Oil Spill Detection, Identification, and Tracing / Ying Li.

Format:

Book

Author/Creator:

Li, Ying, author.

Language:

English

Subjects (All):

Detectors.

Oil spills--Case studies.

Oil spills.

Oil spills--Identification.

Tracers (Chemistry).

Genre:

Case studies.

Physical Description:

1 online resource (310 pages)

Edition:

First edition.

Place of Publication:

Amsterdam, Netherlands : Elsevier, [2024]

Summary:

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.

Contents:

Front Cover

OIL SPILL DETECTION,IDENTIFICATION, AND TRACING

Copyright

Contents

Preface

Acknowledgments

1 - Introduction

1.1 Oil spill and its impacts

1.2 Sources of oil spills and their characteristics

1.3 Oil spill remote sensing and tracing

1.3.1 Oil spill detection and identification technology

1.3.2 Oil spill tracing

1.3.2.1 Infrared spectroscopy

1.3.2.2 Fluorescence spectroscopy

1.3.2.3 Gas chromatography

1.3.2.4 Gas chromatography-mass spectrometry

1.3.2.5 Stable isotope mass spectrometry

References

2 - Theoretical basis

2.1 Basics of electromagnetic radiance

2.1.1 Properties of electromagnetic waves

2.1.1.1 Maxwell equations

2.1.1.2 Mass equation

2.1.1.3 Fluctuation of electromagnetic field

2.1.1.4 Propagation speed

2.1.2 Electromagnetic wavebands

2.1.3 Basic law of electromagnetic radiation

2.2 Basic terms of remote sensing

2.2.1 Observation angle

2.2.2 Radiation terminology

2.2.3 Polarization

3 - Passive optical remote sensing technology for oil spill detection

3.1 Remote sensors and sensing platforms

3.2 Theoretical basis for the oil spill remote sensing using visible bands

3.2.1 Solar radiation

3.2.2 Transmission of visible light in the atmosphere

3.2.3 Interaction between visible light and oil slick

3.3 Oil spill detection using infrared bands

3.3.1 Theoretical basis of infrared radiation

3.3.2 Interaction between infrared radiation and atmosphere

3.3.3 Infrared characteristics of oil spills

3.4 Passive optical remote sensing technology

3.4.1 Oil spill detection and identification based on reflectance spectrum

3.4.1.1 Feature selection and feature extraction of hyperspectral data

3.4.1.2 Spectral characteristics parameters.

3.4.2 Oil spill extraction in hyperspectral image

3.4.3 Spectral unmixing technology for oil spill detection

3.4.3.1 Spectral mixing model

3.4.3.2 Spectral unmixing model

3.4.3.3 Abundance estimation

4 - Active optical remote sensing technology for oil spill detection

4.1 Remote sensors and sensing platforms

4.1.1 Airborne LIF system for oil spill detection and identification

4.1.2 Portable LIF device for oil spill detection and identification

4.2 Principle of oil spill detection based on LIF

4.2.1 Principle of LIF

4.2.2 Influence factors of LIF

4.2.2.1 Conjugated π bonds system

4.2.2.2 Rigid planar structure

4.2.2.3 Lowest singlet excited state properties

4.2.2.4 Electron donor substituents

4.3 Oil spill identification based on LIF

4.3.1 Spectral differences analysis

4.3.2 Spectral feature extraction

4.3.3 Crude oil identification method

5 - Oil spill detection based on marine radar

5.1 Radar sensors and platforms

5.2 Principle of oil spill detection based on marine radar

5.3 Oil spill identification and extraction based on marine radar

5.3.1 Marine radar image preprocessing

5.3.1.1 Coordinate transpormation

5.3.1.2 Suppressing shared-frequency interference

5.3.1.2.1 Median filter

5.3.1.2.2 Adaptive median filter

5.3.1.2.3 Performance analysis of the shared-frequency noise suppression

5.3.1.3 Suppressing the interference of noise pixels

5.3.2 Oil spill information extraction based on marine radar image

5.3.2.1 Power attenuation correction method

5.3.2.2 Texture analysis method

5.3.2.3 Adaptive threshold method

5.3.2.4 Classification by machine learning algorithm

5.3.2.4.1 SVM

5.3.2.4.2 k-NN

5.3.2.4.3 LDA

5.3.2.4.4 Ensemble Learning (EL).

5.3.2.4.5 Oil spill detection on the texture analyzed image using machine learning algorithm and adaptive threshold method

