Assessment of Land Use/Cover Change and Urban Expansion Using Remote Sensing and GIS: A Case Study in Phuentsholing Municipality, Chukha, Bhutan
International Journal of Energy and Environmental Science
Volume 2, Issue 6, November 2017, Pages: 127-135
Received: Oct. 19, 2017;
Accepted: Oct. 28, 2017;
Published: Dec. 11, 2017
Views 1978 Downloads 95
Chimi Chimi, Department of Civil Engineering and Architecture, College of Science and Technology, Royal University of Bhutan, Phuentsholing, Bhutan
Jigme Tenzin, Department of Civil Engineering, Jigme Namgyel Engineering College, Royal University of Bhutan, Dewathang, Bhutan
Tshering Cheki, Department of Civil Engineering and Architecture, College of Science and Technology, Royal University of Bhutan, Phuentsholing, Bhutan
The rapid phase of urbanization and infrastructure development in Bhutan has been observed recently. This leads to causing of decrease in vegetation cover and growth in urban sprawl undergoing rapid land use/land cover change (LULC). This paper attempts to analyze the temporal and spatial patterns of LULC change and detects the urbanization processes of Phuentsholing city over a period of three decades (1996-2016) using multi temporal remotely sensed data. For this, the satellite images of Landsat 5, 7 and 8 were used to assess the changes of vegetation cover, built form and water bodies. This study has found that urban built area was increased from 6.7% in 1996 to 17% in 2016 and similarly vegetation cover was declined from 48.4% in 1996 to 49.9% in 2016. This urban expansion causes loss of vegetation cover that hinders the country’s regulation of retaining 60% forest according to The Constitution of the Kingdom of Bhutan. These finding can provide city planners and decision makers with information about the past and current spatial dynamics of LULC change to investigate, plan and monitor the urban development and management of Phuentsholing municipality.
Assessment of Land Use/Cover Change and Urban Expansion Using Remote Sensing and GIS: A Case Study in Phuentsholing Municipality, Chukha, Bhutan, International Journal of Energy and Environmental Science.
Vol. 2, No. 6,
2017, pp. 127-135.
Alsaaideh, B., Hanbali, A. A. & Tateishi, R. (2011). Assessment of Land Use/Cover Change and Urban Expansion of the Central Part of Jordan Using Remote Sensing and GIS. Asian Journal of Geoinformatics, Vol. 11 (3).
Banko, G. (1998). A review of assessing the accuracy of classification of remotely sensed data and methods including remote sensing data in forest inventory. http://citeseerx.ist.psu.edu/viewdoc/dowmload?doi=10.1.1.200.7822&rep=rep1&type=pdf. Accessed 1october 2016.
Byrne G., Crapper P. & Mayo K. (1980). Monitoring Land-Cover Change by Principal Component Analysis of Multitemporal Landsat Data. Remote Sensing of Environment, 10, 175-184.
Campbell, J. B. (1987). Introduction to remote sensing. The Guilford Press.
Cheruto, C. M., K Kautil, M. K., Kisangau, D. P., & Kariuki, P. (2016). Assessment of Land Use and Land Cover Change Using GIS and Remote Sensing Techniques: A Case Study of Makueni County, Kenya, Journal of Remote Sensing & GIS, Vol 5, (4).
Congalton, R. G., & Green, K. (1999). Assessing the accuracy of remotely sensed data: Principles and practices (pp. 43-64). Boca Rotan, Florida’ Lewis Publishers.
Elvidge, C. D., Sutton, P. C., Wagner, T. W., et al. (2004). Urbanization. In G. Gutman, A. Janetos, Justice C., et al., (Eds.), Land change science: Observing, monitoring, and understanding trajectories of change on the earth’s surface (pp. 315-328). Dordrecht, Netherlands’ Kluwer Academic Publishers.
Esmail, M., Masria, A., & Negm, A. (2016). Monitoring Land Use/Land Cover Changes Around Damietta Promontory, Egypt, Using RS/GIS. Procedia Engineering 154 (2016) 936-942.
