Quantifying urban flood extent using satellite imagery and machine learning
The risk of floods from tropical storms is increasing due to climate change and human
development. Maps of past flood extents can aid in planning and mitigation efforts to …
development. Maps of past flood extents can aid in planning and mitigation efforts to …
UrbanSARFloods: Sentinel-1 SLC-Based Benchmark Dataset for Urban and Open-Area Flood Mapping
Due to its cloud-penetrating capability and independence from solar illumination satellite
Synthetic Aperture Radar (SAR) is the preferred data source for large-scale flood mapping …
Synthetic Aperture Radar (SAR) is the preferred data source for large-scale flood mapping …
[HTML][HTML] An integrated framework for satellite-based flood mapping and socioeconomic risk analysis: A case of Thailand
N Prasertsoong, N Puttanapong - Progress in Disaster Science, 2024 - Elsevier
This study introduces a novel approach to monitoring floods and estimating socioeconomic
impacts in Thailand. The approach leverages advancements in geospatial data, employing …
impacts in Thailand. The approach leverages advancements in geospatial data, employing …
Rapid Adaptation of Earth Observation Foundation Models for Segmentation
This study investigates the efficacy of Low-Rank Adaptation (LoRA) in fine-tuning Earth
Observation (EO) foundation models for flood segmentation. We hypothesize that LoRA, a …
Observation (EO) foundation models for flood segmentation. We hypothesize that LoRA, a …
Mapping Global Floods with 10 Years of Satellite Radar Data
A Misra, K White, SF Nsutezo, W Straka… - arXiv preprint arXiv …, 2024 - arxiv.org
Floods cause extensive global damage annually, making effective monitoring essential.
While satellite observations have proven invaluable for flood detection and tracking …
While satellite observations have proven invaluable for flood detection and tracking …
Data, guidelines and ethics for managing flood risk when people are already forcibly displaced
Data, guidelines and ethics for managing flood risk when people are already forcibly
displaced Page 1 ACCEPTED MANUSCRIPT • OPEN ACCESS Data, guidelines and ethics …
displaced Page 1 ACCEPTED MANUSCRIPT • OPEN ACCESS Data, guidelines and ethics …
Live twinning: A vision of ml enabled assets in leo for rapid response to natural catastrophes
Situational awareness during a catastrophic natural disaster, such as a flood, wildfire,
tsunami or earthquake is often described by disaster responders as an information 'fog'as …
tsunami or earthquake is often described by disaster responders as an information 'fog'as …
Rapid Distributed Fine-tuning of a Segmentation Model Onboard Satellites
M Plumridge, R Maråk, C Ceccobello, P Gómez… - arXiv preprint arXiv …, 2024 - arxiv.org
Segmentation of Earth observation (EO) satellite data is critical for natural hazard analysis
and disaster response. However, processing EO data at ground stations introduces delays …
and disaster response. However, processing EO data at ground stations introduces delays …
Multimodal and Multitemporal Data Fusion for Flood Extent Segmentation Exploiting Kurosiwo and WorldFloods Sentinel Datasets
In this work, we introduce a synergistic framework to perform multitemporal and multimodal
flood extent mapping from multispectral and SAR satellite image time series. Two state-of …
flood extent mapping from multispectral and SAR satellite image time series. Two state-of …
Enhancing global flood detection and forecasting using deep learning
MF Mir - 2023 - politesi.polimi.it
Flood prediction is crucial for risk management and adaptation to reduce the impacts caused
by increasing hydrological risk. Current continental or global hydrological models, such as …
by increasing hydrological risk. Current continental or global hydrological models, such as …