Abstract
Accurate information on, and human interpretation of, urban land cover using satellite-derived sensor imagery is critical given the intricate nature and niches of socioeconomic, demographic, and environmental factors occurring at multiple temporal and spatial scales. Detailed knowledge of urban land and their changing pattern over time periods associated with ecological risk is, however, required for the best use of critical land and its environmental resources. Interest in this topic has increased recently, driven by a surge in the use of open-source computing software, satellite-derived imagery, and improved classification algorithms. Using the machine learning algorithm Random Forest, combined with multi-date Landsat imagery, we classified eight periods of land cover maps with up-to-date spatial and temporal information of urban land between the period of 1972 and 2015 for the mega-urban region of greater Dhaka in Bangladesh. Random Forest—a non-parametric ensemble classifier—has shown a quantum increase in satellite-derived image classification accuracy due to its outperformance over traditional approaches, e.g., Maximum Likelihood. Employing Random Forest as an image classification approach for this study with independent cross-validation techniques, we obtained high classification accuracy, user and producer accuracy. Our overall classification accuracy ranges were between 85% and 97% with kappa values between 0.81 and 0.94. The area statistics derived from the thematic land cover map show that the built-up area in the 43-year study period expanded quickly, from 35 km2 in 1972 to 378 km2 in 2015, with a net increase rate of approximately 980% and an average annual growth rate of 6%. This growth rate, however, was higher in peripheral areas, with a 2903% increase and an annual expansion rate of 8%, compared to a 460% increase with an annual growth rate of 4% in the core city area (Dhaka City Corporation). This huge urban expansion took place in the north, northwest, and southwest regions of Dhaka, transforming areas that were previously agricultural land, vegetation cover, wetland, and water bodies. The main factors driving the city towards northern corridors include flood-free higher land, the availability of a transportation network, and the agglomeration of manufacturing-based employment centers. The resulting thematic map and spatial information produced from this study therefore serve to facilitate a detailed understanding of urban growth dynamics and land cover change patterns in the mega-urban region of Dhaka, Bangladesh.
Highlights
The overwhelming majority of Bangladesh’s population lives in rural settings with a low level of urbanization compared to other Asian countries, the megacity ofDhaka has experienced massive urbanization in recent years, which sharply contrasts with the rate of urbanization in other nations
Using the ensemble classifier Random Forest with multi-date remote sensing imagery, we studied land cover change and urban expansion of the greater Dhaka for the period of 1972 to 2015
Since non-parametric-based regression models performed well once they were calibrated with sufficient variables [45], we developed 23 variables including three topographic variables, i.e., elevation, slope, and aspect, and 17 spectral variables from Landsat imagery
Summary
The overwhelming majority of Bangladesh’s population lives in rural settings with a low level of urbanization compared to other Asian countries (currently 34%), the megacity ofDhaka has experienced massive urbanization in recent years, which sharply contrasts with the rate of urbanization in other nations. The Dhaka mega-urban center is projected to reach an annual population growth rate of 2.98% by 2030, with the total population in the city territory surpassing 27.37 million by this time [1,3], and exceeding the growth rate of other major urban centers such as Beijing, Shanghai, and Mexico City. Rural dwellers immigrate to the urban center either looking for work in a booming industrial sector (i.e., such as readymade garments around the city) [5] or to avail themselves of civic facilities such as health care clinics, education, and so on Such growth has resulted from the increasing frequency of natural disasters like floods, erosion, increasing salinization, and concomitant loss of agricultural productivity in the surrounding countryside, which has previously caused large-scale rural-to-urban migration. Coupled with an unbearable traffic gridlock, high pollution levels, and insufficient infrastructure and housing development [2], this ranks Dhaka as one of the least livable cities on Earth [7]
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