A4 Article in conference proceedings
Analyzing Artificial Nighttime Lighting Using Hyperspectral Data from ENMAP (2024)

Lind, L., Cerra, D., Pato, M., & Pölönen, I. (2024). Analyzing Artificial Nighttime Lighting Using Hyperspectral Data from ENMAP. In IGARSS 2024 : 2024 IEEE International Geoscience and Remote Sensing Symposium (pp. 8069-8073). IEEE. IEEE International Geoscience and Remote Sensing Symposium proceedings. https://doi.org/10.1109/igarss53475.2024.10641253

JYU authors or editors

Publication details

All authors or editors: Lind, Leevi; Cerra, Daniele; Pato, Miguel; Pölönen, Ilkka

Parent publication: IGARSS 2024 : 2024 IEEE International Geoscience and Remote Sensing Symposium

Conference:

Place and date of conference: Athens, Greece, 7.-12.7.2024

ISBN: 979-8-3503-6033-2

eISBN: 979-8-3503-6032-5

Journal or series: IEEE International Geoscience and Remote Sensing Symposium proceedings

ISSN: 2153-6996

eISSN: 2153-7003

Publication year: 2024

Publication date: 07/07/2024

Pages range: 8069-8073

Publisher: IEEE

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1109/igarss53475.2024.10641253

Publication open access: Not open

Publication channel open access: 

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/97184

Abstract

Over the years, space-based remote sensing of nighttime light has mostly utilized panchromatic or multispectral sensors. The hyperspectral mission EnMAP, primarily intended for daytime observations, can also produce hyperspectral data of nighttime lighting. EnMAP data from the Las Vegas Strip was analyzed by detecting locations of certain lighting types using matched filtering and detection of sharp emission spikes at known wavelengths. Additionally, images from different nights were compared to determine how changes in observation geometry affect the observed spectra. The results indicate that corrections for geometric effects would be necessary to produce robust time-series data. The EnMAP data were also used to approximate two in-dices related to the efficiency and spectral quality of the light, the luminous efficiency of radiation (LER) and the spectral G index. Future developments will include ana-lyzing scenes from other cities using similar approaches. Program code used in this work is available at https://github.com/silmae/EnMAP_nightlights.

Keywords: geometry; codes; lighting; urban areas

Free keywords: geometry; strips; codes; filtering; urban areas; lighting; sensors

Contributing organizations

Related projects

Ministry reporting: Yes

VIRTA submission year: 2024

Preliminary JUFO rating: 1