PRESENTING AND COMPARING THE OBJECT BASED IMAGE ANALYSIS AND STANDARD IMAGE ANALYSIS FOR CHANGE DETECTION OF FOREST AREAS, USING LOW-RESOLUTION SATELLITE IMAGERY

11th International Multidisciplinary Scientific GeoConference SGEM2011, www.sgem.org, SGEM2011 Conference Proceedings/ ISSN 1314-2704, June 20-25, 2011, Vol. 2, 329-336 pp

ABSTRACT

The objectives of this study were to present and compare methods for change detection
of forest areas in low-resolution satellite imagery, using object based image analysis and
standard image analysis techniques (pixel based). Considering that huge area in Serbia
is covered with forest, this study is of great importance for detecting and tracking
changes over time. The data used in this study were optical remote sensing satellite
images Landsat TM (22-08-1986) and Landsat ETM+ (23-06-2002). These images were
processed in order to classify and identify four main land cover classes, namely: forest,
agricultural, urban and water areas. The images are analyzed and the process of change
detection was applied on forest areas. The results show the type and the place of landuse
changes occurred in these main four classes during those years. Change analyses
were performed based on object image analysis and standard image analysis techniques
on the other hand. The research reported here shows that the object-oriented
classification method is most accurate when it comes to the classification of land cover.
The research also shows that the method of post-classification on object classification
results is the most accurate method of change detection in forest areas.

Keywords: remote sensing, change detection, image analysis, classification, object image analysis