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Potential geothermal areas were identified and classified according to geothermal, geological and geophysical spatial associations in Fujian province, China. Five publicly available datasets were used in this study: seismic activity, geomagnetism, fault distribution, intrusive rock distribution, and Bouguer gravity anomaly, which were digitally processed into five impact factors maps: Gutenberg-Richter b-value, magnetic anomaly, distance to faults, distance to intrusive rock and distance to major grabens, respectively. Based on the geographic information system supported weight-of-evidence model and fuzzy logic model, the geothermal prediction maps were established using the impact factors maps. The prediction maps divide the potential geothermal areas of Fujian province into four grades, where the extremely high potential geothermal area covers 14,000 km2, accounting for 11.54% of the total area and the developed geothermal area is in good agreement with the extremely high potential area. The results reveal that the weight-of-evidence model is more accurate, and the application of each fuzzy operator in the process of fuzzy synthesis of the fuzzy logic model has a certain subjectivity, which requires higher professional knowledge to drive. It is anticipated that this paper will guide further investigations in Fujian province and guide the study of delineating potential geothermal regions with limited information. Image 1 • Potential geothermal areas were identified based on GIS-supported models. • Five impact factors were established by geothermal, geological and geophysical data. • The weight-of-evidence model showed a more accurate prediction. • The fuzzy logic model has a certain subjectivity. [ABSTRACT FROM AUTHOR]

Potential geothermal areas were identified and classified according to geothermal, geological and geophysical spatial associations in Fujian province, China. Five publicly available datasets were used in this study: seismic activity, geomagnetism, fault distribution, intrusive rock distribution, and Bouguer gravity anomaly, which were digitally processed into five impact factors maps: Gutenberg-Richter b-value, magnetic anomaly, distance to faults, distance to intrusive rock and distance to major grabens, respectively. Based on the geographic information system supported weight-of-evidence model and fuzzy logic model, the geothermal prediction maps were established using the impact factors maps. The prediction maps divide the potential geothermal areas of Fujian province into four grades, where the extremely high potential geothermal area covers 14,000 km2, accounting for 11.54% of the total area and the developed geothermal area is in good agreement with the extremely high potential area. The results reveal that the weight-of-evidence model is more accurate, and the application of each fuzzy operator in the process of fuzzy synthesis of the fuzzy logic model has a certain subjectivity, which requires higher professional knowledge to drive. It is anticipated that this paper will guide further investigations in Fujian province and guide the study of delineating potential geothermal regions with limited information. Image 1 • Potential geothermal areas were identified based on GIS-supported models. • Five impact factors were established by geothermal, geological and geophysical data. • The weight-of-evidence model showed a more accurate prediction. • The fuzzy logic model has a certain subjectivity. [ABSTRACT FROM AUTHOR]