Rafique, A.Karas, I.R.Abujayyab, S.K.M.Khan, A.A.Demiral, E.2024-09-292024-09-2920201682-1750https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-351-2020https://hdl.handle.net/20.500.14619/88445th International Conference on Smart City Applications, SCA 2020 -- 7 October 2020 through 8 October 2020 -- Safranbolu -- 167323Exploratory Spatial Analysis Techniques (ESDA) have become popular to identify the spatial association of different variables in many fields of natural and social sciences. The application of Global Moran's I statistics enables us to provide visual insights of spatial data. It helps to detect spatial patterns and hotspots of an activity or process, based on spatial autocorrelation. This study aims to investigate the spatial dependence of domestic and inbound tourist arrivals to 123 cities of all eight provinces of the Aegean Region of Turkey. For analysis, city-level data about domestic and inbound tourist arrivals during 2015-2019 is collected from the Turkish Ministry of Culture and Tourism and is converted to logarithm form to avoid any skewness. The Arc GIS and GeoDa programs are employed for the analysis of spatial autocorrelation and visualization of hotspots of tourist flows in the regions. The results of the study reveal that tourist flows in the region are concentrated in the coastal areas, while inland cities receive an insufficient number of tourists. The hotspots of tourist flow are located mostly in the coastal towns of the provinces of Izmir, Aydin, and Mugla. The study is significant in the provision of useful information regarding resource allocation to the tourism hotspots and the implication of sustainable tourism policy to better utilization of tourism potential. © 2020 International Society for Photogrammetry and Remote Sensing. All rights reserved.eninfo:eu-repo/semantics/openAccessAutocorrelationExploratory Spatial AnalysisHotspot AnalysisThe Aegean RegionTourismConference Object10.5194/isprs-archives-XLIV-4-W3-2020-351-20202-s2.0-851019305603544/W3N/A35144