干旱区生态环境知识资源中心(Arid): Modeling the response of ecological service value to land use change through deep learning simulation in Lanzhou, China

Arid

DOI	10.1016/j.scitotenv.2021.148981
	Modeling the response of ecological service value to land use change through deep learning simulation in Lanzhou, China
	Liu, Jiamin; Xiao, Bin; Jiao, Jizong; Li, Yueshi; Wang, Xiaoyun
通讯作者	Jiao, JZ (corresponding author), Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou 730000, Peoples R China.
来源期刊	SCIENCE OF THE TOTAL ENVIRONMENT
ISSN	0048-9697
EISSN	1879-1026
出版年	2021
卷号	796
英文摘要	Land use (LU) changes caused by urbanization, climate, and anthropogenic activities alter the supply of ecosys-tem services (ES), which affects the ecological service value (ESV) of a given region. Existing LU simulation models extract neighborhood effects with only one data time slice, which ignores long-term dependence in neighborhood interactions. Previous studies on the dynamic relationship between LU change and ES in semi -arid areas is rare than that in humid coastal areas. Here, we selected a semi-arid city, Lanzhou, in Northwest China as the study area, to simulate LU changes in 2030 under natural growth (NG), ecological protection (EP), economic development (EP), and ecological protection-economic development (EPD) scenarios, using a novel deep learning method, named CL-CA. Convolutional neural network and long short term memory (CNN-LSTM) with cellular automata (CA) were utilized to extract the spatiotemporal neighborhood features. The overall sim-ulation performance of the proposed model was larger than 0.92, which is surpassed that of LSTM-CA, artificial neural network (ANN)-CA, and recursive neural network (RNN)-CA. Ultimately, we utilized LU and ES to quan-titatively evaluate the ESV changes. The results indicated that: (1) The variable trend of ESV in arid area is different from that in coastal humid areas. (2) Forest land and water were the main factors that affect the ESV change. (3) The EPD scenario was more suitable for sustainable urban development. (c) 2021 Elsevier B.V. All rights reserved.
英文关键词	Deep learning Land use change Ecological service value Scenario simulation Semi-arid region Lanzhou
类型	Article
语种	英语
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000698511100017
WOS关键词	USE/LAND-COVER CHANGE ; ECOSYSTEM SERVICES ; URBAN-GROWTH ; CELLULAR-AUTOMATA ; TRANSITION RULES ; WETLAND LOSS ; IMPACTS ; BIODIVERSITY ; EXPANSION ; PATTERNS
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
来源机构	兰州大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/364582
作者单位	[Jiao, Jizong] Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou 730000, Peoples R China; Minist Educ MOE, Key Lab Western Chinas Environm Syst, Lanzhou 730000, Peoples R China
推荐引用方式 GB/T 7714	Liu, Jiamin,Xiao, Bin,Jiao, Jizong,et al. Modeling the response of ecological service value to land use change through deep learning simulation in Lanzhou, China[J]. 兰州大学,2021,796.
APA	Liu, Jiamin,Xiao, Bin,Jiao, Jizong,Li, Yueshi,&Wang, Xiaoyun.(2021).Modeling the response of ecological service value to land use change through deep learning simulation in Lanzhou, China.SCIENCE OF THE TOTAL ENVIRONMENT,796.
MLA	Liu, Jiamin,et al."Modeling the response of ecological service value to land use change through deep learning simulation in Lanzhou, China".SCIENCE OF THE TOTAL ENVIRONMENT 796(2021).