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Author Saito, R.; Sasaki, H.; Yamada, H.; Hiroe, Y.; Inagake, D.; Saito, T. url  doi
openurl 
  Title Development of a technique to estimate the horizontal distribution of lit fishing vessels in the East China Sea using satellite luminescence Type Journal Article
  Year 2020 Publication Fisheries Science Abbreviated Journal Fish Sci  
  Volume 86 Issue 1 Pages 13-25  
  Keywords Remote Sensing  
  Abstract The East China Sea is a semi-enclosed sea, surrounded by Japan, China, South Korea and Taiwan, and is continuously influenced by lit fishing vessels overexploiting fishery resources. Quantitative analysis of this fishing activity is essential to sustainable resource management. Recent advances in satellite remote sensing technology, notably the introduction of the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite, which gathers luminescence data, have enabled the detection of lit fishing vessels operating at night. In the present study, we collected in situ observation data (ship radar images and visual observation data for lit fishing gear types) for the period when the Suomi NPP satellite passed over the East China Sea at night. The geographical position of each fishing gear type was extracted from the radar image and compared with the corresponding position of satellite luminescence in order to obtain the luminescence specific to each fishing gear type. We statistically analyzed the luminescence data to specify the luminescence range of each fishing gear type. The luminescence range of Chinese lit falling-net fishing vessels during nighttime fishing operations was distinguished from the ranges of other fishing gear types. We are now able to estimate the horizontal distribution of Chinese lit falling-net fishing vessels from Suomi NPP satellite luminescence, using its own luminescence range.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0919-9268 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number UP @ altintas1 @ Serial (down) 3142  
Permanent link to this record
 

 
Author Zhai W.; Han B.; Cheng C. url  doi
openurl 
  Title Evaluation of Luojia 1-01 Nighttime Light Imagery for Built-Up Urban Area Extraction: A Case Study of 16 Cities in China Type Journal Article
  Year 2019 Publication IEEE Geoscience and Remote Sensing Letters Abbreviated Journal  
  Volume in press Issue Pages in press  
  Keywords Remote Sensing  
  Abstract On June 2, 2018, the Luojia 1-01 (LJ1-01) nighttime light satellite was launched from China with a spatial resolution of 130 m at nadir, which is a significant improvement over the resolutions of previous nighttime light satellites. However, few studies have focused on the applications of LJ1-01 imagery. This letter aimed to evaluate the potential of utilizing LJ1-01 data to extract built-up urban areas in comparison with Visible Infrared Imaging Radiometer Suite (VIIRS) day-night band (DNB) data by conducting a case study of 16 cities involved in the Belt and Road Initiative in China. The built-up urban areas of the 16 cities were extracted by thresholding segmentation in reference to administrative statistical data, and 30-m-resolution artificial impervious data were adopted as the benchmark (ground truth). Qualitative and quantitative assessments were implemented for an evaluation, revealing that the built-up urban areas extracted by LJ1-01 data outperformed the areas extracted by VIIRS DNB data. We argue that these improvements originate from the superior spatial resolution and image quality of LJ1-01 over its predecessors. The LJ1-01 data presented excellent suitability for the extraction of built-up urban areas at the city scale, and hence, these data may be further applied to other related investigations.  
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  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1558-0571 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number UP @ altintas1 @ Serial (down) 3140  
Permanent link to this record
 

 
Author Ivan, K.; Holobâcă, I.-H.; Benedek, J.; Török, I. url  doi
openurl 
  Title VIIRS Nighttime Light Data for Income Estimation at Local Level Type Journal Article
  Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 12 Issue 18 Pages 2950  
  Keywords Remote Sensing  
  Abstract The aim of the paper is to develop a model for the real-time estimation of local level income data by combining machine learning, Earth Observation, and Geographic Information System. More exactly, we estimated the income per capita by help of a machine learning model for 46 cities with more than 50,000 inhabitants, based on the National Polar-orbiting Partnership–Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime satellite images from 2012–2018. For the automation of calculation, a new ModelBuilder type tool was developed within the ArcGIS software called EO-Incity (Earth Observation–Income city). The sum of light (SOL) data extracted by means of the EO-Incity tool and the observed income data were integrated in an algorithm within the MATLAB software in order to calculate a transfer equation and the average error. The results achieved were subsequently reintegrated in EO-Incity and used for the estimation of the income value at local level. The regression analyses highlighted a stable and strong relationship between SOL and income for the analyzed cities. The EO-Incity tool and the machine learning model proved to be efficient in the real-time estimation of the income at local level. When integrated in the information systems specific for smart cities, they can serve as a support for decision-making in order to fight poverty and reduce social inequalities.  
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  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial (down) 3138  
Permanent link to this record
 

