Suchergebnisse

As an overarching policy and development model, transit-oriented development (TOD) is widely used to promote the integration of land use and transit services, which arguably brings about many benefits. TOD advocates have continuously paid much attention to metro station areas (MSAs), i.e., areas within a reasonable walking distance to a metro station. To TOD advocates, well-planned MSAs should have a sufficient supply of TOD-nesses encapsulating characteristics such as destinations, density, diversity, and design. In the existing scholarship, however, little has been done on (a) TOD-nesses' potential "consumers," the population that is only a short metro ride away from an MSA, i.e., the metro-based accessibility (MBA) to the consumers of the MSA; and (b) whether and how TOD-nesses of one MSA and several MSAs in proximity are affected by the MBA. With the help of big and/or open data, we examine whether and to what degree the MBA of an MSA cluster (MSAC), a set of MSAs within t minutes of a metro ride from a metro station is correlated to that MSAC's TOD-nesses in Shenzhen, China. We measure the MBA by the daytime/nighttime population in the same MSAC. We quantify TOD-nesses using the published indices or the averages of the indices in a refereed article. Coefficient of geography association, Gini index, pairwise correlation, and linear regression analyses are carried out. We find that the MBA in one period significantly predicts MSAC-level TOD-nesses in ensuing periods. However, the MBA's prediction power decreases or even disappears over time. Besides, metro station characteristics such as the jurisdiction membership significantly predict the overall TOD-nesses and individual aspects of the TOD-nesses after controlling for the MBA. Our study thus sheds new light on meso- or MSAC-level TOD-nesses and related policy and planning evaluation.

The beginning of 2020 has seen coronavirus spreading to many countries and regions. To contain the virus, China adopted, arguably, the most stringent quarantine countermeasures in the country's history concerning restricting people flows, limiting outdoor activities, and extending the Spring Festival break. On the one hand, thousands of doctors and nurses directly fought and are still fighting coronavirus in various medical facilities; on the other hand, millions and even billions of residents and tourists self-quarantined and are still self-quarantining themselves in their homes (or temporary homes), fighting the virus in another manner. Across cities and regions, which have the highest percentage of "fighters" at home? To answer this, we downloaded and processed the publicly available Baidu Qianxi (migration) data for 11 consecutive days in 2019 and 2020. Then we geovisualized the answer. The visual indicates that several cities in Hubei, as expected, had the highest percentage, followed by several cities in Zhejiang Province and several cities in Guangxi Zhuang Autonomous Region and Hainan Province. In terms of percentage ranking across regions, East China is no.1.

Like pubs in Western countries, restaurants in China are not just places where people consume drinks and eat food. They are also venues where acquaintances, friends, colleagues and families meet, relax, entertain, talk and socialize. In the era of fast-paced life, Fordism, easy online ordering and increased metro mobility, what could happen to restaurants in cities? To answer this, we collected and processed two distinct years (2014 and 2017) of point of interest and metro network data in Shenzhen, China. The visuals based on the data indicate that most metro station areas saw the advent of new restaurants as Shenzhen expanded its metro network, shortening the average travel time by transit between the two officially designated central business districts (CBDs): Luohu and Futian. Several metro station areas in or around the CBDs enjoyed the most growth in new restaurants. In terms of the 10 metro station areas that experienced the greatest decline in the number of restaurants, five of them were in areas that were around 15 minutes' metro travel from the CBDs. The remaining five scattered within suburbs rather than exurbs.

As more and more metro lines and stations have started serving our metropolises, they have (re)shaped our travels and lives, creating (new) venues and (additional) opportunities for serendipitous contacts. To know the odds and locales of serendipitous contacts among millions of metro riders, we employ the smartcard data of the metro riders in Beijing to visualize metro riders' identifical trip trajectories and to visualize/disclose connections between metro station pairs because of these trajectories. We find that the pairs that produce the largest and smallest numbers of identifical trip trajectories are not randomly distributed in the city. Rather, they concentrate in the northwest and in the central, respectively.

In contemporary cities, the catering sector is much more than only food and/or eating. On the one hand, it is an important source of income, employment and waste; on the other hand, it provides many opportunities for eating out and social interaction. For a given city, where does the catering sector concentrate the most and how far are people, on average, from this location across hours of a day? Are people, on average, closer to the concentration around the prime dinner time? Taking advantage of open and big data, we geovisualised the answers in the context of Beijing, the capital of China, with a population of 22+ million people. Specifically, the data we used were the 2015 points of interest of Baidu Map (the Chinese counterpart of Google Maps) and 10–16 August 2015 cellular network data for Beijing. The former provide us with the number and location of most if not all restaurants around the local metro-served area (MSA) – that is, areas that are within an 800-metre radius of a metro station. The latter allow us to derive the average number of cellular phone users (as a proxy for the general population, residents and/or employees) by MSA across hours of a day. We depict the top five population/employment/residential centres (quantified by the average number of cellular phone users) at three different times of the day, and the top 10 food centres (measured by the number of restaurants) at the MSA level in Beijing.

China is generally considered a safe place: among the safest for foreigners to visit. For local (long-term) residents and for Chinese criminology scholars, China as a country and its individual cities might be safer compared to many of their foreign peers; however, they might not be as safe as some travel agents claim. To show why this is the case, we crawled and geovisualized the 2015–2016 crime records ( n = 24,803) available to the public online. The geovisualization shows that the seven crimes ( n = 12,516) that were most likely to be influenced by space in Beijing were aggravated assault, blackmail, cheating and bluffing, dangerous driving, picking quarrels and provoking trouble, robbery and theft. It also shows a Beijing that many might not have known before.