Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Impact assessment of vegetation loss on the ecosystem functions in a semiarid watershed in Iran

Zarandian Ardavan, Mehrian Majid Ramezani, Mohammadyari Fatemeh

Acta Geophysica

2022

Vol. 70, no 2

677--696

The main purpose of this study is to investigate the effects of land cover changes and vegetation loss under conditions of change in climatic parameters (temperature and precipitation) and determining their impacts on different ecological functions in the eastern watershed of Lake Urmia and its four sub-watersheds in northwestern Iran. The method used has been a quantitative assessment of selected ecosystem functions using a self-parameterizing, physically based model called Water World Policy Support System as well as applying satellite images to detect land-use/cover changes. Modeling of important ecological and hydrological parameters including vegetation density, water balance, surface runoff, and soil erosion was performed and for each of them, the quantity of changes was calculated and mapped. Then, by standardizing the maps for each parameter and overlapping them, cumulative impact levels across the watershed were classified. The result showed that with decrease in rainfall and increase in temperature, the average vegetation density decreased by 32% in the watershed and from 79 to 47%. Decreased vegetation, followed by increased runoff by about 2.5% and equivalent to 19,656.95 cubic meters per year. Consequently, the average net soil erosion has been changed from −0.012 to 0.20 mm per year per square meter. Hence, the average soil erosion in the watershed has increased by more than 3 tons per hectare. Based on the final results, more than 40% of the watershed area is under severe and very severe ecological impact.

Modelling of expansion changes of Vilnius city area and impacts on landscape patterns using an artificial neural network

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

Ecological Chemistry and Engineering. S

2021

Vol. 28, nr 3

429--447

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.