Abstract. The visualization model of GIS and BIM fusion can provide data bearing platform and main technical support for future urban operation centers, digital twin cities, and smart cities. Based on the analysis of the features and advantages of GIS and BIM Fusion, this paper proposes a construction method of the spatio-temporal data visualization platform for GIS and BIM Fusion. It expounds and analyzes the overall architecture design of platform, multi-dimensional and multi-spatial scales visualization, space analysis for GIS and BIM fusion, and platform applications and so on. The urban virtual simulation spatio-temporal data platform project of Teda New District in Tianjin has verified and demonstrated that the effect of application is good. This provides a feasible solution for the construction of spatio-temporal Data Visualization Platform.

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Image segmentation is an important task in image processing and analysis but due to the same ground object having different spectra and different ground objects having similar spectra, segmentation, particularly on high-resolution remote sensing images, can be significantly challenging. Since the spectral distribution of high-resolution remote sensing images can have complex characteristics (e.g., asymmetric or heavy-tailed), an innovative image segmentation algorithm is proposed based on the hierarchical Student’s-t mixture model (HSMM) and spatial constraints with adaptive smoothing. Considering the complex distribution of spectral intensities, the proposed algorithm constructs the HSMM to accurately build the statistical model of the image, making more reasonable use of the spectral information and improving segmentation accuracy. The component weight is defined by the attribute probability of neighborhood pixels to overcome the influence of image noise and make a simple and easy-to-implement structure. To avoid the effects of artificially setting the smoothing coefficient, the gradient optimization method is used to solve the model parameters, and the smoothing coefficient is optimized through iterations. The experimental results suggest that the proposed HSMM can accurately model asymmetric, heavy-tailed, and bimodal distributions. Compared with traditional segmentation algorithms, the proposed algorithm can effectively overcome noise and generate more accurate segmentation results for high-resolution remote sensing images.

Abstract. As a component of smart city, smart community is the community form in the information age. With people's higher pursuit of living environment, safety, convenience and other intelligent aspects, the construction of smart community continues to accelerate. However, there are still some problems such as uneven community safety management level, data island, insufficient quality service projects and lack of participation of residents. This paper studies and practices the construction of smart community based on GIS and tilt photogrammetry. The smart community uses tilt photogrammetry technology to restore the real scene of the community as the data source. The core work of field data acquisition, 3D model construction and monomer modelling of the real scene is carried out. Then, the smart community web terminal is built based on Cesium.js and Vue.js framework, and the mobile terminal is developed by using WeChat applet. The experiment shows that this system can build a communication bridge between managers and users, and it is convenient for property management personnel to carry out accurate positioning verification, inspection, maintenance and timely feedback of community events on the information reported by users in real time. The whole smart community system can provide intelligent and convenient conditions for residents of the community, It can improve the existing management level of the community and provide the valuable technical reference for the current construction of smart communities.