Machine Learning for Remote Sensing Workshop

Remote sensing data (also referred to as Earth observation or satellite data) has become an increasingly popular modality for machine learning research. This interest has largely been driven by the opportunities that remote sensing data present for contributing to challenges urgently important to society, such as climate change, food security, conservation, disasters, and poverty. This growing interest in ML research for remote sensing data is also driven by the challenges presented by its unique characteristics compared to other data modalities (e.g., images, text, video). Remote sensing datasets are very high-dimensional and often have spatial, temporal, and spectral dimensions more complex than traditional RGB images or videos. The diversity of instruments used for observing the Earth at different wavelengths, temporal cadences, and spatial resolutions has driven active research in domain adaptation, data fusion, and other topic areas. In this workshop, we aim to stimulate and highlight research on new methods, datasets, and systems for machine learning for remote sensing data and especially encourage submissions and discussions about research in the African context.

Call for Papers

Important Dates

Topics Covered

The goal of this workshop is to solicit research papers addressing advancements in the following topics as well as other relevant topics in Machine Learning for Remote Sensing:

We will solicit two types of papers: short proposal papers (3 pages) and short papers describing new and ongoing/in progress research (4 pages). Page limits do not include references, which are unlimited. Papers will be non-archival. To prepare your submission, please use the LaTeX style files for ICLR 2023. Paper reviews will be double blind. When submitting your manuscript, make sure you do not include any personally-identifying information such as author names or Github links which would de-anonymize the submission.

Machine Learning for Remote Sensing is non-archival and thus dual submission is allowed where permitted by third parties.

Submission site:


Start time Topic
9:00 Opening Remarks: Anthony Ortiz (Microsoft)
9:10 Keynote: “WorldCereal: making global crop maps and learning from the experience”, Kristof Van Tricht (VITO)
9:40 Coffee break
10:10 Accepted paper oral talks (5 x 10 min each w/ questions)
11:00 Panel: Challenges & opportunities for ML + RS in Africa
12:00 Lunch
13:30 Keynote: “Mapping the built up environment of Africa and beyond”, Abigail Annkah (Google)
14:00 Poster session
14:30 Coffee break
15:00 Accepted paper oral talks (3 x 10 min each w/ questions)
15:30 Poster session
16:00 Keynote: “Application of Artificial Intelligence using Earth Observation for land use in Uganda”, Joyce Nakatumba-Nabende (Makerere AI)
16:30 Panel: Bridging the gap between research & deployment
17:30 Adjourn

Accepted Papers

  Paper Title Authors
Oral (10:10) Towards Explainable Land Cover Mapping: a Counterfactual-based Strategy Cassio F. Dantas, Diego Marcos, Dino Ienco
Oral (10:20) Enhancing Acoustic Classification using Meta-Data Lorène LJ Jeantet, Emmanuel Dufourq
Oral (10:30) Explaining Multimodal Data Fusion: Occlusion Analysis for Wilderness Mapping Burak Ekim, Michael Schmitt
Oral (10:40) Mask Conditional Synthetic Satellite Imagery Zixi Chen, Van Anh Le, Mengyuan Li, Varshini Reddy Bogolu, Xinran Tang, Simone Fobi, Anthony Ortiz, Caleb Robinson
Oral (10:50) Optimizing ecological restoration efforts to improve landscape connectivity Michael D Catchen, Michelle Lin, Timothée Poisot, Andrew Gonzalez
Oral (15:00) Urban-rural disparities in satellite-based poverty prediction Emily L Aiken, Esther Rolf, Joshua Blumenstock
Oral (15:10) Linking population data to high resolution maps: a case study in Burkina Faso Basile Rousse, Sylvain Lobry, Géraldine Duthé, Valérie Golaz, Laurent Wendling
Oral (15:20) Polygonizer: An auto-regressive building delineator Maxim Khomiakov, Michael Andersen, Jes Frellsen
Poster Aerial View Localization with Reinforcement Learning: Towards Emulating Search-and-Rescue Aleksis Pirinen, Anton Samuelsson, John Backsund, Karl Åström
Poster Improved marine debris detection in satellite imagery with an automatic refinement of coarse hand annotations Marc Rußwurm, Dilge Gül, Devis Tuia
Poster Titan Cloud Identification with Deep Transfer Learning Zachary R Yahn, Conor Nixon, John W Santerre, Douglas Trent, Ethan Duncan
Poster Evaluation Challenges for Geospatial ML Esther Rolf
Poster Building Light Models with Competitive Performance for Remote Sensing Olga Garces Ciemerozum, Javier Marin
Poster Unsupervised Domain Adaptation for semantic segmentation of dwellings with Unbalanced Optimal Transport Pratichhya Sharma, Nicolas Courty, Getachew Workineh Gella, Stefan Lang
Poster Efficient Ship Detection on Large Open Sea Areas Aitor Jara García, Javier Marin
Poster Remote Control: Debiasing Remote Sensing Predictions for Causal Inference Megan Ayers
Poster Improve State-Level Wheat Yield Forecasts in Kazakhstan on GEOGLAM’S EO Data by Leveraging a Simple Spatial-Aware Technique Anh N Nhu, Ritvik Sahajpal, Christina Justice, Inbal Becker-Reshef
Poster Pixel-wise t-test: a new algorithm for persistent building damage detection in synthetic aperture radar imagery Ollie Ballinger, Gennadii Donchtys

Keynote speakers

Panel speakers


Program Committee

Full name Organization
Alex Hernandez-Garcia Mila - Quebec AI Institute
Anthony Ortiz Microsoft
Anthony Vodacek Rochester Institute of Technology
Arthur Ouaknine Telecom Paris
Begum Demir TU Berlin
Bertrand Le Saux ESA / Phi-lab
Caleb Robinson Microsoft AI for Good Research Lab
Charlotte Pelletier Université de Bretagne du Sud
Christian Ayala Tracasa Instrumental
Dalton Lunga Oak Ridge National Laboratory
Devis Tuia EPFL
Jan Dirk Wegner University of Zurich
Jocelyn Chanussot Grenoble Institute of Technology
Jonathan Sullivan University of Arizona
Kevin Booth Radiant Earth Foundation
Kristof Van Tricht VITO
Lewis Fishgold Azavea
Loic Landrieu IGN
Lukas Kondmann German Aerospace Center
Marc Rußwurm École Polytechnique Fédérale de Lausanne
Mark Wronkiewicz Jet Propulsion Laboratory
Nathan Jacobs Washington University in St. Louis
Patrick Gray Select One
Pedram Ghamisi Helmholtz-Zentrum Dresden-Rossendorf
Qiusheng Wu University of Tennessee
Ritvik Sahajpal University of Maryland
Rohit Mukherjee The University of Arizona
Sergii Skakun University of Maryland
Subit Chakrabarti Cloud To Street
Tyler Erickson independent
VIvien Sainte Fare Garnot University of Zurich
Zhiang Chen Arizona State University
Zhuangfang Yi Regrow

Travel Support

Limited funding is available to support the travel of students to attend the workshop held at ICLR 2023. Awards are based on merit with additional consideration based on need and travel distance. Priority will be given to those whose papers are accepted for presentation at the workshop.

The deadline for submitting this application was February 26, 11:59pm Anywhere on Earth.

Application form link


If you or your organization is interested in becoming a workshop sponsor, please see the sponsorship prospectus and contact the organizing team using the email below.

Platinum Sponsors

CMU Africa logo Microsoft logo

Gold Sponsors

GRSS logo

Silver Sponsors

astraea logo


For questions or information about the Machine Learning for Remote Sensing workshop at ICLR 2023 please contact