@inproceedings{4265d9b4a3c548cf8595c868908b9e7c,
title = "Introducing SpaceNet 9 - Cross-Modal Satellite Imagery Registration for Natural Disaster Responses",
abstract = "Computer vision algorithms are increasingly leveraged to accelerate geospatial analysis for disaster response and recovery. As the diversity of remote sensing imagery grows with optical, SAR, and other modalities, a perquisite for analytics is cross-modal image registration. There is a high potential to harness computer vision for this pre-processing requirement toward enabling downstream analytics such as heterogeneous change detection, automated feature extraction, and data fusion. Advancement in these areas has the potential to simplify data wrangling tasks and further accelerate disaster response timelines. The SpaceNet 9 challenge (launching in mid-2024) focuses on addressing the cross-modal image registration problem and demonstrating the utility of such modules on earthquake impacted scenarios. This paper describes the motivation for the SpaceNet 9 and provides a first overview of the dataset, the baseline algorithm, and implications for seeking cross-modal image registration in Earth observation. Code is available at https://github.com/SpaceNetChallenge/SpaceNet9.",
keywords = "computer vision, cross-modal learning, disaster response, earthquake, High-resolution optical satellite imagery, image registration, natural disaster, SAR data",
author = "Ronny H{\"a}nsch and Jacob Arndt and Philipe Dias and Abhishek Potnis and Dalton Lunga and Desiree Petrie and Bacastow, {Todd M.}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 ; Conference date: 07-07-2024 Through 12-07-2024",
year = "2024",
doi = "10.1109/IGARSS53475.2024.10640611",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "234--238",
booktitle = "IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",
}