Patrick Matgen
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View article: Extraction of built-up areas using Sentinel-1 and Sentinel-2 data with automated training data sampling and label noise robust cross-fusion neural networks
Extraction of built-up areas using Sentinel-1 and Sentinel-2 data with automated training data sampling and label noise robust cross-fusion neural networks Open
Up-to-date mapping of built-up areas is of paramount importance for urban planning, environmental monitoring, and disaster management. In recent years, there has been a growing interest in employing supervised machine learning and deep lea…
View article: Building a global archive of flood events for the last decade based on Sentinel-
Building a global archive of flood events for the last decade based on Sentinel- Open
The observation of floods from space using Synthetic Aperture Radars (SAR) is a powerful means to understand how inundations unfold across space and time, together with the ensuing impacts. The systematic quantification of the extension of…
View article: Multisensor Diffusion-Driven Optical Image Translation for Large-Scale Applications
Multisensor Diffusion-Driven Optical Image Translation for Large-Scale Applications Open
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 while preserving the original content. Denoising Diffusion Impl…
View article: Urban Flood Mapping Using Satellite Synthetic Aperture Radar Data: A Review of Characteristics, Approaches and Datasets
Urban Flood Mapping Using Satellite Synthetic Aperture Radar Data: A Review of Characteristics, Approaches and Datasets Open
Understanding the extent of urban flooding is crucial for assessing building damage, casualties and economic losses. Synthetic Aperture Radar (SAR) technology offers significant advantages for mapping flooded urban areas due to its ability…
View article: Monitoring of Spatio-Temporal Variations of Oil Slicks via the Collocation of Multi-Source Satellite Images
Monitoring of Spatio-Temporal Variations of Oil Slicks via the Collocation of Multi-Source Satellite Images Open
Monitoring oil drift by integrating multi-source satellite imagery has been a relatively underexplored practice due to the limited time-sampling of datasets. However, this limitation has been mitigated by the emergence of new satellite con…
View article: Combining SAR imagery and topography for the automatic retrieval of floodwater depth maps
Combining SAR imagery and topography for the automatic retrieval of floodwater depth maps Open
International audience
View article: A Localized Particle Filtering Approach to Advance Flood Frequency Estimation at Large Scale Using Satellite Synthetic Aperture Radar Image Collection and Hydrodynamic Modelling
A Localized Particle Filtering Approach to Advance Flood Frequency Estimation at Large Scale Using Satellite Synthetic Aperture Radar Image Collection and Hydrodynamic Modelling Open
This study describes a method that combines synthetic aperture radar (SAR) data with shallow-water modeling to estimate flood hazards at a local level. The method uses particle filtering to integrate flood probability maps derived from SAR…
View article: Optical Image-to-Image Translation Using Denoising Diffusion Models: Heterogeneous Change Detection as a Use Case
Optical Image-to-Image Translation Using Denoising Diffusion Models: Heterogeneous Change Detection as a Use Case Open
We introduce an innovative deep learning-based method that uses a denoising diffusion-based model to translate low-resolution images to high-resolution ones from different optical sensors while preserving the contents and avoiding undesire…
View article: Early Flood Warning Using Satellite-Derived Convective System and Precipitation Data -- A Retrospective Case Study of Central Vietnam
Early Flood Warning Using Satellite-Derived Convective System and Precipitation Data -- A Retrospective Case Study of Central Vietnam Open
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 sequence of extreme events that took place in central Vietna…
View article: Towards Digital Twin in Global Flood Forecasting - A Proof-of-Concept in Severn catchment and Alzette catchment
Towards Digital Twin in Global Flood Forecasting - A Proof-of-Concept in Severn catchment and Alzette catchment Open
Advancements in Earth Observation, coupled with the swift progress in big data analysis and access to distributed computing and storage, open up exciting possibilities for the development of Digital Twins of the Earth. These Digital Twins …
View article: Assimilation of probabilistic flood maps into large scale hydraulic models to retrieve missing river geometry data using a tempered particle filter
Assimilation of probabilistic flood maps into large scale hydraulic models to retrieve missing river geometry data using a tempered particle filter Open
MO1.R7: Topographic and Hydrologic Mapping
View article: On the potential of Sentinel-1 for sub-field scale soil moisture monitoring
On the potential of Sentinel-1 for sub-field scale soil moisture monitoring Open
Soil moisture (SM) datasets at high spatial resolutions are beneficial for a wide range of applications, such as monitoring and prediction of hydrological extremes, numerical weather prediction, and precision agriculture. For large scale a…
View article: Estimating ensemble likelihoods for the Sentinel-1 based Global Flood Monitoring product of the Copernicus Emergency Management Service
Estimating ensemble likelihoods for the Sentinel-1 based Global Flood Monitoring product of the Copernicus Emergency Management Service Open
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 provides global, near-real time flood extent masks for each new…
View article: Estimating ensemble likelihoods for the Sentinel-1 based Global Flood Monitoring product of the Copernicus Emergency Management Service
