IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i12p2184-d1543784.html
   My bibliography  Save this article

Mapping of Forest Species Using Sentinel-2A Images in the Alentejo and Algarve Regions, Portugal

Author

Listed:
  • Crismeire Isbaex

    (MED—Mediterranean Institute for Agriculture, Environment and Development & CHANGE—Global Change and Sustainability Institute, Institute for Advanced Research and Training, University of Évora, P.O. Box 94, 7002-544 Évora, Portugal)

  • Ana Margarida Coelho

    (ICT—Institute of Earth Sciences, Institute for Advanced Research and Training, Colégio Luis António Verney, Rua Romão Ramalho, University of Évora, 59, 7002-554 Évora, Portugal)

  • Ana Cristina Gonçalves

    (MED—Mediterranean Institute for Agriculture, Environment and Development & CHANGE—Global Change and Sustainability Institute, Institute for Advanced Research and Training, Rural Engineering Department, School of Science and Technology, University of Évora, P.O. Box 94, 7002-544 Évora, Portugal)

  • Adélia M. O. Sousa

    (MED—Mediterranean Institute for Agriculture, Environment and Development & CHANGE—Global Change and Sustainability Institute, Institute for Advanced Research and Training, Remote Sensing Laboratory—EaRSLab, Rural Engineering Department, School of Science and Technology, University of Évora, P.O. Box 94, 7002-544 Évora, Portugal)

Abstract

Land use and land cover (LULC) studies, particularly those focused on mapping forest species using Sentinel-2 (S2A) data, face challenges in delineating and identifying areas of heterogeneous forest components with spectral similarity at the canopy level. In this context, the main objective of this study was to compare and analyze the feasibility of two classification algorithms, K-Nearest Neighbor (KNN) and Random Forest (RF), with S2A data for mapping forest cover in the southern regions of Portugal, using tools with a free, open-source, accessible, and easy-to-use interface. Sentinel-2A data from summer 2019 provided 26 independent variables at 10 m spatial resolution for the analysis. Nine object-based LULC categories were distinguished, including five forest species ( Quercus suber , Quercus rotundifolia , Eucalyptus spp., Pinus pinaster , and Pinus pinea ), and four non-forest classes. Orfeo ToolBox (OTB) proved to be a reliable and powerful tool for the classification process. The best results were achieved using the RF algorithm in all regions, where it reached the highest accuracy values in Alentejo Central region (OA = 92.16% and K = 0.91). The use of open-source tools has enabled high-resolution mapping of forest species in the Mediterranean, democratizing access to research and monitoring.

Suggested Citation

  • Crismeire Isbaex & Ana Margarida Coelho & Ana Cristina Gonçalves & Adélia M. O. Sousa, 2024. "Mapping of Forest Species Using Sentinel-2A Images in the Alentejo and Algarve Regions, Portugal," Land, MDPI, vol. 13(12), pages 1-21, December.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:12:p:2184-:d:1543784
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/12/2184/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/13/12/2184/
    Download Restriction: no
    ---><---

    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:jlands:v:13:y:2024:i:12:p:2184-:d:1543784. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.