Identification and Geographic Distribution of Accommodation and Catering Centers

Abstract

As the most important manifestation of the activities of the life service industry, the reasonable layout of spatial agglomeration and dispersion of the accommodation and catering industry plays an important role in guiding the spatial structure of the urban industry and population. Applying the contour tree and location quotient index methods, based on points of interest (POI) data of the accommodation and catering industry in Beijing and on the identification of the spatial structure and cluster center of the accommodation and catering industry, we investigated the distribution and agglomeration characteristics of the urban accommodation and catering industry from the perspective of industrial spatial differentiation. The results show that: (1) the accommodation and catering industry in Beijing presents a polycentric agglomeration pattern in space, mainly distributed within a radius of 20 km from the city center and on a relatively large scale; areas beyond this distance contain isolated single cluster centers. (2) From the perspective of the industry, the cluster centers close to the core area of the city are characterized by the agglomeration of multiple advantageous industries, while those in the outer suburbs of the city are more prominent in a single industry. (3) From the perspective of the location quotient of cluster centers, the leisure catering industries are mainly located close to the urban centers. On the contrary, the cluster centers in the outer suburbs and counties are relatively small and dominated by restaurants and fast food industries. Commercial accommodation businesses are mainly distributed in the transportation hub centers and in entertainment and leisure areas.

Importance of Semivolatile/Intermediate-Volatility Organic Compounds to Secondary Organic Aerosol Formation from Chinese Domestic Cooking Emissions

“…Therefore, the contribution of cooking emissions to ambient OA will increase 1.3 times after considering the secondary formation. Assuming the annual cooking operation time for a restaurant is 2160 h year –1 and the number of restaurants is 30,000 in Beijing, the annual POA emission and SOA formation will be 7.0 and 8.9 t, respectively. However, this estimation has great uncertainties.…”

“…Organic aerosols (OA) contribute a significant mass fraction of submicrometer aerosols, , negatively influencing air quality, climates, and human health . Recently, cooking-related organic aerosol (COA) has been proposed as a vital source of urban OA, especially in megacities of China (up to 45% on clean days in Beijing). − With the rapid development of the urban catering industry in China, the effects of cooking emissions on OA should be considered.…”

“…5 Recently, cooking-related organic aerosol (COA) has been proposed as a vital source of urban OA, especially in megacities of China (up to 45% on clean days in Beijing). 6−8 With the rapid development of the urban catering industry in China, 9 the effects of cooking emissions on OA should be considered.…”

Realizing the soft infrastructure mixing of Shanghai's catering industry based on land expansion and population growth

“…The dynamic interplay between urban construction land expansion and the availability, affordability, acceptability, and accessibility of restaurants is key to understanding the development of urban soft infrastructure and the impact of urban planning strategies [ 44 ]. This interplay reflects the complexity of how soft infrastructure adapts to demographic and spatial changes during urbanization, profoundly affecting the sustainable development of cities and the quality of life for residents [ 45 ]. Urban land expansion, typically accompanied by the development of new commercial and residential areas, directly increases the opportunities and locations for restaurant establishments, thereby enhancing restaurant availability.…”

Identifying Centers and Subcenters in the Metropolitan Region of Belo Horizonte Through Google Places of Interest

“…Thus, we propose a two-step approach for identifying urban centers and subcenters in the MRBH that involves: 1-the estimation of spatial distribution density; 2-the construction of a contour tree. This method has been applied in recent studies to identify urban centralities in different cities (DENG et al , 2019 ;HAN;SONG, 2020).…”