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Coastal areas include highly complex ecosystems that encompass many different and productive resources worldwide. Although having such great importance, the lack of basic knowledge concerning the marine habitat distribution and biodiversity along the Turkish shoreline is an undeniable reality. In this study, seagrass beds in the bays along the Eastern Aegean Sea coast were located and mapped. Traditionally, sea-truth data used for satellite-image and other analysis are collected through direct observations requiring scuba divers or by aquatic video-camera observation. This study included a combination of acoustic technology, video recording and interpretation, geomorphological, oceanographic, and sedimentological evaluation in order to make significant contributions of current technology. The classification of the evaluated Subbottom Profiler (SBP) records exhibited their high discrimination capacity between different sea-bed features, making them appropriate for ground distinction. Linking of the SBP data sets to the Side Scan Sonar (SSS) records (object-based analysis) provide to full coverage, high resolution benthic habitat maps. For this purpose, Side Scan Sonar, 3.5/10 kHz Subbottom Profiler data were collected to a range of 50 m water depth, the data was recorded for a total 1600 km 2 coastal area that consists of approximately a total 3000 km long and 1km wide grid system for Edremit, Çandarlı, Gülbahçe, Ildır, Güllük and Gökova Bays. In the study area, it was determined that the seagrasses are under danger where high human influence is located. Dense distribution of invasive macroalgae (Caulerpa cylindracea, Stypopodium schimperi) were seen at the southern and northern part of the study area subjected to human activities.

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In this study Multi-Sensor (Sentinel-1, Sentinel-2 and Landsat-8) based approach is used to investigate natural seepage and manmade oil pollution in the Caspian Sea along the coast of Bakü, Azerbaijan. The processing of the satellite images was carried out using the sentinel application platform (SNAP, 6.0), which is an open source common architecture and oil pollution for different dates was determined. The largest oil seepage was detected on January 19, 2018 that covered almost 465 square km. Sentinel-2 image was also processed by SNAP 6.0 and by using object-based image analysis (OBIA) the polluted areas were determined. ACOLITE software was used for processing however did not provide expected output. As a result of this study, it was determined that multisensor based satellite monitoring is an efficient approach for the collection, visualization and analysis of information on oil pollution in the marine environment.

Pollution risk assessment of heavy metals (Pb, Cr, Cu, Ni, Zn, As) in sediment samples from 68 locations in the Gulf of Edremit, western Turkey, was performed using single and complex indices of pollution assessment approaches. The pollution indices used in the sediment analyses included pollution load index(PLI), contamination factor(CF), contamination degree(Cdeg) for individual metals, geoaccumulation index (Igeo), enrichment factors(EF), toxic risk index(TRI), modified pollution index (MPI), frequency of adverse biological effects (TEL-PEL), percent incidence of biological effects (ERL-ERM), and total risk quotients (QTEL-QPEL). Results indicated a low degree of contamination for the entire surveyed area except moderate contamination factor for arsenic using single indices. Enrichment factors and geoaccumulation indices indicated moderate to significant enrichment and uncontaminated to moderately contaminated both for arsenic(As) and lead(Pb), respectively. According to the results of ecological risk assessment based on TELs and PELs, the adverse biological effects of heavy metals on aquatic organisms; are for As, Cr, Ni frequently, Cu and Pb occasionally and Zn rare. The TRI values displayed low to considerably toxic risk for the entire Gulf and calculated TRI results showed that arsenic accounted for most of the entire sediment toxicity. Transport patterns of sediment grain size trend analyses were correlated with the results of pollution assessment models. Transport trends are compatible with the sources of lithogenic, anthropogenic, mining activities and wastewater treatment/geothermal originated arsenic.