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Deep Learning‐based Semantic Segmentation in Remote Sensing

Semantic segmentation consists of the generation of a categorical map, given an image in which each pixel of the image is automatically assigned a class. Deep learning allows the influence of the pixel's context to be learned by capturing the non-linear re ...

Wiley2021

Overview: Integrative and Comprehensive Understanding on Polar Environments (iCUPE) – concept and initial results

Julia Schmale, Imad El Haddad, Jakob Boyd Pernov, Jenny Thomas

The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. We set up the ERA-PLANET ...

Copernicus Publications2020

Sun-synchronous repeat ground tracks and other useful orbits for future space missions

Sun Hee Kim, Luzius Gregor Kronig

The development of oceanography and meteorology has greatly benefited from satellite-based data of Earth's atmosphere and ocean. Traditional Earth observation missions have utilised Sun-synchronous orbits with repeat ground tracks due to their advantages i ...

2020

Three-dimensional radiative transfer effects on airborne and ground-based trace gas remote sensing

Alexis Berne, Dominik Brunner, Thomas Wagner

Air mass factors (AMFs) are used in passive trace gas remote sensing for converting slant column densities (SCDs) to vertical column densities (VCDs). AMFs are traditionally computed with 1D radiative transfer models assuming horizontally homogeneous condi ...

2020

Foreword to the Special Issue on Computer Vision-Based Approaches for Earth Observation

Devis Tuia

The five papers in this special section focus on computer vision-based approaches for Earth observation. These papers followed a series of events promoting works at the interface between computer vision and remote sensing: the special sessions organized at ...

2020

Joint Anomaly Detection and Spectral Unmixing for Planetary Hyperspectral Images

Harold Gabriel Eugène Justin Clenet, Nicolas Courty

Hyperspectral (HS) images are commonly used in the context of planetary exploration, particularly for the analysis of the composition of planets. As several instruments have been sent throughout the Solar System, a huge quantity of data is getting availabl ...

Institute of Electrical and Electronics Engineers2016

Efficient global optimization of reservoir geomechanical parameters based on synthetic aperture radar-derived ground displacements

Francesco Comola

When large volumes of fluids are removed from or injected into underground formations for, e.g., hydrocarbon and water production, CO_2 storage, gas storage, and geothermal energy exploitation, monitoring of surface deformations coupled to numerical modeli ...

Soc Exploration Geophysicists2016

Synergy of hyperspectral and microwave remote sensing data to derive bio- and geo-physical parameters for land applications

Jelena Stamenkovic

Retrieval of bio/geophysical variables from remote sensing imagery is an important research field. Due to the development and availability of different EO satellites, especially the ones with hyperspectral sensors, the combined use of radar and optical ima ...

EPFL2015

Detection of Floods In Sar Images with Non-Linear Kernel Clustering and Topographic Prior

Jean-Philippe Thiran, Devis Tuia, Frank Grégoire Jean de Morsier, Maurice Borgeaud

After a major flood catastrophe, a precious information is the delineation of the affected areas. Remote sensing imagery, especially synthetic aperture radar, allows to obtain a global and complete view of the situation. However, the detection of the flood ...

2013

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Efficient global optimization of reservoir geomechanical parameters based on synthetic aperture radar-derived ground displacements

Francesco Comola

Soc Exploration Geophysicists2016

Three-dimensional radiative transfer effects on airborne and ground-based trace gas remote sensing

Alexis Berne, Dominik Brunner, Thomas Wagner

2020

Synergy of hyperspectral and microwave remote sensing data to derive bio- and geo-physical parameters for land applications

Jelena Stamenkovic

EPFL2015

Detection of Floods In Sar Images with Non-Linear Kernel Clustering and Topographic Prior

Jean-Philippe Thiran, Devis Tuia, Frank Grégoire Jean de Morsier, Maurice Borgeaud

2013