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

Publications associées (27)

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Investigation of microbial community dynamics in soil during variable hydrological forcing

Simiao Wang

Climate change is expected to alter the temporal distribution of precipitation events, leading to prolonged drought periods and an increased frequency of extreme precipitation events. Changes in precipitation pattern will directly affect soil moisture dyna ...

EPFL2024

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

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

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

Soil warming alters tree water use and canopy stomatal conductance in a mixed subtropical forest

Charlotte Grossiord, Christoph Bachofen

As air temperature and vapor pressure deficit (VPD) increase continuously, forests are losing more water through evapotranspiration, with large consequences for local and global hydrological cycles. In regions with high vegetation cover, soil warming can b ...

Elsevier2024

Residual-based attention in physics-informed neural networks

Nikolaos Stergiopoulos, Sokratis Anagnostopoulos

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Elsevier Science Sa2024

Data and scripts for "Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling"

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

This repository contains field observations and processed data from the Weather Research and Forecasting (WRF) model simulations and the Cloud Resolving Model Radar Simulator (CR-SIM), alongside scripts designed to reproduce the figures presented in the pa ...

Zenodo2024

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

Ghost imaging using two SPAD array detectors: a parameter study towards the realization of a 3D quantum microscope

Edoardo Charbon, Claudio Bruschini, Paul Mos, Yang Lin

Quantum ghost imaging can be an important tool in making optical measurements. One of the most useful aspects of ghost imaging is the unique ability to correlate two sets of independently collected information. We aim to use the principles of ghost imaging ...

Spie-Int Soc Optical Engineering2024

Snowfall microphysics: a dual-frequency and Doppler spectral radar perspective

Anne-Claire Marie Billault--Roux

Snowfall is an essential component of the hydrological cycle, as it is involved in most precipitation on Earth, either directly as snow falling to the ground or indirectly as rain melted from snow. At the same time, the ice phase of clouds and precipitatio ...

EPFL2023

Privacy-Preserving Machine Learning on Graphs

Sina Sajadmanesh

Graph Neural Networks (GNNs) have emerged as a powerful tool for learning on graphs, demonstrating exceptional performance in various domains. However, as GNNs become increasingly popular, new challenges arise. One of the most pressing is the need to ensur ...

EPFL2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Anne-Claire Marie Billault--Roux, Gionata Ghiggi

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan region

Danya Li

Crop maps are crucial for agricultural monitoring and food management and can additionally support domain-specific applications, such as setting cold supply chain infrastructure in developing countries. Machine learning (ML) models, combined with freely-av ...

Elsevier2023

CellCharter reveals spatial cell niches associated with tissue remodeling and cell plasticity

Albert Santamaria Martinez, Daniele Tavernari

Tissues are organized in cellular niches, the composition and interactions of which can be investigated using spatial omics technologies. However, systematic analyses of tissue composition are challenged by the scale and diversity of the data. Here we pres ...

Nature Portfolio2023

AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES

Lloyd Haydn Hughes

Taking advantage of Capella's ability to dwell on a target for an extended period of time (nominally 30s) in its spotlight (SP) mode, an unsupervised methodology for detecting moving targets in this data is presented in this paper. By colourizing short seg ...

IEEE2023

Doppler spectra collected by weather and cloud radars during the POPE 2020 campaign at Princess Elisabeth Antarctica

Alexis Berne, Alfonso Ferrone

This repository contains the datasets of Doppler spectra collected by two meteorological radars in the vicinity of the Belgian research base Princess Elisabeth Antarctica (PEA). The measurement campaign has been conducted by the Environmental Remote S ...

Zenodo2023

Global Mapping of Potential and Climatic Plant‐Available Soil Water

Dani Or, Sara Bonetti

The estimation of plant-available soil water (PASW) is essential to quantify transpiration fluxes, the onset of heatwaves, irrigation water management, land-use decisions, vegetation ecology, and land surface memory in climate models. PASW is the amount of ...

2023

Linking Soil Structure, Hydraulic Properties, and Organic Carbon Dynamics: A Holistic Framework to Study the Impact of Climate Change and Land Management

Sara Bonetti

Climate change and unsustainable land management practices have resulted in extensive soil degradation, including alteration of soil structure (i.e., aggregate and pore size distributions), loss of soil organic carbon, and reduction of water and nutrient h ...

2023

Methodology for selecting measurement points that optimize information gain for model updating

Ian Smith, Numa Joy Bertola

Information collected through sensor measurements has the potential to improve knowledge of complex-system behavior, leading to better decisions related to system management. In this situation, and particularly when using digital twins, the quality of sens ...

2023

Unlocking a multimodal archive of Southern Chinese martial arts through embodied cues

Sarah Irene Brutton Kenderdine, Yumeng Hou

Purpose: Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have created new avenues to open up cultural data resources, yet mainly as appa ...

2023

Supercell Thunderstorms in the Alpine Region - From Weather Radar Observations to Idealized Modeling

Monika Feldmann

The high-impact nature and increasing occurrence of severe weather phenomena pushes forward research on their occurrence and improving our understanding thereof. Supercell thunderstorms are the focus of much severe convective research, as they represent on ...

EPFL2023