Analysis of chlorophyll-A distribution on the south-western coast of Istanbul during 2008-2010 using GIS

In this study, Istanbul, which is the most crowded city in Turkey, was selected as the study area and the chlorophyll-a distribution was monitored using GIS technologies and in situ measurements at the southwestern coast of the Istanbul metropolitan area, which would be expected to be influenced by nutrient run offs from the city. Five sampling stations located at the south- western coast of the city were selected for investigating the spatial and temporal chlorophyll-a distribution in the region. Monitoring stations were selected at locations that were either highly urbanized or heavily deteriorated. Sampling in these stations was carried out monthly between January 2008 and December 2010. The parameters of air and sea surface temperature were measured in the selected stations in situ. The chlorophyll-a measurements varied between 0.23 and 181.4 μg/l throughout the sampling period. The lowest value was measured in October 2008 as 0.23 μg/l at Station 1 and the highest value was measured in August 2010 as 181.4 μg/l at the Kucukcekmece Station. The significant station at Kucukcekmece Lagoon was selected in order to represent the lagoon ecosystem and its connection to the Marmara Sea via a narrow channel. Generally, the water exchange rate of the Kucukcekmece Lagoon is too small to describe it as an estuarine lagoon. Under these circumstances, the dynamics of the environmental parameters and the chlorophyll-a values in the lagoon would be expected to be considerably different from the other station. In this study, the developed GIS database contains basically two layers, the administrative boundaries of the related districts and the locations of the sampling stations. The chlorophyll-a concentrations that were measured at the Kucukcekmece station were different than those measured at other stations, just like the physical and chemical parameters of this station being different than those of other stations. These differences would easily be demonstrated using GIS as an important tool for the analysis and display of all kinds of temporally collected spatial data and their related attributes.