Yixuan Wu , Chenhao Huang , Yang Ye , Linlu Mei , Yalan Liu , Dacheng Wang , Weirong Chen , Jinsong Deng
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By integrating urban functional zoning data to supplement the demand for nighttime lighting, a Nighttime Light Supply-Demand Mismatch Index (NLSDMI) was developed to quantify the imbalance of nighttime light between supply side and demand side. The results showed that Shanghai's nighttime light pollution area covered 78.25 km<sup>2</sup> (15.10 %), a higher proportion than Beijing's 115.61 km<sup>2</sup> (11.29 %) of the study area. Shanghai also exhibited higher peak NLSDMI values. In both cities, residential zones were among the primary contributors to nighttime light pollution. Additionally, in Beijing, the largest share was distributed in parks and green spaces, while in Shanghai, the second major distribution was found in industrial zones. The spatial patterns of nighttime light pollution reflected the distinct characteristics of the two megacities: Beijing focuses on cultural and administrative functions, while Shanghai tends to play its role as an economic hub. Accordingly, feasible countermeasures, including targeted lighting strategy formulation, urban land-use planning refinement and energy-saving lighting technology innovation, were proposed to mitigate light pollution and promote urban sustainability. This study demonstrated the promising potential of SDGSAT-1 glimmer imagery in advancing light pollution assessment and urban management. It also provides practical pathways toward the achievement of multiple Sustainable Development Goals (SDGs), especially SDG 3 (Good Health and Well-being), SDG 7 (Affordable and Clean Energy), and SDG 11 (Sustainable Cities and Communities). Future research should focus on enhancing data accuracy, improving validation methods, and exploring the applicability of findings to cities with diverse types and scales, thus providing broader theoretical support and practical guidance for global nighttime light pollution management.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"328 ","pages":"Article 114894"},"PeriodicalIF":11.4000,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification and evaluation of nighttime light pollution in residential gathering area of megacities based on SDGSAT-1 glimmer imagery\",\"authors\":\"Yixuan Wu , Chenhao Huang , Yang Ye , Linlu Mei , Yalan Liu , Dacheng Wang , Weirong Chen , Jinsong Deng\",\"doi\":\"10.1016/j.rse.2025.114894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Nighttime light pollution has become an increasingly serious issue in rapidly urbanizing megacities. It not only disrupts circadian rhythms and affects mental health, but also leads to energy waste and undermines the stability of urban and surrounding ecosystems, posing a significant threat to sustainable development. This study evaluated nighttime light pollution in the residential gathering areas of two typical megacities in China (Beijing and Shanghai) using 40-m SDGSAT-1 glimmer imagery (reflecting actual supply) and population grids (reflecting human demand) refined by the high-performance Random Forest model (with R<sup>2</sup> values of 0.93 for Beijing and 0.81 for Shanghai). By integrating urban functional zoning data to supplement the demand for nighttime lighting, a Nighttime Light Supply-Demand Mismatch Index (NLSDMI) was developed to quantify the imbalance of nighttime light between supply side and demand side. The results showed that Shanghai's nighttime light pollution area covered 78.25 km<sup>2</sup> (15.10 %), a higher proportion than Beijing's 115.61 km<sup>2</sup> (11.29 %) of the study area. Shanghai also exhibited higher peak NLSDMI values. In both cities, residential zones were among the primary contributors to nighttime light pollution. Additionally, in Beijing, the largest share was distributed in parks and green spaces, while in Shanghai, the second major distribution was found in industrial zones. The spatial patterns of nighttime light pollution reflected the distinct characteristics of the two megacities: Beijing focuses on cultural and administrative functions, while Shanghai tends