Remote Sensing

GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks

While numerous recent benchmarks focus on evaluating generic Vision-Language Models (VLMs), they fall short in addressing the unique …

Muhammad Sohail Danish, Muhammad Akhtar Munir, Syed Roshaan Ali Shah, Kartik Kuckreja, Fahad Shahbaz Khan, Paolo Fraccaro, Alexandre Lacoste, Salman Khan

International Conference on Computer Vision (ICCV), 2025.

EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision

This paper presents EarthView, a comprehensive dataset specifically designed for self-supervision on remote sensing data, intended to …

Diego Velazquez, Pau Rodriguez, Sergio Alonso, Josep M. Gonfaus, Jordi Gonzalez, Gerardo Richarte, Javier Marin, Yoshua Bengio, Alexandre Lacoste

Workshop at the Winter Conference on Applications of Computer Vision (WACV), 2025.

A General Purpose Neural Architecture for Geospatial Systems

Geospatial Information Systems are used by researchers and Humanitarian Assistance and Disaster Response (HADR) practitioners to …

Alexandre Lacoste, Martin Weiss, Nasim Rahaman

Workshop at the Neural Information Processing Systems (NeurIPS), 2022.

RaVAEn: Unsupervised Change Detection of Extreme Events Using ML On-Board Satellites

Applications such as disaster management enormously benefit from rapid availability of satellite observations. Traditionally, data …

Vít Růžička, Anna Vaughan, Daniele De Martini, James Fulton, Valentina Salvatelli, Chris Bridges, Gonzalo Mateo-Garcia, Valentina Zantedeschi

Nature Scientific Reports, 2022.

Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark

Recent progress in self-supervision shows that pre-training large neural networks on vast amounts of unsupervised data can lead to …

Alexandre Lacoste, Hannah Kerner, Hamed Alemohammad, Björn Lütjens, Jeremy Irvin, David Dao, Alex Chang, Mehmet Gunturkun, Alexandre Drouin, Pau Rodriguez, David Vazquez, Evan D. Sherwin

Workshop at the Neural Information Processing Systems (NeurIPS), 2021.

Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data

Remote sensing and automatic earth monitoring are key to solve global-scale challenges such as disaster prevention, land use …

Oscar Manas, Alexandre Lacoste, Xavier Giro-i-Nieto, David Vazquez, Pau Rodriguez

International Conference on Computer Vision (ICCV), 2021.

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery

Cattle farming is responsible for 8.8% of greenhouse gas emissions worldwide. In addition to the methane emitted due to their digestive …

Issam H. Laradji, Pau Rodriguez, Alfredo Kalaitzis, David Vazquez, Ross Young, Ed Davey, Alexandre Lacoste

Workshop at the Neural Information Processing Systems (NeurIPS), 2020.

Extending the Spatial Scale of Land Use Regression Models for Ambient Ultrafine Particles using Satellite Images and Deep Convolutional Neural Networks

We paired existing land use regression (LUR) models for ambient ultrafine particles in Montreal and Toronto, Canada with satellite …

Kris Y. Hong, Pedro O. Pinheiro, Laura Minet, Marianne Hatzopoulou, Scott Weichenthal

Journal of Environmental Science (JES), 2019.

Learning Global Variations in Outdoor PM_2.5 Concentrations with Satellite Images

Here we present a new method of estimating global variations in outdoor PM2.5 concentrations using satellite images combined with …

Yukai (Kris) Hong, Pedro O. Pinheiro, Scott Weichenthal

Workshop at the International Conference on Machine Learning (ICML), 2019.

GEO-Bench-2: From Performance to Capability, Rethinking Evaluation in Geospatial AI

Geospatial Foundation Models (GeoFMs) are transforming Earth Observation (EO), but evaluation lacks standardized protocols. …

Alexandre Lacoste

Transactions on Machine Learning Research (TMLR), 2017.