A GIS-based technique analysis of land use and land cover change detection in taluka Mirpur Mathelo: A case study in district Ghotki, Pakistan

Land use and land cover changes at the regional scale are necessary for a wide range of uses, including land planning, global warming, erosion, and landslide, etc. In this study, Land use and land cover change detection were studied by using remote sensing and GIS in taluka Mirpur Mathelo, Ghotki. For this purpose, ArcGIS 10.3 software was used. Firstly, supervised classification performance was applied to Landsat imageries which were acquired in 2013-2020. Image classification of six bands of Landsat imageries was carried out via a maximum likelihood classification process with the help of ground trothing data and signature file for both images 2013-2020 year. The second part focused on the land use and land cover change detection was evaluated with overlapping of the images. The results of the study indicated that severe land use and land cover change detection has occurred in the area during 2013-2020. The total relative change in the settlement is 2439.45 ha (1.94%) during the years. 592.38 ha (0.47%) changed in the vegetation cover. A total change of 3.16 ha (3.16 %) in the sand area. While barren land/plain -5094.63 ha (-4.06%) changed during the years. -1906.2 ha (-1.52%) shortage in the water body. It has been seen that decrease in barren land/plain and waterbody which has been converted into more in the sand and some portion in agriculture.

Keywords:

Change Detection, GIS, Landsat imagery, Land use land cover Mirpur Mathelo, Remote sensing,

PDF

___

1. Weng, Q., A remote sensing-GIS evaluation of urban expansion and its impacts on the temperature in the Zhujiang Delta, China. Int J Remote Sens, 2001. 22(10): p. 1999-2014.
2. Asselman, N.E.M. Middelkoop, H. Floodplain sedimentation quantities, Patterns and processes. Earth Surf. Process. Landf, 1995. 20(6): p. 481-499.
3. Reveshty M.A., The assessment and predicting of land use changes to the urban area using multi-temporal satellite imagery and GIS: A case study on Zanjan, Iran (1984-2011). Journal of Geographic Information System, 2011. 3(4): p. 298-305.
4. Wang, Y., Zhang, X., A dynamic modelling approach to simulating socio-economic effects on landscape changes. Ecological Modelling, 2001. 140(1-2): p. 141-162.
5. Harshika, A. K. and Sopan, I., Land use land cover classification and change detection using high-resolution temporal satellite data. Journal of Environment, 2012. 1(4): p. 146-152.
6. Mas, J.F., Monitoring land-cover changes: Comparison of change detection techniques. Int. J. Remote Sensing, 1999. 20: p. 139-152.
7. Shi, H., Yu, K., Feng, Y., Dong, X., Zhao, H. and Deng, X., RS and GIS-based analysis of landscape pattern changes in Urban-Rural Ecotone: A case study of Daiyue District, Tai'an City, China. Journal of Landscape Research, 2012. 4(9): p. 20-23.
8. Efrem, G., Landuse, and land cover dynamics and rural livelihood perspective in the semi-arid areas of Central Rift Valley of Ethiopia. Faculty of Forest Sciences, Department of Forest Resource Management Umea. Sweden: Swedish University of Agricultural Sciences. Doctoral Disseration, 2010.
9. Yeh, A.G.O. and Li, X., Principle component analysis of stacked multi-temporal images for the monitoring of rapid Urban expansion in the Pearl River. Int. J. Remote Sensing, 1998. 19(8): p. 1501-1518.
10. Lu, D., Mausel, P. and Brondizio, E., Change detection techniques. Int. J. Remote Sens., 2004. 25(12): p. 2365-2407.
11. Reis, S., Analyzing land use/land cover changes using remote sensing and GIS in Rize, North-East Turkey. Sensors, 2008. 8(10): p. 6188-6202.
12. Pervez, W., Uddin, V., Khan, S.A. and Khan. J.A., Satellite-based land use mapping: Comparative analysis of Landsat-8, Advanced Land Imager, and big data Hyperion imagery. J. Appl Remote Sens, 2016. 10(2): 026004.
13. PBS (2017). Blockwise Provisional Summary results of the 6th Population and Housing Census. Pakistan Bureau of Statistics. [cited 2020 20 December]; Available from: http://www.pbscensus.gov.pk.
14. Shah, S.A. and Siyal, A.A., GIS-based approach estimation of area under Wheat and other major Rabi crops in district Ghotki and corresponding irrigation water requirement. ACTA Scientific Agriculture, 2019. 3(12): p. 59-70.
15. Mundia, C.N. and Aniya, M., Analysis of land use/cover changes and urban expansion of Nairobi city using remote sensing and GIS. Int. J. Remote Sensing, 2005. 26: p. 2831-2849.
16. Dibs, Hayder., Maximum likelihood for land-use/land-cover mapping and change detection using Landsat satellite images: A case study “South of Johor”. International Journal of Computational Engineering Research, 2013. 3(6): p. 26-33.
17. Han, J., Hayashi, Y., Cao, X., and Imura, H., Evaluating land-use change in rapidly urbanizing China: A case study of Shanghai. Journal of Urban Planning and Development, 2009. 135(4): p. 166-171.
18. Myneni, R.B., A large carbon sink in the woody biomass of northern forests. Proceeding of the National Academy of Sciences of the United States of America. 2001. 98(26): p. 14784-14789.
19. Chen, D., and Brutsaert, W., Satellite sensed distribution and spatial patterns of vegetation parameters over a tallgrass prairie, Journal of the Atmospheric Sciences. 1998. 55(7): p. 1225-1238.
20. Weng, Q., & Lo, C.P., Spatial analysis of urban growth impacts on vegetative greenness with Landsat TM data. Geocarto International, 2001. 16(4): p. 17-25.

International Advanced Researches and Engineering Journal-Cover

Yayın Aralığı: Yılda 3 Sayı
Başlangıç: 2017
Yayıncı: Dr. Ceyhun YILMAZ

Arşiv