基于遥感与机器学习的辽河口盐沼湿地时空分异及驱动机制研究OACHSSCD
Spatiotemporal patterns and driving mechanisms of salt marshes in the Liaohe Estuary based on remote sensing and machine learning
聚焦我国纬度较高的辽河口盐沼湿地,提出"时间序列遥感+物候约束+潮位校正+机器学习"的综合技术路线,基于谷歌地球引 擎(Google Earth Engine,GEE)云平台,集成 1990-2024 年多源多时相 Landsat 系列遥感影像,结合随机森林算法(Random Forest,RF)和数字岸线分析系统(Digital Shoreline Analysis System,DSAS)探讨河口盐沼湿地的时空分异过程.结果表明:(1)辽河口盐沼呈波动式先降后升态势,年均面积 42.71km2,1990-2003 年为下降阶段(年均减少 1.25km2/a),2004-2024 年为上升阶段(年均增加 1.48km2/a);(2)河口西岸盐沼面积约为东岸的 2-3 倍,其变化态势也呈波动式先降后升,年均22.43km2;河口东岸盐沼面积波动上升,年均 13.71km2,年均增速 0.28km2/a;(3)河口岸线形态总体趋于曲折化,西岸岸线呈现高强度且不均衡的冲淤动态(80.58%淤积断面与 19.42%侵蚀断面共存),东岸岸线以渐进式淤积为主(85.50%断面显著淤积),强动态区段(西岸 c1 段)的剧烈变迁与围垦-清退高度相关;(4)辽河口盐沼变化主要受人类活动控制,尽管近年来上游水沙量波动增加,但因潮流动力较弱且围垦养殖等人为工程阻断输沙路径,其并非盐沼变化的主要原因;海平面持续上升背景下,退养还湿等生态修复工程抵消了部分不利影响,盐沼暂未因海平面上升呈现负面变化;但未来仍面临沉积物供给不足、海平面上升及历史性功能损伤引发的盐沼退化风险.研究揭示了辽河口盐沼变迁在自然和人类活动影响下呈现显著的时空异质性及其复杂驱动机制,可为辽河口及其他类似河口三角洲的针对性生态修复策略和海岸带可持续管理提供关键科学依据.
This study comprehensively investigates the long-term dynamics and spatial heterogeneity of Liaohe Estuary,which is one of the most important salt marsh wetlands and located at a relatively high latitude in China.Recognizing the dynamics of salt marshes to both natural and anthropogenic pressures,we proposed an integrated technical framework that combined time-series remote sensing analysis,phenological constraint application,tidal correction,and machine learning approaches.Leveraging the computational power of the Google Earth Engine(GEE)cloud platform,multi-temporal Landsat imagery spanning the period from 1990 to 2024 was processed,enabling consistent monitoring over more than three decades.The spatio-temporal evolution of estuarine salt marshes was quantitatively examined using the Random Forest(RF)classification algorithm for accurate wetland mapping and the Digital Shoreline Analysis System(DSAS)model for assessing shoreline change rates and patterns.The results revealed distinctive dynamic phases and pronounced spatial differences in salt marsh evolution:(1)Salt marshes in the Liaohe Estuary exhibited a fluctuating trajectory,with an average annual area of 42.71km2.From 1990 to 2003,a notable degradation phase occurred,characterized by a mean annual decrease of 1.25km2.In contrast,the period from 2004 to 2024 demonstrated the signal of ecological recovery,with an average annual growth of 1.48km2.(2)Spatially,the western bank salt marshes were approximately two to three times more extensive than those on the eastern bank,following a similar decline-recovery pattern and maintaining an average area of 22.43km2.Conversely,eastern bank salt marshes displayed a fluctuating but overall upward trajectory,averaging 13.71km2 with a growth rate of 0.28km2/a.(3)Shoreline change analysis further illustrated asymmetric morphodynamical processes:the western shoreline experienced intense,spatially heterogeneous accretion-erosion dynamics,where 80.58%of transects showed accretion and 19.42%underwent erosion.By comparison,the eastern shoreline was dominated by progressive accretion,with 85.50%of transects experiencing significant siltation.In dynamic sectors,such as segment c1 on the western bank,shoreline changes were strongly associated with reclamation-restoration processes.(4)Driving mechanism analysis indicates that human activities,such as reclamation and restoration projects,were the primary forces shaping salt marsh change.Although increased upstream sediment discharge in recent years could potentially enhance wetland expansion,its effect was mitigated by relatively weak tidal energy and anthropogenic disruption of sediment transport pathways.Ecological restoration initiatives,notably"returning aquaculture ponds to wetlands",mitigated certain negative impacts caused by sea-level rise.Nevertheless,future risks were considerable,particularly due to sediment supply insufficiency,accelerating sea-level rise,and cumulative historical disturbances.This research reveals pronounced spatio-temporal heterogeneity and highlights the complex interplay between natural and human drivers in the dynamics of estuarine salt marsh.The findings provide critical scientific guidance for achieving adaptive restoration strategies and sustainable coastal management in the Liaohe Estuary and other comparable estuarine regions worldwide.
黄栋;庞天一;戴志军
辽宁师范大学海洋可持续发展研究院教育部人文社科重点研究基地,大连 116029||辽宁师范大学辽宁省"海洋经济高质量发展"高校协同创新中心,大连 116029辽宁师范大学海洋可持续发展研究院教育部人文社科重点研究基地,大连 116029||辽宁师范大学辽宁省"海洋经济高质量发展"高校协同创新中心,大连 116029华东师范大学河口海岸全国重点实验室,上海 200062
盐沼变迁机器学习谷歌地球引擎(GEE)围垦/退养还湿海平面上升辽河口
salt marsh dynamicsmachine learningGoogle Earth Engine(GEE)reclamation/wetland restorationsea-level riseLiaohe Estuary
《生态学报》 2026 (9)
4742-4758,17
国家重点研发计划政府间国际科技创新合作重点专项(2023YFE0121200)辽宁省教育厅科学研究一般项目(LJ212510165009)
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