Oil Spill Detection, Identification, and Tracing
- 1st Edition - October 23, 2023
- Imprint: Elsevier
- Author: Ying Li
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 3 7 7 8 - 5
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 3 7 7 9 - 2
Oil Spill Detection, Identification and Tracing provides readers with currently applicable technical methods, including early warning monitoring of trace oil film in ports, re… Read more
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Oil Spill Detection, Identification and Tracing provides readers with currently applicable technical methods, including early warning monitoring of trace oil film in ports, remote sensing monitoring of sea surface oil spills, and source tracing. Beginning with the causes and characteristics of oil spills on water, chapters then evaluate a range of different detection methods, including passive optical remote sensing, active optical remote sensing, marine radar, and GNSS-R. The book then reviews oil spill traceability technology, highlighting the ecological effect of oil spills on oceanic environment, current studies on oil spill fingerprinting, and the application of stable isotope technology in oil spill tracing.
The book concludes with three key case studies with real-world scenarios, making it a practical resource for students, researchers and engineers interested in oil spill pollution, environmental science and the marine environment.
- Includes principles and methods of emerging remote-sensing technologies (e.g., fluorescent remote sensing, marine radar, and GNSS-R to monitor oil spills)
- Provides a detailed introduction of oil-spill traceability technology, especially the use of stable isotope analysis for oil spill tracing
- Describes the application of detection, identification and tracing technologies used in marine oil spill research
- Focuses on prevention and remediation through technological advances
Researchers in oil spill pollution and remote sensing, Maritime safety agencies, Local environmental agencies, Graduate students in remote sensing, oceanography, environmental science, and engineering, Readers interested in the environment and specifically ocean pollution caused by oil spillage, Professionals: Oil sector: e.g., petroleum engineers, Environmental engineers and managers, Offshore engineers, Ecologists, Students: As a textbook or reference book for graduate-level courses in “Ocean Remote Sensing,” “Ocean Optics,” and “Introduction to Spill Science.”
1 Introduction
1.1 Background
1.1.1 Causes and characteristics of oil spills on water
1.1.2 Status and trends
1.2 A review on oil spill detection and identification
1.3 A review on oil spill tracing. This chapter introduces the research background of monitoring, identification, and tracing of oil spills on water, the status and development trend of related technologies.
2 Theoretical bases
2.1 Basis of electromagnetic wave
2.1.1 Properties of electromagnetic wave
2.1.2 Categories of electromagnetic wave
2.1.3 Basic law of electromagnetic radiation
2.2 Basic terminology of remote sensing
2.2.1 Observation angle
2.2.2 Terminology of radiation
2.1.3 Polarization This chapter introduces the basic theories and terminologies of electromagnetic waves and radiation that are necessary to appreciate remote sensing technology discussed in the following chapters.
3 Oil spill detection based on passive optical remote sensing
3.1 Remote sensors and sensing platforms
3.2 Basic principles of passive optical remote sensing
3.2.1 Solar radiation
3.2.2 Transmission of visible light in the atmosphere
3.2.3 Interaction between visible light and oil film
3.3 Basic principles of infrared remote sensing
3.3.1 Infrared radiation
3.3.2 Interaction between infrared radiation and the atmosphere
3.3.3 Infrared radiation of the oil film
3.4 Oil spill identification and extraction technology using optical remote sensing
3.4.1 Spectral analysis and identification
3.4.2 Oil spill extraction from imagery
3.4.3 Spectral unmixing This chapter introduces the principle of passive optical remote sensing for oil spill monitoring, the method of extracting spectral features, and hyperspectral data unmixing methods.
4 Oil spill detection based on active optical remote sensing
4.1 Remote sensors and sensing platforms
4.1.1 Airborne LIF oil spill detection and identification system
4.1.2 Portable LIF oil spill detection and identification system
4.2 Basic principles of active optical remote sensing
4.2.1 Principles of LIF
4.2.2 Influence factors of LIF
4.3 Oil spill detection based on LIF
4.3.1 Fluorometric spectral analysis
4.3.2 Spectrum feature extraction
4.3.3 Oil types - identification based on LIF This chapter introduces the principle of laser-induced fluorescence for oil spill detection and identification. Some typical methods of fluorometric spectral analysis are also discussed.
5 Oil spill detection based on marine radar
5.1 Remote sensors and sensing platforms
5.2 Basic principles of marine radar
5.3 Oil spills and its effects on radar images
5.4 Oil spill extraction based on marine radar
5.4.1 Radar image processing
5.4.2 Oil spill information extraction This chapter introduces the principle of marine radar and its application in oil spill detection. The whole process of oil spill extraction in radar image, including coordinate transformation, signal denoising, threshold determination, oil spill extraction algorithms are described.
6 Oil spill detection based on SAR
6.1 Remote sensors and sensing platforms
6.2 Basic principles of SAR
6.2.1 SAR imaging
6.2.2 Polarized SAR
6.2.3 Influence factors on polarized SAR imaging
6.3 Oil spill extraction based on SAR
6.3.1 SAR image processing 6.3.2 SAR image segmentation
6.3.3 Oil spill extraction using single-polarized SAR
6.3.4 Oil spill extraction using dual-polarized SAR
6.3.5 Oil spill extraction using fully polarized SAR
6.3.6 Distinguishing looks-alike target in SAR image This chapter introduces the principle of SAR and its application in oil spill detection, and especially emphasizes the application and comparison of single-, dual- and fully- polarized SAR technology.
