关键词: 河湖水系, 遥感监测, 演变趋势, 演变原因, 河湖形态

Abstract:

[Objective] A bibliometric analysis is conducted using data from China National Knowledge Infrastructure (CNKI) to examine the application of remote sensing technology in monitoring river and lake morphology and water bodies (including runoff monitoring, sediment monitoring, water level monitoring, water surface monitoring, and water volume estimation). The study focuses on discussing the temporal distribution of research publications, spatial distribution of study areas, types of sensors used, and variations in research methods within China. It summarizes key applications and development trends of remote sensing technology in China’s river and lake evolution and management, and compares them with literature on similar topics published between 2014 and 2023 from the Web of Science (WOS) Core Collection. [Methods] Using the advanced search tool of the CNKI database, 25 topics were selected, including “evolution”, “erosion and deposition”, “sediment”, “turbidity”, “main channel”, “fluvial facies”, “bank collapse”, “river regime”, “shrinkage”, “expansion”, “wetland”, “riparian zone”, “connectivity”, “unmanned aerial vehicle (UAV)”, and others. Using the Advanced Search tool in the WOS, this study retrieved relevant literature from the WOS Core Collection of the past decade on similar topics. After excluding literature irrelevant to “river-lake system evolution”, this study ultimately selected 284 articles from CNKI and 745 from WOS for analysis. [Results] In the CNKI dataset, the quantity of literature on river and lake evolution studies using remote sensing technology has shown fluctuating increase since 2002, peaking in 2023 with annual literature quantity of 33 papers. In the WOS dataset, literature quantity has increased steadily since 2018, reaching its peak between 2020 and 2022. Earlier co-occurring keywords included “wetland” and “sediment transport”, while more recent keywords included “Surface Water and Ocean Topography (SWOT)”, “human activities”, “river morphology”, “bank erosion”, and “Google Earth Engine”. Further statistical analysis of the remote sensing data sources used in these studies reveals that Landsat satellite data were the most commonly used, followed by platforms such as MODIS, Chinese Resources Satellites, Environmental Satellites, Sentinel satellites, and Gaofen series. [Conclusion] The application of remote sensing technology in river and lake evolution studies in China has transitioned from reliance on single-source passive optical sensors (visible to infrared spectrum) to multi-source remote sensing through the integration of optical and microwave multi-satellite synergy. This development overcomes limitations of traditional methods for observation, simulation, and management of river-lake systems. Remote sensing technology provides long-term image data, and with further improvement in image interpretation capabilities, more accurate methods for identifying water bodies, vegetation, and other features are expected to further support research. Leveraging remote sensing to deepen the understanding of river-lake ecosystems is of great significance for achieving integrated watershed management.

Key words: river-lake systems, remote sensing monitoring, evolution trends, driving factors, river and lake morphology