Multisource and multitemporal data fusion in remote sensing: A comprehensive review of the state of the art
This article brings together the advances of multisource and multitemporal data fusion
approaches with respect to the various research communities and provides a thorough and …
approaches with respect to the various research communities and provides a thorough and …
Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources
This paper reviews the most important information fusion data-driven algorithms based on
Machine Learning (ML) techniques for problems in Earth observation. Nowadays we …
Machine Learning (ML) techniques for problems in Earth observation. Nowadays we …
Towards global flood mapping onboard low cost satellites with machine learning
Spaceborne Earth observation is a key technology for flood response, offering valuable
information to decision makers on the ground. Very large constellations of small, nano …
information to decision makers on the ground. Very large constellations of small, nano …
Fully convolutional neural network for rapid flood segmentation in synthetic aperture radar imagery
Rapid response to natural hazards, such as floods, is essential to mitigate loss of life and the
reduction of suffering. For emergency response teams, access to timely and accurate data is …
reduction of suffering. For emergency response teams, access to timely and accurate data is …
A fully automated TerraSAR-X based flood service
In this paper, a fully automated processing chain for near real-time flood detection using
high resolution TerraSAR-X Synthetic Aperture Radar (SAR) data is presented. The …
high resolution TerraSAR-X Synthetic Aperture Radar (SAR) data is presented. The …
Microwave remote sensing of flood inundation
GJP Schumann, DK Moller - Physics and Chemistry of the Earth, Parts a/b/c, 2015 - Elsevier
Flooding is one of the most costly natural disasters and thus mapping, modeling and
forecasting flood events at various temporal and spatial scales is important for any flood risk …
forecasting flood events at various temporal and spatial scales is important for any flood risk …
A Bayesian network for flood detection combining SAR imagery and ancillary data
Accurate flood mapping is important for both planning activities during emergencies and as
a support for the successive assessment of damaged areas. A valuable information source …
a support for the successive assessment of damaged areas. A valuable information source …
Flood hazard and flood risk assessment using a time series of satellite images: A case study in Namibia
In this article, the use of time series of satellite imagery to flood hazard mapping and flood
risk assessment is presented. Flooded areas are extracted from satellite images for the flood …
risk assessment is presented. Flooded areas are extracted from satellite images for the flood …
Semantic segmentation of remote-sensing images through fully convolutional neural networks and hierarchical probabilistic graphical models
M Pastorino, G Moser, SB Serpico… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Deep learning (DL) is currently the dominant approach to image classification and
segmentation, but the performances of DL methods are remarkably influenced by the …
segmentation, but the performances of DL methods are remarkably influenced by the …
Blending MODIS and Landsat images for urban flood mapping
Satellite images provide important data sources for monitoring flood disasters. However, the
trade-off between spatial and temporal resolutions of current satellite sensors limits their …
trade-off between spatial and temporal resolutions of current satellite sensors limits their …