Urban growth simulation using remote sensing, GIS, and SLEUTH urban model in Gelephu City, Bhutan.

Abstract

Urbanization is one of the most evident global changes. Gelephu city under Sarpang Dzongkhag has experienced rapid urbanization over the past decades. The number of people living in urban areas has drastically increased mainly arising from natural population growth and rural-urban migration along with socio-economic development. This ultimately leads to the unplanned and uncontrolled urban expansion causing an irreversible change of urban landscape posing great threats to natural environments.

The primary objective of the research was to apply remote sensing and geographic information system technology with the integration of cellular automata (CA) based SLEUTH urban growth model to simulate the urban expansion and evaluate the urban growth factors through the development of future growth scenarios. The model was calibrated with historical data for the period 1990-2017, extracted from a time series of satellite images. The dataset consists of four historical urban extents (1990, 2000, 2010, and 2017), two land-use layers (1990, 2017), two transportation layers (1990, 2017), slope layer, hillshade layer, and urban excluded layers.

Three specific scenarios were designed to simulate the spatial growth consequences of urban growth under different land-use conditions. The first scenario is to simulate the unmanaged growth in business as usual (BAU) scenario with no restriction on land use categories except water bodies. The second scenario is to project the managed growth scenario (MGS) trend by taking into consideration of moderate environmental protection, specifically for forest land and open spaces. The last scenario is to simulate the compact growth scenario (CGS) with maximum protection. It was found that altering the level of growth protection in the urban exclusion layer for different land-use types patently affects the growth changes in the region. In the BAU scenario, it is estimated to gain approximately 26 sq.km of urban land by 2047, which is twice the current urban area in 2017. Approximately, 9 sq.km of the resources could be saved by the third scenario, compact growth with maximum growth protection of (80 percent) was applied. However, the growth seems to be highly underestimated in the areas which have high growth probability. The second scenario was found to be the ideal growth scenario in the current study area where moderate growth protection (50 percent) was applied. Though the scenario consumes 23 sq.km of urban land by 2047, it attempts to save the limited agriculture land and facilitate future growth in a much-sustained manner considering the topography of the region.

Findings suggest that the SLEUTH model can be applied successfully and produce a realistic projection of urban growth that it can assist urban planner and policymakers to establish proper urban planning as a decision-support tool for sustainable development.

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