DETERMINATION OF VARIATIONS IN LAND COVER AND LAND USE BY REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS AROUND THE CITY OF SIVAS (TURKEY)

Abstract

Land use/cover data are significant and useful information source for the planners. Remote Sensing (RS) and Geographic Information Systems (GIS) are commonly used for obtaining this type of information. In this study, aerial photographs for the years 1973 and 2005 and Landsat TM/ETM+ satellite images for the years 1987 and 2002 have been used to determine land use/land cover variations for the city of Sivas and environs. Digitization processing with visual interpretation has been carried out based on the land cover boundaries on mosaicked aerial photographs. Concurrently supervised classification has been applied to the Landsat TM satellite images with the help of the maximum likelihood algorithm, and comparisons following advanced classification were used for the satellite images from both years. Four land use/cover classes, namely settlements, non-agricultural land, agricultural land and surface waters, have been recognized with the help of visual-interpretation-derived aerial photographs. Satellite images also have been grouped into eight different categories for land use planning: surface waters, natural vegetation, bare soil, settlement, agricultural land, forest land, rockies1, and rockies2. Land use/land cover variations of the study area have been determined for the years 1973, 1987, 2002 and 2005 with the help of RS and GIS techniques, and the development of settlements has been monitored. When land use/cover variations were analysed, it was determined that the city of Sivas has been developing mainly towards the north-east, south and south-west via encroachment upon agricultural land. Considering the settlements that are developing towards the Kizilirmak River with increasing population, it is concluded that this situation might constitute a threat to the Kizilirmak River and have a negative impact on natural resources. Information regarding these changes has contributed to a better understanding of spatiotemporal influences on the growth of Sivas.