@Article{GenovezFreSanBenLor:2017:OiSlDe,
author = "Genovez, Patr{\'{\i}}cia Carneiro and Freitas, Corina da Costa
and Sant'Anna, Sidnei Jo{\~a}o Siqueira and Bentz, Cristina Maria
and Lorenzzetti, Jo{\~a}o Ant{\^o}nio",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Centro de Pesquisa da
Petrobr{\'a}s (CENPES)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)}",
title = "Oil Slicks Detection From Polarimetric data using stochastic
distances between complex wishart distributions",
journal = "IEEE Journal of Selected Topics in Applied Earth Observations and
Remote Sensing",
year = "2017",
volume = "10",
number = "2",
pages = "463--477",
month = "Feb.",
keywords = "Information theory, oil slicks detection, polarimetry,
region-based classification, stochastic distances, synthetic
aperture radar (SAR), uncertainty maps.",
abstract = "Polarimetric synthetic aperture radars (PolSAR) have been used to
detect oil slicks at the sea surface. Different techniques to
extract information from polarimetric data, using an adequate
statistical distribution are currently available. A region-based
classifier for PolSAR data - named PolClass - uses a supervised
approach to compare stochastic distances between scaled complex
Wishart distributions and hypothesis tests to associate confidence
levels into the classification results. In this paper, the
integrated use of these distances together with the uncertainty
maps is applied for the first time to detect oil slicks. A
quad-pol Radarsat-2 data, acquired during one open-water
controlled exercise, was used to perform this test. The PolClass
achieved similar overall accuracies for four stochastic distances,
reaching 96.54% of global accuracy, the best result obtained by
the Hellinger distance. A comparison between the full-and dual-pol
matrices indicated that the results obtained with the VV-HH-HV,
HH-HV, and VV-HV polarizations are statistically equivalent, but
different from that obtained using the HH-VV. Therefore, the
exclusion of the HV channel affected the detection of only mineral
oils. The classifier demonstrated the potential to detect the
three types of oils released, being more effective in detecting
biogenic oils rather than mineral oils. The uncertainty levels
increase from the center to the border of the mineral oil slicks,
indicating the presence of transition regions, possibly related to
different weathering mechanisms. The proposed approach will
contribute to the understanding of where different physical and
chemical processes may be acting, associating confidence levels to
the classification results.",
doi = "10.1109/JSTARS.2016.2628325",
url = "http://dx.doi.org/10.1109/JSTARS.2016.2628325",
issn = "1939-1404 and 2151-1535",
language = "en",
targetfile = "genovez_oil.pdf",
urlaccessdate = "02 maio 2024"
}