Could Ocean-Land Invasion be detected using Multi-temporal Images of Landsat?

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Ayeni, A.O.
Cho, M.A.
Kuton, M.P.
Cukwu, L.O.
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Nigerian Association of Hydrological Sciences (NAHS)
One of the most certain consequences of global sea level rise is ocean – land invasion and is likely to increase in the near future. The coastal rural fishing communities are mostly at risk of the invasion. To address the menace spatially through scientific research interventions, different coastal mapping techniques have been adopted over the years for different research problems e.g. shoreline erosion studies, barrier island migration coastal erosion vulnerability assessment etc. The methods adopted varied from simple analysis, manual analysis of uncorrected topographic maps and aerial photo, digital interpretation of corrected multi-temporal images of low and high resolution images (e.g. Landsat, spot, Ikonos), and hyper-spectral images (e.g. AVIRIS, CASI, hyperion). In complimenting previous studies, this study provides answer to the question “Could ocean-land invasion be detected using multi-temporal images of Landsat?” Orthorectified Landsat remotely sense datasets of MSS (1984), TM (2000), combination of TM & ETM+ (2012) were acquired from GLS portal. The study demarcated 704km2 around the Eastern Obolo LGA shoreline and processed it using ENVI maximum likelihood and change detection techniques. The classes invaded by ocean were not well revealed due to Landsat low resolution; nevertheless, between 1984 and 2012, ocean invaded about 1.39km2 of the vegetal class. Ocean downturns which may result to serious invasion in future were also detected. This 28years demonstration shows that Multi-temporal Landsat Images are useful for ocean – land invasion study, but increased spatial resolution may be needed for detecting more subtle changes.
Scholarly articles
Coastal , erosion , land , Landsat , temporal , Research Subject Categories::SOCIAL SCIENCES
Ayeni A. O., Cho, M.A. Kuton, M.P. and Chukwu,L.O. (2012). Could Ocean-Land Invasion be detected using Multi-temporal Images of Landsat? In: Matins O., Idowu O. A., Mbajiorgu C. C., Jimoh O. D. and Oluwasanya G. O. (eds), Hydrological for Disaster Management, Special Publication of the Nigerian Association of Hydrological Sciences, 2012: 315 – 326