Potential of a post-classification change detection analysis to identify land use and land cover changes : a case study in northern Greece

The use of remotely sensed data is an important method to indicate land use and land cover changes. Remote sensing can provide a better picture of monitoring land use and land cover changes. It makes it feasible to locate geographically changed areas in order to employ it further detailed studies on environmental changes (e.g. land degradation). The study area is a heterogeneous and small-structured agriculturally dominated prefecture in northern Greece. The core post-classification change detection analysis was based on two Landsat 5 TM and Landsat 7 ETM+ images. Maximum likelihood classification was applied on the satellite data. A basic arithmetic combination was used to compare the classification outcomes to detect and locate land use and land cover changes over a period of 14 years. The accomplished post-classification change detection analysis performed weakly.