Determination of spreading spring greenhouses areas on different physiographical units with remote sensing and GIS techniques; a key study from elmali depression, Antalya, Turkey
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Abstract (EN)
Meeting the growing food need and sustainability is an economic and vital necessity of societies. Especially in the Mediterranean coast where intensive farming is carried out, extreme temperatures and high humidity experienced in summer months make the production in greenhouse areas impossible. This important problem has trended producers and investors to the highland areas where production can be made during the months in question. One of the places where uncontrolled and very fast spring cultivation activities has increased in recent years is the Elmalı district of Antalya. In Elmalı, which is chosen as the study area, it is aimed to determine temporal and spatial changes on three different physiographic units. Within the scope of the research, the old lake bases and alluvial fan physiological units were studied. In the Eskihisar region, Pansharped sattellite name and spatial resolution in 2009 and 2016 respectively, GeoEye-1 0,5m and WorldView-3 0,4m, in the Gölova-Çukurelma region with 0,6m GeoEye-1 satellite images with 0,5m and finally, in the Beyler region, 0.5m WorldView-2 and Spot-7 1,5m satellite images were used. As a result of the classification made with Maximum Likelihood technique which is one of the controlled classification techniques, the total greenhouse assets calculated from the raster data were compared with the total greenhouse assets calculated from the data obtained by the terrestrial measurements, the accuracy of the study was calculated. When the most recent dates and classification results are evaluated, physiographic units and greenhouse production areas are respectively 126,19 ha in the Eskihisar region on alluvial land, 104,41 ha in Gölova-Çukurelma area, which contains very old lake base and alluvial fan, and finally, 38.23 ha in the Beyler area on the land of the basement. When the percentage increase in greenhouse activities is evaluated as time dependent, the highest increase is in Gölova-Çukurelma region (%313,51), second in Eskihisar region (%166,27) and the lowest increase is in Beyler region (%61.35). When the accuracy rates of the study are examined, the highest accuracy of the year 2009 (%94.83) in the Eskihisar region, in 2016 (92.04), Gölova-Çukurlema 2008 (%89.33), the lowest accuracy in 2016 (%83.52) in the Beyler region in 2011 (%87,72) in 2016 (%83,95).
Author
Kadir Buyurgan
Institution
How to Cite
Kadir Buyurgan (Master Thesis). Determination of spreading spring greenhouses areas on different physiographical units with remote sensing and GIS techniques; a key study from elmali depression, Antalya, Turkey, 2019, Akdeniz University.
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