The purpose of the current study is to examine the map reading skills of Social Studies pre-service teachers with orienteering, which is an activity-based and more active practice. To this end, a total of 10 students attending the Department of Social Studies Teaching in the Education Faculty of Burdur Mehmet Akif Ersoy University and taking the course of Map Skills and Applications were selected. An analytical rubric consisting of four criteria and scored in four categories was used to collect data in the study. The content validity of the developed rubric was calculated with the Davis Technique and it was thought that sufficient evidence was obtained for the content validity. During the orienteering activity, the map reading skills of the students were scored by 5 raters with this rubric in terms of four criteria, direction/location, recognizing signs/symbols, using landforms and managing time. They were examined with the many-facet Rasch model (MFRM). Map reading skills were evaluated according to the severity/leniency of the raters and the difficulty of the students in exhibiting the behavior. The results of the analysis showed that the agreement between the raters was found to be good. It was also concluded that the most difficult skill is determining direction/location and the easiest skill is using landforms.

Karst Rocky Desertification (KRD) is the reduction of vegetative productivity of this land with the release of bedrock as a result of the full or partial transportation of the fertile soil through natural processes and human activities in karst landscapes. The purpose of this study is to reveal the effectiveness of Remote Sensing methods in monitoring, mapping, and evaluating KRD. Landsat 8 OLI images were used to carry out these procedures. In monitoring this process, Karst Bare Rock Index (KBRI), Normalized Difference Rock Index (NDRI), Carbonate Rock Index 2 (CRI2), Normalized Difference Build-Up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Dimidiate Pixel Model (DPM), Multi Endmember Spectral Mixture Analysis (MESMA) and Support Vector Machine (SVM) were used from the spectral indices. In order to evaluate the results obtained, KRD was divided into 4 basic classes such as none, mild, moderate, and severe. According to these classification levels, it was determined that SVM method had the highest accuracy. For this reason, it was concluded that the SVM method can be used effectively in determining KRD. In the study, it was concluded that the KRD strengthens as one goes from south to north and from west to east in the research area. This study points out KRD is one of the effective land problems in the Mediterranean region, Turkey.