Urbanization and urban modernization are the main driving forces of socio-economic development [1
]. It is predicted that by 2050, about 64% of the developing world and 86% of the developed world will be urbanized, with more than half of the world’s population living in urban areas [3
]. These changes pose a significant challenge to urban infrastructure and services, and increase the demand for the orderly management of cities [4
]. In this regard, a digital city management system can be used to manage a city’s assets in an advanced way. This integrates geographic information systems (GIS), information and communication technology (ICT), and internet of things technology (IoT) to drive the informatization, intellectualization, and automation in city management [6
One of the main objects of a digital city management system is the city component itself, which incorporates the urban environment and citizen activities [8
]. The China National Standard defines the city component as a combination of urban public facilities, transport facilities, urban appearance and environmental facilities, landscaping facilities, and other elements [9
]. To effectively incorporate these into a digital city management system, object identification technology is used to label every component with a digital code [10
]. Identification codes, which are assigned according to a unified framework, help to improve the standardization of city component management and enhance the construction of a digital city management system. It is therefore important to examine the identification code for city components, which is the basis of city component digitalization.
Currently, identification systems usually have various application requirements and business parameters, so city components are encoded separately within different frameworks. Mostly, these codes work well within the system boundaries, but do not guarantee a consistent code for the same component across different systems. Take a fire hydrant, for example: the water department is responsible for its water supply, the fire department uses it for fire control, and the municipal department is also involved in managing its maintenance. Each department holds an identification code for this fire hydrant, which is usually different from that of the others. As a result, when sharing and operating data across systems, it takes extra effort to use different data dictionaries to match common elements, thereby reducing management efficiency and increasing costs. A popular solution to this problem is to integrate the administrative division code, category code, and sequence code to form a unified coding framework [12
]. This unified code has been used in a city components census [13
] and urban grid management [14
]. However, the administrative division code only contains spatial information at the urban scale, which is too large for accurate positioning, and thus is limited in its application. Li proposed a method to identify the city components by integrating a spatial information grid code and an object code [15
]. This contained administrative division codes at four different scales and could represent more detailed location information. It was used in the city management and service system in Wuhan, China [6
], however, it did not contribute to spatial analysis and geospatial computation in a geographic information system, as the administrative regions are irregularly shaped and are coded by sequential numbers.
In this paper, we propose an improved identification code for city components, using the discrete global grid system (DGGS) for geo-referencing [17
]. DGGS divides the Earth’s surface into grids with multiple levels, thereby forming a hierarchy of multi-resolution grids [19
]. Each grid is indexed by a one-dimensional integer code, with its location being represented explicitly [21
]. The grid code can also be used in spatial analysis and geospatial computation [23
]. Using the grid code to identify and manage city components can build a logical association between the location information and identification codes. Therefore, it may enhance the efficient management of city components and improve the overall service that is provided by a digital city management system.
With rapid urbanization, city management has become digitized. The city component is a key element, whose identification process plays an important role in digital city management. This paper proposes an improved method for identifying city components based on the discrete global grid system. According to their spatial location, city components were identified with one-dimensional integer codes. These codes were of universal utility across systems, explicitly expressing accurate location and implicitly expressing spatial relationships. On this basis, they were used for data queries and geospatial computation. They performed much better than the traditional codes. Therefore, we conclude that the improved identification code is conducive to the more efficient management of city components, and hence may be used to improve digital city management.