Abstract
The main objective of this study is to detect and predict the urban area expansion at Hanoi, a typical urbanization city in Vietnam. For this purpose, firstly, temporal SPOT-5 images for years 2003, 2007, and 2011 were used to classify four land cover classes, open water, vegetation, barren, and residential area. Secondly, Impervious Surface Index (ISI) computed from the spectral bands of the above imagery. This index was then used to extract impervious surface information of the study area from residential area. Using the three derived land use/land cover maps, the area of land use/land cover types in the Hanoi area for years 2019 and 2027 were simulated and predicted using a Markov chain model. There results showed that the impervious surfaces of the Hanoi will increase 8.27% and 14.09% of total study area in 2019 and 2027, respectively. The results from this study provide valuable information to the local city planners in their urban planning and development.
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Nguyen, T.V., Nguyen, N.V., Le, H.T.T., La, H.P., Tien Bui, D. (2018). Detection and Prediction of Urban Expansion of Hanoi Area (Vietnam) Using SPOT-5 Satellite Imagery and Markov Chain Model. In: Tien Bui, D., Ngoc Do, A., Bui, HB., Hoang, ND. (eds) Advances and Applications in Geospatial Technology and Earth Resources. GTER 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-68240-2_8
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DOI: https://doi.org/10.1007/978-3-319-68240-2_8
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