Classification of cities in Bangladesh based on remote sensing derived spatial characteristics

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Abstract

In Bangladesh, cities are conventionally classified based on population size and revenue collection. This conventional city classification system neglects the spatial characteristics inherit in cities. Providing a more comprehensive city classification system is essential for the country's future budget allocation and infrastructure development. Five spatial features: city size (area), urban form (AWMPFD), the ratio of built-up and non-built-up areas, urban growth rate, and total night lights intensity for 331 cities of Bangladesh are derived from remote sensing data. This study classifies these cities into six classes using a hierarchical clustering algorithm based on five selected spatial characteristics. The six categories are named for their levels of spatial development, with Cluster 1 being the highest level and Cluster 6 being the lowest level. The share of employment in the primary sector (agriculture) gradually rises from Cluster 1 to Cluster 6. In contrast, the employment share of the service sector follows a reverse trend from Cluster 2 to Cluster 6. Both per capita income and expenditure is higher for the large cities of Cluster 2 than for the metropolitans of Cluster 1. Comparisons across the six classes with non-spatial attributes validate the classification system. Findings also reveal that remote sensing derived spatial information can explain non-spatial characteristics of cities. Therefore, remote sensing derived spatial attributes of cities can be used for city classification where census data are scarce.

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APA

Rahman, M. S., Mohiuddin, H., Kafy, A. A., Sheel, P. K., & Di, L. (2019). Classification of cities in Bangladesh based on remote sensing derived spatial characteristics. Journal of Urban Management, 8(2), 206–224. https://doi.org/10.1016/j.jum.2018.12.001

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