IDEAS home Printed from https://ideas.repec.org/a/gam/jgeogr/v3y2023i1p10-177d1072058.html
   My bibliography  Save this article

Monitoring and Analyzing the Seasonal Wetland Inundation Dynamics in the Everglades from 2002 to 2021 Using Google Earth Engine

Author

Listed:
  • Ikramul Hasan

    (Department of Geosciences, Florida Atlantic University, Boca Raton, FL 33431, USA)

  • Weibo Liu

    (Department of Geosciences, Florida Atlantic University, Boca Raton, FL 33431, USA)

  • Chao Xu

    (Department of Geosciences, Texas Tech University, Lubbock, TX 79409, USA)

Abstract

Inundation dynamics coupled with seasonal information is critical to study the wetland environment. Analyses based on remotely sensed data are the most effective means to monitor and investigate wetland inundation dynamics. For the first time, this study deployed an automated thresholding method to quantify and compare the annual inundation characteristics in dry and wet seasons in the Everglades, using Landsat imagery in Google Earth Engine (GEE). This research presents the long-term time series maps from 2002 to 2021, with a comprehensive spatiotemporal depiction of inundation. In this paper, we bridged the research gap of space-time analysis for multi-season inundation dynamics, which is urgently needed for the Everglades wetland. Within a GIS-based framework, we integrated statistical models, such as Mann–Kendall and Sen’s Slope tests, to track the evolutionary trend of seasonal inundation dynamics. The spatiotemporal analyses highlight the significant differences in wet and dry seasons through time and space. The stationary or permanent inundation is more likely to be distributed along the coastal regions (Gulf of Mexico and Florida Bay) of the Everglades, presenting a warning regarding their vulnerability to sea level rise.

Suggested Citation

  • Ikramul Hasan & Weibo Liu & Chao Xu, 2023. "Monitoring and Analyzing the Seasonal Wetland Inundation Dynamics in the Everglades from 2002 to 2021 Using Google Earth Engine," Geographies, MDPI, vol. 3(1), pages 1-17, February.
    • Handle: RePEc:gam:jgeogr:v:3:y:2023:i:1:p:10-177:d:1072058
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2673-7086/3/1/10/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2673-7086/3/1/10/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sanjay Jain & Arun Saraf & Ajanta Goswami & Tanvear Ahmad, 2006. "Flood inundation mapping using NOAA AVHRR data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 949-959, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liwei Xing & Liang Chi & Shuqing Han & Jianzhai Wu & Jing Zhang & Cuicui Jiao & Xiangyang Zhou, 2022. "Spatiotemporal Dynamics of Wetland in Dongting Lake Based on Multi-Source Satellite Observation Data during Last Two Decades," IJERPH, MDPI, vol. 19(21), pages 1-17, October.
    2. Joy Sanyal & Alexander Densmore & Patrice Carbonneau, 2014. "2D Finite Element Inundation Modelling in Anabranching Channels with Sparse Data: Examination of Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(8), pages 2351-2366, June.
    3. Rajesh Kumar & Prasenjit Acharya, 2016. "Flood hazard and risk assessment of 2014 floods in Kashmir Valley: a space-based multisensor approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 437-464, October.
    4. Chandra Sharma & Mukund Behera & Atmaram Mishra & Sudhindra Panda, 2011. "Assessing Flood Induced Land-Cover Changes Using Remote Sensing and Fuzzy Approach in Eastern Gujarat (India)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(13), pages 3219-3246, October.
    5. Noy, Ilan & Blanc, Elodie & Pundit, Madhavi & Uher, Tomas, 2023. "Nowcasting from Space: Impact of Tropical Cyclones on Fiji’s Agriculture," ADB Economics Working Paper Series 676, Asian Development Bank.
    6. Rahul Kumar Jaiswal & Gunja Dhruw & Sukant Jain & Ravi V. Galkate & Anil Kumar Lohani & Akhilesh Verma, 2023. "Efficient Segmentation Algorithm for Estimation of Revised Reservoir Capacities in Google Earth Engine," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(10), pages 3795-3812, August.
    7. Ibrahim Sufiyan & Razak Zakariya & Ibrahim Rosnan Yaacob, 2018. "Delineation Of Flood Risk Zones And 3D Modeling In Terengganu River Catchment Using Gis And Swat," Environment & Ecosystem Science (EES), Zibeline International Publishing, vol. 2(2), pages 1-5, January.
    8. Sananda Kundu & S. Aggarwal & Nanette Kingma & Arun Mondal & Deepak Khare, 2015. "Flood monitoring using microwave remote sensing in a part of Nuna river basin, Odisha, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(1), pages 123-138, March.
    9. S. Sarkar & R. Rai, 2011. "Flood Inundation Modeling Using Nakagami-m Distribution Based GIUH for a Partially Gauged Catchment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(14), pages 3805-3835, November.
    10. Alahacoon, Niranga & Matheswaran, Karthikeyan & Pani, Peejush & Amarnath, Giriraj, "undated". "A decadal historical satellite data and rainfall trend analysis (2001–2016) for flood hazard mapping in Sri Lanka," Papers published in Journals (Open Access) H048581, International Water Management Institute.
    11. Dhruvesh Patel & Prashant Srivastava, 2013. "Flood Hazards Mitigation Analysis Using Remote Sensing and GIS: Correspondence with Town Planning Scheme," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2353-2368, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jgeogr:v:3:y:2023:i:1:p:10-177:d:1072058. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.