Bertrand Le Saux

Info

I am a research scientist who designs data-driven techniques for visual understanding at Onera/DTIS, the French aerospace research centre.

My work is at the crossroads of statistics, machine learning, image processing and computer vision. I am interested in tackling practical problems that arise in multimedia, remote sensing and robotics.

Besides that, I teach Image Processing and Computer Vision Research Work at École Polytechnique and Machine Learning at Institut d'Optique Graduate School and ENSTA ParisTech. I also serve as Chair of the IEEE GRSS Image Analysis and Data Fusion Technical Committee.

My up-to-date webpage is now located at https://blesaux.github.io/.

 

 

 

 

 

 

Onera Satellite Change Detection dataset

The Dataset

The Onera Satellite Change Detection dataset address the issue of detecting changes between satellite images at different dates.

It comprises 24 pairs of multispectral images taken from the Sentinel-2 satellite in 2016 and 2017. Locations are picked all over the world, in Brazil, USA, Europe, Middle-East and Asia. For each location, registered pairs of 13-band multispectral satellite images obtained by the Sentinel-2 satellites are provided. Images vary in spatial resolution between 10m, 20m and 60m.

Pixel-level change groundtruth is provided for 14 of the image pairs. The annotated changes focus on urban changes, such as new buildings or new roads. These data can be used for training and setting parameters of change detection algorithms.

beirut-triptych.png
Beirut in 2016 and 2017, with change map

The benchmark

The algorithms can be tested in a benchmark for change detection.

The ground-truth for the 10 remaining images remain undisclosed. Change prediction maps can be uploaded for evaluation on the IEEE GRSS DASE website. Various metrics such as per-class accuracy and confusion matrices are automatically computed on the website, and available for participants. Comparison to the best performing methods is provided in the leaderboard associated with this benchmark.

References

If you use this work for your projects, please take the time to cite our paper:

Urban Change Detection for Multispectral Earth Observation Using Convolutional Neural Networks R. Caye Daudt, B. Le Saux, A. Boulch, Y. Gousseau IEEE International Geoscience and Remote Sensing Symposium (IGARSS’2018) Valencia, Spain, July 2018

@inproceedings{daudt-igarss18,
author = {{Caye Daudt}, R. and {Le Saux}, B. and Boulch, A. and Gousseau, Y.},
title = {Urban Change Detection for Multispectral Earth Observation Using Convolutional Neural Networks},
booktitle = {IEEE International Geoscience and Remote Sensing Symposium (IGARSS'2018)},
venue =  {Valencia, Spain},
month = {July},
year = {2018},
}

The Team

Rodrigo Caye Daudt, rodrigo.daudt@onera.fr
Bertrand Le Saux, bertrand.le_saux@onera.fr
Alexandre Boulch, alexandre.boulch@onera.fr
Yann Gousseau, yann.gousseau@telecom-paristech.fr