Application of modern methods for anthropogenic impact in the Dniester reservoir using remote sensing tools

Remote Sensing & GIS for Environmental Monitoring

Authors

First and Last Name Academic degree E-mail Affiliation
Oleksandra Hulko Ph.D. oleksandra.r.hulko [at] lpnu.ua Lviv Polytechnic National University Lviv, Ukraine
Lviv, Ukraine
Yurii Hubar Sc.D. yurii.p.hubar [at] lpnu.ua Lviv Polytechnic National University Lviv, Ukraine
Lviv, Ukraine
Nataliia Tsudna No nataliia.tsudna.mhdzk.2023 [at] lpnu.ua Lviv Polytechnic National University Lviv, Ukraine
Lviv, Ukraine

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First published on this website: 25.07.2024 - 16:02
Abstract 

The most effective and modern methods that work and have a controlling purpose in environmental and reservoir ecology have been and remain methods based on remote sensing data and the use of geographic information systems (GIS). At the same time, over a long period of time of application and use of satellite systems and their resources, there is already a great deal of experience in remote sensing methods and the use of GIS technologies for solving agricultural technological and natural tasks. However, it is necessary to improve the types of work on methods of image interpretation from space and on the improvement of GIS technologies at the present stage. These are the following proposed ways:

1) development of modern and new methods of satellite imagery interpretation,

2) study of certain informative features in landscape systems,

3) development and construction of models in crisis and unstable conditions, etc.

The effectiveness of the use of information on geographic information systems lies in modern and new vectors for increasing the efficiency of its application to research objects. However, these observations should also be aimed at gaining an understanding of these objects and the processes that accompany them based on computational characteristics. Therefore, there is a need to create qualitatively modern systematic methods for the use of GIS technologies and remote sensing data. 

References 

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