Population Synthesis, Population Grids and Residential Space

Public space, as one of the most important spatial elements that undergird citizens’ lives in urban areas, has always been a primary interest in urban studies. Most existing studies have been limited to assessing the value of public space from the macroscale perspec- tive, such as the distance to urban centers or visibility with indis- pensable landscapes. At the microscale or human-scale perspective, public space refers to the space that involves residents ’ daily life and affects residents ’ perception most directly ( Long and Ye 2016 ; Miller and Tolle 2016 ; Shen et al. 2017 ). Therefore, the micropublic space is considered to be highly related to urban life quality, such as livability and comfort level. High-quality public space can both frame a good built environment network ( Francis et al. 2012 ), improve the quality of residents ’ leisure life and foster community awareness, creating a more sustainable living space (Talen 2000). Thus, from this perspective, the areas of focus should be the elements and characteristics with which humans physically engage and interact ( Long and Ye 2019 ), such as the form, green- ing, and facilities of the space; the ability to measure such elements remains relatively undeveloped, resulting in the ineffective mea- surement of the value of such spaces ’ quality or presence.

1Scientific Data | (2022) 9:563 | https://doi.org/10.1038/s41597-022-01675-x www.nature.com/scientificdata Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways Xinyu Wang 1,3, Xiangfeng Meng1,3 & Ying Long 2 ✉ Spatially explicit population grid can play an important role in climate change, resource management, sustainable development and other fields. Several gridded datasets already exist, but global data, especially high-resolution data on future populations are largely lacking. Based on the WorldPop dataset, we present a global gridded population dataset covering 248 countries or areas at 30 arc- seconds (approximately 1 km) spatial resolution with 5-year intervals for the period 2020–2100 by implementing Random Forest (RF) algorithm. Our dataset is quantitatively consistent with the Shared Socioeconomic Pathways’ (SSPs) national population. The spatially explicit population dataset we predicted in this research is validated by comparing it with the WorldPop dataset both at the sub- national and grid level. 3569 provinces (almost all provinces on the globe) and more than 480 thousand grids are taken into verification, and the results show that our dataset can serve as an input for predictive research in various fields. Background & Summary Global climate change and sustainable development are receiving increasing attention both from researchers and policymakers1.

Neighborhoods are places where people spend the most time in their lives. Neighborhoods have a decisive impact on the residents' health. With several important tasks, including the transformation of old neighborhoods, the maintenance of existing neighborhoods, and the construction of new neighborhoods in the future, a scientific and reasonable evaluation standard is urgently needed to guide the development of healthy neighborhoods. T o build the evaluation system, this paper first clarifies the principles for selecting evaluation indicators, which include: 1) the indicators are selected from a humanistic perspective; 2) the pathways between neighborhoods environment and health outcomes are deeply considered; 3) the indicators are selected from multiple scales. Secondly, based on the combined perspectives of urban planning and public health, it identifies the indicators that affect the residents' health in neighborhoods and searches the literature through the quality assessment to provide evidence to support the accuracy and effectiveness of the indicators. Finally, it proposes prospect to the evaluation, including 1) it is urgent to improve and utilize the healthy neighborhoods based on the Chinese condition; 2) advanced technologies need to be widely applied in neighborhoods in the future; 3) the transitions in cities should be considered in the future development of neighborhoods. It hopes that relevant researchers and government leaders to realize the importance and urgency of healthy neighborhoods to build more healthy neighborhoods in China.

Population distribution and their temporal variation are a direct proxy of urbanization. This study evaluates the population density vari - ation of China between 2000 and 2010 at the township level by using the data of the fifth and sixth national population censuses. The urbanization patterns of China in 2000 and 2010 are depicted based on the population densities at various levels and the urbanization process of China between 2000 and 2010 is then analyzed through a comparative approach. It also tries to visualize the population density dynamics and urbanization pattern variations of China at the township level.

Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=rsrs20 Download by: [114.250.86.149] Date: 17 March 2016, At: 06:48 Regional Studies, Regional Science ISSN: (Print) 2168-1376 (Online) Journal homepage: http://www.tandfonline.com/loi/rsrs20 Outside the ivory tower: visualizing university students’ top transit-trip destinations and popular corridors Mingshu Wang, Jiangping Zhou, Ying Long & Feng Chen To cite this article: Mingshu Wang, Jiangping Zhou, Ying Long & Feng Chen (2016) Outside the ivory tower: visualizing university students’ top transit-trip destinations and popular corridors, Regional Studies, Regional Science, 3:1, 202-206 To link to this article: http://dx.doi.org/10.1080/21681376.2016.1154798 © 2016 The Author(s). Published by Taylor & Francis Published online: 17 Mar 2016. Submit your article to this journal View related articles View Crossmark data REGIONAL GRAPHIC Outside the ivory tower: visualizing university students ’ top transit-trip destinations and popular corridors Mingshu Wanga, Jiangping Zhou b* , Ying Long c and Feng Chen d aDepartment of Geography, University of Georgia, Athens, GA, United States; bSchool of Geography, Planning and Environmental Management, University of Queensland, Brisbane, QLD, Australia; cSchool of Architecture, Tsinghua University, Beijing, China;

In the past decade, an explosion of data has taken place in Chinese cities due to widespread use of mobile Internet devices, Web 2.0 applications, and the development of the “Wired City. ” With advances in data storage and high-performance computing, big/open urban data have opened up important avenues for urban studies, planning practice, and commercial consultancy. Urban researchers and planners are eager to make use of these abundant, sophisticated, and dynamic data to deepen their understanding on urban form and functions. However, in practice, access to such urban data is limited in China due to institutional constraints on data distribution and data holders’ hesitation to share data. And this hampers urban analytics. To draw reliable conclusions about the workings of complex urban systems, efficient and effective interoperation of multi- source urban datasets is needed. Also, dealing with the heterogeneity between datasets is an equally critical challenge, especially for urban planners and government officers. They would derive value from data analytics, but have little data processing experience. To address these issues, we initiated SinoGrids (Plan Xu Xiake), a crowdsourcing platform that standardizes (or “downscales”) microscale urban data in China to facilitate its sharing and interoperation. To assess the performance evaluation of SinoGrids, we propose field-testing with actual urban data and their potential users. Digital desert, a son project of SinoGrids is also included. ARTICLE HISTORY Received 22 May 2015 Accepted 7 December 2015

保障性住房能够改善受保障对象的居住水平和生活质量 ，具有明显的社会效益 ;但城市政府供给保障房用地也意味着损失较多的土地出让收入 (较高的机会成本 )。保障房的合理选址有赖于对上述社会效益和土地机会成本的理性权衡 ，这需要基于城市低收入和中高收入居民的居住选址偏好 ，寻找那些相对于中高收入居民而言 ，低收入居民更为偏好的区位 ，这样的区位意味着较高的社会效益和较低的机会成本 。本文在北京市 1911个微观区块尺度上 ，以 2010 年北京市城市居民家庭调查的大样本微观数据为基础 ，应用显示性偏好法 (Hedonic模型)分析了两类群体的选址偏好差异 ，量化了他们对各个区块的综合支付意愿水平并进行比较 ，建立并计算了北京市内不同区位的保障房选址适宜性指数 。本研究能够为保障房选址决策提供技术支撑 ， 有助于兼顾保障房社会效益和土地出让收入的财政约束 。

】中国人口密度的时空演变是折射城镇化空间格局的最直接表征。本文利用乡镇和街道尺度的“五普”和“六普”人口资料，对2000一 201 O年中国人口密度的空间分布变化进行初步考察，并基于人口密度视角提出城镇化格局的识别指标，进而分析2000年以来我国城镇格局的演变特征。研究旨在廓清21世纪以来中国人口再分布的变化规律，深化对我国新型城镇化空间格局的基本判断。 【

Individuals together with their locations & attributes are essential to feed micro -level applied urban models (for example, spatial micro -simulation and agent -based modeling) for policy evaluation. Existed studies on population spatialization and population synthesis are generally separated. In dev eloping countries like China, population distribution in a fine scale, as the input for population synthesis, is not universally available. With the open -government initiatives in China and the emerging Web 2.0 techniques, more and more open data are becom ing achievable. In this paper, we propose an automatic process using open data for population spatialization and synthesis. Specifically, the road network in OpenStreetMap is used to identify and delineate parcel geometries, while crowd-sourced POIs are gathered to infer urban parcels with a vector cellular automata model. Housing-related online Check-in records are then applied to distinguish residential parcels from all of the identified urban parcels. Finally the published census data, in which the sub -district level of attributes distribution and relationships are available, is used for synthesizing population attributes with a previously developed tool Agenter (Long and Shen, 2013). The results are validated with ground truth manually-prepared dataset by planners from Beijing Institute of City Planning. Key words: population density; population synthesis; parcel; open data; Agenter Acknowledgments: We acknowledge the financial support of the National Natural Science Foundation of China (No. 51408039). We thank Ms Liqun Chen for her proofreading.