6 citations · 7 across the 7 of their papers we have counts for
7 papers
Adaptive federated learning for ship detection across diverse satellite imagery sources
Tran-Vu La, Minh-Tan Pham, Yu Li +2
We investigate the application of Federated Learning (FL) for ship detection across diverse satellite datasets, offering a privacy-preserving solution that eliminates the need for…
Towards Digital Twin in Flood Forecasting with Data Assimilation Satellite Earth Observations -- A Proof-of-Concept in the Alzette Catchment
Thanh Huy Nguyen, Sukriti Bhattacharya, Jefferson S. Wong +4
Floods pose significant risks to human lives, infrastructure, and the environment. Timely and accurate flood forecasting plays a pivotal role in mitigating these risks. This study…
Urban Flood Mapping Using Satellite Synthetic Aperture Radar Data: A Review of Characteristics, Approaches and Datasets
Jie Zhao, Ming Li, Yu Li +2
Understanding the extent of urban flooding is crucial for assessing building damage, casualties and economic losses. Synthetic Aperture Radar (SAR) technology offers significant ad…
Multi-Sensor Diffusion-Driven Optical Image Translation for Large-Scale Applications
João Gabriel Vinholi, Marco Chini, Anis Amziane +3
Comparing images captured by disparate sensors is a common challenge in remote sensing. This requires image translation -- converting imagery from one sensor domain to another whil…
Early Flood Warning Using Satellite-Derived Convective System and Precipitation Data -- A Retrospective Case Study of Central Vietnam
Tran-Vu La, Thanh Huy Nguyen, Patrick Matgen +1
This paper addresses the challenges of an early flood warning caused by complex convective systems (CSs), by using Low-Earth Orbit and Geostationary satellite data. We focus on a s…
Estimating ensemble likelihoods for the Sentinel-1 based Global Flood Monitoring product of the Copernicus Emergency Management Service
Christian Krullikowski, Candace Chow, Marc Wieland +8
The Global Flood Monitoring (GFM) system of the Copernicus Emergency Management Service (CEMS) addresses the challenges and impacts that are caused by flooding. The GFM system prov…
Extracting localized information from a Twitter corpus for flood prevention
Etienne Brangbour, Pierrick Bruneau, Stéphane Marchand-Maillet +4
In this paper, we discuss the collection of a corpus associated to tropical storm Harvey, as well as its analysis from both spatial and topical perspectives. From the spatial persp…