Quantitative Assessment of Remotely Sensed Data for Landcover Change and Environmental Management
Innocent E. BELLO(1*), Momoh L. RILWANI(2)
(1) 
(2) 
(*) Corresponding Author
Abstract
Abstract This paper examines the relevance and application of quantitative techniques in geographic study with emphasis on landcover change and environmental management in a typical urban city of Warri and its environs in Nigeria. It uses an experimental study that adopts Principal Component Analysis (PCA) and Accuracy Assessment in reducing data dimensions and enhancing image visualization for onward classification into landcover classes using 1987 TM, 2002 ETM+ and ETM+ 2011. The 2011 ETM+ was later excluded due to scan line and cloud cover errors. The PCA results show that 1987 Bands of 145 has variance of 834.71 (88.09% of total components) while the 2002 Bands of 147 has variance of 1287.21 (85.344% of total components). Supervised classification results show overall accuracy of 96.19% (for 1987) and 96.30% (for 2002) respectively. The study reveals that there was increase in urban landcover (17.2% to 34.93%) and swamp (10.11% to 11.61%). Correspondingly, light vegetation and thick vegetation decreased from 41.76% to 27.38% and 26.31% to 22.36% while water also reduced from 4.63% to 3.73%. The study indicates a higher demand for urban settlement which requires landuse control to avoid urban blight and environmental decay.
Abstrak Makalah ini membahas relevansi dan penerapan teknik kuantitatif dalam penelitian geografis dengan penekanan pada perubahan tutupan lahan dan pengelolaan lingkungan di kota urban khas Warri dan sekitarnya di Nigeria. Menggunakan studi eksperimental yang mengadopsi Principal Component Analysis (PCA) dan Penilaian Akurasi dalam mengurangi dimensi data dan meningkatkan visualisasi gambar untuk seterusnya klasifikasi ke dalam kelas tutupan lahan menggunakan 1987 TM 2002 ETM + dan ETM + 2011. 2011 ETM + kemudian dikeluarkan karena garis scan dan kesalahan awan. Hasil PCA menunjukkan bahwa 1.987 Bands dari 145 memiliki varians dari 834,71 (88,09% dari total komponen) sedangkan 2002 Bands dari 147 memiliki varians dari 1.287,21 (85,344% dari total komponen). Hasil klasifikasi diawasi menunjukkan akurasi keseluruhan masing-masing 96,19% (untuk 1987) dan 96,30% (tahun 2002). Penelitian ini mengungkapkan bahwa ada peningkatan tutupan lahan perkotaan (17,2% menjadi 34,93%) dan rawa (10.11% menjadi 11,61%). Sejalan dengan itu, vegetasi ringan dan vegetasi tebal menurun dari 41,76% menjadi 27,38% dan 26,31% untuk 22,36% sementara air juga berkurang dari 4,63% menjadi 3,73%. Studi ini menunjukkan permintaan yang lebih tinggi untuk pemukiman perkotaan yang membutuhkan kontrol penggunaan lahan untuk menghindari hawar perkotaan dan pembusukan lingkungan.
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Akinbode, A. (1996), Research Methods in Geography. Ekpoma, Edo State University Publishing House.
Balsley, H.L. (1970), Quantitative Research Methods for Business and Economics. New York, Random House.
Bäring, L. (1988), Regionalization of Daily Rainfall in Kenya by Means of Common Factor Analysis. Inernational Journal Climatology. 8, 371-389. http://dx.doi.org/10.1002/joc.3370080405
Bedi, H.S., and Bindra, M.M.S. (1980), Principal Components of Monsoon Rainfall. Tellus, 32, 296-298. http://dx.doi.org/10.1111/j.2153-3490.1980.tb00956.x
Berry, B.J.L. (1958), A Note Concerning Methods of Classification. Annals of Association of America Geographers, 48(3): 300-303
Cassell, C. and Symon, G. (1994), Qualitative research in work contexts. In C. Cassell, & G. Symon (Eds.), Qualitative methods in Organizational Research (pp. 1-13). Thousand Oaks, CA, Sage Publications.
Das, R.P. (na). Principal Component Analysis in Multispectral Satellite Images. (Online): http://ficta.in/attachments/article/55/18%20PRINCIPAL%20COMPONENT%20ANALYSIS%20IN%20MULTISPECTRAL%20SATELLITE%20IMAGES.pdf, accessed July 19, 2015.
Daultrey, S. (1976), Principal Component Analysis. Norwich Great Britain. Geo. Abstracts Ltd.
Feranec, J., Otahel, J. and Pravda J. (1998), CORINE Land Cover Tourist Map of Slovakia. ITC Journal, 1: 25-30.
Fowdur, S.C., Vir Rughooputh, S.D., Cheeneebash, J., Booghanon, R. and Gopaul, A. (2014). Rainfall Analysis over Maurisius Using Principal Component Analysis.
