Segmentation based classification of aerial images and its potential to support the update of existing land use data bases

Description

The interpretation of aerial images is normally carried out by means of visual interpretation as traditional classification routines are too limited in dealing with the complexity of very high resolution data. Segmentation based classifers can overcome this limitation by dividing images into homogenous segments and using them as basis for further classification procedures. In this paper this approach is examined in view of its potential to support the update of existing land use data bases. A workflow was developed that allows the classification of high-resolution aerial images, the subsequent comparison with land use data and the assessment of identified changes. Special emphasis is put on the transferability of the procedure in terms of study area as well as image and land use data.

Period	17 May 2005
Event title	ISPRS Hannover Workshop 2005, High Resolution Earth Imaging for Geospatial Information
Event type	Other
Degree of Recognition	International