Open mining operations have brought number of environmental challenges, which may result in soil erosion, dust, noise, water pollution, and severe impacts on biodiversity. Determination of the mining activities and its surrounding environment is a major issue in sustainable resource management. Many remote sensing indices have been developed and widely applied as an effective tool to determine different land surface types. The main objective of this study was to determine quarry mines and its surroundings land use and land cover (LULC) categories in the selected study area of Istanbul using different remote sensing indices including Tasseled Cap Transformation (Brightness, Greenness and Wetness) and Normalized Difference Bareness Index (NDBa1s). In this study, an open mining area in the northern Black Sea coastal part of Istanbul was selected as study area. Freely available Landsat 8 OLI & TIRs image was used to determine quarries and land cover/ land use categories in the concerned area. By using original bands of Landsat 8 OLI, TCT components and NDBaI, three different data sets were created. Each image was then separately subjected to support vector machine classification and processed to identify and quantify LULC categories. The accuracy of classification results were evaluated in a comparitive manner using error matrix. Data set C had the highest overall accuracy and Kappa statistics that were calculated as 83.00 and 0.80, respectively.