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

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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

Chattez avec Graph Search

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

Investigation of microbial community dynamics in soil during variable hydrological forcing

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

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

Residual-based attention in physics-informed neural networks

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

Aggregating Spatial and Photometric Context for Photometric Stereo

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

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

Privacy-Preserving Machine Learning on Graphs

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

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

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

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

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

Global Mapping of Potential and Climatic Plant‐Available Soil Water

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

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

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

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