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A Scientometric Visualization Analysis for Night-Time Light Remote Sensing Research from 1991 to 2016

1
The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2
Faculty of Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China
3
Economics and Management School, Wuhan University, Wuhan 430079, China
4
Center for Regional Economics Research, Wuhan University, Wuhan 430079, China
5
Changjiang Spatial Information Technology Engineering Co., Ltd, Wuhan 430000, China
*
Author to whom correspondence should be addressed.
Received: 31 May 2017 / Revised: 20 July 2017 / Accepted: 1 August 2017 / Published: 4 August 2017
(This article belongs to the Special Issue Recent Advances in Remote Sensing with Nighttime Lights)
In this paper, we conducted a scientometric analysis based on the Night-Time Light (NTL) remote sensing related literature datasets retrieved from Science Citation Index Expanded and Social Science Citation Index in Web of Science core collection database. Using the methods of bibliometric and Social Network Analysis (SNA), we drew several conclusions: (1) NTL related studies have become a research hotspot, especially after 2011 when the second generation of NTL satellites, the Suomi National Polar-orbiting Partnership (S-NPP) Satellite with the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor was on board. In the same period, the open-access policy of the long historical dataset of the first generation satellite Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) started. (2) Most related studies are conducted by authors from USA and China, and the USA takes the lead in the field. We identified the biggest research communities constructed by co-authorships and the related important authors and topics by SNA. (3) By the visualization and analysis of the topic evolution using the co-word and co-cited reference networks, we can clearly see that: the research topics change from hardware oriented studies to more real-world applications; and from the first generation of the satellite DMSP/OLS to the second generation of satellite S-NPP. Although the Day Night Band (DNB) of the S-NPP exhibits higher spatial and radiometric resolution and better calibration conditions than the first generation DMSP/OLS, the longer historical datasets in DMSP/OLS are still important in long-term and large-scale human activity analysis. (4) In line with the intuitive knowledge, the NTL remote sensing related studies display stronger connections (such as interpretive frame, context, and academic purpose) to the social sciences than the general remote sensing discipline. The citation trajectories are visualized based on the dual-maps, thus the research preferences for combining the environmental, ecological, economic, and political science disciplines are clearly exhibited. Overall, the picture of the NTL remote sensing research is presented from the scientist-level, topic-level, and discipline-level interactions. Based on these analyses, we also discuss the possible trends in the future work, such as combining NTL studies with social science research and social media data. View Full-Text
Keywords: scientometric analysis; NTL; DMSP/OLS; Suomi NPP; VIIRS DNB; bibliometric; SNA scientometric analysis; NTL; DMSP/OLS; Suomi NPP; VIIRS DNB; bibliometric; SNA
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MDPI and ACS Style

Hu, K.; Qi, K.; Guan, Q.; Wu, C.; Yu, J.; Qing, Y.; Zheng, J.; Wu, H.; Li, X. A Scientometric Visualization Analysis for Night-Time Light Remote Sensing Research from 1991 to 2016. Remote Sens. 2017, 9, 802. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9080802

AMA Style

Hu K, Qi K, Guan Q, Wu C, Yu J, Qing Y, Zheng J, Wu H, Li X. A Scientometric Visualization Analysis for Night-Time Light Remote Sensing Research from 1991 to 2016. Remote Sensing. 2017; 9(8):802. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9080802

Chicago/Turabian Style

Hu, Kai, Kunlun Qi, Qingfeng Guan, Chuanqing Wu, Jingmin Yu, Yaxian Qing, Jie Zheng, Huayi Wu, and Xi Li. 2017. "A Scientometric Visualization Analysis for Night-Time Light Remote Sensing Research from 1991 to 2016" Remote Sensing 9, no. 8: 802. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9080802

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