# A Combined Method for Preparation of Landslide Susceptibility Map in Izmir (Turkije)
## 5 Conclusions  
A landslide inventory map was compiled using previously mapped literature from GDMRE [84] and Avsar [83]. With the help of landsat images and aerial photos, this map was then updated and a final landslide inventory map was prepared. When the final landslide inventory map was analyzed, it was determined that 0.86% of the total area is covered by existing landslide areas.  
Figure 13: ROC curves of the LR, FR, AHP, IOE and CM methods.  
The geo-environmental factors of slope angle, slope aspect, lithology, slope curvature, elevation, density of discontinuity, stream power index (SPI), land use and distance to stream were used to determine landslide susceptibility. The data obtained was standardized in values of 0-1 using a fuzzy logic algorithm.  
In the landslide susceptibility analysis studies conducted so far, generally one or a few LSMs are produced and the results of these maps are compared. It is evident that maps composed using different methods will produce different results. This study aims to minimise the negative effects of the errors that might arise from the shortcomings of each method for creating LSMs by making use of these differences and integrating maps prepared using different methods. In this study, LSMs were first prepared using the LR, AHP, FR and IOE methods, as the methods most commonly used recently, and then the final LSM was prepared using the combined method.  
For determining success rates of the different methods used in this study, conformities between LSMs and the landslide inventory map were compared. Total areas of high and extremely high landslide susceptibility were compared with existing landslide localities. Success rates were calculated using these results. Success rates of 60.27%, 81.53%, 86.17% and 89.80% corresponded to the LR, AHP, FR and IOE LSMs, respectively. The best method--the combined method, which is combination of the LR, AHP, FR and IOE methods--had a success rate of 94.93%.  
This study offers a preliminary guide for local authorities, engineers working in practice and academics working in this field. The results are promising, and were verified based on real-life phenomena. The results can constitute the basis of risk-based maps in the region.  
The approach certainly has several limitations. Cartographic scale datasets were used for modelling; this causes unreliability in spatial analysis, which necessitates detailed field investigation. For instance, the geological data were obtained from the lithological map with a spatial resolution of approximately 25 \(\times\) 25 m, but the GDEM used has a spatial resolution of 30 m. In should be noted that this is a preliminary approach for landslide susceptibility assessment.  
Conceptualization, C.K.; methodology, C.K. and H.K.; software, C.K. and H.K.; validation, C.K. and H.K.; formal analysis, H.K.; investigation, C.K. and H.K.; resources, C.K.; data curation, C.K. and H.K.; writing--original draft preparation, C.K. and H.K.; writing--review and editing, C.K. and H.K.; visualization, C.K. and H.K.; supervision, C.K.; project administration, C.K.; funding acquisition, C.K. and H.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data available on request due to privacy restrictions. The data presented in this study are available on request from the corresponding author.  
The authors are grateful to [PERSON] for his support in statistical analyses and [PERSON] for his support in use of ArcMap software. Critical reviews by four anonymous reviewers in an earlier version of this manuscript are gratefully acknowledged. The authors also appreciate the contribution of [PERSON] for her support in language editing.  
The authors declare no conflict of interest.