Product Classification by Using Remote Sensing (RS) and Geographic Information Systems (GIS) Techniques in Kahramanmaraş Province Kartalkaya Left Bank Water
2022
Ispi̇r, Mehmet Ali | Aybek, Ali
The aim of the study is to classify the most grown crops in Kahramanmaraş province Kartalkaya Left Bank Water Users Association’fields in 2014 using remote sensing (UA) and geographic information systems (GIS) techniques. The product patterns discussed in the study were made in the form of uncontrolled and controlled classification using Landsat, Spot-5 and Spot-6 satellite images. In addition, the soil in the research area was checked with the manufacturer's declarations received from Kartalkaya Left Bank Water Users Association and District Agriculture Directorate, and corn-sunflower, pasture, cereal, garlic, empty fields and non-agricultural areas were determined on the basis of parcels with controlled classification. As a result of the evaluation made over 150 points using the error matrix, the general classification accuracy was obtained from Landsat-8's 92nd day and 172nd day satellite images of 82% and 91%, while the general kappa statistics were determined as 72% and 86%, respectively.
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Este registro bibliográfico ha sido proporcionado por Ministry of Agriculture and Forestry, Department of Training and Publication, National AGRIS Center (Türkiye)