SEA OIL SLICK DETECTION, CLASSIFICATION AND CHARACTERIZATION: POLSAR-BASED APPROACHES ♣
A. Buono , F. Nunziata
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, X. Li , Y. Wei , X. Ding
[email protected] ♣
Dipartimento di Ingegneria, Universit` a degli Studi di Napoli “Parthenope”, Napoli, Italy ♠ NOAA/NESDIS, Global Science & Technology, College Park, MD 20740, USA ♦ Shanghai Ocean University, College of Marine Science, Shanghai 201306, China
MOTIVATIONS Marine oil pollution is a hot scientific and environmental topic. Oil sources are very different and, therefore, the observation systems should satisfy different requirements [1]. Official statistics state that ≈ 70% of the overall oil released at sea is due to human activities related to petroleum consumption: they represent random and frequent sources of small-size oil spills. A large amount of oil spills is also related to petroleum extraction and transportation activities (≈ 10% and 20%, respectively): the former represent sources of crude oil and refined products that lead to well-located and highly variable in nature and size (i.e., natural oil seepages) oil spills, while the latter include both small-size frequent oil spills due to operational activities and large accidental disasters (i.e., the Deepwater Horizon case). Accordingly, a sea oil pollution observation system should meet different measurements:
POLARIMETRIC SAR-BASED APPROACHES Polarimetric SAR-based approaches for sea oil slick monitoring rely on a physical rationale based on the sea surface Bragg scattering model. Under low-to-moderate sea state regimes and for intermediate incidence angles, the slick-free sea surface, as well as weak-damping look-alikes (ships’ wakes, biogenic pollutants, etc.), is characterized by the almost deterministic Bragg scattering, while a strong departure applies over strong damping oil slicks [2]. Such departure can be reliably estimated using a large set of polarimetric features that can be classified according to the kind of available SAR data:
DUAL-POL SAR
COMPACT-POL SAR
QUAD-POL SAR
When DP SAR measurements are available (i.e., two scattering amplitudes), coherent co-polarized data, i.e., HH-VV channels, are needed. Thresholding algorithms have to be applied for oil detection purposes. As an example, the σ approach results are shown [2]:
When CP SAR measurements are available, (i.e., backscattered waves coherently received in the H-V basis once circularly (HP) or slant linearly (π/4) polarized waves are transmitted), thresholding algorithms can be avoided using µw or sin(2χ). HP Pw approach results are shown [2]:
When QP SAR measurements are available (i.e., the full scattering matrix), the maximum amount of physical information on the observed scene can be exploited. Logical binary outputs can be automatically obtained using µ. N P H-based characterization results are shown [2,3]:
REFERENCES [1] Fingas, M. F. and Brown, C.E., 2015 , Handbook of Oil Spill Science and Technology: Oil Spill Remote Sensing. Wiley, pp. 313-356. [2] Migliaccio, M. Nunziata, F. and Buono, A., 2015, A Review on SAR Polarimetry for Sea Oil Slick Observation. International Journal Remote Sensing, in print. [3] Migliaccio, M. and Nunziata, F., 2014, On the Exploitation of PolSAR Data to Map Damping Properties of the DWH Oil Spill. IJRS, 35, no. 10, pp. 3499-3519.
