Remote Sensing and Machine Learning Tools to Support Wetland Monitoring: A Meta-Analysis of Three Decades of Research

被引:14
|
作者
Jafarzadeh, Hamid [1 ]
Mahdianpari, Masoud [1 ,2 ]
Gill, Eric W. [1 ]
Brisco, Brian [3 ]
Mohammadimanesh, Fariba [2 ]
机构
[1] Mem Univ Newfoundland, Dept Elect & Comp Engn, St John, NL A1B 3X5, Canada
[2] C CORE, St John, NL A1B 3X5, Canada
[3] Canada Ctr Mapping & Earth Observat, Ottawa, ON K1S 5K2, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
wetlands; remote sensing; machine learning; meta-analysis; systematic review; GOOGLE EARTH ENGINE; RANDOM FOREST CLASSIFICATION; LAND-COVER CLASSIFICATION; MAPPING WETLANDS; TIME-SERIES; IMAGE CLASSIFICATION; INUNDATION DYNAMICS; COASTAL WETLANDS; MULTIPLE SOURCES; NEURAL-NETWORKS;
D O I
10.3390/rs14236104
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Despite their importance to ecosystem services, wetlands are threatened by pollution and development. Over the last few decades, a growing number of wetland studies employed remote sensing (RS) to scientifically monitor the status of wetlands and support their sustainability. Considering the rapid evolution of wetland studies and significant progress that has been made in the field, this paper constitutes an overview of studies utilizing RS methods in wetland monitoring. It investigates publications from 1990 up to the middle of 2022, providing a systematic survey on RS data type, machine learning (ML) tools, publication details (e.g., authors, affiliations, citations, and publications date), case studies, accuracy metrics, and other parameters of interest for RS-based wetland studies by covering 344 papers. The RS data and ML combination is deemed helpful for wetland monitoring and multi-proxy studies, and it may open up new perspectives for research studies. In a rapidly changing wetlands landscape, integrating multiple RS data types and ML algorithms is an opportunity to advance science support for management decisions. This paper provides insight into the selection of suitable ML and RS data types for the detailed monitoring of wetland-associated systems. The synthesized findings of this paper are essential to determining best practices for environmental management, restoration, and conservation of wetlands. This meta-analysis establishes avenues for future research and outlines a baseline framework to facilitate further scientific research using the latest state-of-art ML tools for processing RS data. Overall, the present work recommends that wetland sustainability requires a special land-use policy and relevant protocols, regulation, and/or legislation.
引用
收藏
页数:38
相关论文
共 50 条
  • [1] Three Decades of Research on Induced Hypocrisy: A Meta-Analysis
    Priolo, Daniel
    Pelt, Audrey
    St Bauzel, Roxane
    Rubens, Lolita
    Voisin, Dimitri
    Fointiat, Valerie
    PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN, 2019, 45 (12) : 1681 - 1701
  • [2] Research on Wildfires and Remote Sensing in the Last Three Decades: A Bibliometric Analysis
    Batista dos Santos, Sarah Moura
    Bento-Goncalves, Antonio
    Vieira, Antonio
    FORESTS, 2021, 12 (05):
  • [3] Three Decades of Indian Remote Sensing in Coastal Research
    M. V. Ramana Murthy
    Tune Usha
    R. S. Kankara
    Journal of the Indian Society of Remote Sensing, 2022, 50 : 599 - 612
  • [4] Three Decades of Indian Remote Sensing in Coastal Research
    Murthy, M. V. Ramana
    Usha, Tune
    Kankara, R. S.
    JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2022, 50 (04) : 599 - 612
  • [5] Deep learning in remote sensing applications: A meta-analysis and review
    Ma, Lei
    Liu, Yu
    Zhang, Xueliang
    Ye, Yuanxin
    Yin, Gaofei
    Johnson, Brian Alan
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2019, 152 : 166 - 177
  • [6] Three decades in: Priming for meta-analysis in play-literacy research
    Roskos, Kathleen A.
    Christie, James F.
    Widman, Sarah
    Holding, Allison
    JOURNAL OF EARLY CHILDHOOD LITERACY, 2010, 10 (01) : 55 - 96
  • [7] On the Costs and Benefits of Emotional Labor: A Meta-Analysis of Three Decades of Research
    Hulsheger, Ute R.
    Schewe, Anna F.
    JOURNAL OF OCCUPATIONAL HEALTH PSYCHOLOGY, 2011, 16 (03) : 361 - 389
  • [8] Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review
    Sheykhmousa, Mohammadreza
    Mahdianpari, Masoud
    Ghanbari, Hamid
    Mohammadimanesh, Fariba
    Ghamisi, Pedram
    Homayouni, Saeid
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 13 : 6308 - 6325
  • [9] Satellite remote sensing of forest resources: three decades of research development
    Boyd, DS
    Danson, FM
    PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT, 2005, 29 (01): : 1 - 26
  • [10] Over three decades of longitudinal research on the development of foster children: A meta-analysis
    Goemans, Anouk
    van Geel, Mitch
    Vedder, Paul
    CHILD ABUSE & NEGLECT, 2015, 42 : 121 - 134