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

Kai Hu,Qingfeng Guan,Jingmin Yu,Yaxian Qing,Kunlun Qi,Huayi Wu,Jie Zheng,Chuanqing Wu,Xi Li

doi:10.3390/rs9080802

Abstract

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.

Highlights

Night-Time Light (NTL) remote sensing, a process using satellite sensors to acquire the city lights, vessel lights, burning biomass, and gas flares, is important for studying social issues such as poverty, environment, and ecology because NTL reflects real human activities
NTL remote sensing is used as an important supplementary dataset to the census in decision making processes
We present a systematic analysis using the clues provided by sophisticated bibliometric and Social Network Analysis (SNA) analysis

Summary

Introduction

Night-Time Light (NTL) remote sensing, a process using satellite sensors to acquire the city lights, vessel lights, burning biomass, and gas flares, is important for studying social issues such as poverty, environment, and ecology because NTL reflects real human activities. NTL remote sensing is used as an important supplementary dataset to the census in decision making processes. Census data are not always efficient or accurate given popular mistrust of government agencies or because of data collection issues stemming from social unrest, wars, or poverty. NTL remote sensing can help mitigate the deficiencies in these datasets. NTL can be used to investigate different types of development issues related to human activities [1], including ecological pressures, the degree of country-level economic activity, the rate of city-level urbanization, and light pollution. In 2011, Chen et al used the NTL imagery data as the proxy for economic analysis [2]

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