Research on the spatiotemporal distribution and evolution of remote sensing: A data-driven analysis
Research on the spatiotemporal distribution and evolution of remote sensing: A data-driven analysis
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遥感时空分布与演化研究：数据驱动分析
DOI：
10.3389/fenvs.2022.932753
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发表时间：
2022-08
影响因子：
4.6
通讯作者：
Lijun Xing
中科院分区：
文献类型：
--
作者：
Yu Liu;Xi Kuai;Fei Su;Shaochen Wang;Kaifeng Wang;Lijun Xing
遥感技术的发展在很大程度上反映了一个国家或地区的科研水平。鉴于研究成果的数量和质量是评估科学实力的重要指标，本研究利用Web of Sciences数据库，对2012年至2021年发表的遥感研究成果进行了探索性空间数据分析和科学计量分析。本研究探究了国家/地区层面的空间分布及时空演变，以揭示遥感领域知识溢出的时空特征。研究结果表明，全球遥感研究产出的空间分布呈现出显著的离散性；美国和中国是最活跃的国家。在研究期间，《迁移深度卷积神经网络用于高分辨率遥感影像场景分类》是遥感领域乃至整个科学界最具影响力的研究之一。关于遥感研究产出的空间演变，各大洲之间的差距和区域不平衡呈下降趋势，而亚洲在洲内差异方面排名第一，欧洲排名最后。对于试图优化科技资源空间配置以缩小区域差距的相关国家/地区和机构而言，本研究提供了基础数据和决策参考。
The development of remote sensing technology largely reflects the scientific research level of a country or region. Given that the quantity and quality of research works are important indicators for scientific prowess evaluation, exploratory spatial data analysis and scientometric analysis of remote sensing work 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 research 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 studies, both in the field of remote sensing and in the whole scientific community. With respect to the spatial evolution of research 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 and decision-making references.
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影响因子：
3.9
作者：
Yanhua Zhuang;Xingjian Liu;Thuminh Nguyen;Qingqing He;Song Hong
通讯作者：
Yanhua Zhuang;Xingjian Liu;Thuminh Nguyen;Qingqing He;Song Hong
影响因子：
2.9
作者：
Lee DK;In J;Lee S
通讯作者：
Lee S
DOI：
10.1515/28785
发表时间：
2021-02
期刊：
Bulletin of Geography. Socio-economic Series
影响因子：
--
作者：
A. A. Mikhailov-A.;A. Mikhaylova;K. Alsynbaev;Vitaliy M. Bryksin;D. Hvaley
通讯作者：
A. A. Mikhailov-A.;A. Mikhaylova;K. Alsynbaev;Vitaliy M. Bryksin;D. Hvaley
影响因子：
3.9
作者：
S. Kocaman;N. Ozdemir
通讯作者：
S. Kocaman;N. Ozdemir
DOI：
10.1109/igarss.2019.8898378
发表时间：
2019-07
期刊：
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
影响因子：
--
作者：
Qingmiao Ma;Yingjie Li;Jing Chen-;Xin Li;Bo-Lan Liu;Jinzhi Li;Yalan Li;Chenze Zhang
通讯作者：
Qingmiao Ma;Yingjie Li;Jing Chen-;Xin Li;Bo-Lan Liu;Jinzhi Li;Yalan Li;Chenze Zhang