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学者姓名：陈佐旗
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Abstract ：
The Sustainable Development Goals Satellite 1 (SDGSAT-1), equipped with the Glimmer Imager (GLI), provides high-resolution nighttime light (NTL) data across multiple spectral bands. Thus, it can notably monitor human dynamics and light pollution with enhanced spectral and spatial resolution. However, cloud cover and lowquality observations often contaminate the SDGSAT-1 GLI NTL data, limiting its effectiveness. This challenge is addressed by the development of a novel method, namely the SpatioTemporal And spectRal gap-filling method for Sdgsat-1 (STARS) GLI NTL images, which combines spatiotemporal and spectral information to generate cloud-free NTL images with satisfactory pixel brightness and continuity. STARS is the first method to effectively address gap-filling in multiband NTL data using RGB spectral information, even with irregular time intervals and limited image inputs. Compared with traditional methods such as the temporal gap-filling method and the meanweighted gap-filling method, the Cloud Removing bY Synergizing spatioTemporAL information (CRYSTAL) method, and the spatial and temporal adaptive reflectance fusion model (STARFM), which do not specifically account for the differences in light source variations in multi-band NTL data, STARS demonstrates superior performance (higher R-squared (R2) and lower root-mean-square error (RMSE)) in simulations across seven global cities, demonstrating its effectiveness in filling cloud-induced gaps in multi-band NTL data. On average, STARS achieves R2 values for the gap-filling results compared to the actual values of 0.79, 0.78, and 0.70 in the RGB bands, respectively. The cloud-free images produced by STARS extend the time series of the SDGSAT-1 GLI NTL data, supporting multitemporal quantitative analysis. In cloudy regions like Tianjin, China, STARS effectively captures dynamic changes in NTL before and after the Spring Festival, closely matching human activity patterns from Baidu Maps, both spatially and temporally. Overall, STARS offers an innovative and effective approach for gap-filling multiband NTL data, with potential applications in similar datasets.
Keyword ：
Cloud removal Cloud removal Gap-filling Gap-filling Glimmer imager Glimmer imager Human dynamics monitoring Human dynamics monitoring Image reconstruction Image reconstruction SDGSAT-1 SDGSAT-1
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| GB/T 7714 | Wang, Congxiao , Xu, Wei , Chen, Zuoqi et al. STARS: A novel gap-filling method for SDGSAT-1 nighttime light imagery using spatiotemporal and spectral synergy [J]. | REMOTE SENSING OF ENVIRONMENT , 2025 , 322 . |
| MLA | Wang, Congxiao et al. "STARS: A novel gap-filling method for SDGSAT-1 nighttime light imagery using spatiotemporal and spectral synergy" . | REMOTE SENSING OF ENVIRONMENT 322 (2025) . |
| APA | Wang, Congxiao , Xu, Wei , Chen, Zuoqi , Liu, Shaoyang , Li, Wei , Zhang, Lingxian et al. STARS: A novel gap-filling method for SDGSAT-1 nighttime light imagery using spatiotemporal and spectral synergy . | REMOTE SENSING OF ENVIRONMENT , 2025 , 322 . |
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随着城市化进程加快和气候异常变化,台风灾害对中国亚热带地区经济发展造成的威胁和影响日益加剧.此外,中国正处于城乡融合发展的关键时期,科学评估台风灾后城乡经济变化特征具有重要意义.实地调查数据获取困难,导致传统灾损研究尺度较粗,而传统光学遥感数据难以刻画灾后经济损失.得益于夜光遥感数据具备挖掘社会经济信息的能力,使得利用该数据监测灾后经济变化有望成为传统灾损评估方法的有效补充.基于此,以2019年8月受"利奇马"台风影响的浙江省三县(市)重灾区为例,利用美国国家航空航天局(NASA)发布的高质量VNP46A3逐月夜光遥感数据,在乡镇尺度上计算了兼顾传统经济维度和新经济维度的夜间灯光景观指数,对重灾区典型乡镇灾后经济损失与恢复进行评估,并分析其城乡差异.结果表明:(1)在传统的经济总量与经济空间维度上,城市乡镇相较于农村乡镇具有更小的损失比重和更快的恢复速度;而混合乡镇的经济总量和经济空间变化复杂,其损失程度总体介于农村乡镇与城市乡镇之间.(2)平均经济水平、经济饱和度及经济均衡性这3个新维度的变化主要集中于以城市为主的乡镇,少部分集中于以农村为主的乡镇.但与平均经济水平和经济饱和度在灾后损失阶段出现下降,在恢复阶段出现上升不同的是经济均衡性在灾后损失阶段呈现上升趋势,而在恢复阶段则出现下降.上述实证分析结果表明,夜光景观指数能够在精细尺度下从不同维度客观地反映灾后经济变化.本研究也为深入了解灾害对当地经济的破坏程度并为制定具有针对性的恢复重建方案提供科学依据和指导.
