Collating multisource geospatial data for vegetation detection using Bayesian network-a case study of Yellow River Delta | |
Mo, Dingyuan1,2; Yu, Liangju1![]() ![]() | |
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. |
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