DOI: 10.1016/j.marpolbul.2014.11.036
Scopus记录号: 2-s2.0-84922212163
论文题名: A damage assessment model of oil spill accident combining historical data and satellite remote sensing information: A case study in Penglai 19-3 oil spill accident of China
作者: Wei L. ; Hu Z. ; Dong L. ; Zhao W.
刊名: Marine Pollution Bulletin
ISSN: 0025-326X
EISSN: 1879-3363
出版年: 2015
卷: 91, 期: 1 起始页码: 258
结束页码: 271
语种: 英语
英文关键词: Comprehensive assessment
; Information extraction
; Loss of oil spill
; Multiple regression analysis
; Remote sensing
Scopus关键词: Accidents
; Complex networks
; Damage detection
; Information retrieval
; Neural networks
; Oil shale
; Oil spills
; Regression analysis
; Remote sensing
; Surface waters
; Synthetic aperture radar
; Wind
; Comprehensive assessment
; Damage assessment models
; Independent variables
; Multiple regression analysis
; Multiple regression equations
; Neural network classification
; Satellite remote sensing
; Sea-surface wind speed
; Marine pollution
; accident
; artificial neural network
; cleanup
; environmental assessment
; multiple regression
; oil spill response
; remote sensing
; satellite data
; synthetic aperture radar
; Article
; calibration
; chemical accident
; China
; coastal waters
; contrast
; digital filtering
; entropy
; geometry
; history
; image processing
; oil spill
; radiometry
; satellite imagery
; sea pollution
; statistical model
; trend study
; variance
; water temperature
; wind
; accident
; analysis
; artificial neural network
; environment
; environmental monitoring
; evaluation study
; human
; pollution
; procedures
; remote sensing
; theoretical model
; China
; Penglai
; Shandong
; petroleum
; Accidents
; China
; Environment
; Environmental Monitoring
; Environmental Pollution
; Humans
; Models, Theoretical
; Neural Networks (Computer)
; Petroleum
; Petroleum Pollution
; Remote Sensing Technology
; Wind
Scopus学科分类: Agricultural and Biological Sciences: Aquatic Science
; Earth and Planetary Sciences: Oceanography
; Environmental Science: Pollution
英文摘要: Oil spills are one of the major sources of marine pollution; it is important to conduct comprehensive assessment of losses that occur as a result of these events. Traditional methods are required to assess the three parts of losses including cleanup, socioeconomic losses, and environmental costs. It is relatively slow because assessment is complex and time consuming. A relatively quick method was developed to improve the efficiency of assessment, and then applied to the Penglai 19-3 accident. This paper uses an SAR image to calculate the oil spill area through Neural Network Classification, and uses historical oil-spill data to build the relationship between loss and other factors including sea-surface wind speed, and distance to the coast. A multiple regression equation was used to assess oil spill damage as a function of the independent variables. Results of this study can be used for regulating and quickly dealing with oil spill assessment. © 2014 The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/86533
Appears in Collections: 过去全球变化的重建 全球变化的国际研究计划
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作者单位: College of Resources Environment and Tourism, Capital Normal University, Beijing, China; Laboratory of Resources Environment and Geographic Information System, Capital Normal University, Beijing, China; Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing, China; State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation, Ministry of Science and Technology, Beijing, China
Recommended Citation:
Wei L.,Hu Z.,Dong L.,et al. A damage assessment model of oil spill accident combining historical data and satellite remote sensing information: A case study in Penglai 19-3 oil spill accident of China[J]. Marine Pollution Bulletin,2015-01-01,91(1)