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学者姓名：陈佐旗
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Abstract ：
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 等. "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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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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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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叶绿素a浓度可以评估海水富营养化状况，对沿海叶绿素a浓度影响因素的研究在海洋环境保护方面具有重要意义。而现有研究多关注自然因素对沿海叶绿素a浓度的影响，忽视了人为因素的作用。因此实验以夜间灯光遥感数据表征人类活动强度，根据夜间灯光亮度和沿海叶绿素a浓度间的关系将东南沿海的城市分为3个类型，并同时结合海表温度、风速、太阳辐射、降水等自然因素，通过广义相加模型（GAM）分析不同季节下3类城市中人为和自然等多重因素对沿海叶绿素a浓度的影响。结果表明：在北海、汕头等类型Ⅰ城市中自然因素主导叶绿素a浓度的变化，春季的主导因素为风速，夏、秋、冬季为海表温度；而人类活动对叶绿素a浓度的影响较小且没有显著的影响关系。珠海、东莞等类型Ⅱ城市的叶绿素a浓度受自然因素主导，春、秋、冬季的主导因素为风速，夏季为海表温度；而人类活动在夏、秋季对沿海叶绿素a浓度有较大的促进作用。深圳、香港等类型Ⅲ城市中人为因素主导叶绿素a浓度的变化，春、夏、秋季人类活动对叶绿素a浓度的影响最大且为负相关，冬季海表温度对叶绿素a浓度的影响最大。
Keyword ：
东南沿海 东南沿海 人类活动 人类活动 叶绿素a 叶绿素a 广义相加模型(GAM) 广义相加模型(GAM) 自然因素 自然因素
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| GB/T 7714 | 张婧薇 , 陈佐旗 , 苏华 . 基于广义相加模型的东南沿海叶绿素a浓度的多重影响与季节差异 [J]. | 遥感技术与应用 , 2024 , 39 (01) : 134-148 . |
| MLA | 张婧薇 et al. "基于广义相加模型的东南沿海叶绿素a浓度的多重影响与季节差异" . | 遥感技术与应用 39 . 01 (2024) : 134-148 . |
| APA | 张婧薇 , 陈佐旗 , 苏华 . 基于广义相加模型的东南沿海叶绿素a浓度的多重影响与季节差异 . | 遥感技术与应用 , 2024 , 39 (01) , 134-148 . |
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Tidal wetlands provide a variety of ecosystem services to coastal communities but suffer severe losses due to anthropogenic activities in the Yangtze River Estuary (YRE). However, the detailed dynamics of tidal wetlands have not been well studied with sufficient spatiotemporal resolution. Here, we proposed a rapid classification method that integrates the COntinuous monitoring of Land Disturbance (COLD) algorithm and Median Composite (MC) based on the dense Landsat time series to track the dynamic processes of tidal wetlands in the YRE from 1990 to 2020. The results showed that the COLD-MC demonstrated remarkable effectiveness in detecting the change of tidal wetlands and excellent overall accuracy and kappa coefficient ranging from 90% to 96% and 0.89-0.95, respectively. The overall accuracy of change detection was 97% with an absolute error of 0.4 years. We found that the total area of tidal wetlands experienced a net loss of 59.75 km2 in the YRE, but the gain and loss of the study period were 1556.07 and 1615.82 km2, respectively. Land reclamation, sediment reduction, and Spartina alterniflora invasion pose significant threats to tidal wetlands. Sustainable management could be implemented through the establishment of nature reserves and ecological sediment enhancement engineering projects.