 
Author Elvidge, C.D.; Ghosh, T.; Hsu, F.-C.; Zhizhin, M.; Bazilian, M. url  doi
openurl 
  Title The Dimming of Lights in China during the COVID-19 Pandemic Type Journal Article
  Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 12 Issue 17 Pages 2851  
  Keywords Remote Sensing; VIIRS; Day-night band (DNB); Nighttime lights; COVID-19; Pandemic; VIIRS-DNB  
  Abstract A satellite survey of the cumulative radiant emissions from electric lighting across China reveals a large radiance decline in lighting from December 2019 to February 2020—the peak of the lockdown established to suppress the spread of COVID-19 infections. To illustrate the changes, an analysis was also conducted on a reference set from a year prior to the pandemic. In the reference period, the majority (62%) of China’s population lived in administrative units that became brighter in March 2019 relative to December 2018. The situation reversed in February 2020, when 82% of the population lived in administrative units where lighting dimmed as a result of the pandemic. The dimming has also been demonstrated with difference images for the reference and pandemic image pairs, scattergrams, and a nightly temporal profile. The results indicate that it should be feasible to monitor declines and recovery in economic activity levels using nighttime lighting as a proxy.  
  Address Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines, Golden, CO 80401, USA; celvidge(at)mines.edu  
  Corporate Author Thesis  
  Publisher MDPI Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ john @ Serial (down) 3134  
Permanent link to this record
 

 
Author Peng, J.; Lin, H.; Chen, Y.; Blaschke, T.; Luo, L.; Xu, Z.; Hu, Y.’na; Zhao, M.; Wu, J. url  doi
openurl 
  Title Spatiotemporal evolution of urban agglomerations in China during 2000–2012: a nighttime light approach Type Journal Article
  Year 2020 Publication Landscape Ecology Abbreviated Journal Landscape Ecol  
  Volume 35 Issue 2 Pages 421-434  
  Keywords Remote Sensing  
  Abstract Context

Urban agglomeration is an advanced spatial organization of cities, usually caused by urbanization processes when cities develop to a certain level – typically associated with higher population density and a certain density of built environment. However, compared with various studies focusing on specific cities, urban agglomerations are still understudied, especially for the quantitative identification of spatiotemporal evolution of urban agglomerations.

Objectives

This study aims to identify the boundary of urban agglomerations in China from 2000 to 2012, and to explore the temporal evolution and spatial difference of urban agglomerations.

Methods

Firstly, the core zone of urban agglomerations was identified using an appropriate threshold of the digital number (DN) of nighttime light. Secondly, the mean patch area and gravity model were used to determine the affected zone of urban agglomerations. Thirdly, spatiotemporal contrast was conducted focusing on the 23 main urban agglomerations in China.

Results

By 2012, the most highly developed Yangtze River Delta and Pearl River Delta urban agglomerations met the standard of world level, with the Beijing–Tianjin–Hebei urban agglomeration for regional level, as well as 11 urban agglomerations for sub-regional level. Regional differences in urban agglomerations between southern and northern China, or between coastal and inland China remained stable over the study period of 2000–2012. Compared with the western urban agglomerations, the outward expansion of eastern urban agglomerations decelerated. From 2000 to 2012, the overall development mode of urban agglomerations shifted from the core-expansion to the peripheral-development, together with slower expansion of urban agglomerations after 2006.

Conclusions

Nighttime light data are effective in exploring the spatiotemporal evolution of urban agglomerations.
 
  Address  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0921-2973 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial (down) 3131  
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