Research on the spatiotemporal distribution and evolution of remote sensing: A data-driven analysis - Liu, Yu; Kuai, Xi; Su, Fei; Wang, Shaochen; Wang, Kaifeng; Xing, Lijun (Frontiers in Environmental Science, 2022)
The development of remote sensing technology largely reflects the scientific research level of a country/region. Given that the quantity and quality of papers are important indicators for scientific prowess evaluation, exploratory spatial data analysis and scientometric analysis of remote sensing papers published from 2012 to 2021 were performed in this study utilizing the Web of Sciences database. This study probed the spatial distribution and spatiotemporal evolution at the country/regional level to reveal the spatiotemporal characteristics of knowledge spillover in remote sensing. According to the results, the global spatial distribution of paper output in remote sensing presented a significant dispersion; the United States and China were the most active countries. During the study period, Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery was one of the most influential papers both in the field of remote sensing and in the whole scientific community. With respect to the spatial evolution of paper output in remote sensing, the gap between continents and the regional imbalance showed a downward trend, while Asia ranked first in the intracontinental disparity, and Europe ranked last. For relevant countries/regions and institutions trying to optimize the spatial allocation of scientific and technological resources to narrow regional disparities, this study provides fundamental data as well as decision-making references.