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Suitable sites for built-up area expansion in Kamalamai municipality, Sindhuli district, Nepal
Kamalamai municipality has witnessed significant built-up development in recent years but there has been very limited planning and regulation for controlling this trend. Haphazard built-up expansion may risk environmental sensitive areas and could expand towards areas lacking basic facilities. Identification of suitable areas for built-up development is critical to regulate future development in an efficient manner. The main objective of the study was to identify suitable sites for built-up expansion in Kamalamai municipality. Landsat images of 2001, 2016, and 2021 were used for Land Use Land Cover (LULC) trend analysis. Suitability analysis was done based on Analytical Hierarchy Process (AHP) pair-wise comparison. Multi-layer Preceptor (MLP) neural network was used for transition sub-modeling of each LULC class to built-up. Markov model was used for future urbanization modeling in combination with constraint/incentive to redirect the change in expansion suitable areas. During 2001 and 2021 the built-up had increased from 0.5% (1.09 Km²) to 1.9% (3.95 Km²). The model predicted the built-up to increase to 2.5% (5.13 Km²) by 2031, 3.3% (6.69 Km²) by 2041, and 4% (8.25 Km²) by 2051. The region has significantly urbanized since 2016 mainly contributed by in-migration and is predicted to follow the trend in the future.
Suitable sites for built-up area expansion in Kamalamai municipality, Sindhuli district, Nepal
Kamalamai municipality has witnessed significant built-up development in recent years but there has been very limited planning and regulation for controlling this trend. Haphazard built-up expansion may risk environmental sensitive areas and could expand towards areas lacking basic facilities. Identification of suitable areas for built-up development is critical to regulate future development in an efficient manner. The main objective of the study was to identify suitable sites for built-up expansion in Kamalamai municipality. Landsat images of 2001, 2016, and 2021 were used for Land Use Land Cover (LULC) trend analysis. Suitability analysis was done based on Analytical Hierarchy Process (AHP) pair-wise comparison. Multi-layer Preceptor (MLP) neural network was used for transition sub-modeling of each LULC class to built-up. Markov model was used for future urbanization modeling in combination with constraint/incentive to redirect the change in expansion suitable areas. During 2001 and 2021 the built-up had increased from 0.5% (1.09 Km²) to 1.9% (3.95 Km²). The model predicted the built-up to increase to 2.5% (5.13 Km²) by 2031, 3.3% (6.69 Km²) by 2041, and 4% (8.25 Km²) by 2051. The region has significantly urbanized since 2016 mainly contributed by in-migration and is predicted to follow the trend in the future.
Suitable sites for built-up area expansion in Kamalamai municipality, Sindhuli district, Nepal
Poudel, Samin (author) / Shahnawaz, Shahnawaz (author) / Shrestha, Him Lal (author)
2023-08-31
doi:10.6093/1970-9870/9968
TeMA - Journal of Land Use, Mobility and Environment; Vol 16 No 2 (2023): The city challenges and external agents. Methods, tools and best practices; 279-305 ; Tema. Journal of Land Use, Mobility and Environment; V. 16 N. 2 (2023): The city challenges and external agents. Methods, tools and best practices; 279-305 ; 1970-9870 ; 1970-9889
Article (Journal)
Electronic Resource
English
DDC:
500
Suitable sites for built-up area expansion in Kamalamai municipality, Sindhuli district, Nepal
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