Sains Malaysiana 48(11)(2019): 2307–2315

http://dx.doi.org/10.17576/jsm-2019-4811-02

 

Urban Expansion Analysis using Landsat Images in Penang, Malaysia

(Analisis Pengembangan Bandar menggunakan Imej Landsat di Pulau Pinang, Malaysia)

 

YI LIN TEW1, MOU LEONG TAN1*, NARIMAH SAMAT1 & XIAOYING YANG2

 

1Geography Section, School of Humanities, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia

 

2Department of Environmental Science and Engineering, Fudan University, No. 220 Handan Rd, Shanghai 200433, China

 

Received: 31 March 2019/Accepted: 15 August 2019

 

ABSTRACT

Urban expansion mapping is important in urban planning, land use and water resources management. The purpose of this study is to evaluate the spatio-temporal trends of urban expansion in Penang using three Landsat satellite images taken in 2004, 2011 and 2018. Maximum Likelihood was used to classify the land uses into urban, agricultural, water, and forest. Comparison of the classified images with time-series Google Earth images and field data collection resulting an accuracy up to 90%. The results showed that urban have been expanded around 5% from 2004 to 2018. Major urban development is mainly found in the eastern part of Penang island. Meanwhile, major development in the Penang mainland can be found in the middle and western regions. Due to the limited development land on the Penang Island, a rapid urban expansion can be found in the south-western part of the Penang mainland that near to the second bridge. In order to maintain the city and community sustainability in Penang, government needs to plan on balanced socio-economic growth for the near future.

 

Keywords: Change detection; land use and land cover change; maximum likelihood classifier; Penang; urban growth analysis

 

ABSTRAK

Pemetaan keluasan bandar adalah penting dalam perancangan bandar, pengurusan guna tanah dan sumber air. Kajian ini bertujuan untuk menilai corak perubahan ruang-masa kawasan bandar di Pulau Pinang dengan menggunakan tiga imej satelit Landsat yang diambil pada tahun 2004, 2011 dan 2018. Kaedah kebolehjadian maksimum telah diguna pakai untuk mengelaskan jenis guna tanah kepada bandar, pertanian, air dan hutan. Perbandingan antara hasil pengelasan imej dengan imej siri masa Google Earth dan kerja lapangan menunjukkan ketepatan hasil kajian ini mencapai 90%. Keputusan menunjukkan kawasan bandar telah bertambah 5% dari 2004 hingga 2018. Perkembangan pesat di bahagian Pulau tertumpu di bahagian timur. Manakala perkembangan utama di tanah besar Pulau Pinang boleh didapati di bahagian timur dan selatan. Disebabkan kekurangan tanah pembangunan di bahagian pulau, kawasan di sebelah barat daya tanah besar Pulau Pinang yang berhampiran dengan jambatan kedua telah mengalami perkembangan yang pesat. Oleh itu, kerajaan perlu mengambil tindakan dalam pengimbangan perkembangan sosio-ekonomi selaras dengan perkembangan bandar di negeri Pulau Pinang demi kelestarian bandar dan komuniti pada masa depan.

 

Kata kunci: Analisis pengembangan bandar; klasifikasi kebolehjadian maksimum; pengesanan perubahan; perubahan guna tanah; Pulau Pinang

REFERENCES

Ahmad, M.S., Fahmi, M.R., Rahim, M.A. & Ibrahim, N. 2016. Kesan gabungan aktiviti guna tanah dan perubahan musim terhadap kualiti sumber air: Kajian kes di terusan Utara, Kedah. Sains Malaysiana 45(12): 1857-1867.

An, Y., Tsou, J.Y., Wong, K., Zhang, Y., Liu, D. & Li, Y. 2018. Detecting land use changes in a rapidly developing city during 1990-2017 using satellite imagery: A case study in Hangzhou urban area, China. Sustainability 10(9): 3303.

Asnawi, N.H. & Lam, K.C. 2016. Analisis perubahan guna tanah dan litupan bumi di Gombak, Selangor menggunakan data penderiaan Jauh. Sains Malaysiana 45(12): 1869-1877.

Boakye, E., Odai, S.N., Adjei, K.A. & Amor, F.O. 2008. Landsat images for assessment of the impact of land use and land cover changes on the Barekese Catchment in Ghana. European Journal of Scientific Research 21(4): 617-626.

Chander, G., Markham, B.L. & Helder, D.L. 2009. Summary of current radiometric calibration coefficints for Landsat MSS, TM, EM+, and EO-1 ALI sensors. Remote Sensing of Environment 113: 893-903.

Chen, L., Ren, C., Zhang, B., Wang, Z. & Liu, M. 2018. Quantifying urban land sprawl and its driving forces in Northeast China from 1990 to 2015. Sustainability 10(1): 188.

Chen, S. & Rao, P. 2008. Land degradation monitoring using multi-temporal Landsat TM/ETM data in a transition zone between grassland and cropland of northeast China. International Journal of Remote Sensing 29(7): 2055-2073.

Cheruto, M.C., Kauti, M.K., Klsangau, P.D. & Katuki, 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 5(4): 175.