Estimating ensemble likelihoods for the Sentinel-1 based Global Flood Monitoring product of the Copernicus Emergency Management Service Open
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 provides global, near-real time flood extent masks for each new…
View article: Estimating ensemble likelihoods for the Sentinel-1 based Global Flood Monitoring product of the Copernicus Emergency Management Service
Estimating ensemble likelihoods for the Sentinel-1 based Global Flood Monitoring product of the Copernicus Emergency Management Service Open
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 provides global, near-real time flood extent masks for each new…
View article: Reinvestigating Groundwater Drought Using In Situ and GRACE Data
Reinvestigating Groundwater Drought Using In Situ and GRACE Data Open
Groundwater plays a unique role in the terrestrial water cycle. It is one of the prime sources of water during periods of severe drought. Depletion of groundwater reaching certain thresholds substantially lead to the degradation of water q…
View article: A likelihood analysis of the Global Flood Monitoring ensemble product
A likelihood analysis of the Global Flood Monitoring ensemble product Open
Flooding is a natural disaster that can have devastating impacts on communities and individuals, causing significant damage to infrastructure, loss of life, and economic disruption. The Global Flood Monitoring (GFM) system of the Copernicu…
View article: High resolution soil moisture drought monitoring over Luxembourg
High resolution soil moisture drought monitoring over Luxembourg Open
With the emergence of accurate high resolution remotely sensed datasets of hydrological variables, opportunities arise to study hydrological processes at an unprecedented scale and resolution. We took this opportunity to study spatiotempor…
View article: Insight of deep convection and sea surface wind gusts link through collocated GEO and LEO data
Insight of deep convection and sea surface wind gusts link through collocated GEO and LEO data Open
Convective system (CS) is an extreme weather event occurring regularly over the subtropical and tropical regions such as the Gulf of Guinea, the Gulf of Mexico, Lake Victoria, Southeast Asia, India, and Australia. Certain CS types, i.e., m…
View article: Making use of multi-sensor satellite imagery for oil spill observation and oil drift monitoring
Making use of multi-sensor satellite imagery for oil spill observation and oil drift monitoring Open
Over the last ten years, satellite imagery has become one of the most effective means to observe offshore oil spills, especially over a large area, thanks to their high spatial resolution and wide swath coverage. In particular, the use of …
View article: Estimating Ensemble Likelihoods for the Sentinel-1-Based Global Flood Monitoring Product of the Copernicus Emergency Management Service
Estimating Ensemble Likelihoods for the Sentinel-1-Based Global Flood Monitoring Product of the Copernicus Emergency Management Service Open
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 provides global, near-real time flood extent masks for each new…
View article: On the Use of Native Resolution Backscatter Intensity Data for Optimal Soil Moisture Retrieval
On the Use of Native Resolution Backscatter Intensity Data for Optimal Soil Moisture Retrieval Open
The accuracy of soil moisture estimated from synthetic aperture radar (SAR) backscatter data at high resolutions is limited by speckle. A common practice to mitigate speckle is to multilook the data prior to retrieving soil moisture. While…
View article: A novel approach for assimilating SAR derived floodextent map into flood forecasting model: the temperedparticle filter
A novel approach for assimilating SAR derived floodextent map into flood forecasting model: the temperedparticle filter Open
<p>Data Assimilation can improve forecast accuracy of flood inundation models by an optimal combination of uncertain model simulations and observations. Particle Filter (PF) has gained interest in the research community for its abili…
View article: Imaging flood depth from space: a method based on the fusion of topography and synthetic aperture radar data
Imaging flood depth from space: a method based on the fusion of topography and synthetic aperture radar data Open
<p>With growing urbanisation and climate change, flooding is likely to become even more frequent and severe. &#160;Therefore, it is essential to constantly monitor water level changes at a large scale. Synthetic Aperture Radar (S…
View article: A joint assimilation of satellite soil moisture and flood extent maps to improve a flood hazard modelling.
A joint assimilation of satellite soil moisture and flood extent maps to improve a flood hazard modelling. Open
<p>The main objective of this study is to investigate how innovative satellite Earth observation techniques that allow for the estimation of soil moisture and the mapping of flood extents can help in reducing errors and uncertainties…
View article: The role of satellite information in forecasting, modeling, and mapping the 2019 Mozambique flood
The role of satellite information in forecasting, modeling, and mapping the 2019 Mozambique flood Open
The application and value of the Global Flood Monitoring System (GFMS) and various remote‐sensing‐based flood products are examined in the context of the severe flood event in Mozambique associated with Cyclone Idai in March 2019. Short‐te…
View article: A Tempered Particle Filter to Enhance the Assimilation of SAR‐Derived Flood Extent Maps Into Flood Forecasting Models
A Tempered Particle Filter to Enhance the Assimilation of SAR‐Derived Flood Extent Maps Into Flood Forecasting Models Open
Data assimilation (DA) is a powerful tool to optimally combine uncertain model simulations and observations. Among DA techniques, the particle filter (PF) has gained attention for its capacity to deal with nonlinear systems and for its rel…