5 papers
Urban Flood Observations: A hand-labeled training and validation dataset of post-flood inundation
Rohit Mukherjee, Hannah K. Friedrich, Beth Tellman +5
Urban flooding affects lives and infrastructure worldwide. Mapping inundation in complex urban environments from satellite imagery remains challenging due to limited spatial resolu…
Cryo-Bench: Benchmarking Foundation Models for Cryosphere Applications
Saurabh Kaushik, Lalit Maurya, Beth Tellman +1
Geo-Foundation Models (GFMs) have been evaluated across diverse Earth observation task including multiple domains and have demonstrated strong potential of producing reliable maps…
Assessing the value of Geo-Foundational Models for Flood Inundation Mapping: Benchmarking models for Sentinel-1, Sentinel-2, and Planetscope for end-users
Saurabh Kaushik, Lalit Maurya, Elizabeth Tellman +1
Geo-Foundational Models (GFMs) enable fast and reliable extraction of spatiotemporal information from satellite imagery, improving flood inundation mapping by leveraging location a…
Prithvi-Complimentary Adaptive Fusion Encoder (CAFE): unlocking full-potential for flood inundation mapping
Saurabh Kaushik, Lalit Maurya, Beth Tellman
Geo-Foundation Models (GFMs), have proven effective in diverse downstream applications, including semantic segmentation, classification, and regression tasks. However, in case of f…
GLACIA: Instance-Aware Positional Reasoning for Glacial Lake Segmentation via Multimodal Large Language Model
Lalit Maurya, Saurabh Kaushik, Beth Tellman
Glacial lake monitoring bears great significance in mitigating the anticipated risk of Glacial Lake Outburst Floods. However, existing segmentation methods based on convolutional n…