District heating (DH) has a major potential to increase the efficiency, security, and sustainability of energy management at the community scale. However, there is a huge challenge for decision makers due to the lack of knowledge about thermal energy demand during a year. Thermal
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District heating (DH) has a major potential to increase the efficiency, security, and sustainability of energy management at the community scale. However, there is a huge challenge for decision makers due to the lack of knowledge about thermal energy demand during a year. Thermal energy demand is strongly dependent on the outdoor temperature, building area, and activities. In this context, this paper presents an innovative monthly thermal energy mapping method to calculate and visualize heat demand accurately for various types of buildings. The method includes three consecutive phases: (i) calculating energy loss, (ii) completing a dataset that includes energy and building information, and (iii) generating the monthly heat demand maps for the community. Determining the amount of demand and the best location for energy generators from the perspective of energy efficiency in a DH system in an urban context is one of the important applications of heat maps. Exploring heat demand characteristics and visualizing them on maps is the foundation of smart DHs.@en