Assessment and enhancement of SAR noncoherent change detection of sea-surface oil spills
Yükleniyor...
Dosyalar
Tarih
2018-01
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Oil spills are one of the most dangerous catastrophes that threaten the oceans. Therefore, detecting and monitoring oil spills by means of remote sensing techniques that provide large-scale assessments is of critical importance to predict, prevent, and clean oil contamination. In this study, the detection of an oil spill using synthetic aperture radar (SAR) imagery is considered. Detection of the oil spill is performed using change detection algorithms between imagery acquired at different times. The specific algorithms used are the correlation coefficient change statistic and the intensity ratio change statistic algorithms. These algorithms and the probabilistic selection of threshold criteria are reviewed and discussed. A recently offered change detection method that depends on generating change maps of two images in a temporal sequence is used. An initial change map is obtained by cumulatively adding sequences in such a manner that common change areas are excluded and uncommon change areas are included. A final change map is obtained by comparing the first and the last images in the temporal sequence. This method requires at least three images to be employed and can be generalized to longer temporal image sequences. The purpose of this approach is to provide a double-check mechanism to the conventional approach and, thus, reduce the probability of false alarm while enhancing change detection. The algorithms are tested on 2010 Gulf of Mexico oil spill imagery. It is shown that the intensity ratio change statistic is a better tool for identification of the changes due to the oil spill compared to the correlation coefficient change statistic. It is also shown that the proposed method can reduce the probability of false alarm.
Açıklama
Anahtar Kelimeler
Change detection (CD), Oil spill, Remote sensing of oceans, Synthetic aperture radar (SAR) imaging, Errors, Marine pollution, Oil spills, Radar, Remote sensing, Signal detection, Synthetic aperture radar, Change detection, Change detection algorithms, Correlation coefficient, Probability of false alarm, Remote sensing of ocean, Remote sensing techniques, Temporal image sequences, Radar imaging
Kaynak
IEEE Journal Of Oceanic Engineering
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
43
Sayı
1
Künye
Bayındır, C., Frost, J. D. & Barnes, C. F. (2018). Assessment and enhancement of SAR noncoherent change detection of sea-surface oil spills. IEEE Journal of Oceanic Engineering, 43(1), 211-220. doi:10.1109/JOE.2017.2714818