to play its role as an economic hub. Accordingly, feasible countermeasures, including targeted lighting strategy formulation, urban land-use planning refinement and energy-saving lighting technology innovation, were proposed to mitigate light pollution and promote urban sustainability. This study demonstrated the promising potential of SDGSAT-1 glimmer imagery in advancing light pollution assessment and urban management. It also provides practical pathways toward the achievement of multiple Sustainable Development Goals (SDGs), especially SDG 3 (Good Health and Well-being), SDG 7 (Affordable and Clean Energy), and SDG 11 (Sustainable Cities and Communities). 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引用次数: 0
摘要
在快速城市化的特大城市中,夜间光污染已成为一个日益严重的问题。它不仅扰乱昼夜节律,影响心理健康,而且还导致能源浪费,破坏城市和周围生态系统的稳定,对可持续发展构成重大威胁。本研究利用40米SDGSAT-1微光图像(反映实际供应)和人口网格(反映人类需求),通过高性能随机森林模型(北京的R2值为0.93,上海的R2值为0.81)对中国两个典型特大城市(北京和上海)的住宅集聚区夜间光污染进行了评估。通过整合城市功能分区数据补充夜间照明需求,建立夜间照明供需失配指数(NLSDMI),量化供给方和需求方夜间照明的不平衡。结果表明:上海市夜间光污染面积78.25 km2(15.10%),高于北京市115.61 km2 (11.29%);上海也表现出更高的NLSDMI峰值。在这两个城市,居民区是夜间光污染的主要来源之一。此外,在北京,最大的份额分布在公园和绿地,而在上海,第二主要分布在工业区。夜间光污染的空间格局反映了两个特大城市的鲜明特征:北京侧重于文化和行政功能,而上海倾向于发挥其经济中心的作用。据此,提出了有针对性地制定照明战略、细化城市土地利用规划、创新节能照明技术等可行对策,以缓解光污染,促进城市可持续发展。该研究展示了SDGSAT-1微光图像在推进光污染评估和城市管理方面的巨大潜力。它还为实现多个可持续发展目标(SDG)提供了切实可行的途径,特别是可持续发展目标3(良好健康和福祉)、可持续发展目标7(负担得起的清洁能源)和可持续发展目标11(可持续城市和社区)。未来的研究应注重提高数据的准确性,改进验证方法,探索研究结果对不同类型和规模城市的适用性,从而为全球夜间光污染管理提供更广泛的理论支持和实践指导。
Identification and evaluation of nighttime light pollution in residential gathering area of megacities based on SDGSAT-1 glimmer imagery
Nighttime light pollution has become an increasingly serious issue in rapidly urbanizing megacities. It not only disrupts circadian rhythms and affects mental health, but also leads to energy waste and undermines the stability of urban and surrounding ecosystems, posing a significant threat to sustainable development. This study evaluated nighttime light pollution in the residential gathering areas of two typical megacities in China (Beijing and Shanghai) using 40-m SDGSAT-1 glimmer imagery (reflecting actual supply) and population grids (reflecting human demand) refined by the high-performance Random Forest model (with R2 values of 0.93 for Beijing and 0.81 for Shanghai). By integrating urban functional zoning data to supplement the demand for nighttime lighting, a Nighttime Light Supply-Demand Mismatch Index (NLSDMI) was developed to quantify the imbalance of nighttime light between supply side and demand side. The results showed that Shanghai's nighttime light pollution area covered 78.25 km2 (15.10 %), a higher proportion than Beijing's 115.61 km2 (11.29 %) of the study area. Shanghai also exhibited higher peak NLSDMI values. In both cities, residential zones were among the primary contributors to nighttime light pollution. Additionally, in Beijing, the largest share was distributed in parks and green spaces, while in Shanghai, the second major distribution was found in industrial zones. The spatial patterns of nighttime light pollution reflected the distinct characteristics of the two megacities: Beijing focuses on cultural and administrative functions, while Shanghai tends to play its role as an economic hub. Accordingly, feasible countermeasures, including targeted lighting strategy formulation, urban land-use planning refinement and energy-saving lighting technology innovation, were proposed to mitigate light pollution and promote urban sustainability. This study demonstrated the promising potential of SDGSAT-1 glimmer imagery in advancing light pollution assessment and urban management. It also provides practical pathways toward the achievement of multiple Sustainable Development Goals (SDGs), especially SDG 3 (Good Health and Well-being), SDG 7 (Affordable and Clean Energy), and SDG 11 (Sustainable Cities and Communities). Future research should focus on enhancing data accuracy, improving validation methods, and exploring the applicability of findings to cities with diverse types and scales, thus providing broader theoretical support and practical guidance for global nighttime light pollution management.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.