Modelling Impact of Urban Expansion on Ecosystem Services: A Scenario-Based Approach in a Mixed Natural/Urbanised Landscape

The present study aims at predicting future land use/land cover (LULC) and quantifying and mapping the ecosystem services (ESs) of water yield, outdoor recreation opportunity and food production in current (here, 2017) and future landscapes in Northern Iran, using the InVEST, Recreation Opportunity...

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Bibliographic Details
Published inLand (Basel) Vol. 12; no. 2; p. 291
Main Authors Mohammadyari, Fatemeh, Zarandian, Ardavan, Mirsanjari, Mir Mehrdad, Suziedelyte Visockiene, Jurate, Tumeliene, Egle
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.01.2023
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Summary:The present study aims at predicting future land use/land cover (LULC) and quantifying and mapping the ecosystem services (ESs) of water yield, outdoor recreation opportunity and food production in current (here, 2017) and future landscapes in Northern Iran, using the InVEST, Recreation Opportunity Spectrum (ROS) and yield models. To that end, two LULC scenarios known as business as usual (BAU) and protection-based (PB) plan were applied for 2028, using the Markov Artificial Neural Network and Multi-objective land allocation (MOLA) models. The results show that rapid urbanisation, caused by the expansion of human settlements and industrial areas, has led to a decline in the ESs in the region. Compared to the ESs in 2017, the service of water yield increases as urban expansion increases, whereas food production and recreation services decrease as urban expansion increases, under the BAU scenario. On the other hand, in the PB scenario, relatively better conditions can be observed for all three ESs. Considering that the ecological structures of this region have been severely affected by rapid urban expansion, the results of this research will be useful for maintaining the existing ESs and can greatly affect planning and decision-making regarding future development towards urban sustainability.
ISSN:2073-445X
2073-445X
DOI:10.3390/land12020291