LAND USE AND LAND COVER CHANGES USING SPOT 5 PANSHARPEN IMAGES; A CASE STUDY IN AKDENIZ DISTRICT, MERSIN-TURKEY

Year 2019, Volume: 3 Issue: 1, 32 - 38, 01.01.2019

Cigdem Göksel , Filiz Bektaş Balçık

https://doi.org/10.31127/tuje.444685

Cited By: 2

Abstract

The main objective of the study is to quantify main changes in urban area of Akdeniz district of Mersin province using Pan sharpen SPOT 5 MS (with 3 bands) satellite images. In this study, land cover and land use maps of 2006 and, 2014 are produced using Maximum Likelihood supervised classification technique to detect the growth of urban area in the selected area. Preprocessing methods, including geometric and radiometric correction were performed. From to changes method was applied to determine the land cover/land use transformation in the region. An accuracy assessment was conducted using overall accuracy and Kappa statistics. Results show that maps obtained from images for 2006, and 2014 had an overall accuracy of 82.96%, and 84.00%, and a Kappa coefficient of 0.80, and 0.82, respectively. The results showed that between the selected years the district faced a huge transformation from agricultural fields and bare lands to artificial surfaces. Change detection between 2006 and 2014 shows that most of the agricultural fields (6295,1 ha) have been increased; moreover, artificial surfaces and green houses have also increased. The largest decrease has occurred for bare lands area of which approximately 3942,5 ha. According to the results, artificial surfaces was increased by 189 ha from 2006 to 2014 in Akdeniz District of Mersin.

Keywords

Land Use, Land Cover, Change Detection, SPOT, Remote Sensing

References

• Alphan, H. (2013). Bi-temporal analysis of landscape changes in the easternmost Mediterranean deltas using binary and clas- sified change information. Environmental Management, 51, 541–554.
• Alphan, H., & Celik, N. (2016). Monitoring changes in landscape pattern. Use of Ikonos and Quickbird images. Environmental Monitoring and Assessment, 188(81).
• Alphan, H. and Sonmez, F. (2015). Mapping availability of sea view for potential building development areas. Environmental Monitoring and Assessment, 187(7).
• Aspinall, R. J., & Hill, M. J. (2008). Land use change: science, policy, and management: CRC Press.
• Banister, D., Watson, S., & Wood, C. (1997). Sustainable Cities: Transport, Energy, and Urban Form. Environment and Planning B: Planning and Design, 24(1), 125-143, doi:10.1068/b240125.
• Bektas, F., & Goksel, C. (2005). Remote sensing and GIS integration for land-cover analysis: a case study: Bozcaada Island. Water Science and Technology, 51(11), 239–244.
• Bektaş Balçık, F (2010). Mapping And Monitoring Wetland Environment By Analysis of Different Satellite İmages And Field Spectroscopy, PhD Thesis, Istanbul Technical University
• Bektas Balcik F., Karakacan Kuzucu A. (2016) “Determination of Land Cover/Land Use Using SPOT 7 Data With Supervised Classification Methods”. GeoAdvances Workshop, 2016. Istanbul.
• Bozkaya, A. G., Bektas Balcik, F., Goksel, C., Dogru, A. O.,Ulugtekin, N. N., & Sozen, S. (2014). Satellitebased multitemporal change detection in Igneada flooded forests. Romanian Journal of Geography, 58(2), 161–168.
• Bozkaya, A. G., Bektas Balcik, F., Goksel, C., Esbah, H. (2015) Forecasting land-cover growth using remotely sensed data: a case study of the Igneada protection area in Turkey. Environmental Monitoring Assess, 187: 59
• Burak, S., Doğan, E. and Gazioğlu, C. (2004). Impact of urbanization and tourism on coastal environment. Ocean and Coastal Management, 47(9–10): 515–527.
• Cohen, J. (1960). A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 20(1), 37-46.
• Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37(1), 35-46.
• Sertel, E., Akay, S.S. (2015). High resolution mapping of urban areas using SPOT-5 images and ancillary data" International Journal of Environment and Geoinformatics (IJEGEO)., 2 (2), 63-76
• Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., Lambin, E. (2004) Digital change detection methods in ecosystem monitoring: A review International Journal of Remote Sensing, 25 (9), pp. 1565-1596.
• Dogru, A. O., Bektas Balcik, F., Goksel, C., & Ulugtekin, N. N. (2006). Monitoring Coastal Dunes By Using Remote Sensing And GIS Integration In North West Part Of Turkey: A Case Study Of Kilyos Dunes. Fresenius Environmental Bulletin, 9b, 15
• Elachi, C., & van Zyl, J. J. (2006). Introduction To The Physics and Techniques of Remote Sensing: Wiley.
• Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1), 185-201
• Fung, T., & Siu, W. (2000). Environmental quality and its changes, an analysis using NDVI. International Journal of Remote Sensing, 21(5), 1011–1024.
• Goksel, C., Balcik, F. B., Keskin, M., Celik, B., Cihan, C., Yagmur, N. (2016). Evaluation of Classification Methods for Detection of Greenhouses from Spot 5 Satellite Imagery. 6th International Conference on Cartography and GIS, Albena, Bulgaria, 13-17 June
• Hellawell, J. M. (1991). Development of a rationale for monitoring. In B. Goldsmith (Ed.), Monitoring for Conservation and Ecology (pp. 1-14). Dordrecht: Springer Netherlands.
• Jat, M. K., Garg, P. K., & Khare, D. (2008). Monitoring and modelling of urban sprawl using remote sensing and GIS techniques. International Journal of Applied Earth Observation and Geoinformation, 10(1), 26-43.
• Jensen, J. R. (2004). Digital change detection. Introductory digital image processing: A remote sensing perspective (pp. 467–494). New Jersey: Prentice-Hall
• Liu, J. G., & Mason, P. (2009). Essential Image Processing and GIS for Remote Sensing: Wiley.
• Lu, D., Mausel, P., Brondízio, E., Moran, E. (2004) Change detection techniques. International Journal of Remote Sensing, 25 (12), pp. 2365-2407.
• Mather, P. M. (2004). Computer Processing of Remotely-Sensed Images: An Introduction: Wiley.
• Report, (2016). Project of the Province Wide Research and Analytical Works for the Environmental Master Plan of Mersin. Mersin Municipality (Ed.). In Turkish.
• Richards, J. A., & Jia, X. (2006). Remote Sensing Digital Image Analysis: An Introduction: Springer Berlin Heidelberg.
• Sanlı F., Bektaş, F., & Göksel, C. (2008). Defining temporal spatial patterns of mega city Istanbul to see the impacts of increasing population. Environmental. Monitoring Assess. 146:267–275
• Serra, P., Ponsa, X., & Sauri, D. (2008). Land-cover and land-use change in a Mediterranean landscape: a spatial analysis of driving forces integrating biophysical and human factors. Applied Geography, 28, 189–209
• Turner, B. L. (1990). The Earth as Transformed by Human Action: Global and Regional Changes in the Biosphere Over the Past 300 Years: Cambridge University Press.
• Weng, Q. (2002). Land-use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. Journal of Environmental Management, 64, 273–284.
• Yagoub, M. M., Bizreh A. Al. (2014) Prediction of Land Cover Change Using Markov and Cellular Automata Models: Case of Al-Ain, UAE, 1992-2030. Journal of the Indian Society of Remote Sensing, Volume 42, Issue 3, pp 665–671
• Zhu, S. (1995). Based on the mixed-pixel image classification of remote sensing technology. Journal of the People's Liberation Army Institute of Surveying and Mapping, 12(4). pp. 276-278.