Keyword ：
亚热带遥感 亚热带遥感 台风灾害 台风灾害 城乡差异 城乡差异 夜间灯光景观指数 夜间灯光景观指数 经济变化 经济变化
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| GB/T 7714 | 陈佐旗 , 苏瑞浩 . 基于夜光景观指数的灾区经济变化特征及其城乡差异研究 [J]. | 亚热带资源与环境学报 , 2024 , 19 (4) : 136-146 . |
| MLA | 陈佐旗 et al. "基于夜光景观指数的灾区经济变化特征及其城乡差异研究" . | 亚热带资源与环境学报 19 . 4 (2024) : 136-146 . |
| APA | 陈佐旗 , 苏瑞浩 . 基于夜光景观指数的灾区经济变化特征及其城乡差异研究 . | 亚热带资源与环境学报 , 2024 , 19 (4) , 136-146 . |
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Assessing the promotion of economic growth between China and the world is challenging given data limitations and the lack of consideration of time delay. Based on the time-series nighttime light (NTL) data from satellites covering more than 100 months, we found that the world is lighting in most countries, even after a sudden jump due to the outbreak of COVID-19. Then, we conducted the convergent cross-mapping before COVID-19 (2014.1-2019.12) and during/after COVID-19 (2020.1-2022.11), we found that the influences from China to the world economic growth in these two phases are widely expanded to more and more economies, the number of which increases from 65 to 73, with a longer time lag, which averagely increased from 4.6 to 6.6 months. On the contrary, the number of economies, which can influence China's economy, is increasing from 48 to 55 but the average lag time is stable at around 4.5 months. Meanwhile, a regional multilateral economic network related to China's economy was found. The economies with mutual causalities with China were mostly concentrated in Asia, Africa, and Europe. China indeed can warm the world economy partially, especially in developing countries and has also benefited from the multilateral economy.
Keyword ：
China China convergent cross-mapping convergent cross-mapping Economic growth Economic growth nighttime light remote sensing nighttime light remote sensing
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| GB/T 7714 | Chen, Zuoqi , You, Xiaojun , Wang, Congxiao et al. An increasing mutual promotion of economic growth between China and the world observed from nighttime light remote sensing [J]. | INTERNATIONAL JOURNAL OF DIGITAL EARTH , 2024 , 17 (1) . |
| MLA | Chen, Zuoqi et al. "An increasing mutual promotion of economic growth between China and the world observed from nighttime light remote sensing" . | INTERNATIONAL JOURNAL OF DIGITAL EARTH 17 . 1 (2024) . |
| APA | Chen, Zuoqi , You, Xiaojun , Wang, Congxiao , Wu, Wenting , Wei, Ye , Shi, Kaifang et al. An increasing mutual promotion of economic growth between China and the world observed from nighttime light remote sensing . | INTERNATIONAL JOURNAL OF DIGITAL EARTH , 2024 , 17 (1) . |
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Urban spatial interaction serves as an indicative measure for estimating the intensity and character of interurban linkages and relationships. The previous studies have utilized intercity relational data (e.g., population migration (PM), goods trade, and information exchange) to build up urban connections directly. Besides, the nighttime light (NTL) data have also been adopted to simulate a dynamic urban intercity flow. However, the relevant studies have not clearly defined the urban spatial interaction based on the NTL data. To answer this question, we used trial-and-error testing to define the NTL-based interaction. First, five traditional urban interactions were selected as the potential definitions, including PM, transfer of innovation, information flow (IF), financial flow, and urban composite interaction (CI). Second, as usual, the NTL-based urban interaction, named the NTL interaction (NTLI) index, was simulated based on the NPP-VIIRS-like NTL data and the radiation model. Taking the Yangtze River Delta urban agglomerations (YRDUAs) as an example, we found that the NTL-based urban interaction is more like the PM at the urban agglomeration scale and the provincial scale with R-2 of 0.71 and 0.59, respectively. In addition to this, the NTLI index has a weak correlation with the transfer of patent (TP) index, IF index, economic interaction (EI) index, and CI index. To sum up, the interaction network from NTL data can be an adequate proxy of urban population interaction, rather than the knowledge network or economic network. This study provides a new thought for urban network simulation and urban population mobility research.
