High resolution mapping of urban areas using SPOT-5 images and ancillary data

Year 2015, Volume: 2 Issue: 2, 63 - 76, 03.08.2015

Elif Sertel , Semih Sami Akay

https://doi.org/10.30897/ijegeo.303545

Cited By: 20

Abstract

This research aims to propose new rule sets to be used for object based classification of SPOT-5
images to accurately create detailed urban land cover/use maps. In addition to SPOT-5 satellite
images, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index
(NDWI) maps, cadastral maps, Openstreet maps, road maps and Land Cover maps, were also
integrated into classification to increase the accuracy of resulting maps. Gaziantep city, one of the
highly populated cities of Turkey with different landscape patterns was selected as the study area.
Different rule sets involving spectral, spatial and geometric characteristics were developed to be
used for object based classification of 2.5 m resolution Spot-5 satellite images to automatically
create urban map of the region. Twenty different land cover/use classes obtained from European
Urban Atlas project were applied and an automatic classification approach was suggested for high
resolution urban map creation and updating. Integration of different types of data into the
classification decision tree increased the performance and accuracy of the suggested approach. The
accuracy assessment results illustrated that with the usage of newly proposed rule set algorithms in
object-based classification, urban areas represented with seventeen different sub-classes could be
mapped with 94 % or higher overall accuracy.

Keywords

Urban mapping, remote sensing, SPOT-5

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