IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p14110-d956987.html
   My bibliography  Save this article

Usage PlanetScope Images and LiDAR Point Clouds for Characterizing the Forest Succession Process in Post-Agricultural Areas

Author

Listed:
  • Marta Szostak

    (Department of Forest Resource Management, Faculty of Forestry, University of Agriculture in Krakow, 31-425 Krakow, Poland)

Abstract

The paper investigates using PlanetScope satellite images together with LiDAR data for automation of land use/cover (LULC) mapping and 3D vegetation characteristics in the aspect of mapping and monitoring of the secondary forest succession areas. The study was performed for the tested area in the Biskupice district (South of Poland), where a forest succession occurs on post-agricultural lands. The research area was parcels where the forest overgrowing process was identified. It was verified whether the image processing allows for reliable LULC classification as an identification forest succession area. The PlanetScope classification showed forested areas as 62.77 ha (44.91% of the analyzed area). The overall accuracy of the image classification was 96.40% The airborne laser scanning (ALS) point clouds were used for deriving detailed information about the forest succession process. The precise vegetation parameters i.e., height and canopy cover were determined and presented as raster maps, histograms, or profiles.

Suggested Citation

  • Marta Szostak, 2022. "Usage PlanetScope Images and LiDAR Point Clouds for Characterizing the Forest Succession Process in Post-Agricultural Areas," Sustainability, MDPI, vol. 14(21), pages 1-13, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14110-:d:956987
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/14110/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/14110/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jinquan Ai & Chao Zhang & Lijuan Chen & Dajun Li, 2020. "Mapping Annual Land Use and Land Cover Changes in the Yangtze Estuary Region Using an Object-Based Classification Framework and Landsat Time Series Data," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    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. Ileana Pătru-Stupariu & Constantina Alina Hossu & Simona Raluca Grădinaru & Andreea Nita & Mihai-Sorin Stupariu & Alina Huzui-Stoiculescu & Athanasios-Alexandru Gavrilidis, 2020. "A Review of Changes in Mountain Land Use and Ecosystem Services: From Theory to Practice," Land, MDPI, vol. 9(9), pages 1-21, September.

    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:jsusta:v:14:y:2022:i:21:p:14110-:d:956987. 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.