INTERPRETATION OF REMOTE SENSING DATA BASED ON THE ANALYSIS OF LANDSCAPE FORMING FACTORS
Tursynova T. Saginov K. Sadvakassova S. Aralbekova M. Bazilova A. Karibayeva M. Jaxylykova A. Karabalayeva A. Azbantayeva M. Izenbayev B. Amangeldi A. Sagatbayev Y.
2025Editura Universitatii din Oradea
Geojournal of Tourism and Geosites
2025#62Issue 42409 - 2419 pp.
This article discusses the methodology for assessing the natural and recreational potential of landscapes in the Nura River basin. Based on this assessment, it is possible to make a component-by-component evaluation of the natural and recreational potential (relief, climate, water resources, vegetation, and specially protected natural areas). To calculate the potential, it is proposed to apply the balance method. With the help of the considered method, it is possible to conduct a comparative analysis of the prospective possibilities of the territory and natural and recreational resources. The results obtained in the article were ranked by groups. The interpretation of remote sensing data has become a critical tool in landscape analysis, allowing for the identification and evaluation of various landscape-forming factors such as topography, climate, vegetation, and human activities. This study investigates the use of remote sensing imagery to assess and interpret these factors, with a particular focus on their spatial and temporal relationships in shaping the landscape. By integrating high-resolution satellite data, digital elevation models (DEMs), and land use/land cover maps, we identify key patterns of landscape formation across diverse environments. Advanced image processing and machine learning algorithms are employed to analyze the interactions between natural and anthropogenic forces, revealing insights into landscape evolution and dynamics. The findings suggest that remote sensing not only enhances our understanding of landscape morphology but also provides a robust framework for monitoring land change over time. This approach offers valuable implications for land management, environmental monitoring, and conservation planning, contributing to sustainable landscape development and resilience in the face of climate change.
Akmola region , interpretation of remote sensing data , Lake Teniz , landscape , remote sensing of the Earth , wetlands of Central Asia
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L.N. Gumilyev Eurasian National University, Department of Physical and Economical Geography, Astana, Kazakhstan
Astana International University, Higher School of Natural Sciences, Astana, Kazakhstan
U. Zhanibekov South Kazakhstan Pedagogical University, Faculty of Natural Sciences, Shymkent, Kazakhstan
L.N. Gumilyov Eurasian National University, Tourism Department, Astana, Kazakhstan
L.N. Gumilyov Eurasian National University, Faculty of Architecture and Civil Engineering, Department of Geodesy and Cartography, Astana, Kazakhstan
L.N. Gumilyev Eurasian National University
Astana International University
U. Zhanibekov South Kazakhstan Pedagogical University
L.N. Gumilyov Eurasian National University
L.N. Gumilyov Eurasian National University
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