IGARSS 2026 || Washington, D.C. || 9

TUP1.PI: Harnessing Geospatial Technology and Machine Learning for Flood Management in Fluvial and Glacierized Catchments

Poster

Tue, 11 Aug, 09:45 - 11:00

Location: TBD

Session Type: Poster

Track: Community Contributed Themes

TUP1.PI.1: RESEARCH ON SPACE-AIR-GROUND STEREO MONITORING AND IDENTIFICATION OF RIVER HYDRAULIC PARAMETERS

Cen Zhang, Beijing Water Science & Technology Institute, China

TUP1.PI.2: High-Resolution Flood Extent Detection Using Deep Learning with Random Forest–Derived Training Labels

Azizbek Nuriddinov, Ebrahim Ahmadisharaf, Florida State University, United States; Reza Alizadeh, Michigan State University, United States

TUP1.PI.4: A COMPREHENSIVE ASSESSMENT OF FLOODWATER DEPTH MODELS DURING EXTREME FLOOD EVENTS IN CHANNEL COUNTRY RIVER SYSTEM

ATUL KUMAR RAI, University of Wollongong, Australia; Rajeev Ranjan, Indian Institute of Technology Delhi, India; Timothy J Cohen, University of Wollongong, Australia; Moshe Armon, The Hebrew University of Jerusalem, Israel; Samuel J Marx, University of Wollongong, Australia

TUP1.PI.5: IMPACT OF CLIMATE CHANGE ON FLOOD EXTREMES IN BURHI GANDAK BASIN, INDIA USING DATA-DRIVEN FRAMEWORK INTEGRATED WITH EARTH OBSERVATIONS AND HYDRAULIC MODEL.

Kumar Lal Babu, Ashok K. Keshari, Indian Institute Of Technology, New Delhi, India

TUP1.PI.8: Harnessing Geospatial Technology and Machine Learning for Flood Management in Fluvial and Glacierized Catchments

Laxmi Joshi, Map Earth, India; Tushar Singh, University of North West Himalaya, Dehradun, India, India; Rohit Rai, Engrossone Technology, India

TUP1.PI.9: TRANSFORMER-BASED MODELS FOR OPERATIONAL URBAN FLOODWATER DEPTH ESTIMATION FROM EARTH OBSERVATION DATA

Jeffrey Blay, Leila Hashemi-Beni, North Carolina A&T State University, United States

TUP1.PI.10: A Multi-Sensor Data Fusion Framework for Natural Disaster Mitigation and Recovery

Hadia Rahmani, Amjad Gawanmeh, Shadi Atalla, Alavikunhu Panthakkan, Saed Tarapiah, University of Dubai, United Arab Emirates