互花米草
盐沼
海湾
卫星图像
环境科学
沼泽
随机森林
生长季节
遥感
自然地理学
湿地
生态学
海洋学
地理
计算机科学
地质学
人工智能
生物
作者
Swarna M. Naojee,Armand LaRocque,Brigitte Leblon,Gregory S. Norris,Myriam A. Barbeau,Mark Rowland
出处
期刊:Remote Sensing
[Multidisciplinary Digital Publishing Institute]
日期:2024-12-13
卷期号:16 (24): 4667-4667
被引量:3
摘要
Saltmarshes provide important ecosystem services, including coastline protection, but face decline due to human activities and climate change. There are increasing efforts to conserve and restore saltmarshes worldwide. Our study evaluated the effectiveness of Sentinel-2 satellite imagery to monitor landcover changes using a saltmarsh restoration project undergoing its 9th to 12th year of recovery in the megatidal Bay of Fundy in Maritime Canada. Specifically, in 2019–2022, five satellite images per growing season were acquired. Random Forests classification for 13 landcover classes (ranging from bare mud to various plant communities) achieved a high overall classification accuracy, peaking at 96.43% in 2021. Field validation points confirmed this, with high validation accuracies reaching 93.02%. The classification results successfully distinguished ecologically significant classes, such as Spartina alterniflora–S. patens mix. Our results reveal the appearance of high marsh species in restoration sites and elevational-based zonation patterns, indicating progression. They demonstrate the potential of Sentinel-2 imagery for monitoring saltmarsh restoration projects in north temperate latitudes, aiding management efforts.
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