Assessment of terrestrial oil spill dynamics using field spectra and Sentinel 1 H - α decomposition

M. S. Ozigis; J. Kaduk; C. Jarvis; A. Ogochukwu

doi:10.1117/12.2326176

6 August 2018 Assessment of terrestrial oil spill dynamics using field spectra and Sentinel 1 H - α decomposition

M. S. Ozigis, J. Kaduk, C. Jarvis, A. Ogochukwu

Proceedings Volume 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018); 107730E (2018) https://doi.org/10.1117/12.2326176
Event: Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 2018, Paphos, Cyprus

Abstract

Detection of oil pollution have been evaluated and assessed by several authors adopting such techniques as field spectroscopy, vegetation health indices, canopy water use efficiency and UAVSAR Polarimetric Backscatter and Decomposition among several others. However, no published study at the moment have sought to utilize and assess the potential of Spaceborne Sentinel1 C-Band SAR Datasets in the characterization of vegetation affected by oil pollution. In this study, field work was conducted across 3 sites of a recent, old and a non-polluted site. The field plot center point was used to retrieve image information for the various sites. Effort was made to assess the underlying characteristics of Sentinel -1 C Band derived Entropy and Alpha Plane Polarimetric scatterers and the field spectral responses. Result shows that the Alpha component of the dual polarization decomposition had stable scattering characteristics after the spill compared to the observed random scattering characteristics before the spill. This however indicates a feasible potential of the Alpha plane component scatterers for discerning stressed vegetation as a result of oil pollution.

Citation Download Citation

M. S. Ozigis, J. Kaduk, C. Jarvis, and A. Ogochukwu "Assessment of terrestrial oil spill dynamics using field spectra and Sentinel 1 H - α decomposition", Proc. SPIE 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 107730E (6 August 2018); https://doi.org/10.1117/12.2326176

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available