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Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran

Effective land use and land cover (LULC) change assessment requires tools to measure past, current, and based on them to create a future scenario. LULC changes are unavoidable in the world, particularly in developing countries. Since LULC are too dynamic and complicated without the identification of...

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Main Authors:	Ghalehteimouri, Kamran Jafarpour, Shamsoddini, Ali, Mousavi, Mir Najaf, Che Ros, Faizah, Khedmatzadeh, Ali
Format:	Article
Language:	English
Published:	Elsevier B.V. 2022
Subjects:	Q Science (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://eprints.utm.my/id/eprint/98644/1/FaizahCheRos2022_PredictingSpatialandDecadalofLandUse.pdf http://eprints.utm.my/id/eprint/98644/ http://dx.doi.org/10.1016/j.envc.2021.100399
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spelling	my.utm.986442023-01-30T03:58:21Z http://eprints.utm.my/id/eprint/98644/ Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran Ghalehteimouri, Kamran Jafarpour Shamsoddini, Ali Mousavi, Mir Najaf Che Ros, Faizah Khedmatzadeh, Ali Q Science (General) TA Engineering (General). Civil engineering (General) Effective land use and land cover (LULC) change assessment requires tools to measure past, current, and based on them to create a future scenario. LULC changes are unavoidable in the world, particularly in developing countries. Since LULC are too dynamic and complicated without the identification of appropriate methods and approaches the future perdition will be less accurate. Therefore, the integrated Cellular Automata Markov chain (CA-Markov) model is known as a capable estimator. In this study, LULC changes in Zarriné-Rūd River Basin (ZRB) in Iran was analyzed based on different images and data extracted from satellite data in 1989 and 2019 to create the LULC scenario in 2049. The model was validated using actual and projected to 2019. The overall agreement on two extracted maps was 97.85% in 1989 and 96.55% in 2019. The more detailed analysis of validation of calibration based on the kappa showed the highest data reliability of 0.98 in 1989 and 0.95 in 2019, respectively. According to the transition matrix of probabilities, the most significant changes in the ZRB based on the past scenario (1989–2019) is in rainfed and built up land classes of LULC in 2049. Concurrently, the other classes continue to decline except irrigated agriculture and water bodies. The results obtained showed that the pasture and mountain LULC class had continued to reduce more than other classes. Furthermore, water resources and the amount of the precipitation in past and future are important to spatial and temporal expansion on LULC classes. Elsevier B.V. 2022-01 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/98644/1/FaizahCheRos2022_PredictingSpatialandDecadalofLandUse.pdf Ghalehteimouri, Kamran Jafarpour and Shamsoddini, Ali and Mousavi, Mir Najaf and Che Ros, Faizah and Khedmatzadeh, Ali (2022) Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran. Environmental Challenges, 6 (NA). pp. 1-8. ISSN 2667-0100 http://dx.doi.org/10.1016/j.envc.2021.100399 DOI:10.1016/j.envc.2021.100399
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	Q Science (General) TA Engineering (General). Civil engineering (General)
spellingShingle	Q Science (General) TA Engineering (General). Civil engineering (General) Ghalehteimouri, Kamran Jafarpour Shamsoddini, Ali Mousavi, Mir Najaf Che Ros, Faizah Khedmatzadeh, Ali Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran
description	Effective land use and land cover (LULC) change assessment requires tools to measure past, current, and based on them to create a future scenario. LULC changes are unavoidable in the world, particularly in developing countries. Since LULC are too dynamic and complicated without the identification of appropriate methods and approaches the future perdition will be less accurate. Therefore, the integrated Cellular Automata Markov chain (CA-Markov) model is known as a capable estimator. In this study, LULC changes in Zarriné-Rūd River Basin (ZRB) in Iran was analyzed based on different images and data extracted from satellite data in 1989 and 2019 to create the LULC scenario in 2049. The model was validated using actual and projected to 2019. The overall agreement on two extracted maps was 97.85% in 1989 and 96.55% in 2019. The more detailed analysis of validation of calibration based on the kappa showed the highest data reliability of 0.98 in 1989 and 0.95 in 2019, respectively. According to the transition matrix of probabilities, the most significant changes in the ZRB based on the past scenario (1989–2019) is in rainfed and built up land classes of LULC in 2049. Concurrently, the other classes continue to decline except irrigated agriculture and water bodies. The results obtained showed that the pasture and mountain LULC class had continued to reduce more than other classes. Furthermore, water resources and the amount of the precipitation in past and future are important to spatial and temporal expansion on LULC classes.
format	Article
author	Ghalehteimouri, Kamran Jafarpour Shamsoddini, Ali Mousavi, Mir Najaf Che Ros, Faizah Khedmatzadeh, Ali
author_facet	Ghalehteimouri, Kamran Jafarpour Shamsoddini, Ali Mousavi, Mir Najaf Che Ros, Faizah Khedmatzadeh, Ali
author_sort	Ghalehteimouri, Kamran Jafarpour
title	Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran
title_short	Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran
title_full	Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran
title_fullStr	Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran
title_full_unstemmed	Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran
title_sort	predicting spatial and decadal of land use and land cover change using integrated cellular automata markov chain model based scenarios (2019–2049) zarriné-rūd river basin in iran
publisher	Elsevier B.V.
publishDate	2022
url	http://eprints.utm.my/id/eprint/98644/1/FaizahCheRos2022_PredictingSpatialandDecadalofLandUse.pdf http://eprints.utm.my/id/eprint/98644/ http://dx.doi.org/10.1016/j.envc.2021.100399
_version_	1756684237900087296
score	13.211869

Predicting spatial and decadal of land use and land cover change using integrated Cellular Automata Markov chain model based scenarios (2019–2049) Zarriné-Rūd River Basin in Iran

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