Environmental Management & Sustainable Development, 3(2): 94-108.
Harris, R., Fitzpatrick, K., Souch, C., Brunsdon, C., Jarvis, C., Keylock, C., Orford, S., Singleton, A. and Tate, N. (2013). Quantitative Methods in Geography: Making the Connections between Schools, Universities and Employers. London, Royal Geographical Society (with IBG).
Helmy, A.K. and El-Taweel, G.S. (2009), Authentication Scheme Based on Principal Component Analysis for Satellite Images. International Journal of Signal Processing, Image Processing and Pattern Recognition. 2(3), 1 – 10.
Hotelling, H. (1933). Analysis of a Complex of Statistical Variables into Principal Components. Journal of Educational Psychology. 24, 417-441 and 498–520.
Ibe, P.O; Alagbe, A.O and Egharevha, E. (2012), Geospatial Mapping of Vulnerable areas to Flood Hazard and Risk in Warri Metropolis, Warri South Local Government Area, Delta State, Nigeria in: B. Ayeni and O. Fabiyi (eds.) Geospatial Technologies and Digital Cartography for National Securty, Tourism and Disaster Management. Proceedings of Joint Conference of GEOSON/NCA: 19-21 November, 2012. Pp., 197-212. RECTAS, OAU Campus, Ile-Ife, Osun State, Nigeria. Benin City, Mindex Press Limited.
Janos, V. (2009), Applied GIS – Satellite Image Processing. Miskolci Egyetem Földtudományi Kar, (Online): http://www.tankonyvtar.hu/hu/tartalom/tamop425/0033_SCORM_MFGGT218-EN/sco_01_02.htm, accessed July 28, 2015.
Jolliffe, I.T. (2002), Principal Component Analysis, Series: Springer Series in Statistics, 2nd ed., Springer, NY, XXIX, 487 p. 28 illus. ISBN 978-0-387-95442-4
Kealey, D.J. and Protheroe, D.R. (1996). The Effectiveness of Cross-cultural Training for Expatriates: An assessment of the Literature on the Issue. International Journal of Intercultural Relations. 20(2), 141-165.
Kumar, M. (na), Digital Image Processing. Satellite Remote Sensing & GIS Application in Agricultural Meteorology, Pp. 81 – 102. (Online): Accessed July 23, 2015, retrieved from http://www.wamis.org/agm/pubs/agm8/Paper-5.pdf
Mas, J.F. (1999), Monitoring Land-Cover Changes: A Comparison of Change Detection Techniques. International Journal of Remote Sensing. 20(1), 139–152
Matveev, A.V. (2002), The Advantages Of Employing Quantitative And Qualitative Methods In Intercultural Research: Practical Implications From The Study Of The Perceptions Of Intercultural Communication Competence By American And Russian Managers in: I.N. Rozina & Rostov-on-Don (eds.) ‘Theory of Communication And Applied Communication’. Bulletin of Russian Communication Association. 1(168), 89 – 67. New York, USA, Institute of Management, Business and Law Publishing
Onokerhoraye, A.G. (1994), Geographic Thought, Philosophy and Methodology. Benin Social Science for Africa. Ibadan, Intec Printers Limited.
Overland, J. E. and Preisendorfer, R.W. (1982), A Significance Test for Principal Components Applied to Cyclone Climatology. Monthly Weather Review. 110, 1-4. http://dx.doi.org/10.1175/1520-0493(1982)1102.0.CO;2
Pearson, K. (1901), On Lines and Planes of Closest Fit to Systems of Points in Space. Philosophical Magazine, 2 (11), 559–572. doi:10.1080/14786440109462720.
Preisendorfer, R.W. (1988), Principal Component Analysis in Meteorology and Oceanography. New York, Elsevier.
Principal Components Analysis: https://en.wikipedia.org/wiki/Principal_component_analysis
Rilwani, M. L. (2006). Field studies in Geography and Planning. Benin City, Donald publisher
Robinson, A. H. & Sale, R. D. (1982). Elements of Cartography. 3rd Edition, New York, John Wiley.
Rodarmel, C. & Shan, J. (2002). Principal Component Analysis for Hyperspectral Image Classification. Surveying and Land Information System. 62(2), 115 -123.
Turner, B.L., Skole, D., Sanderson, S., Fischer, G., Fresco, L. and Leemans, R. (1995), Land-Use and Land-Cover Change; Science/Research Plan, IGBP Report No.35, HDP Report No.7. IGBP and HDP, Stockholm and Geneva.
Wyly, E. (2001), Quantitative Geographical Analysis / Background on Principal Components and Factor Analysis. (Online). Retrieved from http://ibis.geog.ubc.ca/~ewyly/teaching/606_pca.pdf, accessed July 22, 2015.
DOI: https://doi.org/10.22146/ijg.17629
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