Automatic detection of oil spills in Envisat, Radarsat and ERS SAR images
نویسندگان
چکیده
We present a framework for automatic detection of oil spills in SAR images. Multi incident angle and multi polarization SAR data are ingested into the framework in order to optimize revisit times and thereby the temporal and spatial coverage. Dark spots in the images are primarily detected by adaptive thresholding. For each of them a number of features are computed in order to classify the slick as either an oil slick or a `lookalike' (other oceanographic phenomena which resemble oil slicks). A classification scheme is utilized based on statistical modeling. A data set of about 100 images from each of the sensors ERS, Radarsat and ENVISAT is or will soon be available to train and test the algorithm. In this paper, only results from ERS and Radarsat are reported because the delivery of ENVISAT images has been delayed.
منابع مشابه
Automatic Oil Spill Detection Based on Envisat, Radarsat and Ers Images
In this paper, we present algorithms for automatic detection of oil spills in SAR images. The algorithms have been trained on a large number of ERS, RADARSAT and ENVISAT images. The performance of the algorithms are compared to manual and semi-automatic approaches in a benchmark study involving 32 RADARSAT images and 28 ENVISAT ASAR images from 2003. Our algorithm performed well both on RADARSA...
متن کاملMonitoring of Crude Oil Spill off the West Coast of the Korean Peninsula Using Sar Images
The nation’s largest maritime oil spill occurred on the west coast of the Korean Peninsula on December 7, 2007. All civilian space-borne SAR sensors including TerraSAR-X, ENVISAT ASAR, RADARSAT-1, ERS-2 SAR, and ALOS PALSAR acquired imageries over the contaminated area. Dark patches observed in these SAR images revealed the presence of oil spills, and showed how wide the spilled area is and how...
متن کاملGenetic Algorithm for Oil Spill Automatic Detection from Multisar Satellite Data
The main objective of this work is to design automatic detection procedures for oil spill in synthetic aperture radar (SAR) satellite data. In doing so the genetic algorithm tool was designed to investigate the occurrence of using ENVISAT and RADARSAT-2 SAR satellite data. The study shows that genetic algorithm provides accurate pattern of oil slick in SAR data. This shown by 90% for oil spill,...
متن کاملComparison between Mahalanobis classification and neural network for oil spill detection using RADARSAT-1 SAR data
Oil spill or leakage into waterways and ocean spreads very rapidly due to the action of wind and currents. The study of the behavior and movement of these oil spills in sea had become imperative in describing a suitable management plan for mitigating the adverse impacts arising from such accidents. But the inherent difficulty of discriminating between oil spills and lookalikes is a main challen...
متن کاملTexture entropy algorithm for automatic detection of oil spill from RADARSAT-1 SAR data
This work presents a method based on the utilisation of texture algorithms for the discrimination of oil spill areas from the surrounding features, e.g. sea surface and look-alikes, using RADARSAT-1 SAR Wide beam mode (W1), Standard beam mode (S2) and Standard beam mode (S1) data acquisition under different wind speeds. The results show that entropy texture algorithm is able to discriminate bet...
متن کامل