Oil slick monitoring using Sentinel-I SAR images

被引:0
|
作者
Rodrigues, Tomas [1 ,2 ]
Marques, Paulo [1 ,2 ]
机构
[1] Inst Super Engn Lisboa ISEL, Lisbon, Portugal
[2] Inst Telecomunicacoes IT, Lisbon, Portugal
关键词
D O I
10.23919/IRS51887.2021.9466231
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents an algorithm developed in the context of an undergraduate degree of Informatics Engineering for the detection of oil slicks in images from a Synthetic Aperture Radar (SAR). Oil slicks represent a serious threat to the marine ecosystem in the coastal areas and SAR images have been increasingly used in the supervision of this environmental disaster, due to its numerous advantages when compared to images in the visible domain. The developed algorithm envisages simplicity and computational efficiency and is divided in four phases: land masking, statistical analysis of sea, detection of suspected oil slick locations, and final validation. The usage of amplitude SAR images, instead of Single Look Complex (SLC) ones, contributes to the overall low computational requirements. The obtained results are encouraging for real-world applications.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Oil slick detection by SAR imagery: potential and limitation
    Girard-Ardhuid, F
    Mercier, G
    Garello, R
    [J]. OCEANS 2003 MTS/IEEE: CELEBRATING THE PAST...TEAMING TOWARD THE FUTURE, 2003, : 164 - 169
  • [22] Automatic oil slick detection from SAR images: Results and improvements in the framework of the PRIMI pilot project
    Trivero, Paolo
    Adamo, Maria
    Biamino, Walter
    Borasi, Maria
    Cavagnero, Marco
    De Carolis, Giacomo
    Di Matteo, Lorenza
    Fontebasso, Fabio
    Nirchio, Francesco
    Tataranni, Francesco
    [J]. DEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY, 2016, 133 : 146 - 158
  • [23] Monitoring Dynamic Evolution of the Glacial Lakes by Using Time Series of Sentinel-1A SAR Images
    Zhang, Bo
    Liu, Guoxiang
    Zhang, Rui
    Fu, Yin
    Liu, Qiao
    Cai, Jialun
    Wang, Xiaowen
    Li, Zhilin
    [J]. REMOTE SENSING, 2021, 13 (07)
  • [24] Partially supervised oil-slick detection by SAR imagery using kernel expansion
    Mercier, Gregoire
    Girard-Ardhuin, Fanny
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2006, 44 (10): : 2839 - 2846
  • [25] A Unified polarimetric approach for SAR sea oil slick observation
    Nunziata, F.
    Gambardella, A.
    Migliaccio, M.
    [J]. 2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, : 533 - 536
  • [26] A Fast Segmentation Algorithm of SAR Oil Slick with An improved Watershed
    Kong, Longteng
    Che, Yunlong
    Guo, Hao
    An, Jubai
    [J]. 2013 2ND INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION AND MEASUREMENT, SENSOR NETWORK AND AUTOMATION (IMSNA), 2013, : 344 - 348
  • [27] On the Mueller Scattering Matrix for SAR Sea Oil Slick Observation
    Nunziata, Ferdinando
    Gambardella, Attilio
    Migliaccio, Maurizio
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2008, 5 (04) : 691 - 695
  • [28] A Backscattering-Suppression-Based Variational Level-Set Method for Segmentation of SAR Oil Slick Images
    Wu, Yongfei
    He, Chuanjiang
    Liu, Yang
    Su, Moting
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 10 (12) : 5485 - 5494
  • [29] CHANGE ANALYSIS USING MULTITEMPORAL SENTINEL-1 SAR IMAGES
    Thu Trang Le
    Atto, Abdourrahmane M.
    Trouve, Emmanuel
    [J]. 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, : 4145 - 4148
  • [30] Research on the Classification for MODIS Images of Oil Slick on the Sea
    Hou, Yifeng
    Guo, Hao
    Wang, Ning
    An, Jubai
    [J]. PROCEEDINGS OF 2012 IEEE 11TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP) VOLS 1-3, 2012, : 966 - +