Keyword ：
Economics Economics Indexes Indexes Nighttime light (NTL) data Nighttime light (NTL) data NTL interaction (NTLI) index NTL interaction (NTLI) index Patents Patents Sociology Sociology Statistics Statistics Urban areas Urban areas urban spatial interaction urban spatial interaction Web and internet services Web and internet services Yangtze River Delta urban agglomerations (YRDUAs) Yangtze River Delta urban agglomerations (YRDUAs)
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| GB/T 7714 | Tu, Yue , Wang, Congxiao , Yu, Bailang et al. What Is the Nighttime Light Interaction Index? Validations at Yangtze River Delta Urban Agglomerations [J]. | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS , 2024 , 21 . |
| MLA | Tu, Yue et al. "What Is the Nighttime Light Interaction Index? Validations at Yangtze River Delta Urban Agglomerations" . | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 21 (2024) . |
| APA | Tu, Yue , Wang, Congxiao , Yu, Bailang , Chen, Zuoqi , Zhang, Tinglin . What Is the Nighttime Light Interaction Index? Validations at Yangtze River Delta Urban Agglomerations . | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS , 2024 , 21 . |
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Urban built-up areas are the main space carrier of population and urban activities. It is of great significance to accurately identify urban built-up area for monitoring urbanization dynamics and their impact on Sustainable Development Goals. Using only nighttime light (NTL) remote sensing data will lead to omission phenomena in urban built-up area extraction, especially for SDGSAT-1 glimmer imager (GLI) data with high spatial resolution. Therefore, this study proposed a novel nighttime Lights integrate Building Volume (LitBV) index by integrating NTL intensity information from SDGSAT-1 GLI data and building volume information from Digital Surface Model (DSM) data to extract built-up areas more accurately. The results indicated that the LitBV index achieved remarkable results in the extraction of built-up areas, with the overall accuracy of 81.25%. The accuracy of the built-up area extraction based on the LitBV index is better than the results based on only NTL data and only building volume. Moreover, experiments at different spatial resolutions (10 m, 100 m, and 500 m) and different types of NTL data (SDGSAT-1 GLI data, Luojia-1 data, and NASA's Black Marble data) showed that the LitBV index can significantly improve the extraction accuracy of built-up areas. The LitBV index has a good application ability and prospect for extracting built-up areas with high-resolution SDGSAT-1 GLI data.
