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学者姓名：陈佐旗
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Abstract ：
The urban scaling theory (UST) strives for a universal taxonomy that depicts relationships among urban indicators (e.g. energy consumption, economic output) with city size. However, the lack of international agreement on city definitions and statistics complicates cross-country comparisons of urban scaling performance. Remote sensing provides a uniform standard for measuring cities around the world. To scrutinize the consistency of UST, we quantified changes in remotely sensed urban built-up areas (UBA) and nighttime lights (NTL) distributions from 11,581 cities in 61 countries spanning 2000-2020, representing urban physical elements and socioeconomic activities, respectively. We find that UBA is well described by UST in all analyzed countries, while NTL aligns with 98% of them. UST quantified by remote sensing shows greater robustness than country-dependent aggregate statistics. We also observed disparities of scaling exponents (beta) among countries, with UBA all being sublinear (beta < 1), and NTL ranging from 0.46 to 1.22 with a median of 0.94. Both UST and rank-size distributions of urban area and population show stronger scaling relationships for countries with larger networks of built environments, (Brazil, China, Germany, Japan, Russia, United States) suggesting that both size and evolution of urban systems impact the underlying scaling processes. Comparison of scaling properties of remotely sensed UBA and NTL captures complementary physical characteristics of built environments while minimizing the Modifiable Area Unit Problem introduced using spatially aggregated metrics within administrative units. Our findings highlight the consistency of urban growth patterns while confirming the systematic socioeconomic disparities among urban systems of varying size and growth trajectory.
Keyword ：
complex systems complex systems remote sensing remote sensing scaling laws scaling laws urban scaling urban scaling urban science urban science
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| GB/T 7714 | Xu, Zhibang , Xu, Gang , Lan, Ting et al. Global consistency of urban scaling evidenced by remote sensing [J]. | PNAS NEXUS , 2025 , 4 (2) . |
| MLA | Xu, Zhibang et al. "Global consistency of urban scaling evidenced by remote sensing" . | PNAS NEXUS 4 . 2 (2025) . |
| APA | Xu, Zhibang , Xu, Gang , Lan, Ting , Li, Xi , Chen, Zuoqi , Cui, Hao et al. Global consistency of urban scaling evidenced by remote sensing . | PNAS NEXUS , 2025 , 4 (2) . |
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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. 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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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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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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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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Poverty is a major problem faced by developing countries. As the world’s largest developing country, China has been committed to poverty eradication. 2020 is the final year of China’s comprehensive victory in the war against poverty. At present, China has entered the post-poverty era, and the reasonable assessment of the poverty reduction effect is the focus of the acceptance work at this stage, which is of great significance to explore a long-term mechanism for solving relative poverty. The county-level geographical unit is the basic unit for China to formulate and implement the macro and micro policies and strategies for regional poverty reduction. Concentrated contiguous poverty-stricken areas concentrated in mountainous areas, old revolutionary base areas, and areas with poor natural resource endowment, with large internal development differences, belong to the most disaster-hit areas of poverty in China. After synthesizing an annual dataset of NPP-VIIRS nighttime light (NTL) data from 2014 to 2020, we developed a county-level NTL index to investigate the poverty reduction effects of 831 national level poverty-stricken counties and 14 concentrated contiguous poverty-stricken areas in China. The economic level of most poverty-stricken counties in China improved significantly during the study period, and the poverty reduction effect was prominent. However, 108 poverty-stricken counties still suffer from negative growth in terms of NTL intensity; these counties are located mainly at the junction of concentrated and contiguous poverty-stricken areas in the western region. The border area, mainly inhabited by ethnic minorities, has a poor ecological environment, a low level of economic development, and a relatively poor self-development ability, which may lead to a relatively poor poverty reduction effect. In addition, the NTL intensity development between the northern and southern parts of the western region is unbalanced. The growth rate of NTL in poor counties decreased from the east to the middle and western regions. In terms of the overall poverty alleviation trend, there was a period of rapid development in poor counties in the year before the declaration of poverty alleviation. However, after the declaration of poverty alleviation, the intensity of NTL decreased, the speed of poverty reduction slowed down, and there may be a risk of returning to poverty in some poor counties. Four NTL development modes, i.e., a small NTL base with a rapid growth rate (mode I), a large NTL base with a rapid growth rate (mode II), a large NTL base with a slow growth rate (mode III), and a small NTL base with a slow growth rate (mode IV), were identified in the 14 concentrated contiguous poverty-stricken areas. The high- and low-restriction modes were distributed at the junction areas of the different provincial administrative boundaries. In addition, poor counties along the border are vulnerable to marginalization. Further analysis indicated that significant NTL changes are apparent in the poverty-stricken counties, as demonstrated by their four poverty alleviation paths including infrastructure poverty alleviation, characteristic industry poverty alleviation, asset income poverty alleviation (photovoltaic poverty alleviation), and relocation poverty alleviation. However, the poverty reduction effect of poverty-stricken counties that take ecological compensation poverty alleviation, social guarantee poverty alleviation, and agricultural industry poverty alleviation as the leading poverty reduction methods are difficult to reflect in the NTL. © 2024 Science Press. All rights reserved.
