Commenced in January 2007
Paper Count: 31181
Determination of Potential Agricultural Lands Using Landsat 8 OLI Images and GIS: Case Study of Gokceada (Imroz) Turkey
Abstract:In present study, it was aimed to determine potential agricultural lands (PALs) in Gokceada (Imroz) Island of Canakkale province, Turkey. Seven-band Landsat 8 OLI images acquired on July 12 and August 13, 2013, and their 14-band combination image were used to identify current Land Use Land Cover (LULC) status. Principal Component Analysis (PCA) was applied to three Landsat datasets in order to reduce the correlation between the bands. A total of six Original and PCA images were classified using supervised classification method to obtain the LULC maps including 6 main classes (“Forest”, “Agriculture”, “Water Surface”, “Residential Area- Bare Soil”, “Reforestation” and “Other”). Accuracy assessment was performed by checking the accuracy of 120 randomized points for each LULC maps. The best overall accuracy and Kappa statistic values (90.83%, 0.8791% respectively) were found for PCA images which were generated from 14-bands combined images called 3- B/JA. Digital Elevation Model (DEM) with 15 m spatial resolution (ASTER) was used to consider topographical characteristics. Soil properties were obtained by digitizing 1:25000 scaled soil maps of Rural Services Directorate General. Potential Agricultural Lands (PALs) were determined using Geographic information Systems (GIS). Procedure was applied considering that “Other” class of LULC map may be used for agricultural purposes in the future properties. Overlaying analysis was conducted using Slope (S), Land Use Capability Class (LUCC), Other Soil Properties (OSP) and Land Use Capability Sub-Class (SUBC) properties. A total of 901.62 ha areas within “Other” class (15798.2 ha) of LULC map were determined as PALs. These lands were ranked as “Very Suitable”, “Suitable”, “Moderate Suitable” and “Low Suitable”. It was determined that the 8.03 ha were classified as “Very Suitable” while 18.59 ha as suitable and 11.44 ha as “Moderate Suitable” for PALs. In addition, 756.56 ha were found to be “Low Suitable”. The results obtained from this preliminary study can serve as basis for further studies.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107363Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2263
 K. Kasturirangan, “Remote sensing in India – Present scenario and future thrust”, Journal of Indian Society of Remote Sensing, vol. 23, pp. 1-6, 1995.
 H. Akıncı, A. Y. Ozalp, and B. Turgut, B., “Agricultural land Suitability analysis using GIS and AHP technique”, Computers and Electronics in Agriculture, vol. 97, pp. 71-82, 2013.
 M. G. Collins, F. R. Steiner, and M. J. Rushman, “Land-use suitability analysis in United States: Historical development and promising technological achievements”, Environmental Management, vol. 28, no. 5, pp. 611-621, 2001.
 J. Malczewski, “GIS-based land-use suitability analysis: A critical overview”, Progress in Planning, vol.62, pp. 3-65, 2004.
 S. Bandyopadhyay, R. K. Jaiswal, S. Hedge, and V. Jayaraman, “Assessment of land suitability potentials for agriculture using remote sensing and GIS based approach”, International Journal of Remote Sensing, vol. 30, no. 4, pp. 879-895, 2009.
 J. M. C. Pereira, and L. Duckstein, “A multiple criteria desicion-making approach to GIS-based land suitability evaluation”, International Journal of Geographical Information Systems, vol. 7, pp. 407-424, 1993.
 G. F. Bonham-Carter, Geographic Information Systems for Geoscientists: Modelling with GIS. New York: Pergamon Press, 1994.
 R. Store, and J. Kangas, “Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modelling”, Landscape and Urban Planning, vol. 55, pp. 79-93, 2001.
 S., Kalogirou, “Expert systems and GIS: An application of land suitability evaluation”, Computers, Environment and Urban Systems, vol. 26, pp. 89-112, 2002.
 D. Kurtener, H. A. Torbert, and E. Krueger, “Evaluation of agricultural land suitability: Application of fuzzy indicators”, Computational Science and Its Applications – ICCSA Lecture Notes in Computer Science, vol. 5072, pp. 475-490, 2008.
 H. R. Yurtseven, and N. Karakas, “Creating a sustainable gastronomic destination: The case of Cittaslow Gokceada-Turkey”, American International Journal of Contemporary Research, vol. 3, no. 3, pp. 91- 100, 2013.
 R. G. Congalton, and Green, K.. 1999. Assessing The Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton: Lewis Publishers, 1999.
 T. Cengiz, C. Akbulak, H. Özcan, and H. Baytekin H., “Gokceada’ da optimal arazi kullanımının belirlenmesi”, Tarım Bilimleri Dergisi, vol. 19, pp. 148-162, 2013.