6 - Oil spill detection based on SAR

6.1 Remote sensors and sensing platforms

6.2 Principles of oil spill detection based on SAR

6.2.1 SAR imaging

6.2.2 Polarized SAR imaging of oil spill

6.2.3 Influence factors of oil spill detection based on SAR

6.3 Oil spill detection process based on SAR

6.3.1 SAR image preprocessing

(1) Radiometric correction

(2) Geometric correction

(3) Filter processing

6.3.2 SAR image segmentation

6.3.2.1 Threshold segmentation

6.3.2.2 Edge segmentation

6.3.2.3 Region segmentation

6.3.2.4 Segmentation based on intelligent algorithm

6.3.3 Oil spill detection based on polarized SAR

6.3.3.1 Extracting polarization characteristic parameter

6.3.3.2 Oil spill detection and analysis based on combined characteristic parameter

6.3.4 False target recognition technology

6.3.4.1 Direct analysis

6.3.4.2 Correlation analysis

7 - Oil spill detection based on GNSS-R

7.1 Remote sensors and sensing platforms

7.1.1 Geometrical structural of GNSS-R

7.1.2 Fresnel reflection coefficient

7.1.3 Mathematical representation of the direct GNSS signal

7.1.4 Mathematical representation of the reflected GNSS signal

7.1.5 Bistatic forward scattering model based on KA-GO

7.2 Oil spill information extraction based on GNSS-R

7.2.1 Normalized bistatic radar cross section of sea surface

7.2.2 MSS model of oil spill sea surface

7.2.3 DDM of oil spill on sea surface

8 - Oil spill tracing technology

8.1 Ecological effect of oil spill

8.1.1 Effects of pollution stress on metabolism of microalgae

8.1.2 Effect of marine oil spill on fatty acid synthesis of microalgae.

8.1.3 Application of stable isotope analysis in marine ecology

8.2 Identification index of oil spill tracing

8.2.1 Saturated hydrocarbon index

8.2.2 Polycyclic aromatic hydrocarbons index

8.2.3 Biomarker index

8.3 Stable isotope fingerprint of spilled oil

8.3.1 Effect of weathering stress on oil fingerprint

8.3.2 Carbon stable isotopes of petroleum

9 - Case study: routine surveillance of the oil spills in coastal environment

9.1 UV-induced fluorescence device for oil spills detection

9.2 Design of UV-induced fluorescence device for oil spills detection

9.3 Long-term experiment of oil spill monitoring using UV-induced fluorescence device

9.4 Routine surveillance of oil spills using UV-induced fluorescence device

10 - Case study: Oil spill extraction in spaceborne dual-polarization SAR image

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 polarization SAR system

10.1.2.1 Scattering mechanism of dual-polarization SAR system

10.1.2.2 Scattering mechanism of fully polarization SAR system

10.1.3 Comparison results of the multimode polarization SAR scattering mechanism of ocean oil films

10.1.3.1 Comparison results on H/α of relative oil film thickness under multimodal polarization SAR

10.1.3.2 Comparison results on H/α of different types of oil films under multimodal polarization SAR

10.1.3.3 Comparison results on H/α of oil films and oil-like films

10.2 Oil spill detection algorithm based on the edge advantage characteristics of multitemporal region of interest

10.2.1 Wind field inversion

10.2.2 ROI extraction method based on potential dark regions

10.2.2.1 Potential dark area extraction

10.2.2.2 Potential dark area frequency result extraction.

10.2.3 Analysis and comparison of different boundary features

10.2.3.1 Feature parameter extraction

10.2.3.2 Random forest classifier

10.3 Experimental area and data source

10.4 Multitemporal dual-polarization oil spill detection results

10.4.1 Radar signal characteristics of oil film under different sea surface wind speed conditions

10.4.2 Results and analysis of ROI extraction

10.4.3 Comparison results of dominant features of different boundaries

10.4.3.1 Feature parameter screening and importance analysis

10.4.3.2 Precision evaluation and analysis of oil spill detection based on random forest

10.4.4 Spatial distribution and temporal change of the oil spills in multi-temporal dual-polarization SAR images

11 - Case study: tracing illegal oil discharge from ships

11.1 Illegal oil discharge from ships

11.2 Oil spill detection and look-a-like elimination from SAR images

11.3 Tracing the source of spills using AIS

12 - Case study: remotely monitoring oil storage facilities

12.1 Inversion method for the height of oil tank

12.1.1 Target detection and recognition method based on traditional image processing and machine learning algorithm

12.1.2 Target detection and recognition method based on deep learning algorithm

12.2 Detection method of storage tank

12.2.1 Spatial geometry between shadow and building

12.2.2 Image shadow length calculation

12.3 Application cases

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.

Notes:

Includes bibliographical references and index.

Description based on print version record.

Other Format:

Print version: Li, Ying Oil Spill Detection, Identification, and Tracing

ISBN:

9780443137792

044313779X