Publications associées à Copernicus (programme)

A seasonal snowpack model forced with dynamically downscaled forcing data resolves hydrologically relevant accumulation patterns

Michael Lehning, Tobias Jonas, Dylan Stewart Reynolds

The Mountain snowpack stores months of winter precipitation at high elevations, supplying snowmelt to lowland areas in drier seasons for agriculture and human consumption worldwide. Accurate seasonal predictions of the snowpack are thus of great importance ...

Frontiers Media Sa2024

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Devis Tuia, Gaston Jean Lenczner, Thiên-Anh Claris Nguyen, Marc Conrad Russwurm

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Elsevier Science Inc2024

Unraveling ice multiplication in winter orographic clouds via in-situ observations, remote sensing and modeling

Athanasios Nenes, Alexis Berne, Satoshi Takahama, Georgia Sotiropoulou, Paraskevi Georgakaki, Romanos Foskinis, Kunfeng Gao, Anne-Claire Marie Billault--Roux

Recent years have shown that secondary ice production (SIP) is ubiquitous, affecting all clouds from polar to tropical regions. SIP is not described well in models and may explain biases in warm mixed-phase cloud ice content and structure. Through modeling ...

Nature Portfolio2024

Monitoring Mesoscale to Submesoscale Processes in Large Lakes with Sentinel-1 SAR Imagery: The Case of Lake Geneva

David Andrew Barry, Ulrich Lemmin, Seyed Mahmood Hamze Ziabari, Mehrshad Foroughan

As in oceans, large-scale coherent circulations such as gyres and eddies are ubiquitous features in large lakes that are subject to the Coriolis force. They play a crucial role in the horizontal and vertical distribution of biological, chemical and physica ...

2022

Humans are Poor Few-Shot Classifiers for Sentinel-2 Land Cover

Devis Tuia, Marc Conrad Russwurm

Learning to predict accurately from a few data samples is a central challenge in modern data-hungry machine learning. On natural images, human vision typically outperforms deep learning approaches on few-shot learning. However, we hypothesize that aerial a ...

IEEE2022

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

Tamar Kohn, Alfred Johny Wüest, Damien Bouffard, Chaojie Li

Propelled by the rapid development of equipment, technology and computational power, the monitoring and simulation of the hydrodynamics in lakes have steadily advanced. In contrast, water quality simulations are more difficult to implement, due to the diff ...

Elsevier2022

Preprocessing Antarctic Weather Station (AWS) data in python

Michael Lehning, Franziska Gerber

There are many sources providing atmospheric weather station data for the Antarctic continent. However, variable naming, timestamps and data types are highly variable between the different sources. The published python code intends to make processing of di ...

EPFL Infoscience2022

Evaluating a prediction system for snow management

Michael Lehning

The evaluation of snowpack models capable of accounting for snow management in ski resorts is a major step towards acceptance of such models in supporting the daily decision-making process of snow production managers. In the framework of the EU Horizon 202 ...

COPERNICUS GESELLSCHAFT MBH2021

Self-supervised Pre-training Enhances Change Detection in Sentinel-2 Imagery

Devis Tuia, Diego Marcos Gonzalez

While annotated images for change detection using satellite imagery are scarce and costly to obtain, there is a wealth of unlabeled images being generated every day. In order to leverage these data to learn an image representation more adequate for change ...

Springer, Cham2021

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Copernicus (programme)

A seasonal snowpack model forced with dynamically downscaled forcing data resolves hydrologically relevant accumulation patterns

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Unraveling ice multiplication in winter orographic clouds via in-situ observations, remote sensing and modeling

Monitoring Mesoscale to Submesoscale Processes in Large Lakes with Sentinel-1 SAR Imagery: The Case of Lake Geneva

Humans are Poor Few-Shot Classifiers for Sentinel-2 Land Cover

Australian Bushfires (2019-2020): Aerosol Optical Properties and Radiative Forcing

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

Preprocessing Antarctic Weather Station (AWS) data in python

Evaluating a prediction system for snow management

Self-supervised Pre-training Enhances Change Detection in Sentinel-2 Imagery

Graph Chatbot

Chattez avec Graph Search

A seasonal snowpack model forced with dynamically downscaled forcing data resolves hydrologically relevant accumulation patterns

Unraveling ice multiplication in winter orographic clouds via in-situ observations, remote sensing and modeling

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Humans are Poor Few-Shot Classifiers for Sentinel-2 Land Cover

Australian Bushfires (2019-2020): Aerosol Optical Properties and Radiative Forcing

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

Evaluating a prediction system for snow management

Monitoring Mesoscale to Submesoscale Processes in Large Lakes with Sentinel-1 SAR Imagery: The Case of Lake Geneva

Self-supervised Pre-training Enhances Change Detection in Sentinel-2 Imagery