuning Hyperspectral Mission Specifications to the End-User Needs through End-to-End Simulations 1: CNES, France; 2: ACRI-ST Toulouse, France; 3: Magellium Artal Group, Toulouse, France New Sunglint Models for Improved Atmospheric Correction of Water Surfaces Jet Propulsion Laboratory, California Institute of Technology, United States of America Towards fast and sensor-independent retrieval of sun-induced fluorescence from spaceborne hyperspectral data 1: Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Jülich, Germany; 2: German Aerospace Center (DLR), Earth Observation Center, Remote Sensing Technology Institute, Oberpfaffenhofen, Germany; 3: RHEA Group c/o European Space Agency (ESA), Largo Galileo Galilei, Frascati, Italy; 4: Forschungszentrum Jülich GmbH, Institute of Advanced Simulations, IAS-8: Data Analytics and Machine Learning, Jülich, Germany Mapping snow properties with SBG and CHIME - How do we achieve the objectives of the decadal survey? 1: Jet Propulsion Laboratory, California Institute of Technology; 2: Leidos Inc.; 3: University of California, Santa Barbara; 4: University of Colorado, Boulder; 5: University of California, Los Angeles; 6: Université Grenoble Alpes Hyperspectral Linear Mixture Models for Topsoil Texture Retrieval 1: CNR, Italy; 2: IUSS, Italy; 3: UNITUS, Italy Potentialities of PRISMA and Sentinel-2 imagery for Soil Organic Carbon estimation at regional scale 1: University of Naples "Federico II", Naples, Italy; 2: Euro.Soft.S.r.l., Naples, Italy; 3: Institute of BioEconomy National Research Council of Italy CNR-IBE Florence, Italy Dealing with wiggles in spaceborne hyperspectral reflectance data – to smooth or not to smooth? Royal Belgian Institute of Natural Sciences (RBINS), Belgium Optimizing spectral indices for multi-platform hyperspectral data using Tree-Structured Parzen Estimators: A case study on NDVI and calcite index 1: Helmholtz-Zentrum Dresden-Rossendorf, Center for Advanced Systems Understanding, Görlitz, Germany; 2: Helmholtz-Zentrum Dresden Rossendorf, Helmholtz-Institute Freiberg for Resource Technology, Freiberg, Germany; 3: Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany PRISMA images for estimating mid-latitude forest functional traits and biodiversity indices University of Milano Bicocca, Italy Mapping Alpine Grasslands with PRISMA, Sentinel-1, and Sentinel-2: A Two-Step Classification Approach Eurac Research, Institute for Earth Observation, Bozen, Italy. Land Use/Land Cover mapping with satellite images and field spectral libraries combined in Linear Mixture Models 1: Institute of Polar Sciences of the National Research Council of Italy (ISP CNR), Via Salaria km 29, 300-00015 Montelibretti, Roma, Italy; 2: University Institute for Advanced Study of Pavia (IUSS), Palazzo del Broletto, Piazza della Vittoria 15, 27100 Pavia, Italy; 3: NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA A comparison the quality of Airborne Hyperspectral and Multispectral satellite remote sensing data to evaluations of forest leaf area index. 1: Department of Applied Geoinformatics and Cartography, Faculty of Science, Charles University, Czech Republic; 2: Global Change Research Institute, Czech Academy of Sciences, Czech Republic; 3: Faculty of Science, Department of Geography, Laboratory on Geoinformatics and Cartography,Masaryk University, Czech Republic; 4: Department of Experimental Plant Biology, Faculty of Science, Charles University, Czech Republic Harnessing Near-Same-Day Multiresolution Hyperspectral Images for Tree Species Identification 1: Department of Earth Systems Research, Helmholtz-Zentrum Dresden-Rossendorf - Center for Advanced Systems Understanding, Görlitz, Germany; 2: Department of Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany; 3: Department of Remote Sensing, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany Fully Autonomous Hyperspectral Imaging System Design for Medium-Altitude Long-Endurance Unmanned Aerial Vehicles Visratek, Turkiye The EnMAP Foreground Mission and harmonised campaign activities 1: German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Germany; 2: German Space Agency, German Aerospace Center (DLR), Germany; 3: German Research Centre for Geosciences, Helmholtz