Md. Shahinoor Rahman|Hossain Mohiuddin|Abdulla ? Al Kafy|Pintu Kumar Sheel|Liping Di
Classification of cities in Bangladesh based on remote sensing derived spatial characteristics
Bangladesh University of Engineering and Technology|George Mason University|University of Iowa|Rajshahi University of Engineering and Technology|Rajshahi University of Engineering and Technology|Khulna University|George Mason University
bangladesh cities conventionally classified based population size revenue collection conventional city classification system neglects spatial characteristics inherit cities providing comprehensive city classification system essential countrys future budget allocation infrastructure development five spatial features city size area urban form awmpfd ratio builtup nonbuiltup areas urban growth rate total night lights intensity 331 cities bangladesh derived remote sensing data study classifies cities six classes using hierarchical clustering algorithm based five selected spatial characteristics six categories named levels spatial development cluster 1 highest level cluster 6 lowest level share employment primary sector agriculture gradually rises cluster 1 cluster 6 contrast employment share service sector follows reverse trend cluster 2 cluster 6 per capita income expenditure higher large cities cluster 2 metropolitans cluster 1 comparisons across six classes nonspatial attributes validate classification system findings also reveal remote sensing derived spatial information explain nonspatial characteristics cities therefore remote sensing derived spatial attributes cities used city classification census data scarce