干旱区生态环境知识资源中心(Arid): Prediction of drought-driven land use/land cover changes in the Bakhtegan Lake watershed of Iran using Markov chain cellular automata model and remote sensing data

Arid

DOI	10.1007/s11069-022-05721-0
	Prediction of drought-driven land use/land cover changes in the Bakhtegan Lake watershed of Iran using Markov chain cellular automata model and remote sensing data
	Mokarram, Marzieh; Pham, Tam Minh
通讯作者	Pham, TM
来源期刊	NATURAL HAZARDS
ISSN	0921-030X
EISSN	1573-0840
出版年	2023
卷号	116 期号:1 页码:1291-1314
英文摘要	The southern region of Iran is a dry land zone where the drought is a driving force of land-use changes controlling water resources and aquatic ecosystems, such as lakes and wetlands. This study aimed to predict the 2040 drought condition in the Bakhtegan Lake watershed (Iran) and its correlation with land use changes. Extracting from Landsat and MODIS imagery, we classify land-use classes in 2000-2020 and investigate its relationship with multiple drought indicators through principal components analysis (PCA) analysis. In addition, using the Markov and cellular automata (CA)-Markov chain, the 2040 prediction maps of land-use and drought indices were made. Then, the regression analysis was used to reveal the influence trend of desertification on land-use activities in the future. Finally, the ecosystem services value and changes in agricultural lands between 2000 and 2020 were studied in the study area. The observed results of drought indices and land-use maps in 2000-2020 indicated that the expansion of the drought susceptibility zone causes the increasing areas of salt and bare land in parts of the northwestern and southern region. Based on PCA analysis, Normalized Difference Vegetation Index, Enhanced Vegetation Index, and Vegetation Condition Index were chosen to be input data in the CA-Markov model for drought-indices prediction in 2040. The value of these indices would decrease in 2040, indicating more drought in the region. The land-use prediction results in 2040 found that it will increase the percentage of bare land to 0.91, salt land to 0.89, and decrease 0.93 and 0.9 percentages of agricultural land and water lakes. Regression results showed that land use changes were related to drought indices with high accuracy (R-2 = 0.93). In addition, the unprincipled use of agricultural lands and their conversion into saline and barren lands has led to a decrease of more than one million and nine hundred thousand dollars annually in the ecosystem services value.
英文关键词	Land use land cover changes Drought indicators Remote sensing PCA method CA-Markov chain GIS
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000890097100001
WOS关键词	ECOSYSTEM SERVICES ; VEGETATION INDEX ; RAINFALL ; IMPACT
WOS类目	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences ; Water Resources
WOS研究方向	Geology ; Meteorology & Atmospheric Sciences ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/397885
推荐引用方式 GB/T 7714	Mokarram, Marzieh,Pham, Tam Minh. Prediction of drought-driven land use/land cover changes in the Bakhtegan Lake watershed of Iran using Markov chain cellular automata model and remote sensing data[J],2023,116(1):1291-1314.
APA	Mokarram, Marzieh,&Pham, Tam Minh.(2023).Prediction of drought-driven land use/land cover changes in the Bakhtegan Lake watershed of Iran using Markov chain cellular automata model and remote sensing data.NATURAL HAZARDS,116(1),1291-1314.
MLA	Mokarram, Marzieh,et al."Prediction of drought-driven land use/land cover changes in the Bakhtegan Lake watershed of Iran using Markov chain cellular automata model and remote sensing data".NATURAL HAZARDS 116.1(2023):1291-1314.