CLASSIFICATION OF VEGETATION TYPES IN KSU RESEARCH AND APPLICATION FOREST IN KAHRAMANMARAS, TURKEY

During the last few decades, remote sensing and Geographic Information Systems (GIS) technologies have become increasingly important tools for mapping, inventorying, and monitoring forest resources around the world. Using remotely sensed aerial images or digitized aerial photographs and GIS techniques to organize and analyze significant amount of spatial data, it is now becoming possible to analyze the number of variables (tree species, size and density, volume and height, growth, and etc.) for ecological and economic management of forests. Large-scale satellite images with good details are widely used in digital image processing and classification. The main purpose of this paper was using automated image processing and classification methods based on a satellite imagery to identify vegetation types in KSU Research and Application Forest in Kahramanmaras, Turkey. KURZFASSUN