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

Jakob Hederich; Shreya Ghosh; Zeyu He; Prasenjit Mitra

doi:10.48550/arXiv.2306.03195

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

Jakob Hederich
, Shreya Ghosh^*
, Zeyu He
, Prasenjit Mitra

^*Korrespondierende*r Autor*in für diese Arbeit

Forschungszentrum L3S

Pennsylvania State University

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

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.

Originalsprache	Englisch
Titel des Sammelwerks	Machine Learning and Knowledge Discovery in Databases
Untertitel	Applied Data Science and Demo Track
Herausgeber/-innen	Gianmarco De Francisci Morales, Francesco Bonchi, Claudia Perlich, Natali Ruchansky, Nicolas Kourtellis, Elena Baralis
Herausgeber (Verlag)	Springer Science and Business Media Deutschland GmbH
Seiten	340-344
Seitenumfang	5
ISBN (elektronisch)	978-3-031-43430-3
ISBN (Print)	9783031434297
DOIs	https://doi.org/10.48550/arXiv.2306.03195 https://doi.org/10.1007/978-3-031-43430-3_27
Publikationsstatus	Veröffentlicht - 17 Sept. 2023
Veranstaltung	European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2023 - Turin, Italien Dauer: 18 Sept. 2023 → 22 Sept. 2023

Publikationsreihe

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band	14175 LNAI
ISSN (Print)	0302-9743
ISSN (elektronisch)	1611-3349

Konferenz

Konferenz	European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2023
Land/Gebiet	Italien
Ort	Turin
Zeitraum	18 Sept. 2023 → 22 Sept. 2023

ASJC Scopus Sachgebiete

Theoretische Informatik
Allgemeine Computerwissenschaft

Zugriff auf Dokument

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

Dieses zitieren

Hederich, J., Ghosh, S., He, Z., & Mitra, P. (2023). Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns. in G. De Francisci Morales, F. Bonchi, C. Perlich, N. Ruchansky, N. Kourtellis, & E. Baralis (Hrsg.), Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track (S. 340-344). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14175 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.48550/arXiv.2306.03195, https://doi.org/10.1007/978-3-031-43430-3_27

Hederich, Jakob ; Ghosh, Shreya ; He, Zeyu et al. / Lumos in the Night Sky : AI-Enabled Visual Tool for Exploring Night-Time Light Patterns. Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track . Hrsg. / Gianmarco De Francisci Morales ; Francesco Bonchi ; Claudia Perlich ; Natali Ruchansky ; Nicolas Kourtellis ; Elena Baralis. Springer Science and Business Media Deutschland GmbH, 2023. S. 340-344 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{22ac13ec7d7c4d6990f57a0206ee6ff6,

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

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.",

keywords = "Night-time light (NTL), pattern mining, Visualization",

author = "Jakob Hederich and Shreya Ghosh and Zeyu He and Prasenjit Mitra",

note = "Funding Information: This research was funded by the Federal Ministry of Education and Research (BMBF), Germany under the project LeibnizKILabor with grant No. 01DD20003. ; European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2023 ; Conference date: 18-09-2023 Through 22-09-2023",

year = "2023",

month = sep,

day = "17",

doi = "10.48550/arXiv.2306.03195",

language = "English",

isbn = "9783031434297",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "340--344",

editor = "\{De Francisci Morales\}, Gianmarco and Francesco Bonchi and Claudia Perlich and Natali Ruchansky and Nicolas Kourtellis and Elena Baralis",

booktitle = "Machine Learning and Knowledge Discovery in Databases",

address = "Germany",

}

Hederich, J, Ghosh, S, He, Z & Mitra, P 2023, Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns. in G De Francisci Morales, F Bonchi, C Perlich, N Ruchansky, N Kourtellis & E Baralis (Hrsg.), Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 14175 LNAI, Springer Science and Business Media Deutschland GmbH, S. 340-344, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2023, Turin, Italien, 18 Sept. 2023. https://doi.org/10.48550/arXiv.2306.03195, https://doi.org/10.1007/978-3-031-43430-3_27

Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns. / Hederich, Jakob; Ghosh, Shreya; He, Zeyu et al.
Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track . Hrsg. / Gianmarco De Francisci Morales; Francesco Bonchi; Claudia Perlich; Natali Ruchansky; Nicolas Kourtellis; Elena Baralis. Springer Science and Business Media Deutschland GmbH, 2023. S. 340-344 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 14175 LNAI).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

TY - GEN

T1 - Lumos in the Night Sky

T2 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2023

AU - Hederich, Jakob

AU - Ghosh, Shreya

AU - He, Zeyu

AU - Mitra, Prasenjit

N1 - Funding Information: This research was funded by the Federal Ministry of Education and Research (BMBF), Germany under the project LeibnizKILabor with grant No. 01DD20003.

PY - 2023/9/17

Y1 - 2023/9/17

N2 - 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.

AB - 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.

KW - Night-time light (NTL)

KW - pattern mining

KW - Visualization

UR - https://www.scopus.com/pages/publications/85174449067

U2 - 10.48550/arXiv.2306.03195

DO - 10.48550/arXiv.2306.03195

M3 - Conference contribution

AN - SCOPUS:85174449067

SN - 9783031434297

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 340

EP - 344

BT - Machine Learning and Knowledge Discovery in Databases

A2 - De Francisci Morales, Gianmarco

A2 - Bonchi, Francesco

A2 - Perlich, Claudia

A2 - Ruchansky, Natali

A2 - Kourtellis, Nicolas

A2 - Baralis, Elena

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 18 September 2023 through 22 September 2023

ER -

Hederich J, Ghosh S, He Z, Mitra P. Lumos in the Night Sky: AI-Enabled Visual Tool for Exploring Night-Time Light Patterns. in De Francisci Morales G, Bonchi F, Perlich C, Ruchansky N, Kourtellis N, Baralis E, Hrsg., Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track . Springer Science and Business Media Deutschland GmbH. 2023. S. 340-344. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.48550/arXiv.2306.03195, 10.1007/978-3-031-43430-3_27