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

TU3.R6: Harnessing Geospatial Technology and Machine Learning for Flood Management in Fluvial and Glacierized Catchments

Tuesday, 11 August, 13:45 - 15:00

Location: Cardozo

Session Type: Oral

Session Co-Chairs: Ashok Keshari, Indian Institute of Technology Delhi and Ramesh Singh, Chapman University and Sashikanta Sahoo, Punjab Remote Sensing Centre

Track: Community Contributed Themes

Tue, 11 Aug, 13:45 - 14:00

TU3.R6.1: IMPROVING OPERATIONAL SAR-BASED FLOOD INUNDATION MAPPING THROUGH PHYSICALLY-INFORMED POST-PROCESSING OF MACHINE LEARNING PREDICTIONS

Yun-Jae Choung, Steven Burian, The University of Alabama, United States; David Vallee, NOAA National Water Center, United States

Tue, 11 Aug, 14:00 - 14:15

TU3.R6.2: SENTINEL-1 SAR–BASED MAPPING OF THE 2024 EXTREME FLOOD EVENT IN THE PORTO ALEGRE METROPOLITAN REGION AND SURROUNDING AREAS, BRAZIL

Tania Hoffmann, National Institute for Space Research, Brazil; Paulo Silva, Eliezer Flores, Aeronautics Institute of Technology, Brazil; Andre Garcia, National Institute for Space Research, Brazil; Dimas Alves, Aeronautics Institute of Technology, Brazil; Angelica Giarolla, Marcos Adami, National Institute for Space Research, Brazil

Tue, 11 Aug, 14:15 - 14:30

TU3.R6.3: SAR SCATTERING MECHANISM SENSITIVE INDICES: AN APPROACH BEYOND BINARY FLOOD EXTENT MAP IN HETEROGENEOUS LANDSCAPES

Rajeev Ranjan, Ashok K. Keshari, Indian Institute of Technology Delhi, India; Erika Podest, NASA, California Institute of Technology, United States

Tue, 11 Aug, 14:30 - 14:45

TU3.R6.4: FLOOD-INVONET: MISH-INVOLUTION ASSISTED MULTI DILATION MULTI KERNEL IMPROVED U-NET FOR FLOOD MAPPING

Kavita Bathe, K. J. Somaiya Institute of Technology, India; S V Shiva Prasad Sharma, National Remote Sensing Centre, Indian Space Research Organisation, India; Vimal Mehta, K J Somaiya Institute of Technology, India; Devanand Bathe, K. J. Somaiya Institute of Technology, India

Tue, 11 Aug, 14:45 - 15:00

TU3.R6.5: Machine Learning Based Flood Detection and Assessment of Extreme Rainfall Induced Crop Damage Using Disaster Vegetation Damage Index (DVDI)

Sashikanta Sahoo, Jitesh Chandra, Punjab Remote Sensing Centre, India; Shubham Awasthi, Department of Earth Science and Engineering, United Kingdom; Sainik Bauri, Brijendra Pateriya, Punjab Remote Sensing Centre, India