Overview of optical remote sensing of marine oil spills and hydrocarbon seepage

被引:0
|
作者
Lu, Yingcheng [1 ,2 ]
Hu, Chuanmin [2 ]
Sun, Shaojie [2 ]
Zhang, Minwei [2 ]
Zhou, Yang [1 ]
Shi, Jing [1 ]
Wen, Yansha [1 ]
机构
[1] International Institute for Earth System Science, Nanjing University, Nanjing,210046, China
[2] College of Marine Science, University of South Florida, St. Petersburg,FL,33701, United States
来源
关键词
Aquatic environments - Detection and quantifications - Environmental conditions - Marine environment monitoring - Ocean - Optical remote sensing - Radiometric resolution - Remote sensing images;
D O I
10.11834/jrs.20166122
中图分类号
学科分类号
摘要
The remote detection and quantification of oil spills and hydrocarbon seepage represent a key research direction in marine environment monitoring and resource management. Passive optical remote sensing using sunlight has been used for several decades, and significant progress has been made in recent years. It exhibits the following characteristics.(1)The optical detection and classification of oil spills and hydrocarbon seepage are based on their different optical properties from oil-free water. These properties include oil slicks of different thicknesses, oil-water mixture(i.e., oil emulsion of different concentrations), thick floating oil, and thin oil slicks, and hydrocarbon gas from seabed hydrocarbon seepage. (2) These different oil and hydrocarbon forms undergo different optical processes when interacting with light because they can reflect, absorb, and scatter the incident light, resulting in different levels of optical contrast from surrounding oil-free water and thus providing a theoretical basis for their detection, classification, and quantification through optical remote sensing. (3) The Fresnel reflection of different surfaces, such as oil-free water or oiled surfaces with different refractive indexes and roughness, helps detection but presents challenges on classification and quantification. This paper provides a brief review of the characteristics of marine oil spills and hydrocarbon seepage in their various forms, and discusses the advantages and challenges in their optical detection and quantification. Many space borne and airborne multi/hyper-spectral or multi-angle optical sensors, such as MODIS, MERIS, AVIRIS, MISR, Hyperion, and Landsat, have been used to detect, quantify, and map oil spills or natural seepage, as shown in the most recent oil spill disasters and natural seepage estimates in the Gulf of Mexico. In these applications, lab-based experimental results provide optical models and key parameters to improve the quantification of surface oil from remote sensing images. Environmental conditions, such as sea state and solar/viewing geometry from a real spill case, can be dramatically different from those in the lab experiments. Thus, applying lab-based results to aquatic environments becomes technically challenging. Significant process has been made in understanding the oil-water spatial and spectral contrasts of these different oil forms under different environmental conditions. However, some key issues still need to be investigated further. These issues include sensor capability (i.e., spectral, spatial, and radiometric resolutions), relationship between spectral/spatial oil-water contrast and oil type and thickness, and optical models for improved detection and quantification at various scales. The fundamental difficulty in determining oil thickness or volume in the field needs to be overcome to refine lab-based models and validate remote sensing estimates. Nevertheless, optical remote sensing is expected to make continuous progress to eventually overcome these challenges and thereby play an increasingly important role in assessing marine oil spills and hydrocarbon seepage. © 2016, Science Press. All right reserved.
引用
收藏
页码:1259 / 1269
相关论文
共 50 条
  • [1] Remote sensing of oil spills
    Fingas, M
    Brown, C
    [J]. SEA TECHNOLOGY, 1997, 38 (09) : 37 - &
  • [2] Remote sensing of oil spills on water
    Sabins, FF
    [J]. 27TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT, PROCEEDINGS: INFORMATION FOR SUSTAINABILITY, 1998, : 583 - 585
  • [3] Optical Remote Sensing of Oil Spills in the Ocean: What Is Really Possible?
    Hu, Chuanmin
    Lu, Yingcheng
    Sun, Shaojie
    Liu, Yongxue
    [J]. JOURNAL OF REMOTE SENSING, 2021, 2021
  • [4] Remote sensing of evolution of oil spills on the water surface
    Ermakov, S.
    Kapustin, I.
    Molkov, A.
    Leshev, G.
    Danilicheva, O.
    Sergievskaya, I.
    [J]. REMOTE SENSING OF THE OCEAN, SEA ICE, COASTAL WATERS, AND LARGE WATER REGIONS 2018, 2018, 10784
  • [5] Research on Cross-Spatiotemporal Remote Sensing Detection of Marine Oil Spills and Emulsions Based on Coupling Optical and Thermal Response Characteristics
    Jiang, Zongchen
    Zhang, Jie
    Ma, Yi
    Mao, Xingpeng
    Du, Kai
    Huang, Xinyue
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62
  • [6] Pattern recognition analysis of marine oil spills in airborne passive infrared multispectral remote sensing images
    Chen, Zizi
    Small, Gary W.
    [J]. ANALYST, 2022, 147 (22) : 5018 - 5027
  • [7] Remote sensing of marine oil spills from airborne platforms using multi-sensor systems
    Robbe, N.
    Hengstermann, T.
    [J]. Water Pollution VIII: Modelling, Monitoring and Management, 2006, 95 : 347 - 355
  • [8] Ultraviolet remote sensing of marine oil spills: a new approach of Haiyang-1C satellite
    Suo, Ziyi
    Lu, Yingcheng
    Liu, Jianqiang
    Ding, Jing
    Yin, Dayi
    Xu, Feifei
    Jiao, Junnan
    [J]. OPTICS EXPRESS, 2021, 29 (09) : 13486 - 13495
  • [9] Remote sensing for detection and monitoring of vegetation affected by oil spills
    Adamu, Bashir
    Tansey, Kevin
    Ogutu, Booker
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2018, 39 (11) : 3628 - 3645
  • [10] Radiometric methods of remote sensing of oil spills on water surfaces
    Krotikov V.D.
    Mordvinkin I.N.
    Pelyushenko A.S.
    Pelyushenko S.A.
    Rakut’ I.V.
    [J]. Radiophysics and Quantum Electronics, 2002, Springer Science and Business Media, LLC (45) : 220 - 229