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Coastal erosion may be caused by natural causes as well as human factors. Karasu town of the city of Sakarya in Turkey which is a touristic region on the Black Sea coast has been experienced a drastic coastal erosion. In recent years, this erosion reached the threatening dimensions for the structures in the settlement. According to the temporal analyses of Landsat satellite images, the maximum erosion on the coastline was detected 100 m between 1987-2013. The results of the study show that the harbour construct on the Karasu coast has the major impact on this event. The secondary factor is that the amount of the sediment carried by the Sakarya River was decreased in time due to different reasons. To prevent the coastal erosion, a series of offshore breakwaters were planned after the failed application of groins on the coastline. In this study, temporal changes of the coastline are investigated by the Landsat satellite data and land surveys, possible reasons of the erosion are discussed and the solutions are proposed regarding the coastal structures. [ABSTRACT FROM AUTHOR]

Soil erosion is one of the most important environmental problems. In the case of small scale areas where soil properties and climate have relatively uniform characteristics, vegetation cover and topography (i.e. ground slope) are the main factors that affect the amount of soil erosion. Lack of vegetation cover on bare soil areas, including forest road side slopes, especially in mountainous regions with steep slopes, may significantly increase the erosion rate. Determining and classifying erosion risks in such areas can help preventing environmental impacts. In this study, remotely sensed data and elevation data were used to extract and classify bare soil erosion risk areas for a study area selected from Hatila Valley Natural Protected Area in northeastern Turkey. High resolution IKONOS imagery was used to apply land use classification in ERDAS Imagine 9.0. To generate erosion risk map of the bare soil areas, classified image was superimposed on top of slope map, generated based on a Digital Elevation Model (DEM) in ArcGIS 9.2. The results indicated that 1.43, 5.85, 34.62, 53.16, and 4.94% of the bare soil areas in the study area were under very low, low, medium, high, and very high erosion risks, respectively. The overall classification accuracy of 82.5% indicated the potential of the proposed methodology. [ABSTRACT FROM AUTHOR]

The objective of this research was to explore an accurate and fast way of estimating chlorophyll-a amount, a water quality parameter (WQP), using IKONOS satellite sensor image and in situ measurements. Since the in situ data of WQPs are limited with the number of sampling locations, deriving a correlation between these measurements and remotely sensed image allows synoptic estimates of the related parameter over large areas even if the areas are in remote and inaccessible locations. In this study, simultaneously collected satellite image data and in situ measurements of chlorophyll-a were correlated using multivariate regression model. Different experiments were designed by changing the numbers and distributions of in situ measurements. Regression coefficients of each design and differences between model-derived data and in situ measurements were calculated to find out the optimum design to produce chlorophyll-a map of study region. Results illustrated that both the number and distribution of in situ measurements have impact on regression analysis, therefore should be selected attentively. Also, it is found that IKONOS imagery is an efficient and effective source to derive chlorophyll-a map of the large areas using limited number of ground measurements. [ABSTRACT FROM AUTHOR]

The article presents a study of the four sandy beaches located on the western part of the Turkish Black Sea coast to determine the characteristics of sand. Remotely sensed data taken simultaneously were used and field studies were conducted. In measuring the reflectance values in the beaches, a hand spectroradiometer was used. The samples of the sand were further sieved in the laboratory to obtain the grain size distribution. The spectral reflectance measurements of the beaches and the grain size distributions were compared with the classified IKONOS satellite images that was taken simultaneously with the field survey.