Keyword ：
Concentration (process) Concentration (process) Developing countries Developing countries Disasters Disasters
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| GB/T 7714 | Hua, Jing , Wu, Bin , Chen, Zuoqi et al. Spatiotemporal variations in nighttime lights in poverty-stricken counties in China [J]. | National Remote Sensing Bulletin , 2024 , 28 (4) : 940-955 . |
| MLA | Hua, Jing et al. "Spatiotemporal variations in nighttime lights in poverty-stricken counties in China" . | National Remote Sensing Bulletin 28 . 4 (2024) : 940-955 . |
| APA | Hua, Jing , Wu, Bin , Chen, Zuoqi , Yang, Chengshu , Tang, Xi , Sun, Feiran et al. Spatiotemporal variations in nighttime lights in poverty-stricken counties in China . | National Remote Sensing Bulletin , 2024 , 28 (4) , 940-955 . |
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Given that Xinjiang Uygur Autonomous Region is a strategic barrier and an important platform of opening up to the western region, assessing its urbanization is critical to promote the national reform strategy and the Belt and Road Initiative. Compared with traditional method, nighttime light (NTL) remote sensing has been proved to be able to monitor human activity intensity and regional comprehensive development level in a more objective, flexible spatial scale and wider coverage. NTL remote sensing data has been able to analyze the urbanization evolution process and the level of social and economic development, but it is still necessary to expand and enrich the breadth and depth of research, especially to explore its spatial pattern and long-term evolution process, so as to more comprehensively understand the urbanization process and social development balance in Xinjiang. This paper comprehensively analyzes and discusses the evolution process of NTL in Xinjiang since the 21st century from three dimensions: time change trend, spatial distribution pattern and social development equilibrium, using NTL remote sensing data of long time series from 2000 to 2020, time series decomposition, spatial standard deviation ellipse and Night Light Development Index (NLDI). (1) From 2000 to 2020, the total amount of NTL in all regions of Xinjiang Uygur Autonomous Region increased to varying degrees. In terms of spatial pattern, urbanization in northern and eastern Xinjiang developed steadily, while rapid development in southern Xinjiang. The planning and construction of transportation lines is one of the important driving forces for the spatial expansion of urbanization in Xinjiang. (2) In the past 20 years, the total amount of NTL in Xinjiang has increased by 5.30 times, and the growth trend is accelerating. The NTL intensity in rural areas of Xinjiang increased by 7.60 times, which was larger than that in urban areas (4.10 times). The process of urbanization in Xinjiang can be divided into three stages: slow development (before 2007), volatile growth (from 2008 to 2014), and rapid development (after 2015). Policy support and the transformation of industrial and agricultural development make Xinjiang’s urbanization transition from the slow development period to the volatile growth period. The growth rate of the volatile growth period is nearly three times that of the slow development period, but at the same time, it is also disturbed by various extreme events. (3) From 2000 to 2019, the NLDI in most areas of Xinjiang decreased, the distribution of population and infrastructure construction in the whole region and most cities in Xinjiang became more reasonable, and the social development showed a trend of balanced development. However, compared with urban areas, the balance in rural areas of Xinjiang is weaker. This is due to the low starting point of urbanization development in rural areas of Xinjiang, which is still in the stage of rapid development, and urbanization is undergoing a process of 'from point to surface', so the current social development balance in rural areas shows a trend of decline. In general, the urbanization process of Xinjiang has been developing rapidly and evenly since the 21st century. © 2024 Science Press. All rights reserved.
Keyword ：
Economic and social effects Economic and social effects Long Term Evolution (LTE) Long Term Evolution (LTE) Remote sensing Remote sensing Time series Time series Urban growth Urban growth
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| GB/T 7714 | Liu, Shaoyang , Chen, Zuoqi , Shi, Kaifang et al. Nighttime light remote sensing reveals the pattern and process of urbanization evolution in northwest China since the 21st century [J]. | National Remote Sensing Bulletin , 2024 , 28 (6) : 1497-1514 . |
| MLA | Liu, Shaoyang et al. "Nighttime light remote sensing reveals the pattern and process of urbanization evolution in northwest China since the 21st century" . | National Remote Sensing Bulletin 28 . 6 (2024) : 1497-1514 . |
| APA | Liu, Shaoyang , Chen, Zuoqi , Shi, Kaifang , Wu, Bin , Wei, Ye , Wang, Congxiao et al. Nighttime light remote sensing reveals the pattern and process of urbanization evolution in northwest China since the 21st century . | National Remote Sensing Bulletin , 2024 , 28 (6) , 1497-1514 . |
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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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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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