Creating geometrically correct and complete 3D models of complex environments remains a difficult problem. Techniques for 3D digitizing and modeling have been rapidly advancing over the past few years although most focus on single objects or specific applications such as architecture and city mapping. The ability to capture details and the degree of automation vary widely from one approach to another. One can safely say that there is no single approach that works for all types of environment and at the same time is fully automated and satisfies the requirements of every application. In this paper we show that for complex environments, those composed of several objects with various characteristics, it is essential to combine data from different sensors and information from different sources. Our approach combines models created from multiple images, single images, and range sensors. It can also use known shapes, CAD, existing maps, survey data, and GPS. 3D points in the image-based models are generated by photogrammetric bundle adjustment with or without self-calibration depending on the image and point configuration. Both automatic and interactive procedures are used depending on the availability of reliable automated process. Producing high quality and accurate models, rather than full automation, is the goal. Case studies in diverse environments are used to demonstrate that all the aforementioned features are needed for environments with a significant amount of complexity.