DocumentCode
2990634
Title
Building-based urban land use classification from vector databases in Manchester, UK
Author
Hussain, Masroor ; Barr, Robet ; Chen, Dongmei
Author_Institution
Dept. of Geogr., Queen´´s Univ., Kingston, ON, Canada
fYear
2012
fDate
15-17 June 2012
Firstpage
1
Lastpage
7
Abstract
The recognition, analysis and classification of urban structures are important in urban land use modeling. The form and the function of individual urban elements such as buildings and street blocks help us better understand the urban morphology. The types, layout and arrangement of these buildings form up the local characteristics of urban areas. A model has been developed to classify urban areas based on the cartometric properties of buildings and the patterns they make. Supervised and un-supervised classification algorithms from data mining techniques along with GIS are explored to help create a framework for extracting information from vector databases and classifying building and blocks. The methodology is developed and applied to Manchester metropolitan in the UK.
Keywords
data mining; geographic information systems; information retrieval; land use planning; pattern classification; terrain mapping; visual databases; GIS; Manchester; UK; building blocks; building cartometric properties; building-based urban land use classification; information extraction framework; street blocks; supervised classification algorithm; unsupervised classification algorithm; urban area local characteristics; urban land use model; urban structure analysis; urban structure classification; urban structure recognition; vector databases; Buildings; Data Mining; Decision Tree; Geographic Information System (GIS); Structural Classification; Urban Areas;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoinformatics (GEOINFORMATICS), 2012 20th International Conference on
Conference_Location
Hong Kong
ISSN
2161-024X
Print_ISBN
978-1-4673-1103-8
Type
conf
DOI
10.1109/Geoinformatics.2012.6270327
Filename
6270327
Link To Document