Renaud Hostache
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View article: High Spatial Resolution Soil Moisture Mapping over Agricultural Field Integrating SMAP, IMERG, and Sentinel-1 Data in Machine Learning Models
High Spatial Resolution Soil Moisture Mapping over Agricultural Field Integrating SMAP, IMERG, and Sentinel-1 Data in Machine Learning Models Open
Soil moisture content (SMC) is a critical parameter for agricultural productivity, particularly in semi-arid regions, where irrigation practices are extensively used to offset water deficits and ensure decent yields. Yet, the socio-economi…
View article: U-NetMN and SegNetMN: Modified U-Net and SegNet models for bimodal SAR image segmentation
U-NetMN and SegNetMN: Modified U-Net and SegNet models for bimodal SAR image segmentation Open
Segmenting Synthetic Aperture Radar (SAR) images is crucial for many remote sensing applications, particularly water body detection. However, deep learning-based segmentation models often face challenges related to convergence speed and st…
View article: Evaluating the Sensitivity of Hydrological Models to Remotely Sensed Precipitation in a Transboundary Basin
Evaluating the Sensitivity of Hydrological Models to Remotely Sensed Precipitation in a Transboundary Basin Open
Accurate precipitation data is vital for hydrological modelling, particularly in transboundary basins with scarce hydro-climatic stations. This study evaluates the performance of 20 gridded precipitation products (GPPs), derived from remot…
View article: Soil Salinity Mapping of Plowed Agriculture Lands Combining Radar Sentinel-1 and Optical Sentinel-2 with Topographic Data in Machine Learning Models
Soil Salinity Mapping of Plowed Agriculture Lands Combining Radar Sentinel-1 and Optical Sentinel-2 with Topographic Data in Machine Learning Models Open
This study assesses the relative performance of Sentinel-1 and -2 and their combination with topographic information for plow agricultural land soil salinity mapping. A learning database made of 255 soil samples’ electrical conductivity (E…
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: 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: 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: Comparison of a conceptual rainfall-runoff model with an artificial neural network model for streamflow prediction
Comparison of a conceptual rainfall-runoff model with an artificial neural network model for streamflow prediction Open
Accurate streamflow forecasting can help minimizing the negative impacts of hydrological events such as floods and droughts. To address this challenge, we explore here artificial neural networks models (ANNs) for streamflow forecasting. Th…
View article: Hydrometeorological Extreme Events in Africa: The Role of Satellite Observations for Monitoring Pluvial and Fluvial Flood Risk
Hydrometeorological Extreme Events in Africa: The Role of Satellite Observations for Monitoring Pluvial and Fluvial Flood Risk Open
This article reviews the state of the art in the use of space-borne observations for analyzing extreme rainfall and flood events in Africa. Floods occur across many space and timescales, from very localized flash flood events to slow propa…
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: 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: 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…
View article: A Comparison of three deep learning-based methods for large-scale urban flood mapping using SAR data
A Comparison of three deep learning-based methods for large-scale urban flood mapping using SAR data Open
<p>Synthetic Aperture Radar (SAR)-based floodwater detection in urban areas remains challenging because of the complex urban environment. Generally, open water appears as dark in SAR intensity images due to low values of backscatteri…
View article: A porosity-based flood inundation modelling approach for enabling faster large scale simulations
A porosity-based flood inundation modelling approach for enabling faster large scale simulations Open
Floods are among the most devastating natural hazards in the world. With climate change and growing urbanisation, floods are expected to become more frequent and severe in the future. Hydrodynamic models are powerful tools for flood hazard…
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 non-linear systems and for its re…
View article: Urban-Aware U-Net for Large-Scale Urban Flood Mapping Using Multitemporal Sentinel-1 Intensity and Interferometric Coherence
Urban-Aware U-Net for Large-Scale Urban Flood Mapping Using Multitemporal Sentinel-1 Intensity and Interferometric Coherence Open
Due to the complexity of backscattering mechanisms in built-up areas, the synthetic aperture radar (SAR)-based mapping of floodwater in urban areas remains challenging. Open areas affected by flooding have low backscatter due to the specul…
View article: Mapping Floods in Urban Areas From Dual-Polarization InSAR Coherence Data
Mapping Floods in Urban Areas From Dual-Polarization InSAR Coherence Data Open
International audience
View article: Deriving exclusion maps from C-band SAR time-series in support of floodwater mapping
Deriving exclusion maps from C-band SAR time-series in support of floodwater mapping Open
Synthetic Aperture Radar (SAR) intensity is used as an input to many flood-mapping algorithms. The appearance of floodwater tends to cause a substantial decrease of backscatter intensity over scarcely vegetated terrain. However, limitation…
View article: Assimilation of probabilistic flood maps from SAR data into a coupled hydrologic–hydraulic forecasting model: a proof of concept
Assimilation of probabilistic flood maps from SAR data into a coupled hydrologic–hydraulic forecasting model: a proof of concept Open
Coupled hydrologic and hydraulic models represent powerful tools for simulating streamflow and water levels along the riverbed and in the floodplain. However, input data, model parameters, initial conditions, and model structure represent …