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基于文献计量的中国水利遥感研究热点分析OACSTPCD

Research Hotspots Analysis of Chinese Water Conservancy Remote Sensing Based on Bibliometric Method

中文摘要英文摘要

近20a来,遥感监测技术在水利领域的广泛应用为获取大范围、高频率以及高分辨率的数据提供了有效手段,同时其多光谱和多源数据融合的能力也愈发凸显.探究遥感技术在水利领域的应用前景,通过对中国知网数据库内近20a水利遥感文献的可视化数据知识图谱分析,揭示了其中的研究热点和主要趋势.研究结果显示,遥感关键技术、水旱地灾防治、城市化进程分析、生态环境保护、智慧水利工程建设和助力乡村振兴战略成为水利遥感研究的焦点.与此同时,研究趋势逐渐集中于运用无人机、深度学习等高新技术,进一步提升遥感影像解译和应用能力,从而为智慧水利建设提供有力支持.

Over the past two decades,the widespread application of remote sensing technology in the field of water conservancy has provided an effective means to acquire data over large areas with high frequency and resolution,while the capability of multi-spectral and multi-source data fusion has become increasingly prominent.Aiming to explore the prospects of remote sensing technology in the water conservancy domain,through a visual analysis of a knowledge graph constructed from water conservancy remote sensing literature within the Chinese national knowl-edge infrastructure database over the past two decades,we identified the focal areas and major trends.The findings reveal that key remote sens-ing techniques,water-related disaster prevention and mitigation,urbanization process analysis,ecological environment conservation,the construc-tion of intelligent water conservancy projects,and contributions to rural revitalization strategies have emerged as focal points in water conservan-cy remote sensing research.Furthermore,there is a discernible trend towards the utilization of advanced technologies,such as unmanned aerial vehicles and deep learning algorithms,to augment the interpretative and application capabilities of remote sensing imagery.This advancement is anticipated to provide robust support for the development of intelligent water conservancy initiatives.

方喻弘;宋丽;肖潇;郑学东

长江水利委员会长江科学院,湖北 武汉 430000

测绘与仪器

水利遥感智慧水利知识图谱CiteSpace

remote sensing technologysmart water conservancyknowledge graphCiteSpace

《地理空间信息》 2024 (008)

15-22 / 8

国家自然科学基金长江水科学研究联合基金资助项目(U2240224);湖南省重大水利科技项目(XSKJ2022068-12);国家重点研发计划课题资助项目(2023YFC3209502、2023YFC3209503);长江科学院中央级公益性科研院所基本科研基金资助项目(CKSF2021485+KJ).

10.3969/j.issn.1672-4623.2024.08.004

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