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Remote Sensing
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Remote Sensing Technologies, Applications and Perspectives at Night: Nightlight, Nighttime...
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Remote Sensing Technologies, Applications and Perspectives at Night: Nightlight, Nighttime Thermal Infrared and Synthetic Aperture Radar (SAR)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: 30 October 2025 | Viewed by 3643

Special Issue Editors

Dr. Di Liu

E-Mail Website
Guest Editor
Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA
Interests: nightlight remote sensing; moonlight remote sensing; synthetic aperture radar; artificial intelligence applications of multisource remote sensing
Dr. Jiajun Li

E-Mail
Guest Editor
South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China
Interests: fisheries remote sensing; fishing vessel monitoring; nighttime remote sensing; fishery habitat dynamics
Special Issues, Collections and Topics in MDPI journals
Dr. Weiying Lin

E-Mail Website
Guest Editor
Department of Geography, Texas A&M University, College Station, TX 77843, USA
Interests: nightlight remote sensing; urban geography; urban greenspace; spatial analysis
Dr. Chengbin Deng

E-Mail Website
Guest Editor
Department of Geography and Environmental Sustainability, The Center for Spatial Analysis, University of Oklahoma, Norman, OK, USA
Interests: remote sensing image processing; land use and land cover change; environmental change; urbanization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Daytime measurements of reflected sunlight in the visible spectrum have long been a standard for Earth-observing radiometers. However, at night, these optical sensors are limited in their ability to capture detailed information on many critical weather and climate parameters. This limitation hampers our ability to fully characterize the diurnal behavior and processes essential for the improved monitoring, understanding, and modeling of weather and climate systems.

This Special Issue aims to provide a series of case studies demonstrating the use of a wide spectrum of remote sensing for science at night: technologies, applications, and perspectives. This issue aims to find the advances of remote sensing technologies in night-time environmental monitoring for a range of practical and research applications, Earth observation datasets, and challenges.

Dr. Di Liu
Dr. Jiajun Li
Dr. Weiying Lin
Dr. Chengbin Deng
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.

Keywords

  • nightlight remote sensing
  • night-time thermal infrared remote sensing
  • night-time synthetic aperture radar (SAR)
  • ecological applications
  • human settlement applications
  • other night-time applications

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Published Papers (4 papers)

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Research

18 pages, 10902 KiB  
Article
Analyzing the Sources and Variations of Nighttime Lights in Hong Kong from VIIRS Monthly Data
by Shengjie Liu, Chu Wing So and Chun Shing Jason Pun
Remote Sens. 2025, 17(8), 1447; https://doi.org/10.3390/rs17081447 - 18 Apr 2025
Viewed by 569
Abstract
The long-term monitoring of nighttime lights is essential for understanding sources of light pollution. Nighttime lights observed in space are affected by atmospheric conditions as they transmit from the Earth surface through clouds and aerosols to the top of the atmosphere. In this [...] Read more.
The long-term monitoring of nighttime lights is essential for understanding sources of light pollution. Nighttime lights observed in space are affected by atmospheric conditions as they transmit from the Earth surface through clouds and aerosols to the top of the atmosphere. In this study, based on the monthly cloud-free VIIRS/DNB products, we analyzed the long-term nighttime lights in Hong Kong (2012–2020). We found that the monthly variations in nighttime lights were large, especially in bright regions. The 12-month average of nighttime lights ranged from 13.0 to 18.9 nWcm−2sr−1. Public transportation facilities, such as port facilities and the airport, were the brightest, twice as bright as other urban areas. Public residential areas were slightly brighter than private ones. These urban areas were at least four times brighter than undeveloped regions, showing a significant alteration in light at night due to artificial facilities. Further, we used an unsupervised clustering method to identify specific patterns. While nighttime lights were stable in most regions, increasing trends were found at construction sites of a new artificial island and the airport expansion. Abnormal patterns, such as wildfires, were also recognized. We found that the background nighttime lights were brighter in wet months (e.g., April) and dimmer in dry months (e.g., January). The amount of water in the atmosphere affects nighttime light scattering, with a linear correlation (R = 0.68) between humidity and the occurrence of bright nighttime lights each month. The diverse sources and variations in nighttime lights call for continuous monitoring and advanced analytical methods to better understand their environmental and societal impacts. Full article
(This article belongs to the Special Issue Remote Sensing Technologies, Applications and Perspectives at Night: Nightlight, Nighttime Thermal Infrared and Synthetic Aperture Radar (SAR))
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25 pages, 10984 KiB  
Article
Machine-Learning-Based Monitoring of Night Sky Brightness Using Sky Quality Meters and Multi-Source Remote Sensing
by Siyue Zheng, Yanrong Chen, Anwar Eziz, Alishir Kurban, Tim Van de Voorde and Philippe De Maeyer
Remote Sens. 2025, 17(8), 1332; https://doi.org/10.3390/rs17081332 - 8 Apr 2025
Viewed by 562
Abstract
With the rapid pace of urbanization, light pollution has emerged as a critical environmental issue. Evaluating and managing light pollution effectively is challenging, as traditional monitoring methods often fail to capture its spatial distribution and driving factors comprehensively. To address this limitation, this [...] Read more.
With the rapid pace of urbanization, light pollution has emerged as a critical environmental issue. Evaluating and managing light pollution effectively is challenging, as traditional monitoring methods often fail to capture its spatial distribution and driving factors comprehensively. To address this limitation, this study integrates Sky Quality Meter (SQM) observational data from three diverse locations—Chaozhou (China), Urumqi (China), and Ghent (Belgium)—with multi-source remote sensing data to construct predictive models of night sky brightness (NSB) using machine learning approaches. Among the tested models, the voting ensemble model demonstrated superior performance, achieving high predictive accuracy and robust generalization across diverse regional datasets. The generated local-scale NSB distribution maps reveal substantial regional variations in light pollution, highlighting the critical influence of local environmental and anthropogenic factors. By combining remote sensing and machine learning, this study offers a scalable and efficient method for evaluating and monitoring light pollution levels at regional scales. The findings underscore the value of these methods in providing actionable insights for light pollution mitigation and management strategies, supporting efforts to reduce its adverse impacts on the environment and society. Full article
(This article belongs to the Special Issue Remote Sensing Technologies, Applications and Perspectives at Night: Nightlight, Nighttime Thermal Infrared and Synthetic Aperture Radar (SAR))
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Graphical abstract

