Collating multisource geospatial data for vegetation detection using Bayesian network-a case study of Yellow River Delta

doi:10.1504/IJCSE.2017.087407

YIC-IR > 中国科学院海岸带环境过程与生态修复重点实验室 > 海岸带信息集成与战略规划研究中心

	Collating multisource geospatial data for vegetation detection using Bayesian network-a case study of Yellow River Delta
	Mo, Dingyuan 1,2; Yu, Liangju1 ; Gao, Meng1
ISSN	1742-7185
	2017
卷号	15 期号:3-4 页码:277-284
关键词	Bayesian networks Geographic information systems Road construction Sensitivity analysis
DOI	10.1504/IJCSE.2017.087407
产权排序	(1) Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, No. 17, Chunhui Road, Yantai; 264003, China; (2) University of Chinese Academy of Sciences, Beijing; 100049, China
作者部门	海岸带信息集成与综合管理实验室
英文摘要	Multisource geospatial data contains a lot of information that can be used for environment assessment and management. In this paper, four environmental indicators representing typical human activities in Yellow River Delta, China are extracted from multisource geospatial data. By analysing the causal relationship between these human-related indicators and NDVI, a Bayesian network (BN) model is developed. Part of the raster data pre-processed using GIS is used for training the BN model, and the other data is used for model testing. Sensitivity analysis and performance assessment showed that the BN model was good enough to reveal the impacts of human activities on land vegetation. With the trained BN model, the vegetation change under three different scenarios was also predicted. The results showed that multisource geospatial data could be successfully collated using the GIS-BN framework for vegetation detection. © 2017 Inderscience Enterprises Ltd.
文章类型	Conference article
资助机构	This work was partly supported by the Youth Innovation Promotion Association of the Chinese Academy of Sciences (2016195), S&T Service Network Initiative (KFJ-EW-STS-127-2), CAS Knowledge Innovation Project (KZCX2-EW-QN209), and National Natural Science Foundation of China (31570423).
收录类别	EI
语种	英语
研究领域[WOS]	Highway Engineering
EI主题词	Bayesian networks ; Geographic information systems ; Road construction ; Sensitivity analysis
EI入藏号	20174304291178
引用统计
文献类型	期刊论文
条目标识符	http://ir.yic.ac.cn/handle/133337/25214
专题	中国科学院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心中国科学院海岸带环境过程与生态修复重点实验室
作者单位	1.Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, No. 17, Chunhui Road, Yantai; 264003, China; 2.University of Chinese Academy of Sciences, Beijing; 100049, China
推荐引用方式 GB/T 7714	Mo, Dingyuan,Yu, Liangju,Gao, Meng. Collating multisource geospatial data for vegetation detection using Bayesian network-a case study of Yellow River Delta[J],2017,15(3-4):277-284.
APA	Mo, Dingyuan,Yu, Liangju,&Gao, Meng.(2017).Collating multisource geospatial data for vegetation detection using Bayesian network-a case study of Yellow River Delta.,15(3-4),277-284.
MLA	Mo, Dingyuan,et al."Collating multisource geospatial data for vegetation detection using Bayesian network-a case study of Yellow River Delta".15.3-4(2017):277-284.