Keyword ：
building volume building volume built-up area built-up area nighttime light remote sensing nighttime light remote sensing SDGSAT-1 SDGSAT-1 sustainable development goals sustainable development goals
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| GB/T 7714 | Liu, Shaoyang , Wang, Congxiao , Wu, Bin et al. Integrating NTL Intensity and Building Volume to Improve the Built-Up Areas' Extraction from SDGSAT-1 GLI Data [J]. | REMOTE SENSING , 2024 , 16 (13) . |
| MLA | Liu, Shaoyang et al. "Integrating NTL Intensity and Building Volume to Improve the Built-Up Areas' Extraction from SDGSAT-1 GLI Data" . | REMOTE SENSING 16 . 13 (2024) . |
| APA | Liu, Shaoyang , Wang, Congxiao , Wu, Bin , Chen, Zuoqi , Zhang, Jiarui , Huang, Yan et al. Integrating NTL Intensity and Building Volume to Improve the Built-Up Areas' Extraction from SDGSAT-1 GLI Data . | REMOTE SENSING , 2024 , 16 (13) . |
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Poverty continues to pose significant global challenges. Analyzing poverty distribution is pivotal for identifying spatial and demographic disparities, informing targeted policy interventions, and fostering inclusive and equitable development. The absence of a worldwide pixel-scale time-series poverty dataset has hampered effective policy formulation. To address this gap, we employ the international wealth index (IWI) derived from household survey data to represent poverty levels. Subsequently, a random forest regression model was constructed, with IWI serving as the dependent variable and representative features extracted from nighttime lights, land cover, digital elevation model, and World Bank statistical data serving as independent variables. This yielded a global map of the IWI for low- and middle-income nations at a 10-km resolution spanning 2005 to 2020. The model demonstrated robust performance with an R2 value of 0.74. Over the studied period, areas and populations with IWI <= 50 decreased by 8.85% and 16.17%, indicating a steady decrease in global poverty regions. Changes in the IWI at the pixel scale indicate that areas closer to cities have faster growth rates. Furthermore, our poverty estimation models present a novel method for real-time pixel-scale poverty assessments. This study provides valuable insights into the dynamics of poverty, both globally and nationally.
Keyword ：
Global poverty Global poverty International Wealth Index International Wealth Index nighttime light data nighttime light data random forest regression model random forest regression model time-series time-series
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| GB/T 7714 | Li, Yangguang , Wu, Bin , Wang, Congxiao et al. Measuring human settlement wealth index at 10-km resolution in low- and middle-income countries from 2005 to 2020 using multi-source remote sensing data [J]. | INTERNATIONAL JOURNAL OF DIGITAL EARTH , 2024 , 17 (1) . |
| MLA | Li, Yangguang et al. "Measuring human settlement wealth index at 10-km resolution in low- and middle-income countries from 2005 to 2020 using multi-source remote sensing data" . | INTERNATIONAL JOURNAL OF DIGITAL EARTH 17 . 1 (2024) . |
| APA | Li, Yangguang , Wu, Bin , Wang, Congxiao , Chen, Zuoqi , Liu, Shaoyang , Yu, Bailang . Measuring human settlement wealth index at 10-km resolution in low- and middle-income countries from 2005 to 2020 using multi-source remote sensing data . | INTERNATIONAL JOURNAL OF DIGITAL EARTH , 2024 , 17 (1) . |
