Publications related to Pléiades (satellite)

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

Stay close, but not too close: aerial image analysis reveals patterns of social distancing in seal colonies

Devis Tuia, Benjamin Alexander Kellenberger

Many species aggregate in dense colonies. Species-specific spatial patterns provide clues about how colonies are shaped by various (a)biotic factors, including predation, temperature regulation or disease transmission. Using aerial imagery, we examined the ...

2023

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

Classification of Tropical Deforestation Drivers with Machine Learning and Satellite Image Time Series

Devis Tuia, Jan Pisl, Marc Conrad Russwurm, Lloyd Haydn Hughes

Tropical deforestation is a major environmental problem with severe consequences such as carbon emissions or biodiversity loss. While much research focuses on monitoring and mapping deforestation, less attention is paid to understanding the various reasons ...

The Institute of Electrical and Electronics Engineers, Inc.2023

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

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

Semantic Segmentation of Remote Sensing Images With Sparse Annotations

Devis Tuia

Training convolutional neural networks (CNNs) for very high-resolution images requires a large quantity of high-quality pixel-level annotations, which is extremely labor-intensive and time-consuming to produce. Moreover, professional photograph interpreter ...

2022

Developing a UV climatology for public health purposes using satellite data

Athanasios Nenes, David Vernez

The effects of solar ultraviolet (UV) radiation on life on Earth differ greatly. While overexposure to UV rays is harmful, small amounts of exposure are necessary for the synthesis of Vitamin D and good health. To optimize individual exposure to solar UV, ...

2021

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

A deep learning framework for matching of SAR and optical imagery

Devis Tuia, Sylvain Lobry, Lloyd Haydn Hughes

SAR and optical imagery provide highly complementary information about observed scenes. A combined use of these two modalities is thus desirable in many data fusion scenarios. However, any data fusion task requires measurements to be accurately aligned. Wh ...

2020

Citizen Visual Search Engine: Detection and Curation of Urban Objects

Jeffrey Huang, Immanuel Chee Beng Koh

Increasingly, the ubiquity of satellite imagery has made the data analysis and machine learning of large geographical datasets one of the building blocks of visuospatial intelligence. It is the key to discover current (and predict future) cultural, social, ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

The Importance of Systematic Spatial Variability in the Surface Heat Flux of a Large Lake: A Multiannual Analysis for Lake Geneva

David Andrew Barry, Ulrich Lemmin, Andrea Cimatoribus, Abolfazl Irani Rahaghi

The spatiotemporal surface heat flux (SurHF) distribution over Lake Geneva, the largest lake in Western Europe, was estimated for a 7‐year period (2008–2014). Data sources included hourly maps of over‐the‐lake assimilated meteorological data from a validat ...

American Geophysical Union2019

Decision Fusion Of Spot6 And Multitemporal Sentinel2 Images For Urban Area Detection

Cyril Vincent Wendl

Fusion of very high spatial resolution multispectral (VHR) images and lower spatial resolution image time series with more spectral bands can improve land cover classification, combining geometric and semantic advantages of both sources. This study present ...

IEEE2018

Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response

Stéphane Joost, Devis Tuia, Matthew Josef Parkan, Carlos Castillo, Muhammad Imran, Patrick Meier, Julien Briant

Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resol ...

Mary Ann Liebert, Inc2016

High spatial resolution distributed sensing in optical fibers by Brillouin gain-profile tracing

Luc Thévenaz

A novel BOTDA technique for distributed sensing of the Brillouin frequency in optical fibers with cm-order spatial resolution is proposed. The technique is based upon a simple modulation scheme, requiring only a single long pump pulse for acoustic excitati ...

Optical Society of America2010