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Erscheinungsjahr: 
2019
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[Journal:] Journal of Urban Management [ISSN:] 2226-5856 [Volume:] 8 [Issue:] 2 [Year:] 2019 [Pages:] 206-224
Verlag: 
Elsevier, Amsterdam
Zusammenfassung: 
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.
Schlagwörter: 
Bangladesh
City classification
Clustering
Remote sensing
Urban extent
Urban growth
Urbanization
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