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2020年是中国全面打赢脱贫攻坚战的收官之年。合理评估减贫效果是当前验收工作的重点，并对探索解决相对贫困的长效机制具有重要意义。本文通过生产精准扶贫阶段（2014年—2020年NPP-VIIRS）夜间灯光遥感年合成数据，构建县域夜间灯光指数和变化指数，分别探讨了中国831个国家级贫困县和14个集中连片特困区的减贫效果。结果表明：2014年以来中国大部分贫困县的经济水平得到显著提高，减贫效果突出；仍有108个贫困县夜间灯光强度呈现负增长趋势，主要位于西部地区的集中连片特困区交界处，西部地区内部出现南北发展不平衡现象；14个集中连片特困地区的夜间灯光亮度变化呈现出基数小增速快（Ⅰ型）、基数大增速快（Ⅱ型）、基数大增速慢（Ⅲ型）和基数小增速慢（Ⅳ型） 4种类型，且在集中连片特困区交界处和省级行政边界交汇处呈现高高集聚和低低制约的空间分布格局，交界处的贫困县易被边缘化。进一步分析表明，实施基础设施扶贫、特色产业扶贫、资产收益扶贫（光伏扶贫）、易地搬迁扶贫这4类脱贫路径的贫困县夜间灯光变化明显。
Keyword ：
NPP-VIIRS NPP-VIIRS 减贫效果 减贫效果 国家级贫困县 国家级贫困县 夜间灯光 夜间灯光 时空变化 时空变化 集中连片特困地区 集中连片特困地区
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| GB/T 7714 | 华婧 , 吴宾 , 陈佐旗 et al. 精准扶贫背景下中国贫困县的夜间灯光时空变化分析 [J]. | 遥感学报 , 2024 , 28 (04) : 940-955 . |
| MLA | 华婧 et al. "精准扶贫背景下中国贫困县的夜间灯光时空变化分析" . | 遥感学报 28 . 04 (2024) : 940-955 . |
| APA | 华婧 , 吴宾 , 陈佐旗 , 杨成术 , 唐曦 , 孙斐然 et al. 精准扶贫背景下中国贫困县的夜间灯光时空变化分析 . | 遥感学报 , 2024 , 28 (04) , 940-955 . |
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新疆维吾尔自治区（以下简称“新疆”）作为中国西部战略屏障和向西开放的重要窗口，评估其城市化发展状况对于全国改革发展大局和“一带一路”倡议具有重要意义。相较于传统研究，夜间灯光遥感已被证明能够对人类活动强度和地区综合发展水平进行更客观、空间尺度更灵活、覆盖范围更广的监测。因此，本文利用2000年—2020年长时序夜间灯光遥感数据，采用标准差椭圆、时间序列分解以及夜间灯光发展指数等方法，从空间格局与时序演化上综合分析了21世纪以来新疆城市化进程。结果显示，2000年—2020年新疆城市化发展整体呈现向西南方向扩张的趋势，南疆地区发展速度强劲；21世纪以来新疆城市化演化过程可分为缓慢发展期（2007年之前）、波动增长期（2008年—2014年）和加速上升期（2015年之后） 3个阶段；新疆城镇地区及大部分地市的社会发展愈趋均衡，而乡村地区仍处于快速发展的差异化阶段。总体而言，21世纪以来新疆城市化进程处于快速且均衡发展的状态。
Keyword ：
城市化演化 城市化演化 夜间灯光发展指数 夜间灯光发展指数 夜间灯光遥感 夜间灯光遥感 新疆维吾尔自治区 新疆维吾尔自治区 时间序列分解 时间序列分解
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| GB/T 7714 | 刘少阳 , 陈佐旗 , 施开放 et al. 夜间灯光遥感揭示21世纪以来中国西北部地区城市化演化格局与过程 [J]. | 遥感学报 , 2024 , 28 (06) : 1497-1514 . |
| MLA | 刘少阳 et al. "夜间灯光遥感揭示21世纪以来中国西北部地区城市化演化格局与过程" . | 遥感学报 28 . 06 (2024) : 1497-1514 . |
| APA | 刘少阳 , 陈佐旗 , 施开放 , 吴宾 , 魏冶 , 王丛笑 et al. 夜间灯光遥感揭示21世纪以来中国西北部地区城市化演化格局与过程 . | 遥感学报 , 2024 , 28 (06) , 1497-1514 . |
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Industrial agglomeration, as a typical aspect of industrial structures, significantly influences policy development, economic growth, and regional employment. Due to the collection limitations of gross domestic product (GDP) data, the traditional assessment of industrial agglomeration usually focused on a specific field or region. To better measure industrial agglomeration, we need a new proxy to estimate GDP data for different industries. Currently, nighttime light (NTL) remote sensing data are widely used to estimate GDP at diverse scales. However, since the light intensity from each industry is mixed, NTL data are being adopted less to estimate different industries' GDP. To address this, we selected an optimized model from the Gaussian process regression model and random forest model to combine Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data and points-of-interest (POI) data, and successfully estimated the GDP of eight major industries in China for 2018 with an accuracy (R2) higher than 0.80. By employing the location quotient to measure industrial agglomeration, we found that a dominated industry had an obvious spatial heterogeneity. The central and eastern regions showed a developmental focus on industry and retail as local strengths. Conversely, many western cities emphasized construction and transportation. First-tier cities prioritized high-value industries like finance and estate, while cities rich in tourism resources aimed to enhance their lodging and catering industries. Generally, our proposed method can effectively measure the detailed industry agglomeration and can enhance future urban economic planning.