Centre Potsdam (GFZ),Germany; 4: German Space Operations Center (GSOC), German Aerospace Center (DLR), Germany; 5: Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany; 6: Institute of Soil Science, Leibniz University Hannover, Germany Validating Surface Reflectance Over Tall Vegetation maitec, Australia Lessons learned from inter-comparison of multi- and hyper-spectral atmospherically corrected surface reflectance products 1: Earth Observation Center (EOC), DLR, Germany; 2: University of Valencia, Spain; 3: Planetek Italia, Italy; 4: Starion Group c/o European Space Agency (ESA), Italy; 5: Remote Sensing Laboratories, Department of Geography, University of Zurich, Switzerland Water quality retrievals from EnMAP and Sentinel-2 1: Alfred-Wegener Institute, Helmholtz Center for Polar and Marine Research (AWI), Klußmannstr. 3d, D-27570 Bremerhaven, Germany; 2: Deutsches Zentrum für Luft- und Raumfahrt (DLR), Earth Observation Center, Remote Sensing Technology Institute, Oberpfaffenhofen, 82234 Wessling, Germany; 3: Commonwealth Scientific and Industrial Research Organisation (CSIRO), Environment, Brisbane, QLD 4001, Australia; 4: Institute of Environmental Physics, University of Bremen, D-28334 Bremen, Germany WISPstation for validation of hyperspectral satellite data in the CYANOBLOOM project 1: Water Insight; 2: Brockmann Geomatics; 3: Brockmann Consult A synergetic approach of spaceborne Imaging Spectroscopy data for improving water quality mapping frequency 1: CNR-IREA, Italy; 2: Tartu Observatory, Estonia; 3: Sapienza University, Italy; 4: CNR-IBE, Italy; 5: Klaipeda University, Lithuania HIGH-RESOLUTION MAPPING OF FOREST LEAF PIGMENT CONTENTS FOR CALIBRATION AND VALIDATION OF SPACEBORNE PRODUCTS 1: Department of Geography, Universität Bonn, Germany; 2: School of Geography, Planning, and Spatial Sciences, University of Tasmania, Australia; 3: Global Change Research Institute of the Czech Academy of Sciences, Czech Republic; 4: School of Earth and Environmental Sciences, University of Queensland, Australia; 5: CSIRO, Space and Astronomy, Australia; 6: CSIRO, Land and Water, Australia; 7: Centre d’Etudes Spatiales de la Biosphère - UPS, CNES, CNRS, IRD, Université de Toulouse, France The USGS Earth Mapping Resource Initiative 1: USGS, Denver, CO, United States of America; 2: USGS, Reston, VA, United States of America Large-scale validation of fractional vegetation cover maps using high-resolution RGB-UAV videos. German Aerospace Center (DLR), Earth Observation Center (EOC), Weßling, Germany Cal/Val Activities for CHIME L2B High Priority Prototype Products 1: Global Change Research Institute of the Czech Academy of Sciences (CzechGlobe), Brno, Czech Republic; 2: Image Processing Laboratory, University of Valencia, Spain; 3: Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany Latest validation results of the EnMAP Level-2A bottom-of-atmosphere reflectance product produced with the EnMAP Processing Tool (EnPT) 1: Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany; 2: Leibniz University Hannover, Institute of soil science, Herrenhäuser Str. 2, 30419 Hannover, Germany WATERHYPERNET – Using a prototype network of automated in situ measurements of hyperspectral water reflectance for validation of hyperspectral satellite missions 1: Royal Belgian Institute of Natural Sciences (RBINS), Belgium; 2: National Physical Laboratory (NPL), Teddington, United Kingdom; 3: Consiglio Nazionale delle Ricerche (CNR-ISMAR), Rome, Italy; 4: Laboratoire Océanographique de Villefranche, Sorbonne Université (SU/LOV), Villefranche-sur-mer, France; 5: Instituto de Astronomía y Física del Espacio, Consejo Nacional de Investigaciones Científicas y Técnicas (IAFE, CONICET/UBA), Buenos Aires, Argentina; 6: Tartu University (TU), Tartu, Estonia; 7: Flanders Marine Institute (VLIZ), Oostende, Belgium; 8: Consiglio Nazionale delle Ricerche (CNR-IREA), Milan, Italy Cross-Mission Methodology for Masking Validation: EnMAP cloud mask with Sentinel-5P 1: German Aerospace Center (DLR), Earth Observation Center (EOC), Remote Sensing Technology Institute (IMF), Oberpfaffenhofen, Germany; 2: Center for Research and Advanced Studies of the National Polytechnic Institute (Cinvestav), Telecommunications