Modelling of Expansion Changes of Vilnius City Area and Impacts on Landscape Patterns Using an Artificial Neural Network

Mirsanjari, Mir Mehrdad; Visockiene, Jurate Suziedelyte; Mohammadyari, Fatemeh; Zarandian, Ardavan

doi:10.2478/eces-2021-0029

Abstract

The present study aimed to analyse changes in the land cover of Vilnius city and its surrounding areas and propose a scenario for their future changes using an Artificial Neural Network. The land cover dynamics modelling was based on a multilayer perceptron neural network. Landscape metrics at a class and landscape level were evaluated to determine the amount of changes in the land uses. As the results showed, the Built-up area class increased, while the forest (Semi forest and Dense forest) classes decreased during the period from 1999 to 2019. The predicted scenario showed a considerable increase of about 60 % in the Built-up area until 2039. The vegetation plant areas consist about 47 % of all the area in 2019, but it will be 36 % in 2039, if this trend (urban expansion) continues in the further. The findings further indicated the major urban expansion in the vegetation areas. However, Built-up area would expand over Semi forest land and Dense forest land, with a large part of them changed into built- up areas.

References

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Modelling of Expansion Changes of Vilnius City Area and Impacts on Landscape Patterns Using an Artificial Neural Network

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