Nowadays, applying clean and renewable energy has been developed quite impressively. Because of limited sources, natural and environmental hazards and high costs of fossil energy, many industrial and developing countries have turned to use renewable energies more than ever. Geothermal energy is one the most important natural energy resources ranking in this list. According to the type of the reservoir including its depth, volume, and amount of its energy, the application of a geothermal resource can range from the direct heating usage, to electricity production in power stations. Geothermal energy resources are globally distributed, yet one could be exploited technically and economically only if it is formed under favorable geological and structural settings. The favorable settings to form an exploitable geothermal energy resource in an area can be determined by means of exploration investigations, first on the country scale, and then on larger scales and eventually limited scales. The existence of geothermal resource potential has been approved in many zones in Iran, specifically on its volcanic belt, through previous studies. The next exploration step is to study each of these zones to restrict the investigation area, and to find out more detailed information about the energy resource. East Azerbaijan province with many young volcanic mountains and other exploration evidences has been recognized as one of these high potential areas in Iran. In the present research, areas with high potential in terms of geothermal energy are delineated in the East Azerbaijan province by means of a Geographic Information System (GIS). The aim of this study is to introduce the favorable areas in order to carry out next exploration stages to discover geothermal reservoir(s). Geological studies, remotely sensed data, and geophysical surveys are employed as different exploration methods in this research. In this regard, evidences related to existence of geothermal resource have been specified and processed. Dataset comprises the geological (lithology, faults and volcanic centers), geophysical (airborne magnetic survey and micro-earthquakes) and remotely sensed (hydrothermal alteration, Fe-oxides and land surface temperature) data layers which are prepared in 1:250000 scale and processed. Collected information, as different layers, is fused using Boolean, Weighted Overlay and Fuzzy logic integration models. The results of these knowledge-driven integration methods highlight the most favorable areas for the next step of geothermal exploration project in the province. These areas which cover small portion of the province are consistent and correlated with each other as they do with the ground truths
