CRII: III: Understanding Urban Vibrancy: A Geographical Learning Approach Employing Big Crowd-Sourced Geo-Tagged Data

充满活力的社区被定义为具有以下特征的地方：渗透性、生命力、多样性、可访问性、认同感和易读性。发展充满活力的社区有助于促进商业活动、加强公共安全、促进社会互动，从而创造出宜居、可持续和可行的环境。随着移动和传感技术的出现，从城市空间的不同来源(如建筑物、车辆、人、传感器、设备)获得的大型众包地理标记数据(BCGD)越来越多，为了解城市活力和促进智能增长提供了宝贵的情报来源。该项目将开发新颖、系统和有效的分析技术，通过利用BCGD的丰富资源，显著推进城市活力中的关键问题。在这个项目中开发的算法和工具将直接影响社区规划、城市治理和城市经济学。该项目的教育部分包括开发一门新课程，将研究纳入课堂，并为来自代表性不足群体的学生提供参与研究的机会。该项目将开发新的分析技术，以发现、分析和利用BCGD内部的模式和BCGD之间的关系，以了解和维持城市活力。将从三个方向设计适合城市活力的新方法：测量、模式和机制。在研究测量方面，将引入衡量城市活力的指标应满足的公理，并将设计原则性指标来评估社区活力并了解其如何分布。在模式研究中，将提出一个分析框架，从城市活力的BCGD中发现复杂的空间形态模式。该框架旨在确定相容的维度和相应的测量方法，以及空间配置的最佳组合和地理呈现。在研究机制方面，将开发新的机器学习模型，通过利用空间观和移动性观之间的一致性以及地理相关性的规律性来研究空间配置对城市活力的影响。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Vibrant communities are defined as places with the following features: permeability, vitality, variety, accessibility, identity, and legibility. Developing vibrant communities can help boost commercial activities, enhance public security, foster social interaction and, thus, yield livable, sustainable, and viable environments. With the advent of the mobile and sensing technologies, big crowd-sourced geo-tagged data (BCGD) are increasingly available from diverse sources (e.g., buildings, vehicles, human, sensors, devices) in urban space, and represent an invaluable source of intelligence for understanding urban vibrancy and enhancing smart growth. This project will develop novel, systematical, and effective analytical techniques to significantly advance critical problems in urban vibrancy by taking advantage of the wealth of BCGD. The algorithms and tools developed in this project will directly impact community planning, city governance, and urban economics. The educational component of this project includes developing a new curriculum that incorporates research into the classroom and provides students from under-represented groups with opportunities to participate in research.This project will develop new analytical techniques to discover, analyze, and leverage the patterns within and the relationships among BCGD to understand and sustain urban vibrancy. Novel methodologies that are appropriate to urban vibrancy will be designed in three directions: measurements, patterns, and mechanism. In researching measurements, axioms that a metric of urban vibrancy should satisfy will be introduced, and principled metrics will be devised to evaluate community vibrancy and learn how it is distributed. In researching patterns, an analytic framework will be proposed to discover the complex patterns of spatial configuration from BCGD for urban vibrancy. This framework aims to identify the compatible dimensions and corresponding measuring methods, as well as optimal portfolios and geographic presentation of spatial configuration. In researching mechanism, new machine learning models will be developed to examine the impact of spatial configuration on urban vibrancy by exploiting the conformity between spatial view and mobility view and the regularity of geographic dependencies.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.