articles

The effectiveness of modern cities’ functioning depends on the level of development and connectivity of large spatially distributed systems, such as built-up spaces, road networks, engineering infrastructures, and information-communication networks. The consistency of structures of these systems directly affects residents’ access to infrastructure facilities. Urban ­SDS structures evolve under the influence of natural, historical, and anthropogenic factors, demonstrating signs of statistical self-similarity characteristic of stochastic fractal objects. Therefore, applying methods from fractal geometry to study the dynamics of development and self-organization of urban ­SDS has significant potential for planning and modeling transformations of city territories. Classical approaches of fractal analysis are focused on studying general patterns and global characteristics of ­SDS at the city-wide scale. Such data is useful for strategic and tactical planning but insufficient for forming an objective picture at the intra-city territorial units level. To overcome these limitations, it is proposed to perform spatial discretization of the studied ­SDS and obtain two-dimensional maps of spatial fractal data that can be effectively mapped. Building upon the cartograms implemented in the ­DCFA method, a technology for creating schematic maps is proposed, which reflect the distribution of quantitative assessments of fractal dimensionality in the studied urban ­SDS. For quantitatively assessing consistency, a difference map between spatial datasets of the investigated systems is suggested. Additionally, a procedure for calculating an effective sequence of cell sizes for implementing the box-counting algorithm is presented. An example of analyzing the coherence between road networks and urban development in Zelenograd using the proposed procedure is provided.