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. Issue 1 (15th February 2015)

• Record Type: Journal Article
• Authors: Wei, Lai; Hu, Zhuowei; Dong, Lin; Zhao, Wenji
• Is Part Of: Marine pollution bulletin. Volume 91:Issue 1(2015)
• Page Start: 258
• Page End: 271
• Publication Date: 2015-02-15
• Subjects: Comprehensive assessment -- Loss of oil spill -- Remote sensing -- Information extraction -- Multiple regression analysis; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2014.11.036
• Languages: English
• ISSNs: 0025-326X

Abstract

Highlights: The model is a relatively rapid damage assessment method after oil spill accident. The model is associated with oil information, which is extracted by satellite image. The input data of model are extracted from remote sensing, which is timely. The model is suitable for Developing Country, in national conditions at present. Abstract: 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.