Green and Low-Carbon Commuting Evaluation and Optimization of a Cross-Border Metropolitan Region by the Subway Network: The Case of Shenzhen and Hong Kong, China

Abstract

In the context of the One Country–Two Systems policy, Shenzhen and Hong Kong have rapidly grown into a dual-core international metropolis. However, a huge barrier is the commuting cost incurred by the tariff policy, which blocks the road to the high-quality development of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Based on traffic accessibility and kernel density analysis of the subway network and points of interest (POIs) of urban functional areas with ArcGIS, this study analyzed the commute time and convenience level of the functional areas in the two separate tariff zones. The traffic (commute) time in 75 min was taken as the turning point of the efficiency of the Shenzhen–Hong Kong connection, and it was found that both the customs clearance time and the accessible areas show the shape of a parabolic function with an upward opening. It was also found that, in Shenzhen and Hong Kong, the commute time in most of the business, commercial, residential, and industrial areas is 60–75 min. In particular, the comfortable range within 45 min was not achieved. It is necessary to further promote the effectiveness of the Shenzhen–Hong Kong customs clearance system and continuously reduce the customs clearance cost so as to promote the integration of Shenzhen and Hong Kong in order to implement the national strategy of “dual circulation” and innovation-driven development and efficiently drive the coordinated construction of the GBA.

Research on Spatial Patterns and Mechanisms of Live Streaming Commerce in China Based on Geolocation Data

“…Drawing on the existing literature [65][66][67], this paper set the cell size and search radius to the default values, i.e., the coarsest input raster dataset determined the cell size. The use of spatial variables of the "Silverman Rule of Thumb" to calculate the default search radius (bandwidth) for supplier, streamer, and consumer datasets generally avoided the doughnut phenomenon around points that often occur in sparse datasets and prevented spatial outliers (i.e., a few points away from the remaining points) [68], which was well applicable to the data situation in this study (e.g., a frequent occurrence in individual cities within the national scale).…”

The Location and Built Environment of Cultural and Creative Industry in Hangzhou, China: A Spatial Entropy Weight Overlay Method Based on Multi-Source Data

“…(3) Social infrastructure: the creative class tend to congregate in areas with distinctive leisure and entertainment facilities. First, recreational facilities, such as cafes, bars, clubs and studios, are conducive to the exchange and dissemination of tacit knowledge [54]. Second, the accessibility of resources, such as transportation, education and medical care, is also a factor that influences the creative class.…”

Exploring Accessibility and Its Impact in the Mountain City: A Typical Case Study of Nyingchi City, Tibet Autonomous Region, China

“…Therefore, this study, from the viewpoint of traffic-eco-economy-resident coordination [25][26][27][28][29], aims to explore regions with low traffic accessibility in the current traffic and planned network in the mountain city to find effective ways to improve the mountain city's accessibility [30][31][32][33]. It also analyzes the range of residential areas affected by changes in traffic accessibility and their possible industrial choice in the mountain city.…”