High-quality topological structures selection for smart city land spatial understanding and governance

Due to the acceleration of urbanization process in modern society, there are many metropolises throughout the world, such as New York, Tokyo, and Shanghai. Such large cities typically have a carefully designed space planning. For example, the residential area should be distant from the industrial area due to the potential environmental pollution issue. In order to cope with public health emergencies, the infrastructure needed for modern urban governance needs to be improved. Notably, establishing a quality visual model to exploit such sophisticated spatial configurations is an important but challenging task. Such a model can facilitate many applications such as urban planning, environmental evaluation, smart transportation, and urban governance. However, the flexible spatial interactions among multiple regions make it difficult to apply a traditional visual model to encode them. In this work, a quality-guided feature selection framework is proposed to obtain a set of highquality topologies to model the discriminative structures from different land spatial city regions. Given a city region from a metropolitan area, the well-known super pixel algorithm SLIC is used to decompose each land spatial city region image into multiple atomic regions. Based on this, a binary graph is used to model the spatial interactions among these regions. Each binary graph is then decomposed into multiple subgraphs and a topology selection algorithm is proposed to discover subgraphs with highly discriminative topologies. By leveraging these high-quality subgraphs, the image kernel machine is used to convert the high quality subgraphs from each city region's image into a feature vector. Afterward, a multi-category support vector machine (SVM) is learned to classify each city region's image into one particular category. Comprehensive experimental results by comparing with many state-of-the-art have shown the competitiveness of this method. Furthermore, the selected high-quality topologies have demonstrated that highly representative spatial interactions are nicely encoded. The results are of great significance to the establishment of the land spatial database management system. (c) 2020 Elsevier B.V. All rights reserved.