Use of multi-angle high-resolution imagery and 3D information for urban land-cover classification: a case study on Istanbul

The BELSPO-MAMUD project focuses on the use of remote sensing data for measuring and modelling urban dynamics. Remote sensing is a wonderful tool to produce long time-series of sealed surface maps, which are useful for this purpose. In the urban context of Istanbul, a very dynamic city, recent high resolution satellite images and medium resolution images from the past have been exploited to calibrate and validate a regression-based sub-pixel classification method allowing this production.
Image classification in an urban context is a tricky task for several reasons: prominent occurrence of shadowed and occluded areas and urban canyons, spectral confusions between urban and non-urban materials at ground and roof levels, moderately hilly relief ... To cope with these difficulties the combined use of three types of data may be helpful: diachronic (vii), multi-angle and 3D data.
A master multispectral and panchromatic QuickBird image and a panchromatic Ikonos stereopair, all acquired in March 2002, were used in combination with a multispectral and panchromatic Ikonos image of May 2005. A DSM was generated from the Ikonos stereopair and building vector file. It was used for orthorectification, building height estimation and classification. The area covered by the high resolution products was divided in 3 parts and each was classified independently.
This application demonstrates that a recent high resolution land-cover classification produced using multi-date, multi-angle and DSM can be used to produce sealed surface maps from longer time-series of medium resolution images over large urban areas, thus enabling the analysis of urban dynamics.