DocumentCode
143665
Title
Object based building extraction by QuickBird image for population estimation: A case study of the City of Waterloo
Author
Wei Li ; Shiqian Wang ; Li, Jonathan
Author_Institution
Dept. of Geogr. & Environ. Manage., Univ. of Waterloo, Waterloo, ON, Canada
fYear
2014
fDate
13-18 July 2014
Firstpage
3176
Lastpage
3179
Abstract
This paper used QuickBird high resolution image to estimate the population of the city of Waterloo, ON, Canada. Two approaches of object based classification were compared to extract buildings from the original image. One is rule based classification and the other is example based classification. We chose two districts which are Lakeshore and Columbia as our testing areas. Rule based result is better than example based. The overall accuracy of rule based classification in Lakeshore District and Columbia District are 92.5% and 85.5%. With census data, the average area per person is about 38.8 m2 and the estimated population of the city of Waterloo is about 109589.
Keywords
buildings (structures); feature extraction; geophysical image processing; image classification; image resolution; knowledge based systems; Canada; Columbia district; Lakeshore district; ON; QuickBird high resolution image; Waterloo city; building extraction; object based building extraction; object based classification; population estimation; rule based method; Accuracy; Buildings; Cities and towns; Estimation; Remote sensing; Sociology; Statistics; QuickBird; high resolution; object-based classification; population estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location
Quebec City, QC
Type
conf
DOI
10.1109/IGARSS.2014.6947152
Filename
6947152
Link To Document