Phase II I/UCRC Harvard: Center for Spatiotemporal Thinking, Computing and Applications (STCA)

II 期 I/UCRC 哈佛大学：时空思维、计算和应用中心 (STCA)

• 批准号: 1841403
• 负责人: Sankaran Subramanian
• 金额: $ 50万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841403&HistoricalAwards=false
• 关键词: Phase; II; UCRC; Harvard; Center

Everything happens at some place, some time. Through collaboration among George Mason University, University of California at Santa Barbara, and Harvard University, this project builds national spatiotemporal capacity and advances education and research. This project aims to acquire superior knowledge of spatiotemporal principles, build computational infrastructure capable of processing big spatiotemporal data efficiently, develop insights on how to apply these principles and capabilities to solve real-world problems, and implement educational programs with state-of-the-art spatiotemporal curricula in order to understand our world better, to respond to regional and global emergencies in a timely way, and to prepare the next generation's workforce. As a center, the three universities will collaborate with industry, government agencies, and other organizations to form a leading national and international consortium for building a comprehensive infrastructure base for spatiotemporal thinking, computing, and application; conducting research to develop spatiotemporal thinking and its methodologies; developing new spatiotemporal technologies, solutions, datasets, tools, and software that will be integrated with existing and future industry products and services; building demonstrative applications for government agencies and organizations to improve the impact and reach of this work; and formulating new educational methodologies and materials to advance human knowledge for the public. The center will be a platform for academia, industry, and agencies to collaborate to achieve fundamental and discipline-wide results. Members from academia will get unique opportunities to interact with industry and agencies to understand real world problems and research needs. Industry members will be able to access the research results and turn them into future products and services to improve their competitiveness. Agencies will be able to apply the research results, incorporating them into their operations for better efficiency. The products, services, and operations will serve thousands to millions of end users, from the public and K-16 to professionals. Research results will be presented in international conferences or symposiums; published in Geographic Information System (GIS) journals or books; shared as code packages in GitHub (https://github.com/cga-harvard), posted on the center website (https://www.stcenter.net/), and circulated as center published newsletters, posters or flyers. Platforms developed by this project will be publicly accessible (as approved by the sponsoring board members).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.

任何事情都会在某个地方、某个时间发生。通过乔治梅森大学、加州大学圣巴巴拉分校和哈佛大学的合作，该项目建设了国家时空能力，促进了教育和研究。该项目旨在获取时空原理的高级知识，建立能够高效处理大型时空数据的计算基础设施，深入了解如何应用这些原理和能力来解决现实世界的问题，并利用最先进的时空课程实施教育计划，以便更好地了解我们的世界，及时应对区域和全球紧急情况，并为下一代劳动力做好准备。作为中心，这三所大学将与行业、政府机构和其他组织合作，组成一个领先的国家和国际联盟，以建设时空思维、计算和应用的综合基础设施基地；开展研究以开发时空思维及其方法；开发新的时空技术、解决方案、数据集、工具和软件，这些技术、解决方案、数据集、工具和软件将与现有和未来的行业产品和服务相集成；为政府机构和组织构建示范应用程序，以提高这项工作的影响和覆盖范围；并制定新的教育方法和材料，以促进公众的人类知识。该中心将成为学术界、产业界和机构合作取得基础性和跨学科成果的平台。来自学术界的成员将获得与行业和机构互动的独特机会，以了解现实世界的问题和研究需求。业界成员将能够获得研究成果，并将其转化为未来的产品和服务，以提高自己的竞争力。各机构将能够应用研究成果，将它们纳入到他们的业务中，以提高效率。产品、服务和运营将服务于数千到数百万最终用户，从公众和K-16到专业人士。研究成果将在国际会议或研讨会上发表；在地理信息系统(地理信息系统)期刊或书籍上发表；在GitHub(https://github.com/cga-harvard)，)中以代码包的形式分享；在中心网站(https://www.stcenter.net/)，)上张贴，并作为中心发布的通讯、海报或传单分发。该项目开发的平台将向公众开放(由赞助商董事会成员批准)。该奖项反映了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。

项目成果

Developing the Chinese Academic Map Publishing Platform

开发中国学术地图出版平台

• DOI: 10.3390/ijgi8120567
• 发表时间: 2019
• 期刊: ISPRS International Journal of Geo-Information
• 影响因子: 3.4
• 作者: Xu, Yongming;Lewis, Benjamin;Guan, Weihe Wendy
• 通讯作者: Guan, Weihe Wendy

Large-Scale High-Resolution Coastal Mangrove Forests Mapping Across West Africa With Machine Learning Ensemble and Satellite Big Data

• DOI: 10.3389/feart.2020.560933
• 发表时间: 2021-01
• 作者: Xue Liu;T. Fatoyinbo;N. Thomas;W. Guan;Y. Zhan;P. Mondal;D. Lagomasino;M. Simard;C. Trettin;Rinki Deo;Abigail Barenblitt

A multiscale measure of spatial dependence based on a discrete Fourier transform

• DOI: 10.1080/13658816.2021.2017440
• 发表时间: 2021-12
• 期刊: International Journal of Geographical Information Science
• 影响因子: 5.7
• 作者: Hanchen Yu;S. Fotheringham

A spatiotemporal data collection of viral cases for COVID-19 rapid response

• DOI: 10.1080/20964471.2020.1844934
• 发表时间: 2021-01-01
• 期刊: BIG EARTH DATA
• 影响因子: 4
• 作者: Sha, Dexuan;Liu, Yi;Yang, Chaowei
• 通讯作者: Yang, Chaowei

A Systematic Spatial and Temporal Sentiment Analysis on Geo-Tweets

• DOI: 10.1109/access.2019.2961100
• 发表时间: 2020-01-01
• 期刊: IEEE ACCESS
• 影响因子: 3.9
• 作者: Hu, Tao;She, Bing;Clunis, Julaine
• 通讯作者: Clunis, Julaine