IEEE GRSS
First Slide
2026 IEEE International Geoscience and Remote Sensing Symposium
9 - 14 August 2026 • Washington, D.C.
MOP2.PJ: Earth Observation for Civil Security
Monday, 10 August, 15:00 - 16:15
Location: Poster Area J
Session Type: Poster
Session Chair: Sergio Albani, European Union Satellite Centre
Track: Community Contributed Themes
Poster Area J

MOP2.PJ.1: Space-to-Seabed Maritime Infrastructure Surveillance with SAR, AIS, and DAS
Kristian Aalling Sørensen, Hasse Bülow Pedersen, Henning Heiselberg, Technical University of Denmark, Denmark
Poster Area J

MOP2.PJ.2: Geographically aware AIS trajectory forecasting with curriculum learning
Peder Heiselberg, Mathias Povelsen, Idil Turasi, Freja Berth, Jesus Nevarro, Technical University of Denmark, Denmark
Poster Area J

MOP2.PJ.3: architectures for discretized vessel trajectory prediction in resource-constrained settings
Peder Heiselberg, Andrea Sanvito, Antonio Riverso, Daniil Losev, Technical University of Denmark, Denmark
Poster Area J

MOP2.PJ.4: CRHT: a continuous regression hybrid transformer for vessel trajectory prediction with online cluster sampling
Peder Heiselberg, Alexander Schiøtz, Bertram Hage, Christian Rand, Felix Thomsen, Technical University of Denmark, Denmark
Poster Area J

MOP2.PJ.5: FROM SHIP WAKES TO PSEUDO-AIS: DARK VESSEL DETECTION WITH SENTINEL-1 AND SENTINEL-2
Andrea Mazzeo, Angela Carmen Cristofano, Maria Daniela Graziano, Alfredo Renga, University of Naples Federico II, Italy; Giuliano Vernengo, University of Genoa, Italy; Davide Bonaldo, Consiglio Nazionale delle Ricerche, Italy; Diego Villa, Nicola Petacco, University of Genoa, Italy; Gian Marco Scarpa, Federica Braga, Paolo Vavasori, Stefano Menegon, Consiglio Nazionale delle Ricerche, Italy
Poster Area J

MOP2.PJ.6: NASA’s Land, Atmosphere Near real-time Capability for Earth observation – bridging data systems and society today and into the future
Jenny Hewson, Diane Davies, NASA, United States
Poster Area J

MOP2.PJ.7: Adaptive Federated Learning for Ship Detection on Multi-Source Satellite Imagery
Tran-Vu La, EarthLab, Luxembourg; Yu Li, Thanh-Huy Nguyen, Patrick Matgen, Marco Chini, Luxembourg Institute of Science and Technology, Luxembourg