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Deep learning: To better understand how human activities affect the value of ecosystem services-A case study of Nanjing

文献类型：期刊论文

作者Liu, Chang1; Qi, Yi2; Wang, Zhenbo3; Yu, Junlan1; Li, Shan1; Yao, Hong4; Ni, Tianhua1
刊名PLOS ONE
出版日期2020-10-06
卷号15期号:10页码:16
ISSN号1932-6203
DOI10.1371/journal.pone.0238789
通讯作者Yao, Hong(yaohong@ntu.edu.cn) ; Ni, Tianhua(thni@nju.edu.cn)
英文摘要The value of ecosystem services is affected by increasing human activities. However, the anthropogenic driving mechanisms of ecosystem services are poorly understood. Here, we established a deep learning model to approximate the ecosystem service value (ESV) of Nanjing City using 23 socioeconomic factors. A multi-view analysis was then conducted on feasible impact mechanisms using model disassembly. The results indicated that certain factors had their own significant and independent effects on ESV, such as the proportion of water areas in the land-use structure and the output value of the secondary industry. The proportion of ecological water should be increased as much as possible, whereas the output value of the secondary industry should be reasonably controlled in Nanjing. Other intrinsically related factors were likely to be composited together to affect ESV, such as industrial water consumption and industrial electricity consumption. In Nanjing, simultaneously optimizing socio-economic factors related to city size, resources, and energy use efficiency likely represents an effective management strategy for maintaining and enhancing regional ecological service capabilities. The results of this work suggest that deep learning is an effective method of deepening studies on the prediction of ESV trends and human-driven mechanisms.
WOS关键词URBANIZATION ; BUNDLES ; IMPACTS ; AREAS ; CITY ; NEED
资助项目Department of Ecology and Environment of Jiangsu Provvince[2018008] ; Department of Science and Technology of Jiangsu Province[201904]
WOS研究方向Science & Technology - Other Topics
语种英语
出版者PUBLIC LIBRARY SCIENCE
WOS记录号WOS:000578473000046
资助机构Department of Ecology and Environment of Jiangsu Provvince ; Department of Science and Technology of Jiangsu Province
源URL[http://ir.igsnrr.ac.cn/handle/311030/157169]  
专题中国科学院地理科学与资源研究所
通讯作者Yao, Hong; Ni, Tianhua
作者单位1.Nanjing Univ, Sch Geog & Ocean Sci, Nanjing, Peoples R China
2.Nanjing Univ, Sch Architecture & Urban Planning, Nanjing, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
4.Nantong Univ, Sch Geog, Nantong, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Chang,Qi, Yi,Wang, Zhenbo,et al. Deep learning: To better understand how human activities affect the value of ecosystem services-A case study of Nanjing[J]. PLOS ONE,2020,15(10):16.
APA Liu, Chang.,Qi, Yi.,Wang, Zhenbo.,Yu, Junlan.,Li, Shan.,...&Ni, Tianhua.(2020).Deep learning: To better understand how human activities affect the value of ecosystem services-A case study of Nanjing.PLOS ONE,15(10),16.
MLA Liu, Chang,et al."Deep learning: To better understand how human activities affect the value of ecosystem services-A case study of Nanjing".PLOS ONE 15.10(2020):16.

入库方式： OAI收割

来源：地理科学与资源研究所

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