IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i3p759-d311238.html
   My bibliography  Save this article

Identification of Heracleum sosnowskyi -Invaded Land Using Earth Remote Sensing Data

Author

Listed:
  • Jūratė Sužiedelytė Visockienė

    (Department of Geodesy and Cadastre, Vilnius Gediminas Technical University, Sauletekio av. 11, LT-10223 Vilnius, Lithuania)

  • Eglė Tumelienė

    (Department of Geodesy and Cadastre, Vilnius Gediminas Technical University, Sauletekio av. 11, LT-10223 Vilnius, Lithuania
    Institute of Land Management and Geomatics, Vytautas Magnus University Agriculture Academy, Studentu 11, Akademija, LT-53361 Kaunas district, Lithuania)

  • Vida Maliene

    (Institute of Land Management and Geomatics, Vytautas Magnus University Agriculture Academy, Studentu 11, Akademija, LT-53361 Kaunas district, Lithuania
    Department of the Built Environment, Built Environment and Sustainable Technologies Research Institute, Faculty of Engineering and Technology, Liverpool John Moores University, Byrom street, Liverpool L3 3AF, UK)

Abstract

H. sosnowskyi ( Heracleum sosnowskyi ) is a plant that is widespread both in Lithuania and other countries and causes abundant problems. The damage caused by the population of the plant is many-sided: it menaces the biodiversity of the land, poses risk to human health, and causes considerable economic losses. In order to find effective and complex measures against this invasive plant, it is very important to identify places and areas where H. sosnowskyi grows, carry out a detailed analysis, and monitor its spread to avoid leaving this process to chance. In this paper, the remote sensing methodology was proposed to identify territories covered with H. sosnowskyi plants (land classification). Two categories of land cover classification were used: supervised (human-guided) and unsupervised (calculated by software). In the application of the supervised method, the average wavelength of the spectrum of H. sosnowskyi was calculated for the classification of the RGB image and according to this, the unsupervised classification by the program was accomplished. The combination of both classification methods, performed in steps, allowed obtaining better results than using one. The application of authors’ proposed methodology was demonstrated in a Lithuanian case study discussed in this paper.

Suggested Citation

  • Jūratė Sužiedelytė Visockienė & Eglė Tumelienė & Vida Maliene, 2020. "Identification of Heracleum sosnowskyi -Invaded Land Using Earth Remote Sensing Data," Sustainability, MDPI, vol. 12(3), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:759-:d:311238
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/3/759/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/3/759/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Suziedelyte Visockiene, J. & Tumeliene, E. & Maliene, V., 2019. "Analysis and identification of abandoned agricultural land using remote sensing methodology," Land Use Policy, Elsevier, vol. 82(C), pages 709-715.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Eglė Tumelienė & Jūratė Sužiedelytė Visockienė & Vida Malienė, 2021. "The Influence of Seasonality on the Multi-Spectral Image Segmentation for Identification of Abandoned Land," Sustainability, MDPI, vol. 13(12), pages 1-16, June.
    2. Eglė Tumelienė & Jūratė Sužiedelytė Visockienė & Vida Maliene, 2022. "Evaluating the Eligibility of Abandoned Agricultural Land for the Development of Wind Energy in Lithuania," Sustainability, MDPI, vol. 14(21), pages 1-14, November.

    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. Chi, Yuan & Liu, Dahai & Wang, Jing & Wang, Enkang, 2020. "Human negative, positive, and net influences on an estuarine area with intensive human activity based on land covers and ecological indices: An empirical study in Chongming Island, China," Land Use Policy, Elsevier, vol. 99(C).
    2. Movahedi, Reza & Jawanmardi, Sina & Azadi, Hossein & Goli, Imaneh & Viira, Ants-Hannes & Witlox, Frank, 2021. "Why do farmers abandon agricultural lands? The case of Western Iran," Land Use Policy, Elsevier, vol. 108(C).
    3. Yingqian Huang & Fengqin Li & Hualin Xie, 2020. "A Scientometrics Review on Farmland Abandonment Research," Land, MDPI, vol. 9(8), pages 1-26, August.
    4. Subedi, Yuba Raj & Kristiansen, Paul & Cacho, Oscar, 2022. "Reutilising abandoned cropland in the Hill agroecological region of Nepal: Options and farmers’ preferences," Land Use Policy, Elsevier, vol. 117(C).
    5. Ingrid Belčáková & Branislav Olah & Martina Slámová & Zuzana Pšenáková, 2021. "A Cultural and Environmental Assessment of a Landscape Archetype with Dispersed Settlements in Čadca Cadastral District, Slovakia," Sustainability, MDPI, vol. 13(3), pages 1-23, January.
    6. Sowińska-Świerkosz, Barbara & Soszyński, Dawid, 2022. "Spatial indicators as a tool to support the decision-making process in relation to different goals of rural planning," Land Use Policy, Elsevier, vol. 119(C).
    7. De Yu & Shougeng Hu & Luyi Tong & Cong Xia, 2020. "Spatiotemporal Dynamics of Cultivated Land and Its Influences on Grain Production Potential in Hunan Province, China," Land, MDPI, vol. 9(12), pages 1-22, December.
    8. Anny Mulyani & Budi Mulyanto & Baba Barus & Dyah Retno Panuju & Husnain, 2022. "Geospatial Analysis of Abandoned Lands Based on Agroecosystems: The Distribution and Land Suitability for Agricultural Land Development in Indonesia," Land, MDPI, vol. 11(11), pages 1-19, November.

    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:12:y:2020:i:3:p:759-:d:311238. 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.