Research on environmental changes based on fractal characteristics of satelliteimages

verfasst von

Viktoriia Hnatushenko, Anna Zhurba, Andrew Zimoglyad, Kateryna Ostrovska

Abstract

Most natural structures that are widely studied today using computer science have a complex fractal structure. Fractal analysis of such structures is used to model, study, and explain the properties of surfaces and structures of complex objects in various fields of science and technology. Images of a large number of natural surfaces and structures are satellite images that exhibit fractal properties. Satellite images in modern life have high spatial resolution, which gives researchers and users satisfactory initial data for solving various types of problems. A promising direction for increasing the informativeness of satellite images is the use of fractal image analysis methods. The complexity of the forms of the underlying surface and vegetation can be described using the fractal dimension. Characteristic values of the fractal dimension allow decoding of space images. The paper proposes a method for studying environmental changes in satellite images based on the calculation of fractal characteristics, such as fractal dimension, fractal distribution and fractal segmentation. The ecological indicators for assessing the state of the environment were selected as trends in forest numbers, water and land resources. Satellite images of the Amazon forests, Bolivia in 1991, 1996, 2006, 2012, 2016, 2020, which were subjected to mass deforestation, were selected for the study. The experimental results show that the fractal dimension increases each time (Fractal Dimension (FR) = 1.441 in 1991, FR = 1.825 in 2020), and the green areas in this area decrease. The depth of the seas (Black Sea, Tyrrhenian Sea, Mediterranean Sea, Philippine Sea) was studied. The least homogeneous with the largest amplitude of distribution modes has the fractal distribution of the Philippine Sea, which indicates a more pronounced relief of the seabed. As a result of the study of winter fields with different levels of snow cover, it was found that an increase in its value leads to an increase in the value of the fractal dimension (FR=1.702 February, FR=1.894 March). Thus, fractal analysis of winter fields allows us to estimate the relative amount of moisture that will enter the soil in the spring. The study highlights the need for further research in developing more efficient fractal methods to improve the accuracy of change area detection, which will favor the analysis of the causes and consequences of the environmental situation.

Organisationseinheit(en)

Institut für Photogrammetrie und Geoinformation

Externe Organisation(en)

Ukrainian State University of Science and Technologies

Typ

Aufsatz in Konferenzband

Seiten

62-71

Anzahl der Seiten

10

Publikationsdatum

15.06.2025

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Allgemeine Computerwissenschaft

Ziele für nachhaltige Entwicklung

SDG 15 – Lebensraum Land

Elektronische Version(en)

https://ceur-ws.org/Vol-4005/paper5.pdf (Zugang: Offen)