Gao, J. & Liu, Y. 2010. Determination of land degradation causes in Tongyu County, Northeast China via land cover change detection. International Journal of Applied Earth Observation and Geoinformation 12: 9-16.

Geyman, A. & Baz, I. 2007. Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area. Environment Monitoring Assessment 136(3): 449-459.

Gounaridis, D., Symeonakis, E., Chorianopoulos, I. & Koukoulas, S. 2018. Incorporating density in spatiotemporal land use/ cover change patterns: The case of Attica, Greece. Remote Sensing 10(7): 1034.

Hasan, H.B., Radi, N.F.B.A. & Kassim, S.B. 2012. Modeling of extreme temperature using Generalized Extreme Value (GEV) distribution: A case study of Penang. Proceedings of the World Congress on Engineering, July 4 - 6, 2012, London, U.K. Volume I.

Hassan, M.M. & Southworth, J. 2017. Analyzing land cover change and urban growth trajectories of the Mega-Urban Region of Dhaka using remotely sensed data and an ensemble classifier. Sustainability 10(10): 24.

Hu, Y., Kong, X., Zheng, Ji., Sun, J., Wang, L. & Min, M. 2018. Urban expansion and farmland loss in Beijing during 1980- 2015. Sustainability 10(11): 3927.

Jia, Z., Ma, B., Zhang, J. & Zeng, W. 2018. Simulating spatial-temporal changes of land-use based on ecological redline restrictions and landscape driving factors: A case study in Beijing. Sustainability 10(4): 1299.

Kharas, H. 2010. The Unprecedented Expansion of the Global Middle Class. Washington: Global Economy & Development at Brookings.

Khoo, N. 2016. Batu Kawan’s future potential. EdgeProp Smarter property seach. https://www.edgeprop.my/content/1000715/ batu-kawan%E2%80%99s-future-potential#

Landis, J.R. & Koch, G.G. 1977. A One-way components of variance model for categorial data. Biometrics 33(4): 671- 679.

Mahiny, A.S. & Keith, C. 2012. Guiding SLEUTH land-use/ land-cover change modeling using multicriteria evaluation: Towards dynamic sustainable land-use planning. Environment and Planning B Planning and Design 39: 21. https://doi. org/10.1068/b37092.

Mandeep, J.S. & Hassan, S.I.S. 2008. Cloud attenuation for satellite applications over equatorial climate. IEEE Antennas and Wireless Propagation Letters 7: 152-154.

Masum, K.M., Mansor, A., Sah, S.A.M. & Lim, H.S. 2017. Effect of differential forest management on land-use change (LUC) in a tropical hill forest of Malaysia. Journal of Environmental Management 200: 468-474.

Ong, K.M. & Tan, B.T.N. 2017. Penang’s Economy is Healthy and Strong, with Incomes Rising and Inequality Decreasing. Penang Institute Issues November 2017.

Penang State Government. 2018. Penang 2030: A Family- Focused Green and Smart State to Inspire the Nation. https:// www.penang.gov.my/kenyataan-akhbar/360297-penang- 2030-a-family-focused-green-and-smart-state-to-inspire-the-nation.

Rimal, B., Zhang, L., Stork, N., Sloan, S. & Rijal, S. 2018. Urban expansion occured at the expense of agricultural lands in the Tarai Region of Nepal from 1989 to 2016. Sustainability 10: 1341.

Rozenstein, O. & Karnieli, A. 2011. Comparison of methods for land-use classification incorporating remote sensing and GIS inputs. Applied Geography 31(2): 533-544.

Samat, N., Ghazali, S., Hasni, R. & Elhadary, Y. 2014. Urban expansion and its impact on local communities: A case study of Seberang Perai, Penang, Malaysia. Social Science & Humanities 2(22): 349-367.

Su, S., Sun, Y., Lei, C., Weng, M. & Cai, Z. 2017. Reorienting paradoxial land use policies towards coherence: A self-adaptive ensemble learning geo-simulation of tea expansion under different scenarios in subtropical China. Land Use Policy 67(11): 0624-8377.

Tan, K.C., Lim, H.S., MatJafri, M.Z. & Abdullah, K. 2010. Landsat data to evaluate urban expansionand determine land use/land cover changes in Penang Island, Malaysia. Environmental Earth Sciences 60(7): 1509-1521.

Tan, M.L., Samat, N., Chan, N.W., Lee, A.J. & Li, C. 2019. Analysis of precipitation and temperature extremes over the Muda River Basin, Malaysia. Water 11(2): 283.

Tong, S., Dong, Z., Zhang, J., Bao, Y., Guna, A. & Bao, Y. 2018. Spatiotemporal variations of land use/cover changes in Inner Mongolia (China) during 1980-2015. Sustainability 10: 4730.

Yang, F. 2009. If ‘Smart’ is ‘Sustainable’? An analysis of Smart Growth Policies and its successful practices. Graduate Theses and Dissertations. Iowa: Iowa State University (Unpublished).

Zhang, Y., Wang, P., Wang, T., Cai, C., Li, Z. & Teng, M. 2018. scenarios simulation of spatio-temporal land use changes for exploring sustainable management strategies. Sustainability 10: 1013.

 

*Corresponding author; email: mouleong@usm.my

 

 

 

 

 

previous