A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Urban growth modeling of Kathmandu metropolitan region, Nepal
Research highlights ► The weight of evidence approach integrated with cellular automata has demonstrated to be effective to handles categorical maps and missing data problems, which is appropriate to the place where the amount and quality of geographic information and other ancillary data are missing or very limited. ► The three-map comparison approach (overlaying the reference map of time 1, reference map of time 2, and prediction map of time 2) is transparent in validating the modeling results. ► The modeling result mirrors dynamic spatial patterns and composition of Kathmandu urban development for the next 20 years. ► The urban development in the Kathmandu valley will continue through both in-filling in existing urban space and outward expansion toward the east, south, and west directions in the future which will be greatly affected by the existing urban space, population growth, topographic complexity, and transportation network.
Abstract The complexity of urban system requires integrated tools and techniques to understand the spatial process of urban development and project the future scenarios. This research aims to simulate urban growth patterns in Kathmandu metropolitan region in Nepal. The region, surrounded by complex mountainous terrain, has very limited land resources for new developments. As similar to many cities of the developing world, it has been facing rapid population growth and daunting environmental problems. Three time series land use maps in a fine-scale (30m resolution), derived from satellite remote sensing, for the last three decades of the 20th century were used to clarify the spatial process of urbanization. Based on the historical experiences of the land use transitions, we adopted weight of evidence method integrated in cellular automata framework for predicting the future spatial patterns of urban growth. We extrapolated urban development patterns to 2010 and 2020 under the current scenario across the metropolitan region. Depending on local characteristics and land cover transition rates, this model produced noticeable spatial pattern of changes in the region. Based on the extrapolated spatial patterns, the urban development in the Kathmandu valley will continue through both in-filling in existing urban areas and outward rapid expansion toward the east and south directions. Overall development will be greatly affected by the existing urban space, transportation network, and topographic complexity.
Urban growth modeling of Kathmandu metropolitan region, Nepal
Research highlights ► The weight of evidence approach integrated with cellular automata has demonstrated to be effective to handles categorical maps and missing data problems, which is appropriate to the place where the amount and quality of geographic information and other ancillary data are missing or very limited. ► The three-map comparison approach (overlaying the reference map of time 1, reference map of time 2, and prediction map of time 2) is transparent in validating the modeling results. ► The modeling result mirrors dynamic spatial patterns and composition of Kathmandu urban development for the next 20 years. ► The urban development in the Kathmandu valley will continue through both in-filling in existing urban space and outward expansion toward the east, south, and west directions in the future which will be greatly affected by the existing urban space, population growth, topographic complexity, and transportation network.
Abstract The complexity of urban system requires integrated tools and techniques to understand the spatial process of urban development and project the future scenarios. This research aims to simulate urban growth patterns in Kathmandu metropolitan region in Nepal. The region, surrounded by complex mountainous terrain, has very limited land resources for new developments. As similar to many cities of the developing world, it has been facing rapid population growth and daunting environmental problems. Three time series land use maps in a fine-scale (30m resolution), derived from satellite remote sensing, for the last three decades of the 20th century were used to clarify the spatial process of urbanization. Based on the historical experiences of the land use transitions, we adopted weight of evidence method integrated in cellular automata framework for predicting the future spatial patterns of urban growth. We extrapolated urban development patterns to 2010 and 2020 under the current scenario across the metropolitan region. Depending on local characteristics and land cover transition rates, this model produced noticeable spatial pattern of changes in the region. Based on the extrapolated spatial patterns, the urban development in the Kathmandu valley will continue through both in-filling in existing urban areas and outward rapid expansion toward the east and south directions. Overall development will be greatly affected by the existing urban space, transportation network, and topographic complexity.
Urban growth modeling of Kathmandu metropolitan region, Nepal
Thapa, Rajesh Bahadur (author) / Murayama, Yuji (author)
Computers, Environments and Urban Systems ; 35 ; 25-34
2010-07-22
10 pages
Article (Journal)
Electronic Resource
English
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