Monitoring Saltmarsh Restoration in the Upper Bay of Fundy Using Multi-Temporal Sentinel-2 Imagery and Random Forests Classifier

被引:0
|
作者
Naojee, Swarna M. [1 ]
Larocque, Armand [1 ,2 ]
Leblon, Brigitte [2 ]
Norris, Gregory S. [1 ]
Barbeau, Myriam A. [3 ]
Rowland, Matthew [4 ]
机构
[1] Univ New Brunswick, Fac Forestry & Environm Management, Fredericton, NB E3B 5A3, Canada
[2] Lakehead Univ, Fac Nat Resources Management, Thunder Bay, ON P7B 5E1, Canada
[3] Univ New Brunswick, Dept Biol, Fredericton, NB E3B 5A3, Canada
[4] Environm & Climate Change Canada, Gatineau, PQ K1A 0H3, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
saltmarsh vegetation recovery; remote sensing; Sentinel-2; supervised image classification; random forests; SPARTINA-ALTERNIFLORA; NEW-BRUNSWICK; VEGETATION; PATTERN; CANADA; ROOTS; COLOR; TIME; RED;
D O I
10.3390/rs16244667
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
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.
引用
收藏
页数:26
相关论文
共 50 条
  • [1] Forest stand segmentation with multi-temporal Sentinel-2 imagery and superpixels
    Demirpolat, Caner
    Leloglu, Ugur Murat
    JOURNAL OF APPLIED REMOTE SENSING, 2024, 18 (01)
  • [2] Automating field boundary delineation with multi-temporal Sentinel-2 imagery
    Watkins, Barry
    Van Niekerk, Adriaan
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2019, 167
  • [3] An Improved Multi-temporal and Multi-feature Tea Plantation Identification Method Using Sentinel-2 Imagery
    Zhu, Jun
    Pan, Ziwu
    Wang, Hang
    Huang, Peijie
    Sun, Jiulin
    Qin, Fen
    Liu, Zhenzhen
    SENSORS, 2019, 19 (09)
  • [4] Forest Land Cover Mapping at a Regional Scale Using Multi-Temporal Sentinel-2 Imagery and RF Models
    Alonso, Laura
    Picos, Juan
    Armesto, Julia
    REMOTE SENSING, 2021, 13 (12)
  • [5] A Sentinel-2 Based Multi-Temporal Monitoring Framework for Wind and Bark Beetle Detection and Damage Mapping
    Candotti, Anna
    De Giglio, Michaela
    Dubbini, Marco
    Tomelleri, Enrico
    REMOTE SENSING, 2022, 14 (23)
  • [6] Understanding wheat lodging using multi-temporal Sentinel-1 and Sentinel-2 data
    Chauhan, Sugandh
    Darvishzadeh, Roshanak
    Lu, Yi
    Boschetti, Mirco
    Nelson, Andrew
    REMOTE SENSING OF ENVIRONMENT, 2020, 243 (243)
  • [7] Monitoring yellow rust progression during spring critical wheat growth periods using multi-temporal Sentinel-2 imagery
    Ma, Huiqin
    Zhang, Jingcheng
    Huang, Wenjiang
    Ruan, Chao
    Chen, Dongmei
    Zhang, Hansu
    Zhou, Xianfeng
    Gui, Zhiqin
    PEST MANAGEMENT SCIENCE, 2024, 80 (12) : 6082 - 6095
  • [8] MAPPING AND MONITORING WETLANDS USING SENTINEL-2 SATELLITE IMAGERY
    Kaplan, G.
    Avdan, U.
    4TH INTERNATIONAL GEOADVANCES WORKSHOP - GEOADVANCES 2017: ISPRS WORKSHOP ON MULTI-DIMENSIONAL & MULTI-SCALE SPATIAL DATA MODELING, 2017, 4-4 (W4): : 271 - 277
  • [9] Mapping Shrub Coverage in Xilin Gol Grassland with Multi-Temporal Sentinel-2 Imagery
    Gan, Liqin
    Cao, Xin
    Chen, Xuehong
    He, Qian
    Cui, Xihong
    Zhao, Chenchen
    REMOTE SENSING, 2022, 14 (14)
  • [10] Land Use and Land Cover Mapping with VHR and Multi-Temporal Sentinel-2 Imagery
    Cuypers, Suzanna
    Nascetti, Andrea
    Vergauwen, Maarten
    REMOTE SENSING, 2023, 15 (10)