Group, Zapopan, Mexico; 3: Starion Group c/o European Space Agency (ESA), Frascati, Italy Evaluation of the ATCOR methods for ENMAP and EMIT atmospheric correction ReSe Applications LLC, Switzerland CSIMBA: bridging the gap between quality and cost-oriented hyperspectral missions VITO Remote Sensing, Belgium Flying Laboratory of Imaging Systems – Aircraft Infrastructure to Support Spaceborne Imaging Spectroscopy Missions 1: Global Change Research Institute of the Czech Academy of Sciences (CzechGlobe), Brno, Czech Republic; 2: Department of Geography, Masaryk University, Brno, Czech Republic Uncertainty assessment, validation, and propagation for upcoming hyperspectral missions 1: National Physical Laboratory, United Kingdom; 2: Remote Sensing Laboratories, University of Zurich, Switzerland Estimation of forest functional vegetation traits from EnMAP Hyperspectral image using radiative transfer models and Machine Learning techniques Department of Geography, Laboratory for Climatology and Remote Sensing, Deutschhausstraße 12, D-35032 Marburg, Germany Comparative evaluation of airborne CASI and spaceborne PRISMA hyperspectral data in a coastal lagoon 1: CNR-ISMAR, Italy; 2: Università La Sapienza, Italy; 3: CNR-IREA, Italy; 4: e-Geos S.p.A.; 5: CNR-IGG, Italy; 6: CNR-IBE, Italy SBG PLANTS: Plant Traits and Spectral database 1: NASA Jet Propulsion Laboratory, United States of America; 2: NASA Goddard Space Flight Center, United States of America Using the Eradiate radiative transfer model to investigate the impact of surface heterogeneity on satellite image simulations 1: Rayference, Belgium; 2: GRASP, France Sensitivity analysis of PRISMA channels for water quality parameters assessment in different OWT 1: University of Sapienza, Italy; 2: Istituto Superiore di Sanità, Roma, Italy; 3: Agenzia Spaziale Italiana, Roma, Italy Decoding the Spectral Signatures of Acacia saligna Using Multi Resolution Hyperspectral Images 1: Department of Earth Systems Research, Helmholtz-Zentrum Dresden-Rossendorf - Center for Advanced Systems Understanding, Görlitz, Germany; 2: Department of Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany; 3: Plant Ecology Laboratory, School of Plant Science and Food Security, Tel Aviv University, Tel Aviv, Israel; 4: Remote Sensing Laboratory, School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel The EnMAP-Box: Advanced visualization and analysis of EnMAP data and beyond 1: Humboldt-Universität zu Berlin, Germany; 2: University of Helsinki, Finland; 3: University of Greifswald, Germany Innovations and Challenges in L3 Soil Products with Current and Future Spaceborne Imaging Spectroscopy 1: Helmholtz Centre Potsdam GFZ German Research Centre For Geosciences, Germany; 2: Leibniz Universität Hannover, Institute of Soil Science, Germany Nighttime Imaging Spectroscopy from Space German Aerospace Center (DLR), Earth Observation Center (EOC), Germany Leveraging EnMAP for building soil reflectance composites with Sentionel-2 DLR Oberpfaffenhofen, Earth Observation Center, Germany Biophysical parameter retrieval through the inversion of simulated hyperspectral vegetation data National Physical Laboratory, United Kingdom Measuring Canopy Nitrogen Content via Spectroscopy using the EnMAP-Box Hybrid Retrieval Workflow 1: Dept. of Geography, Ludwig-Maximilians-Universität München, Germany; 2: OHB System AG, Oberpfaffenhofen, Germany Simulated trait and spectroscopy data to support retrieval of forest biophysical parameters from spaceborne imaging spectroscopy 1: Global Change Research Institute of the Czech Academy of Sciences (CzechGlobe), Brno, Czech Republic; 2: Department of Geography, Masaryk University, Brno, Czech Republic; 3: Institute of Computer Science, Masaryk University, Brno, Czech Republic Comparative Evaluation of Plant Trait Retrieval Methods: Towards SBG VSWIR Terrestrial Algorithm Development 1: NASA Jet Propulsion Laboratory, United States of America; 2: University of Wisconsin- Madison; 3: NASA Goddard Space Flight Center; 4: University of Maryland Monitoring Forest Disturbance in the Hunsrück-Hochwald National Park using Spaceborne Imaging Spectroscopy 1: Luxembourg Institute of Science and Technology, Belvaux, Luxembourg; 2: Helmholtz GFZ German Research Centre for Geosciences, Germany; 3: University of Trier, Trier, Germany Studying the transferability of the BRDF normalization HABA algorithm from Sen2like multispectral to EnMAP hyperspectral. 