The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-4/W5-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W5-2021, 373–378, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-373-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W5-2021, 373–378, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-373-2021

  23 Dec 2021

23 Dec 2021

INVESTIGATION OF TEMPORAL CHANGE OF LAND USE IN ELMALI BASIN USING REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS

H. Menteşe1 and A. Eymen2 H. Menteşe and A. Eymen
  • 1Graduate School of Natural and Applied Sciences, Geomatic Engineering, Erciyes University, Kayseri, Turkey
  • 2Engineering Faculty, Geomatic Engineering, Erciyes University, Kayseri, Turkey

Keywords: Land Use, Elmalı Basin, Geographic Information Systems, Remote Sensing

Abstract. The sustainable use of water and soil, which are indispensable for living things, is closely related to the concept of land use. While land use is becoming gradually modern as a necessity of the age, urbanization and industrialization are also gaining great importance. So much so that, in Turkey, where agriculture-based economy was emphasized until the 1980s, interest in exports of industrial products has increased in recent years and industrial investments especially in the Marmara region have increased considerably. This situation has increased job opportunities due to the industrialization developing in the region and has led to an increase in the population in parallel. The structure process has accelerated in order to meet the needs of the increasing population.

Basin areas, which contain a wide variety of classes, are among the regions that are highly affected by these changes. Within the scope of the study, Elmalı Basin, which is used to supply potable and utility water to the province of Istanbul, was chosen as the study area. Within the scope of the research, the temporal change of the land use in Elmalı Basin has been investigated by using Landsat-8 satellite with a spatial resolution of 30 meters for the years 2013, 2015, 2018 and 2020 taking advantage of Geographical Information Systems (GIS) and Remote Sensing (RS) technologies. Classification was made with support vector machines, one of the controlled classification methods on satellite images, and the changes in land use were evaluated by comparing the images of working years.