A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series

Shoreline resources constitute one of the most critical terrestrial elements, as they play a pivotal role in fluvial-lacustrine monitoring and the sustainable utilization of spatial resources. As the longest and most economically significant river in China, the Yangtze River exhibits several unique geographical attributes, and as such, research on the spatiotemporal evolution and precise spatial delineation of its shoreline is important. Taking into account the complexity of the geographical environment, the study proposed a multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series data. Longitudinal variations, spatial displacement, and interbank disparities between the northern and southern shores of the Yangtze River, China have been quantitatively assessed, supported by a shoreline change rate model was developed using the Digital Shoreline Analysis System. The results demonstrated a high level of accuracy in shoreline spatial positioning, with clearly demarcated land–water boundaries. From 1990 to 2020, the total shoreline length exhibited a net increase from 12,645.02 km to 13,637.42 km. Both the northern and southern shores displayed synchronous elongation trends, peaking in 2010 before subsequent retreat. Linear regression rate and end point rate analyses revealed overall stability in these migration trends but pronounced interbank heterogeneity. The southern shore exhibited significantly greater linear regression and end point rate variability than the northern shore ( P < 0.05), indicative of the stronger synergistic impacts from anthropogenic and natural drivers in that area. This study establishes a framework for high-resolution dynamic monitoring of shorelines along large river systems and elucidates the spatial differentiation mechanisms governing the fluvial evolution of shorelines. The findings provide empirical support for optimizing shoreline resource allocation, delineating environmental conservation boundaries, and implementing the “Yangtze River Conservation Strategy,” thereby advancing the capacity of regional sustainable development and spatial governance. • A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series data was developed. • The characteristics of shoreline in the Yangtze River, China was explored based on time-series remote sensing image and the DSAS tool. • The spatiotemporal pattern of shoreline in the Yangtze River, China from 1990 to 2020 have been clearly identified and understood.

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Publication Details

Journal
Environmental and Sustainability Indicators
Published
2026-01-30
DOI
https://doi.org/10.1016/j.indic.2026.101153
Primary Topic
Coastal and Marine Dynamics
Type
article
Field-Weighted Citation Impact
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article

A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series

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Coastal and Marine Dynamics
article

A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series

Jian Gao, Aoxiang Zhu, Chao Chen, Xinping Yan, Xiaoyan Yang, Ni Kong, Miao Li, Shuo Lv, Ziyao Jin
article en

Abstract

Shoreline resources constitute one of the most critical terrestrial elements, as they play a pivotal role in fluvial-lacustrine monitoring and the sustainable utilization of spatial resources. As the longest and most economically significant river in China, the Yangtze River exhibits several unique geographical attributes, and as such, research on the spatiotemporal evolution and precise spatial delineation of its shoreline is important. Taking into account the complexity of the geographical environment, the study proposed a multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series data. Longitudinal variations, spatial displacement, and interbank disparities between the northern and southern shores of the Yangtze River, China have been quantitatively assessed, supported by a shoreline change rate model was developed using the Digital Shoreline Analysis System. The results demonstrated a high level of accuracy in shoreline spatial positioning, with clearly demarcated land–water boundaries. From 1990 to 2020, the total shoreline length exhibited a net increase from 12,645.02 km to 13,637.42 km. Both the northern and southern shores displayed synchronous elongation trends, peaking in 2010 before subsequent retreat. Linear regression rate and end point rate analyses revealed overall stability in these migration trends but pronounced interbank heterogeneity. The southern shore exhibited significantly greater linear regression and end point rate variability than the northern shore ( P < 0.05), indicative of the stronger synergistic impacts from anthropogenic and natural drivers in that area. This study establishes a framework for high-resolution dynamic monitoring of shorelines along large river systems and elucidates the spatial differentiation mechanisms governing the fluvial evolution of shorelines. The findings provide empirical support for optimizing shoreline resource allocation, delineating environmental conservation boundaries, and implementing the “Yangtze River Conservation Strategy,” thereby advancing the capacity of regional sustainable development and spatial governance. • A multi-stage strategy and geoscience knowledge-based method for shoreline extraction from Landsat time-series data was developed. • The characteristics of shoreline in the Yangtze River, China was explored based on time-series remote sensing image and the DSAS tool. • The spatiotemporal pattern of shoreline in the Yangtze River, China from 1990 to 2020 have been clearly identified and understood.

Environmental and Sustainability IndicatorsVol. 30
Suzhou University of Science and Technology (CN), Inner Mongolia Electric Power Survey & Design Institute (China) (CN), Inner Mongolia Autonomous Region Meteorological Bureau (CN), Hubei University of Technology (CN), Hubei University (CN)
Openalex Percentile: Top 77%
Coastal and Marine Dynamics
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