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

Author

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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