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Quantitative Assessment of Forest Disturbance with C-Band SAR Data for Decision Making Support in Forest Management

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Lecture Notes in Computational Intelligence and Decision Making (ISDMCI 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 77))

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Abstract

Recently, forest disturbance regimes have intensified all over the world. The usage of Synthetic-aperture radar (SAR) data has proven as a comprehensive tool for mapping forest disturbance that has a natural or human-induced origin and a wide spatiotemporal range. It has become an important component in many applications related to decision-making for sustainable forest management. In this research, we developed a methodologic framework providing detection and quantitative assessment of forest disturbance using C-band SAR data for decision-making support in forest management. Herein, we propose a method to analyze LAI changes over a certain period that reliably indicates the transformations of a forest canopy. Then, asymmetrical formalization of expert knowledge using the AHP and Gompertz model allows not only forest disturbance detection that occurs but also its assessment in the context of the levels of impact. The framework was applied in assessing short-term forest disturbance in the Pushcha-Voditsky forest. The map of the spatial distribution of forest canopy change impact within the Pushcha-Vodytsia study area during 2017–2020 was obtained. The proposed framework contributes to the decision-making process in forest management and may provide a quick response to abrupt forest disturbances in those atmospheric conditions when optical remote sensing is helpless.

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Authors and Affiliations

  1. State Institution “Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine”, Kyiv, Ukraine

    Anna Kozlova, Sergey Stankevich, Mykhailo Svideniuk & Artem Andreiev

Authors
  1. Anna Kozlova
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  2. Sergey Stankevich
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  3. Mykhailo Svideniuk
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  4. Artem Andreiev
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Corresponding author

Correspondence to Anna Kozlova .

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Editors and Affiliations

  1. Department of Physics, Kherson State University, Kherson, Ukraine

    Sergii Babichev

  2. Department of Informatics and Computer Science, Kherson National Technical University, Kherson, Ukraine

    Volodymyr Lytvynenko

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Kozlova, A., Stankevich, S., Svideniuk, M., Andreiev, A. (2022). Quantitative Assessment of Forest Disturbance with C-Band SAR Data for Decision Making Support in Forest Management. In: Babichev, S., Lytvynenko, V. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 77. Springer, Cham. https://doi.org/10.1007/978-3-030-82014-5_37

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