Spectral model of dynamic landscape components based on multispectral space images of the Earth

Authors

  • Vladyslav Yakimchuk Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Olesia Honchara st, 55-B, 01054, Kyiv, Ukraine https://orcid.org/0000-0001-7818-3562
  • Kostiantyn Sukhanov Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Olesia Honchara st, 55-B, 01054, Kyiv, Ukraine https://orcid.org/0000-0002-3518-3471
  • Olha Tomchenko Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Olesia Honchara st, 55-B, 01054, Kyiv, Ukraine https://orcid.org/0000-0001-6975-9099
  • Lyidmila Lischenko Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine, Olesia Honchara st, 55-B, 01054, Kyiv, Ukraine https://orcid.org/0000-0001-6766-6884

DOI:

https://doi.org/10.36023/ujrs.2023.10.4.249

Keywords:

adaptive methods, multi-temporal satellite images, spectral model, dynamic components of landscapes, technogenic karst

Abstract

A geosystem is a model of a landscape as a real geographical complex that encompasses all natural and anthropogenic formations near the earth's surface. The process of building an adequate mathematical model is an important stage in the study of geosystems. The simplest general definition of a model is its interpretation as a substitute object that is similar to the original in some way. Under the original, we will understand both a natural geosystem and a certain process under study. The degree of adequacy of the model to the object of research can never be complete and is determined depending on the purpose and methods of modeling. The dynamics of a geosystem is a change over time in the values of its individual characteristics, states, a set and intensity of processes, and territorial structures, which, unlike evolution, does not lead to the direct formation of a fundamentally new geosystem. This paper presents a spectral model of the dynamic components of the territory's landscapes on the example of Solotvyno salt mine in the Transcarpathian region of Ukraine, based on two multispectral Sentinel-2 satellite images taken over time. This model can be used to trace changes in the following landscape characteristics that are most pronounced in this area: waterlogging, sinkholes, karst, disturbance of the geological environment, vegetation, and changes in the number of anthropogenic objects and buildings. A spectral model is a set of pairs of optimal spectral channels with the largest relative changes in the spectral index between the standards in two images of consecutive dynamic landscape components. The detection of dynamic landscape components corresponding to the reference is performed on two multispectral satellite images, for this purpose it is necessary to scan the area under study with a window corresponding to the size of the reference taking into account the Nyquist frequency. The size of the reference is determined by scanning the area under study with a window corresponding to the size of the reference taking into account the Nyquist frequency. To detect dynamic landscape components in the window, we use a similarity measure as the set of the largest relative changes in time of the spectral index for the scanning window and the reference on two multispectral images. The values of the spectral models for the three references and the values of the similarity measure of the spectral models over the entire image with the reference were obtained, which showed their recognition capabilities, but to specify these changes, we need materials of verification ground observations.

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Published

2023-12-29

How to Cite

Yakimchuk, V., Sukhanov, K., Tomchenko, O., & Lischenko, L. (2023). Spectral model of dynamic landscape components based on multispectral space images of the Earth. Ukrainian Journal of Remote Sensing, 10(4), 4–11. https://doi.org/10.36023/ujrs.2023.10.4.249

Issue

Vol. 10 No. 4 (2023)

Section

Techniques for Earth observation data acquisition, processing and interpretation

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