Although functional identifiability represents a key aspect for promoting visual connotation and sustainable usability in historic building groups, there is still no consensus on how to quantitatively describe its identification basis at a large scale. The recent emergence of the potentiality of deep learning and computer vision has provided an alternative to traditional empirical-based judgment, which is limited by its subjective bias and high traversal costs. To address these challenges, this study aims to build a workflow for a visual analysis of function and facade to extract the different contributions that facade elements provide to functional expression. The approach is demonstrated with an experiment on a section of the Chinese Eastern Railway (CER) where large-scale historical buildings images were categorized to identify functions using deep learning, together with activation and substance for visual calculations. First, the dataset aggregated with images of historic buildings along the CER was used to identify functional categories using SE-DenseNet merging channel attention. The results of the model visualized using t-SNE and Grad-CAM were then used to analyze the relationships of facade features across functional categories and differences in elemental feature representation across functional prototypes. The results show the following: (1) SE-Densenet can more efficiently identify building functions from the closely linked facade images of historic building groups, with the average accuracy reaching 85.84%. (2) Urban–rural differences exist not only in the count of spatial distributions among the CER’s historic building groups, but also in a significant visual divergence between functions related to urban life and those involved in the military, industry, and railways. (3) Windows and walls occupy areas with more characteristics, but their decorative elements have a higher intensity of features. The findings could enhance the objective understanding and deeper characteristics of the historical building group system, contributing to integrated conservation and characteristic sustainability.

Dalian, a typical modern colonial city, originated in the late 19th century and was planned and built by Russian architects. Academics have traditionally focused on the unique qualities of the spatial form from the early stages of urban development, but due to a lack of urban history archives, the formation of the spatial form and the planning ideology of this time have not been examined. For this study, we visited the Russian State Historical Archives to search for relevant materials to restore the process of forming Dalian’s spatial form. Based on this, the heritage value and attributes of Dalian’s modern urban spatial form are discussed. The results show that, although Dalian was always under the control of Russian political power at the early stage of its urban construction, the urban planning ideas were integrated with modern Western urban planning ideas. Secondly, under the influence of modern Western urban planning ideas, including “classicalism” and the “garden city”, the modern Dalian urban space gradually formed a unique form and appearance, bearing the brand of the times and urban memory in a special context. Moreover, this study finds that the evolution of urban space is not simply a cumulative development of itself but the result of the influence of external ideas implanted with unique heritage values and attributes.