Methods Of Studying The Alpine Treeline: A Systematic Review

Purekhovsky, A.G.; Gunya, A.N.; Kolbowsky, E.Y.; Aleinikov, A.A.

Авторы: Purekhovsky A.G., Gunya A.N., Kolbowsky E.Yu, Aleinikov A.A.
Журнал: Geography, Environment, Sustainability
Том: 18
Номер: 1
Год издания: 2025
Издательство: Издательство Русского географического общества
Местоположение издательства: Москва
Первая страница: 105
Последняя страница: 116
DOI: 10.24057/2071-9388-2025-3735
Аннотация: This paper provides a review and comparison of the methods for assessing trends in the dynamics of alpine treeline (ATL) in high mountains are presented in. The methods analyzed are contemporary, traditionally used (dendrochronological and paleocarpological methods, retrospective analysis of historical photographs and geodetic surveying, and multi-temporal aerial photography), and innovative ones developed in recent decades (semi-automatic and automatic methods of interpretation of high- and medium-resolution space imagery and methods of space imagery interpretation using different techniques, such as classification, segmentation, vegetation index analysis, and machine learning algorithms). Different interpretations of the concept of 'alpine treeline', which is currently established in geobotany and landscape sciences, are discussed. The attention to ATL dynamics is caused by global climate change's widespread forest increase and the decline in high mountain pastures. The ATL phenomenon's geographic map is condensed and displayed. There is an overview of the experience with different methods in varying mountain regions around the world. Each method is described in terms of its spatial scale, coverage, advantages, labor intensity, complexity, and limitations. It is shown that The effectiveness of the methods mainly depends on two key factors: the size of the area being studied and the time period over which changes are observed. The problem that still limits the use of remote sensing data is the contradiction between the accuracy of measurements and the coverage of the territories involved. To solve this problem, we suggest using a mix of methods that involve automatically classifying medium-resolution space images. This will be done by training on data collected from both fieldwork and lab experiments using different techniques.
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Methods Of Studying The Alpine Treeline: A Systematic Reviewстатья

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