7 Oil spill detection based on GNSS-R
7.1 Remote sensors and sensing platforms
7.2 Oil spill extraction based on SAR
7.2.1 Normalized bistatic radar cross section of sea surface
7.2.2 Mean surface slope model of oil polluted sea surface
7.2.3 Delay-Doppler Map of oil polluted sea surface This chapter introduces the principle of GNSS-R and its application in oil spill detection. Several different models for oil spill detection are introduced and discussed.
8 Oil spill traceability technology
8.1 Ecological effect of oil spill
8.2 Tracing technology of oil spill
8.3 Stable isotope fingerprint of oil pollutants This chapter introduces the ecological effect of oil spills on oceanic environment, current studies on oil spill fingerprinting methods, and the application of stable isotope technology in oil spill tracing.
9 Case study: Routine surveillance of the oil spills in coastal environments
9.1 Early alarms of oil spills in coastal environments
9.2 LIF device design
9.3 Monitoring sites
9.4 Routine surveillance in the port and drilling platform This chapter introduces the application of LIF device for the early alarms of oil spills in coastal environments.
Chapter 10 Case study: Oil spill extraction in spaceborne dual-polarized SAR imagery
10.1 Scattering mechanism of oil film on the sea surface
10.1.1 Signal-to-noise ratio in SAR system
10.1.2 Scattering mechanism of polarized SAR system
10.2 Oil spill detection algorithm based on the edge advantage characteristics of multi-temporal ROI
10.2.1 Wind field inversion
10.2.2 ROI extraction method based on potential dark regions
10.2.3 Analysis and comparison of advantages of different boundaries
10.3 Experimental area and data source
10.4 Spatial distribution and time series change results of oil spill in multi-temporal dual-polarized SAR
11 Case study: Tracing illegal oil discharge from ships
11.1 Oil spill detection from SAR images
11.2 Elimination of look-alikes
11.3 Tracing the source of spills using AIS This chapter introduces an application case where spaceborne SAR was combined with AIS to trace illegal oil discharge from ship.
12 Case study: Remotely monitoring oil storage facilities
12.1 Oil tank detection in optical remote sensing images
12.1.1 Classic image processing and machine learning algorithm
12.1.2 Oil tank detection based on deep learning algorithm
12.1.3 Delay-Doppler Map of oil polluted sea surface
12.2 Calculating the height of oil tank
12.2.1 Spatial geometry between shadow and building
12.2.2 Image shadow length calculation
12.3 Estimating the volume of oil tank and risks of oil spills This chapter introduces a feasible way to remotely monitor the oil storage facilities and estimate the risks of oil spills.
Chapter 13 Case study: Oil spill tracing based on stable carbon isotope of petroleum hydrocarbons
13.1 Theoretical basis of stable carbon isotope of petroleum hydrocarbon
13.1.1 Stable carbon isotope
13.1.2 Isotope fractionation
13.1.3 Standard stable carbon isotope ratio
13.2 Stable isotope analysis of oil spill
13.2.1 General methodology
13.2.2 Stable carbon isotope fingerprint identification system for spilled oil on water
13.2.3 Oil sample collection
13.2.4 Data processing and analysis
13.3 Analysis of n-alkane composition
13.3.1 Distribution of n-alkanes in crude oil
13.3.2 Distribution of n-alkanes in fuel
13.3.3 Distribution of n-alkanes in oil mixture
13.4 Polycyclic aromatic hydrocarbons (PAHs) composition
13.4.1 Analysis of PAHs in crude oil samples
13.4.2 Analysis of PAHs in fuel
13.5 Comparative analysis of crude oil and fuel oil samples
13.5.1 Stable carbon isotope analysis of n-alkane components in crude oil and fuel oil samples
13.5.2 Stable carbon isotope analysis of PAHs in crude oil and fuel oil samples
- Edition: 1
- Published: October 23, 2023
- Imprint: Elsevier
- Language: English
YL
Ying Li
Ying Li received a Ph.D. in Miyagi, Japan, from Tohoku University. Currently a professor in Dalian Maritime University, China, Dr. Li is the Dean of the national key-field innovation team of maritime traffic safety and spatial information technology. For over 20 years, she has contributed to scientific research in the fields of intelligent perception of at-sea target and navigation environment, oil spill detection, waterborne intelligent transportation.
Her credentials include:
Member, expert committee of the Ministry of Transport,
Dr. Li oversaw > 20 national and ministerial projects.
Awarded > 30 national patents and been published in > 120 scientific papers.
Awarded > 20 provincial and ministerial awards, including second prize for National Technological Invention, special prize for technological invention, Chinese Society of Navigation.
Vice chair, “Digital Ocean” special committee, National Committee of International Digital Earth Society of China
Vice chair, Navigation Remote Sensing Special Committee of Chinese Society of Navigation.
Affiliations and expertise
Professor, Dalian Maritime University, ChinaRead Oil Spill Detection, Identification, and Tracing on ScienceDirect