Keyword ：
COLD-MC COLD-MC dynamic equilibrium dynamic equilibrium land reclamation land reclamation landsat time-series landsat time-series sediment starvation sediment starvation Tidal wetlands Tidal wetlands
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| GB/T 7714 | Wu, Wenting , Lin, Zhibin , Chen, Chunpeng et al. Tracking the dynamics of tidal wetlands with time-series satellite images in the Yangtze River Estuary, China [J]. | INTERNATIONAL JOURNAL OF DIGITAL EARTH , 2024 , 17 (1) . |
| MLA | Wu, Wenting et al. "Tracking the dynamics of tidal wetlands with time-series satellite images in the Yangtze River Estuary, China" . | INTERNATIONAL JOURNAL OF DIGITAL EARTH 17 . 1 (2024) . |
| APA | Wu, Wenting , Lin, Zhibin , Chen, Chunpeng , Chen, Zuoqi , Zhao, Zhiyuan , Su, Hua . Tracking the dynamics of tidal wetlands with time-series satellite images in the Yangtze River Estuary, China . | INTERNATIONAL JOURNAL OF DIGITAL EARTH , 2024 , 17 (1) . |
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Nighttime Light (NTL) is highly concentrated in China ' s coastal zone, leading to negative health impacts on both humans and wildlife. Particularly, in recent years, the widespread adoption of broad-spectrum Light -Emitting Diode (LED) light, a low -carbon technology providing substantial increases in luminosity, has led to certain ecological consequences. Thus, information regarding spatial distribution and composition of different NTL types is essential for formulating sustainable strategies that balance nighttime public security, energy consumption, and ecosystem conservation. However, the availability of such information remains limited. To address this challenge and meet the demand, we developed two new light indices, namely the Ratio Red Light Index (RRLI) and Ratio Blue Light Index (RBLI), based on SDGSAT-1 Glimmer Imager (GLI) multispectral NTL data. We then proposed a threshold method and applied it to the entire coastal zone of China to identify White LED (WLED), Red LED (RLED), and Other lights (Other). Results showed the following. (1) In the coastal zone of China, the total lighting area was 20,517 km 2 , including 20,257 km 2 of terrestrial lights and 260 km 2 of offshore lights; (2) WLED light covered 67% (13,727 km 2 ) of all lighting areas, while RLED lights accounted for only 1% (220 km 2 ); (3) Guangdong had the largest lighting area (5221 km 2 ), with the proportion of WLEDs being the highest among all coastal provinces (almost 90%); (4) The proportions of lighting areas were relatively low in Guangxi, Liaoning, and Hebei. This study represents the first attempt to identify NTL types over large regions at a finer spatial resolution. The approach proposed, including the light indices of RRLI and RBLI, as well as the defined thresholds, is universal and robust for use in NTL type classification. The developed lighting type map, containing comprehensive information on the spatial distribution and composition of NTL, could facilitate the sustainable management of China ' s coastal zones.
Keyword ：
China 's coastal zone China 's coastal zone Light -emitting diode (LED) Light -emitting diode (LED) Light index Light index Nighttime light (NTL) Nighttime light (NTL) SDGSAT-1 GLI SDGSAT-1 GLI
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| GB/T 7714 | Jia, Mingming , Zeng, Haihang , Chen, Zuoqi et al. Nighttime light in China's coastal zone: The type classification approach using SDGSAT-1 Glimmer Imager [J]. | REMOTE SENSING OF ENVIRONMENT , 2024 , 305 . |
| MLA | Jia, Mingming et al. "Nighttime light in China's coastal zone: The type classification approach using SDGSAT-1 Glimmer Imager" . | REMOTE SENSING OF ENVIRONMENT 305 (2024) . |
| APA | Jia, Mingming , Zeng, Haihang , Chen, Zuoqi , Wang, Zongming , Ren, Chunying , Mao, Dehua et al. Nighttime light in China's coastal zone: The type classification approach using SDGSAT-1 Glimmer Imager . | REMOTE SENSING OF ENVIRONMENT , 2024 , 305 . |
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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, potentially facilitating the monitoring of sustainable development goals (SDGs). This study developed a denoising algorithm for the multispectral SDGSAT-1 GLI and demonstrated that its data capacity allows for the measurement of the SDG indicators 7.1.1, 11.5.2, and the achievement of target 7.3. The results indicate that (1) The denoising algorithm can effectively remove strips and salt -and -pepper noise from SDGSAT-1 GLI images, with the residual noise significantly reduced and almost little information loss. (2) SDGSAT-1 GLI data can accurately identify electrified areas at a finer spatial scale for calculating Indicator 7.1.1, compared to the traditional NASA ' s Black Marble Product. The findings show that highly urbanized cities exhibit a greater proportion of their population with access to electricity than underdeveloped cities. (3) SDGSAT-1 proficiently estimates economic losses resulting from nonnatural disasters for Indicator 11.5.2. Changes in SDGSAT-1 NTL intensity strongly correlate with pandemicinduced economic losses, with an R 2 exceeding 0.8. (4) When measuring Target 7.3 achievement, the SDGSAT-1 GLI multispectral bands classify streetlight types into light-emitting diode and high-pressure sodium lamps with acceptable overall accuracy (89.9%). Sequentially, the classification shows that Shanghai achieved a 13.09% energy-saving benefit. Overall, by leveraging the high spatial resolution, multiple spectra, and appropriate satellite overpass times of SDGSAT-1 GLI, the estimated SDG indicators in this study outperform those based on Black Marble products, and SDGSAT-1 GLI data have the potential to serve as a direct data source or reference factor for estimating at least 11 SDG indicators.