Keyword ：
Gaussian process Gaussian process GDP GDP industrial agglomeration industrial agglomeration nighttime light nighttime light points of interest points of interest
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| GB/T 7714 | Chen, Zuoqi , Xu, Wenxiang , Zhao, Zhiyuan . The Assessment of Industrial Agglomeration in China Based on NPP-VIIRS Nighttime Light Imagery and POI Data [J]. | REMOTE SENSING , 2024 , 16 (2) . |
| MLA | Chen, Zuoqi et al. "The Assessment of Industrial Agglomeration in China Based on NPP-VIIRS Nighttime Light Imagery and POI Data" . | REMOTE SENSING 16 . 2 (2024) . |
| APA | Chen, Zuoqi , Xu, Wenxiang , Zhao, Zhiyuan . The Assessment of Industrial Agglomeration in China Based on NPP-VIIRS Nighttime Light Imagery and POI Data . | REMOTE SENSING , 2024 , 16 (2) . |
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Human activity plays a crucial role in influencing PM2.5 concentration and can be assessed through nighttime light remote sensing. Therefore, it is important to investigate whether the nighttime light brightness can enhance the accuracy of PM2.5 simulation in different stages. Utilizing PM2.5 mobile monitoring data, this study introduces nighttime lighting brightness as an additional factor in the PM2.5 simulation model across various time periods. It compares the differences in simulation accuracy, explores the impact of nocturnal human activities on PM2.5 concentrations at different periods of the following day, and analyzes the spatial and temporal pollution pattern of PM2.5 in urban functional areas. The results show that (1) the incorporation of nighttime lighting brightness effectively enhances the model's accuracy (R2), with an improvement ranging from 0.04 to 0.12 for different periods ranges. (2) the model's accuracy improves more prominently during 8:00-12:00 on the following day, and less so during 12:00-18:00, as the PM2.5 from human activities during the night experiences a strong aggregation effect in the morning of the next day, with the effect on PM2.5 concentration declining after diffusion until the afternoon. (3) PM2.5 is primarily concentrated in urban functional areas including construction sites, roads, and industrial areas during each period. But in the period of 8:00-12:00, there is a significant level of PM2.5 pollution observed in commercial and residential areas, due to the human activities that occurred the previous night.
Keyword ：
GWR-GBDT GWR-GBDT Mobile monitoring Mobile monitoring NPP-VIIRS NPP-VIIRS PM2.5 simulation PM2.5 simulation Spatiotemporal analysis Spatiotemporal analysis Urban functional areas Urban functional areas
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| GB/T 7714 | Li, Daichao , Xu, Fangnian , Chen, Zuoqi et al. Fine simulation of PM2.5 combined with NPP-VIIRS night light remote sensing and mobile monitoring data [J]. | SCIENCE OF THE TOTAL ENVIRONMENT , 2024 , 914 . |
| MLA | Li, Daichao et al. "Fine simulation of PM2.5 combined with NPP-VIIRS night light remote sensing and mobile monitoring data" . | SCIENCE OF THE TOTAL ENVIRONMENT 914 (2024) . |
| APA | Li, Daichao , Xu, Fangnian , Chen, Zuoqi , Xie, Xiaowei , Fan, Kunkun , Zeng, Zhan . Fine simulation of PM2.5 combined with NPP-VIIRS night light remote sensing and mobile monitoring data . | SCIENCE OF THE TOTAL ENVIRONMENT , 2024 , 914 . |
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