Satellite images are important information sources of land
cover analysis or land cover change monitoring. We used the
sensors of four different spacecraft: TM, ETM+, OLI and ALI.
We classified the study area using the Maximum Likelihood
algorithm and used segmentation techniques for training area
selection. We validated the results of all sensors to reveal
which one produced the most accurate data. According to
our study Landsat 8’s OLI performed the best (96.9%) followed
by TM on Landsat 5 (96.2%) and ALI on EO-1 (94.8%) while
Landsat 7’s ETM+ had the worst accuracy (86.3%).