30 pages, 31329 KiB  
Article
Virtual 3D Multi-Angle Modeling and Analysis of Nighttime Lighting in Complex Urban Scenes
by Xueqian Gao, Yuehan Wang, Fan Yang, Ximin Cui, Xuesheng Zhao, Mengjun Chao, Xiaoling Wei, Jinke Liu, Guobin Shi, Hansi Yao, Qingqing Li and Wei Guo
Remote Sens. 2025, 17(6), 1088; https://doi.org/10.3390/rs17061088 - 20 Mar 2025
Viewed by 503
Abstract
Urban nighttime lighting extends human activity hours and enhances safety but also wastes energy and causes light pollution. Influenced by building obstructions and surface reflections, light emissions exhibit significant anisotropy. Remote sensing can be used to observe nighttime lighting from high altitudes, but [...] Read more.
Urban nighttime lighting extends human activity hours and enhances safety but also wastes energy and causes light pollution. Influenced by building obstructions and surface reflections, light emissions exhibit significant anisotropy. Remote sensing can be used to observe nighttime lighting from high altitudes, but ground lighting anisotropy introduces angle-related errors. This study constructed a 3D urban nighttime lighting model using virtual simulations and conducted multi-angle observations to investigate anisotropy and its influencing factors. The results show that the illuminance distribution in urban functional areas is typically uneven, with ground-level illuminance varying linearly or exponentially with zenith angle and quadratically with azimuth angle. Some areas exhibit uniform illuminance without significant anisotropy. Nighttime light anisotropy is closely linked to urban geometry and light distribution, with building height, layout, and light source arrangement significantly influencing the anisotropic characteristics. The findings enhance our understanding of nighttime light anisotropy, provide a basis for developing angular effect models of complex scenarios, and quantify the upward light emission angles and intensities. These insights can be used to support corrections for multi-angle spaceborne nighttime lighting observations, contributing to more accurate data for urban planning and light pollution mitigation. Full article
(This article belongs to the Special Issue Remote Sensing Technologies, Applications and Perspectives at Night: Nightlight, Nighttime Thermal Infrared and Synthetic Aperture Radar (SAR))
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16 pages, 8241 KiB  
Article
Tracking the Development of Lit Fisheries by Using DMSP/OLS Data in the Open South China Sea
by Jiajun Li, Zhixin Zhang, Kui Zhang, Jiangtao Fan, Huaxue Liu, Yongsong Qiu, Xi Li and Zuozhi Chen
Remote Sens. 2024, 16(19), 3678; https://doi.org/10.3390/rs16193678 - 2 Oct 2024
Viewed by 1366
Abstract
Nightly images offer a special data source for monitoring fishing activities. This study used images from the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) to analyze the early development of lit fisheries in the open South China Sea (SCS), which mainly occurred [...] Read more.
Nightly images offer a special data source for monitoring fishing activities. This study used images from the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) to analyze the early development of lit fisheries in the open South China Sea (SCS), which mainly occurred around the Zhong Sha and Xi Sha Islands. Based on peak detection and a fixed threshold, lit fishing positions were extracted well from filtered, high-quality DMSP/OLS images. The results indicated that fisheries experienced an apparent rise and fall from 2005 to 2012, with the numbers of lit fishing boats rising to a maximum of ~60 from 2005 to 2008, almost disappearing in 2009, peaking at ~130 from 2010 to 2011, and starting to decline in 2012. The fish price of major fishing targets declined by ~60% in 2009, which obviously impacted the year’s fishing operations. The reason for declined fishing operations in 2012 was that most of the lit fishing operations shifted farther south to fishing grounds around the Nan Sha Islands. We also explored factors shaping the distribution patterns of lit fisheries by using MaxEnt models to relate fishing positions to environmental variables. Major environmental factors influencing the distribution of lit fishing boats varied with years, of which water depth was the most important factor across years, with an optimal depth range of 1000–2000 m. In addition to depth, the distribution of lit fisheries was also influenced by SST, especially for the years 2005–2008, and a suitable SST was found between 26 and 28 °C. This study fills the knowledge gaps of the inception of lit fisheries and their dynamic changes in the SCS. Full article
(This article belongs to the Special Issue Remote Sensing Technologies, Applications and Perspectives at Night: Nightlight, Nighttime Thermal Infrared and Synthetic Aperture Radar (SAR))
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