ML Anthology

Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns

Jakob Hederich, Shreya Ghosh, Zeyu He, Prasenjit Mitra
ECML-PKDD 2023 pp. 340-344
doi:10.1007/978-3-031-43430-3_27 /ecmlpkdd/2023/hederich2023ecmlpkdd-lumos/

Abstract

We introduce NightVIEW, an interactive tool for Night-time light (NTL) data visualization and analytics, which enables researchers and stakeholders to explore and analyze NTL data with a user-friendly platform. Powered by efficient system architecture, NightVIEW supports image segmentation, clustering, and change pattern detection to identify urban development and sprawl patterns. It captures temporal trends of NTL and semantics of cities, answering questions about demographic factors, city boundaries, and unusual differences.

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Cite

Text

Hederich et al. "Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023. doi:10.1007/978-3-031-43430-3_27

Markdown

[Hederich et al. "Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023.](https://mlanthology.org/ecmlpkdd/2023/hederich2023ecmlpkdd-lumos/) doi:10.1007/978-3-031-43430-3_27

BibTeX

@inproceedings{hederich2023ecmlpkdd-lumos,
  title     = {{Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns}},
  author    = {Hederich, Jakob and Ghosh, Shreya and He, Zeyu and Mitra, Prasenjit},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2023},
  pages     = {340-344},
  doi       = {10.1007/978-3-031-43430-3_27},
  url       = {https://mlanthology.org/ecmlpkdd/2023/hederich2023ecmlpkdd-lumos/}
}