TH4.R7.1: DAM MONITORING WITH GROUND MOTION SERVICES – A CASE STUDY OF A GRAVITY DAM WITH THE GERMAN GROUND MOTION SERVICE
Clémence Dubois, Jonas Ziemer, Jannik Jänichen, Natascha Stumpf, Christoph Liedel, Friedrich Schiller University Jena, Germany; Michael Sabrowski, Thüringer Fernwasserversorgung, Germany; Christiane Schmullius, Friedrich Schiller University Jena, Germany
TH4.R7.2: A NOVEL DEEP LEARNING PROSPECTIVE URBAN GROWTH MODEL APPLIED TO MULTISPECTRAL SATELLITE DATA OVER THE CITY OF CORDOBA, ARGENTINA
María Sol Villella, Instituto Gulich, Argentina; Paolo Gamba, University of Pavia, Italy
TH4.R7.3: Improving Urban Tree Species Classification with High Resolution Satellite Imagery and Machine Learning
Romain Wenger, Clément Bressant, Lucie Roettele, LIVE CNRS UMR7362, France; Germain Forestier, IRIMAS UR 7499, France; Anne Puissant, LIVE CNRS UMR7362, France
TH4.R7.4: FROM EUROPEAN GROUND MOTION SERVICE TO DIFFERENTIAL DEFORMATION MAP FOR BUILDINGS
Saeedeh Shahbazi, Anna Barra, Riccardo Palamà, Michele Crosetto, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain
TH4.R7.5: LAND VALUATION USING AN INNOVATIVE MODEL COMBINING MACHINE LEARNING AND SPATIAL CONTEXT
Feride Tanrikulu, Timothy Haithcoat, Grant Scott, Matthew Foulkes, Ilker Ersoy, University of Missouri, United States
TH4.R7.6: URBAN LAND-USE CLASSIFICATION WITH MULTI-SOURCE SELF-SUPERVISED REPRESENTATION LEARNING AND CORRELATION MODELING
Ruiyi Yang, Wuhan University, China; Yu Su, Information Engineering University, China; Yanfei Zhong, Wuhan University, China
TH4.R7.7: TOWARDS A QUASI-GLOBAL ACCURACY ASSESSMENT OF BUILT-UP SURFACE ESTIMATES DERIVED FROM SENTINEL-2 MULTISPECTRAL DATA
Johannes H. Uhl, Martino Pesaresi, European Commission, Italy; Panagiotis Politis, Katarzyna Goch, European Dynamics S.A., Belgium; Michele Melchiorri, Thomas Kemper, European Commission, Italy
