||Nowadays, there are high demands on 3D modeling of urban environments. In urban areas, buildings and trees greatly affect the landscape of urban areas. How to reconstruct 3D models for buildings and trees is an important problem for urban modeling. The large number of buildings and trees requires cheaper and more automatic approaches to be developed. Traditional scanner-based approaches require expensive equipment and can only capture unstructured 3D points without photometric appearance of the scenes, while manual editing approaches require lots of man-power. Here, image-based modeling which can reconstruct the mathematical 3D representation of objects from images with registered color texture map provides a tempting solution. In contrast to traditional image-based building modeling that relies on general smoothness assumption of the reconstructed surface to automatic recover irregular surface meshes or requires fully manual editing to build up the correspondence among images to generate a regularized surface representation, in this thesis, we target to create regularized 3D facade models with less user interactions. We propose methods to improve the key aspects of existing work flow. First, a resampling scheme is proposed to select dominant correspondences which yield a good result for large scale quasi-dense reconstruction as if all correspondences are involved. Then, to model single facade, we propose a concept of unwrappable facades which generalizes the traditional concept of elevations to unwrappable surface. This representation enables us to model larger range of facades with a global shape description semi-automatically than previous methods do. This representation further makes adding detailed decorations and image-based facade synthesis more easily. Finally, we present a facade partition scheme that use the natural vertical lines on the building to automatically separate a large number of urban images and 3D point clouds into the granularity of facade level. With this partition scheme, we demonstrate that automatic image-based facade modeling with rectilinear constraint can be applied to reconstruct large-scale city models. To overcome the drawbacks of existing image-based tree modeling techniques, e.g. lacks of complete multiple view data and tedious user interaction on preprocessing, we describe a system to model a tree with single image. Given a near orthogonal image of a tree, as few as two strokes, one for marking a visible branch and the other for marking the tree crown, are required to model a photo-realistic tree. The marked visible branches are used to guide a branch tracing algorithm to extract remaining visible branches automatically. The extracted visible branches are used to construct a branch library which is later grown using a non-parametric growing algorithm under the constraint of the extracted tree crown. We also demonstrate that additional information from multiple view images and laser scanners can be used to further eliminate this user interaction with the help of joint segmentation and analysis.