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
Session:
TU3.R6: Harnessing Geospatial Technology and Machine Learning for Flood Management in Fluvial and Glacierized Catchments Oral
Track:
Community Contributed Themes
Location:
Cardozo
Presentation Time:
Tuesday, 11 August, 14:30 - 14:45
Session Co-Chairs:
Ashok Keshari, Indian Institute of Technology Delhi and Ramesh Singh, Chapman University and Sashikanta Sahoo, Punjab Remote Sensing Centre
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Session TU3.R6
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
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
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
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
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
Resources
No resources available.