<p><strong>Abstract.</strong> Problems of processing of point clouds of airborne laser scanning using different software for Smart City projects are considered. Results of comparison of suitable software on the base of a test point cloud are presented. For comparison we had chosen a criterion for how results of point cloud processing can be used in the smart city application. The following software were chosen for comparison: Erdas IMAGINE, ENVI Lidar, TerraSolid (without Terraslave), GlobalMapper, Autodesk InfraWorks. Comparison have been conducted in qualitative and quantitative terms. The results presented allowed us to create recommendations on the usage of specific software for airborne laser scanning data processing for Smart City projects.</p>
The article analyzes the master plans and functional areas of 42 cities from different federal districts of the Russian Federation. To identify the dependencies between the characteristics of localities and the allocation of functional zones in them, the data clustering method was applied. Also criteria for clustering were identified – these are quantitative characteristics that are universal for various localities: total area of a locality, population, population density and gross regional product. With these criteria clustering was carried out using the software package «Deductor», based on algorithms of neural network modeling. Self-organizing Kohonen maps (SOM) were used to visualize the obtained data. As a result of the clustering the connection between the characteristics of localities and the ratio of functional zones in them is revealed.
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