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Special Issue Editors

Dr. Johannes Puschnig

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Guest Editor

Department of Physics and Astronomy, Uppsala University, 75236 Uppsala, Sweden
Interests: light pollution; night sky brightness; atmospheric modeling measurements; astrophysics
Special Issues, Collections and Topics in MDPI journals

Dr. Pietro Fiorentin

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Guest Editor

Department of Industrial Engineering, University of Padova, v. Gradenigo, 6, 35131 Padova, Italy
Interests: photometry; radiometry; light pollution; remote sensing of night lights

Special Issue Information

Dear Colleagues,

This is the second Special Issue concerning the Latest Developments and Applications in Remote Sensing with Nighttime Lights.

Over the last decade, it has become clear that constraining long-term trends from photometric night sky brightness measurements is a complex problem that involves many aspects, such as the quantification of instrumental effects (e.g., temporal changes in sensor sensitivity and spectral composition), atmospheric composition (e.g., impact of clouds and aerosols) and the environment (e.g., terrain, vegetation and albedo). While the impact of some of these aspects has been studied recently, to date, no physical framework exists that considers the coupling of several of these parameters. As a result, despite the numerous monitoring campaigns that have been established and are still operating, the temporal change observed in the night sky brightness assessed in these efforts remains an open question.

This Special Issue aims to address this knowledge gap through several pathways, such as combining state-of-the-art (atmospheric) modeling with existing empirical datasets concerned with light pollution, the atmosphere and meteorological conditions. Moreover, authors are invited to contribute to the further assessment of sensor aging effects, using novel or existing methods.

Articles may address, but are not limited to, the following topics:

Long-term trend assessment of light pollution;
Impact of atmosphere on photometric night sky brightness measurements (models and empirical);
Impact of terrain, vegetation and other meteorological conditions on photometric night sky brightness measurements (models and empirical);
Source characterization;
Instrumental effects, such as “sensor aging”.

Dr. Johannes Puschnig
Dr. Pietro Fiorentin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (2 papers)

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Research

22 pages, 15243 KiB

Open AccessArticle

Light-Pollution-Monitoring Method for Selected Environmental and Social Elements

by Justyna Górniak-Zimroz, Kinga Romańczukiewicz, Magdalena Sitarska and Aleksandra Szrek

Remote Sens. 2024, 16(5), 774; https://doi.org/10.3390/rs16050774 - 22 Feb 2024

Viewed by 1249

Abstract

Light pollution significantly interferes with animal and human life and should, therefore, be included in the factors that threaten ecosystems. The main aim of this research is to develop a methodology for monitoring environmental and social elements subjected to light pollution in anthropogenic areas. This research is based on yearly and monthly photographs acquired from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (Suomi NPP) satellite; land cover data from the CORINE Land Cover (CLC) program; and environmental data from the European Environment Agency (EEA) and the World Database on Protected Areas (WDPA). The processing of input data for further analyses, the testing of the methodology and the interpretation of the final results were performed in GIS-type software (ArcGIS Pro). Light pollution in the investigated area was analyzed with the use of maps generated for the years 2014 and 2019. The environmental and social elements were spatially identified in five light pollution classes. The research results demonstrate that the proposed methodology allows for the identification of environmental and social elements that emit light, as well as those that are subjected to light pollution. The methodology used in this work allows us to observe changes resulting from light pollution (decreasing or increasing the intensity). Owing to the use of publicly available data, the methodology can be applied to light pollution monitoring as part of spatial planning in anthropogenic areas. The proposed methodology makes it possible to cover the area exposed to light pollution and to observe (almost online) the environmental and social changes resulting from reductions in light emitted by anthropogenic areas. Full article

(This article belongs to the Special Issue Latest Developments and Applications in Remote Sensing with Nighttime Lights II)

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17 pages, 2565 KiB

Open AccessArticle

Vessel Detection with SDGSAT-1 Nighttime Light Images

by Zheng Zhao, Shi Qiu, Fu Chen, Yuwei Chen, Yonggang Qian, Haodong Cui, Yu Zhang, Ehsan Khoramshahi and Yuanyuan Qiu

Remote Sens. 2023, 15(17), 4354; https://doi.org/10.3390/rs15174354 - 4 Sep 2023

Cited by 3 | Viewed by 1463

Abstract

The Sustainable Development Goals Science Satellite-1 (SDGSAT-1) Glimmer Imager for Urbanization (GIU) data is very sensitive to low radiation and capable of detecting weak light sources from vessels at night while significantly improving the spatial resolution compared to similar products. Most existing methods fail to use the relevant characteristics of vessels effectively, and it is difficult to deal with the complex shape of vessels in high-resolution Nighttime Light (NTL) data, resulting in unsatisfactory detection results. Considering the overall sparse distribution of vessels and the light source diffusion phenomenon, a novel vessel detection method is proposed in this paper, utilizing the high spatial resolution of the SDGSAT-1. More specifically, noise separation is completed based on a local contrast-weighted RPCA. Then, artificial light sources are detected based on a density clustering algorithm, and an inter-cluster merging method is utilized to realize vessel detection further. We selected three research areas, namely, the Bohai Sea, the East China Sea, and the Gulf of Mexico, to establish a vessel dataset and applied the algorithm to the dataset. The results show that the total detection accuracy and the recall rate of the detection algorithm in our dataset are 96.84% and 96.67%, which is significantly better performance than other methods used for comparison in the experiment. The algorithm overcomes the dataset’s complex target shapes and noise conditions and achieves good results, which proves the applicability of the algorithm. Full article

(This article belongs to the Special Issue Latest Developments and Applications in Remote Sensing with Nighttime Lights II)

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