Nadine Nassif^1*, Lena Abou Jaoude², Mhamad El Hage³, Cordula A. Robinson⁴

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¹ Affiliat Department Environmental and Natural Resources Department, Lebanese University, Dekwaneh, Lebanon.
² Department of Environment and Natural Resources, Lebanese University, Dekwaneh, Lebanon.
³ Department of Civil Engineering and Department of Geography (GISRS Lab.), Lebanese University, Tripoli, Lebanon.
⁴ College of Professional Studies, Northeastern University, Boston, MA, USA.
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Abstract: Marine pollution is a serious geoenvironmental problem affecting the Lebanese coast. It mainly affects the coastal zone adjacent to areas of dense population. To detect the sources of pollution along this zone, as well as to identify their characteristics, remote sensing data is used. Landsat 8 Operational Land Imager (OLI) satellite images, which have medium spatial resolution, are analyzed using ENVI 5.2 and ArcGIS 10.3.1 geospatial software for the years of 2014 and 2015. Different routines are applied to reveal anomalous features with the goal being to discriminate polluted water in the marine environment. Results showed anomalies in Akkar region. This might be due to the presence of basalts rocks, and geothermal heating, or the pollution of Oustowan river that flows into the sea. The results also showed that during the dry season, there is low movement of water causing a least extension of the anomalies. In contrary, during the wet season, rivers had an intense flow into the sea which caused an intense water movement and wide extension of anomalies on the coast. Permanently polluted coastal sites are evident in Tripoli, Kalamoun, Chekka, Batroun, Amchit, Jbeil, Jounieh, Nahr Beirut and Ouzai with the most presumed polluted months being in 2014 during April and November and in 2015 in April. The least extended pollution is during July 2014 and 2015. The length and width of each anomaly at each site shows that during the year of 2015; most of the anomalies are larger than in 2014.

Keywords: Geoenvironment, Remote Sensing, Landsat, Sea, Pollution

Cite this paper: Nassif, N. , Jaoude, L. , El Hage, M. and Robinson, C. (2016) Data Exploration and Reconnaissance to Identify Ocean Phenomena: A Guide for In Situ Data Collection. Journal of Water Resource and Protection, 8, 929-943. doi: 10.4236/jwarp.2016.810076.

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