Identification of Standard Sensible Bands for the Study of Oil Spill from Multi-sensor and Multi-spectral Satellite Imagery

  • Vikash Kumar Mishra
  • , Fred Nicolls
  • , Amit Kumar Mishra

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (ISBN)

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Oil spills are a primary concern for environmental health, including aquatic ecosystems. The oil spill phenomenon generally happens in remote and inaccessible areas. Tracking and monitoring such phenomena with traditional methods and field surveys would be risky, costly, and time-consuming. Remote sensing imageries would be an efficient solution to overcome these challenges. Multispectral imagery (MSI) is advanced in both spatial and temporal resolution. In this article, multisensor imagery is used to identify the standard band imageries that are more sensible to the oil spill phenomenon. The four sensors, viz., Sentinel-2, Landsat-8, Landsat-9, and MODIS, are used for the study. The spatial resolution varies between 500 meters to 10 meters, whereas temporal resolution is between 16 days to one day. Three methods, Spectral Reflectance Curve (SRC), Band Separability Analysis (BSA), and Density Slicing (DS) are used for the analysis of spectral bands. It has been observed that Blue, Green, and SWIR2 are standard bands in all four sensors for the study of the oil spill phenomenon.
Iaith wreiddiolSaesneg
Teitl2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)
CyhoeddwrIEEE Press
Nifer y tudalennau6
ISBN (Electronig)979-8-3503-7687-6
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 19 Hyd 2024
Digwyddiad2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI) - Prayagraj, India
Hyd: 19 Hyd 202420 Hyd 2024

Cyfres gyhoeddiadau

EnwInternational Conference on Computer Vision and Machine Intelligence (CVMI)
CyhoeddwrIEEE Press

Cynhadledd

Cynhadledd2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)
Gwlad/TiriogaethIndia
DinasPrayagraj
Cyfnod19 Hyd 202420 Hyd 2024

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