The simulation of the energy balance at the scale of a street become a huge issue. The accurate geometry of the area, detailed atmospheric measurements, and eco-physiological information are necessary to perform faithful simulations. In addition, thermal images showing surface temperatures are also of highly interest to analyse the energy balance between façades and trees. In this context, the aim of our project is to contribute to the development of a methodology for merging 3D geometry of an urban scene with surface temperatures. In this paper, a methodology is proposed for the texturing of a point cloud from a static laser scanner with IR images from a thermal camera. The main idea of the developed methodology is to take part of the ability of the thermal camera to acquire simultaneously RGB and IR images. After determining the relative position and orientation of IR and RGB sensors, the orientations of IR images are deduced from the orientations of RGB images. Then, the point cloud and RGB images are registered by selecting homologous points manually. Finally, the point cloud is textured with the IR images.