Khattak, M. S., Rehman, S., Shoukat, S., & Khan, A. M (2015). Analysis of Land Use Changes using Remote Sensing and GIS Techniques: A Case Study of District Peshawar-Pakistan. International Journal of Engineering Research & Technology. Vol (4) 10, 376-382.
Lillesand, T. M., & Kiefer, R. W. (1994). Remote sensing and image interpretation (4th ed.). New York: Wiley.
Lunetta, R. S., & Balogh, M. (1999). Application of multi-temporal Landsat 5 TM imagery for wetland identification. Photogrammetric Engineering and Remote Sensing, 65, 1303-1310.
Masria, A., Nadaoka, K., Negm, A. Iskander, M. & Carleton, A. (2015). Detection of Shoreline and Land Cover Changes around Rosetta Promontory, Egypt, Based on Remote Sensing Analysis, pp. 216-230.
Mohapatra, S., N. Pani, P, & Sharma, M. (2014). Rapid Urban Expansion and Its Implications on Geomorphology: A Remote Sensing and GIS Based Study. Geography Journal.
NSB (2016) National Statistical Bureau: Statistical Year book- 2016. accessed 20th august 2017.
Owojori A, Xie H (2005) Landsat Image-Based LULC Changes of San Antonio, Texas Using Advanced Atmospheric Correction and Object-Oriented Image Analysis Approaches. 5th International Symposium on Remote Sensing of Urban Areas, Tempe, USA.
Pabi O. (2007). Understanding land-use/cover change process for land and environmental resources use management policy in Ghana. Geo Journal.
PC (1999). Bhutan 2020: A vision for Peace, Prosperity and Happiness parts 1 and 2. Planning commission, Royal government of Bhutan, Thimphu, Bhutan.
Panda, M (2004). City Corporation, Phuentsholing: Ministry of Works & Human Settlements, Royal Government of Bhutan.
Sebastian M., Jayaraman V. & Chandrasekhar M. G. (1998). Facilities management using remote sensing data in a GIS environment. Acta Astronautica, 43 (9-10), 487-491.
Shalaby, A & Tateishi, R. (2007). Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the Northwestern coastal zone of Egypt. Applied Geography. 27, 28-41.
Stow, D. A (1999) Reducing the effects of misregistration on pixel-level change detection, Int. J. Remote Sens., vol. 20, no. 12, pp. 2477-2483.
T Co TKB (2008). The Constitution of the Kingdom of Bhutan. Page-12.
USGS (2015). Landsat 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor). http://lta.cr.usgs.gov/L8. Accessed on 13 January 2017.
USGS (2014). Landsat 8 History. http://landsat.usgs.gov/band_designation_landsat_satellite.php> Accessed on 13 May 2017.
USGS (n. d). Landsat Earth Explorer. http://eathexplorer.usgs.gov> Accessed on 12 December 2016.
Verbyla, D. (2013). Estimating Classification Accuracy using ArcGIS.www.youtube.com/watch?v=9dGuEQie7Y Accessed 12 Decementr 2016.
Weber C. and Puissant A. (2003). Urbanization pressure and modeling of urban growth: example of the Tunis Metropolitan Area. Remote Sensing of Environment, 86 (3), 341-352.
Wolter, P. T., Mladenoff, D. J., Host, G. E., G. E., & T. R. (1995). Improved forest classification in the Northern Lake States using multi-temporal Landsat imagery. Photogrammetric Engineering and Remote Sensing, 61, 1129-1143.
Xiao J., Shen Y., Ge J., Tateishi R., Tang C., Liang Y. & Huang Z. (2006). Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing. Landscape and Urban Planning, 75 (1-2), 69-80.
Yangchen, U, Thinley, U & Wallentin, G. (2015) Land Use Land Cover Changes in Bhutan: 2000-2013. Proceeding of the conference on Climate Change, Environment and Development in Bhutan. 37-46.
Yuan, F., Bauer, M. E., Heinert, N. J., & Holden, G. (2005). Multi-level land cover mapping of the Twin Cities (Minnesota) metropolitan area with multi-seasonal Landsat TM/ETM+data. Geocarto International, 20 (2), 5-14.