Modelling the Impact of Land Cover Changes on Carbon Storage and Sequestration in the Central Zagros Region, Iran Using Ecosystem Services Approach

Japelaghi, M; Hajian, F; Gholamalifard, M; Pradhan, B; Maulud, KNA; Park, HJ

Modelling the Impact of Land Cover Changes on Carbon Storage and Sequestration in the Central Zagros Region, Iran Using Ecosystem Services Approach

Japelaghi, M Hajian, F Gholamalifard, M Pradhan, B

Maulud, KNA Park, HJ

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Land, 2022, 11, (3)
Issue Date:: 2022-03-01

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Field	Value	Language
dc.contributor.author	Japelaghi, M
dc.contributor.author	Hajian, F
dc.contributor.author	Gholamalifard, M
dc.contributor.author	Pradhan, B https://orcid.org/0000-0001-9863-2054
dc.contributor.author	Maulud, KNA
dc.contributor.author	Park, HJ
dc.date.accessioned	2023-03-21T01:49:08Z
dc.date.available	2023-03-21T01:49:08Z
dc.date.issued	2022-03-01
dc.identifier.citation	Land, 2022, 11, (3)
dc.identifier.issn	2073-445X
dc.identifier.issn	2073-445X
dc.identifier.uri	http://hdl.handle.net/10453/167887
dc.description.abstract	Central Zagros region in Iran is a major hotspot of carbon storage and sequestration which has experienced severe land cover change in recent decades that has led to carbon emission. In this research, using temporal Landsat images, land cover maps were produced and used in Land Change Modeler to predict land cover changes in 2020, 2030, 2040 and 2050 using Multilayer Perceptron Neural Network and Markov Chain techniques. Next, resultant maps were used as inputs to Ecosystem Services Modeler. The Intergovernmental Panel on Climate Change (IPCC) report data was used to extract carbon data. Results show that between 1989–2013 about half of forests have been destroyed. Prediction results show that by 2050 about 75% of existing forests will be lost and between 2013–2020 about 157,000 Mg carbon and by 2050 about 565,000 Mg carbon will be lost with more than US$1.9 million to 2020 and AU$3.2 million by 2050 economic compensation.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Land
dc.relation.isbasedon	10.3390/land11030423
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0502 Environmental Science and Management
dc.title	Modelling the Impact of Land Cover Changes on Carbon Storage and Sequestration in the Central Zagros Region, Iran Using Ecosystem Services Approach
dc.type	Journal Article
utslib.citation.volume	11
utslib.for	0502 Environmental Science and Management
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	open_access	*
dc.date.updated	2023-03-21T01:49:03Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	11
utslib.citation.issue	3

Abstract:

Central Zagros region in Iran is a major hotspot of carbon storage and sequestration which has experienced severe land cover change in recent decades that has led to carbon emission. In this research, using temporal Landsat images, land cover maps were produced and used in Land Change Modeler to predict land cover changes in 2020, 2030, 2040 and 2050 using Multilayer Perceptron Neural Network and Markov Chain techniques. Next, resultant maps were used as inputs to Ecosystem Services Modeler. The Intergovernmental Panel on Climate Change (IPCC) report data was used to extract carbon data. Results show that between 1989–2013 about half of forests have been destroyed. Prediction results show that by 2050 about 75% of existing forests will be lost and between 2013–2020 about 157,000 Mg carbon and by 2050 about 565,000 Mg carbon will be lost with more than US$1.9 million to 2020 and AU$3.2 million by 2050 economic compensation.

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http://hdl.handle.net/10453/167887