Keyword ：
Denoising algorithm Denoising algorithm Glimmer imager Glimmer imager Nighttime light Nighttime light SDGs SDGs SDGSAT-1 SDGSAT-1
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| GB/T 7714 | Liu, Shaoyang , Wang, Congxiao , Chen, Zuoqi et al. Efficacy of the SDGSAT-1 glimmer imagery in measuring sustainable development goal indicators 7.1.1, 11.5.2, and target 7.3 [J]. | REMOTE SENSING OF ENVIRONMENT , 2024 , 305 . |
| MLA | Liu, Shaoyang et al. "Efficacy of the SDGSAT-1 glimmer imagery in measuring sustainable development goal indicators 7.1.1, 11.5.2, and target 7.3" . | REMOTE SENSING OF ENVIRONMENT 305 (2024) . |
| APA | Liu, Shaoyang , Wang, Congxiao , Chen, Zuoqi , Li, Wei , Zhang, Lingxian , Wu, Bin et al. Efficacy of the SDGSAT-1 glimmer imagery in measuring sustainable development goal indicators 7.1.1, 11.5.2, and target 7.3 . | REMOTE SENSING OF ENVIRONMENT , 2024 , 305 . |
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Green roof installations and photovoltaic (PV) systems are widely employed roof retrofits that aid cities in mitigating climate change impacts, while avoiding the need for increased land utilization. By integrating PV systems with vegetation on urban roofs, a photovoltaic-green (PV-Green) system can be achieved for multifunctional use of the roof space, thereby simultaneously achieving PV and greening benefits. However, current research solely based on one retrofit type cannot meet the requirement for assessing the multifunctional retrofit potential of urban roofs. In this study, an assessment method is proposed to identify and quantify the multiple retrofit potential of urban roofs by integrating roof attributes (slope, orientation, and area), roof type (gable or flat), solar attributes (radiation and irradiation duration), and biogeochemical simulation. Moreover, three roof retrofit scenarios, Scenario 1 (S1): maximization of PV-Green roofs, Scenario 2 (S2): maximization of PV economic benefits, and Scenario 3 (S3): maximization of public subjective well-being through roof greening, were designed to allocate the use of urban roof spaces and evaluate their respective potential power and carbon benefits at the city scale. Using Shanghai's downtown as an example, the results showed that 85,722 roofs (or 7310.86 ha) were available for multifunctional use. S1 revealed that applying PV-Green roofs can increase the additional green biomass by 0.74 x 107 kg C/yr compared to only installing PV roofs. Moreover, S1 produced the highest power output of 2.31 x 1010 kWh/yr to meet 15.4% of Shanghai's electricity demand. S2 identified 609 flat roofs and 70,527 gable roofs that were uneconomical for PV system installation. This indicated that the solar radiation received by most gable roofs was insufficient to cover the installation cost. S3 offered a biomass production of 1.48 x 107 kg C/yr and increased carbon stocks in Shanghai by 0.87%. This assessment method provides urban planners and policymakers with an analytical tool to optimize the use of urban roof spaces, thereby enhancing urban livability and sustainability.
Keyword ：
GIS GIS Green roof Green roof Photovoltaic-green roof Photovoltaic-green roof Potential area Potential area Retrofit scenario Retrofit scenario Roof retrofitting Roof retrofitting
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| GB/T 7714 | Pan, Zhan , Wang, Congxiao , Yu, Bailang et al. Assessing multifunctional retrofit potential of urban roof areas and evaluating the power and carbon benefits under efficient retrofit scenarios [J]. | JOURNAL OF CLEANER PRODUCTION , 2024 , 444 . |
| MLA | Pan, Zhan et al. "Assessing multifunctional retrofit potential of urban roof areas and evaluating the power and carbon benefits under efficient retrofit scenarios" . | JOURNAL OF CLEANER PRODUCTION 444 (2024) . |
| APA | Pan, Zhan , Wang, Congxiao , Yu, Bailang , Chen, Zuoqi , Yuan, Yuan , Li, Guorong et al. Assessing multifunctional retrofit potential of urban roof areas and evaluating the power and carbon benefits under efficient retrofit scenarios . | JOURNAL OF CLEANER PRODUCTION , 2024 , 444 . |
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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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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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