Automatic identification of oil spills on satellite images

نویسندگان

  • Iphigenia Keramitsoglou
  • Constantinos Cartalis
  • Chris T. Kiranoudis
چکیده

A fully automated system for the identification of possible oil spills present on Synthetic Aperture Radar (SAR) satellite images based on artificial intelligence fuzzy logic has been developed. Oil spills are recognized by experts as dark patterns of characteristic shape, in particular context. The system analyzes the satellite images and assigns the probability of a dark image shape to be an oil spill. The output consists of several images and tables providing the user with all relevant information for decision-making. The case study area was the Aegean Sea in Greece. The system responded very satisfactorily for all 35 images processed. The complete algorithmic procedure was coded in MS Visual CCC 6.0 in a stand-alone dynamic link library (dll) to be linked with any sort of application under any variant of MS Windows operating system. 2004 Elsevier Ltd. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Oil spill detection using in Sentinel-1 satellite images based on Deep learning concepts

Awareness of the marine area is very important for crisis management in the event of an accident. Oil spills are one of the main threats to the marine and coastal environments and seriously affect the marine ecosystem and cause political and environmental concerns because it seriously affects the fragile marine and coastal ecosystem. The rate of discharge of pollutants and its related effects o...

متن کامل

Kohonen Self Organizing for Automatic Identification of Cartographic Objects

Automatic identification and localization of cartographic objects in aerial and satellite images have gained increasing attention in recent years in digital photogrammetry and remote sensing. Although the automatic extraction of man made objects in essence is still an unresolved issue, the man made objects can be extracted from aerial photos and satellite images. Recently, the high-resolution s...

متن کامل

Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms

This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR) for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and co...

متن کامل

Satellite observations of oil spills in Bohai Sea

Several oil spills occurred at two oil platforms in Bohai Sea, China on June 4 and 17, 2011. The oil spills were subsequently imaged by different types of satellite sensors including SAR (Synthetic Aperture Radar), Chinese HJ-1-B CCD and NOAA MODIS. In order to detect the oil spills more accurately, images of the former three sensors were used in this study. Oil spills were detected using the s...

متن کامل

Neural Networks for Oil Spill Detection Using ERS and ENVISAT Imagery

Synthetic Aperture Radar (SAR) images from satellite missions provide a significant support to oil spill detection applications. On the other hands recent studies have demonstrated the potentialities of artificial neural networks for discrimination, starting from SAR imagery, between oil spills and objects which resemble oil spills (called “look-alikes”). The oil spill detection algorithm basic...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Environmental Modelling and Software

دوره 21  شماره 

صفحات  -

تاریخ انتشار 2006