Skip to main content

A method for object-oriented land cover classification combining Landsat TM data and aerial photographs

Buy Article:

$60.90 plus tax (Refund Policy)


Object-oriented classification techniques based on image segmentation are gaining interest as methods for producing output maps directly storable into Geophysical Information System (GIS) databases. A limitation in efficiently applying image segmentation is often represented by the spatial resolution of the image. This contribution proposes a method for overcoming this problem, based on the integrated use of images of different resolution. A high-resolution black and white (b/w) orthophoto and a subscene of a Landsat Thematic Mapper (TM) image have been used to obtain an object-oriented classification of the land cover of a study area in northern Italy. The method consists of a sequential application of segmentation and classification techniques. First, the TM image was classified using the maximum likelihood classifier and additional empirical rules. Subsequently, the orthophoto was segmented by applying a region-based segmentation algorithm. Finally, the classification of the segmented images was performed using as a reference the TM image previously classified. The resulting land cover map was tested for accuracy and the results are dicusssed.

Document Type: Research Article


Affiliations: 1: Geological Survey Division, International Institute for Aerospace Survey and Earth Science (ITC), PO Box 6, 7500AA Enschede, The Netherlands; e-mail:; 2: Department of Geodesy, Delft University of Technology, PO Box 5030, 2600GA Delft, The Netherlands; e-mail:

Publication date: March 1, 2003

More about this publication?

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more