Temperature and humidity are essential factors in analyzing a building’s thermal performance. This research presents the differences in field measurements of vernacular houses in coastal and mountain areas in Indonesia. Field measurements were taken for five consecutive days in four vernacular houses. The variables were measured at the beginning and at the peak of the rainy season. Analysis included a combination of graphic and descriptive methods. The research results show that the location difference between coast and mountain results in a relatively high difference in temperature (43.6%). The outdoor temperature in the mountain area is lower than that of the coastal area. The outdoor humidity of the mountain area is 0.69% higher than that of the coastal area. In the tropical coastal area, the outdoor temperature of the exposed-brick house is 0.94% lower than that of the coastal wooden house. The outdoor air humidity of the brick house is 0.89% higher than that of the coastal wooden house. In the tropical mountain area, the outdoor temperature of the exposed-stone house is 2.47% lower than that of the wooden house. The outdoor air humidity of the stone house is 0.4% lower than that of the wooden house. The outdoor conditions affect the indoor conditions of the respective houses. These microclimatic differences are influenced by micro-environmental factors, such as the density of surrounding buildings, amount of vegetation, and shading. The research shows that height difference is the most dominant factor influencing outdoor microclimate. Regional microclimate becomes the basis for determining the most suitable envelope materials in different areas. The innovative contribution of the work is, among other benefits, the identification of factors that influence the wellbeing of the buildings’ users in the researched geographical area and the analysis of the interaction of the external and internal environment of buildings. From the above facts, it follows that the results of this work can contribute to the development of prediction models to determine the type of cover, material, shape, and load-bearing elements needed to create comfortable and energy-efficient buildings.