1: Universitat de Valencia, Spain; 2: Dept of Geographical Sciencies, Univesity of Maryland, United States; 3: Telespazio France, Satellite System and Operation, France; 4: German Aerospace Center (DLR), Earth Observation Center (EOC), Germany VAE-based Emulator for Fast Hyperspectral Image Generation LISIC, France PRISMA hyperspectral data for cryosphere parameters estimation 1: Eurac Research, Italy; 2: National research council (CNR), Italy; 3: ARPA Val d'Aosta, Italy; 4: University of Milano - Bicocca, Italy; 5: Italian space agency (ASI), Italy Integrating In Situ Forest Traits and Airborne Hyperspectral Data to Support the Development of High Level Spaceborne Imaging Spectroscopy Products 1: Global Change Research Institute of the Czech Academy of Sciences (CzechGlobe), Brno, Czech Republic; 2: Department of Experimental Plant Biology, Charles University, Prague, Czech Republic; 3: Department of Geography, Masaryk University, Brno, Czech Republic PRISMA-SCIENZA Programme, Italy's advances in Hyperspectral Data and Downstream Applications ASI - Italian Space Agency, Italy Improved spectral Earth observations to support EU environmental policy needs 1: Helmholtz GFZ German Research Centre for Geosciences, Germany; 2: Umweltbundesamt - German Environment Agency, Dessau, Germany.; 3: Luxembourg Institute of Science and Technology, Remote Sensing and Natural Resources Modelling Group, 41 rue du Brill, L-4422 Belvaux, Luxembourg; 4: Geography Department, Humboldt-Universität zu Berlin, and Integrative Research Institute of Transformations of Human-Environment Systems (IRI THESys), Humboldt-Universität zu Berlin, Berlin, Germany HYPERedu Online Learning Program: Concept, Implementation Status and Cooperation Opportunities 1: Deutsches GeoForschungsZentrum (GFZ) Potsdam, Germany; 2: Friedrich-Schiller-University of Jena, Department of Earth Observation, Jena, Germany; 3: Ignite education GmbH, Jena, Germany; 4: UBA German Environment Agency, Dessau-Roßlau, Germany; 5: DLR German Space Agency, Bonn, Germany Improvement of EnMAP Cloud and Cloud Shadow Masks with Physically Based Mask Refinements and Machine Learning 1: University of Marburg, Department of Geography, Germany; 2: GeoEngine GmbH, Marburg, Germany; 3: agriBORA GmbH, Darmstadt, Germany GALENE: an envisioned satellite mission for observing coastal and inland aquatic ecosystems and wetlands 1: Sorbonne Université, France; 2: Alfred Wegener Institute - Helmholtz Center for Polar- and Marine Research; 3: ONERA; 4: University of Victoria; 5: University of Zurich; 6: CSIRO; 7: Carl von Ossietzky Universität Oldenburg; 8: German Aerospace Center (DLR); 9: National Research Council (CNR); 10: VITO; 11: University of Tartu; 12: Aberystwyth University; 13: Eawag; 14: TNO; 15: NASA; 16: University of Maryland Baltimore County CHRIS/Proba-1 Reprocessing Campaign to Generate Analysis Ready Data 1: Telespazio UK, United Kingdom; 2: SSTL, United Kingdom; 3: ESA/ESRIN, Italy Summer schools as a tool for top-down and bottom-up preparation and networking. 1: INGV, Italy; 2: Università degli Studi di Cagliari, Italy; 3: Fondazione Montagna Sicura, Italy The CHIME Observation Performance Simulator (OPSI) Software System: development and status at Critical Design Review 1: ACRI-ST, France; 2: OHB, Germany; 3: Thales Alenia Space, France; 4: ESA NASA EMIT Imaging Spectroscopy Observations, Products, and Plans for the Extended Mission NASA JPL Caltech, United States of America Revealing Reef Dynamics with NASA’s EMIT Imaging Spectrometer NASA Jet Propulsion Laboratory, United States of America |
Date: Thursday, 14/Nov/2024 | |
4:30pm - 6:00pm |
Poster Session (Day2) Location: High Bay Poster Session Poster Sessions will occur on Day 1: Wednesday, 13th November 2024, from 12:00-13:00 and on Day 2: Thursday, 14th November 2024, from 16:30-18:00. Please consult the overall Poster list 👉HERE. |
Contact and Legal Notice · Contact Address: Privacy Statement · Conference: Hyperspectral 2024 |
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