(In order of appearance)
LuoJia3-1 Satellite-Intelligent Remote Sensing Satellite Based on Internet
Bio: Professor Deren Li is a scientist in surveying, mapping and remote sensing from Wuhan University, China. He enjoys dual memberships of both Chinese Academy of Sciences and Chinese Academy of Engineering. He is also the member of International Eurasia Academy of Sciences and International Academy of Astronautics. He received doctor degree from University of Stuttgart in 1985 and honorary doctorate from ETH Zürichin 2008. In 2012, International Society for Photogrammetry and Remote Sensing awarded him the Honorary Member, the number of which ISPRS limits to a maximum of ten at any time as the highest honor. In 2020, ISPRS awarded him the Brock Gold Medal in recognition of outstanding contributions to photogrammetry.
Prof. Deren Li was the president of Wuhan Technical University of Surveying and Mapping, and director of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS). At present, he is the honorary director of academic committee of LIESMARS, director of Collaborative Innovation Center of Geospatial Technology, chairman of Wuhan Association for Science and Technology, and chief scientist of Optics Valley of China in Wuhan.
Abstract: This paper mainly describes the first intelligent remote sensing satellitebased on internet, namely theLuoJia3-1. Focusing on the significantdemand for Fast, Accurate and Flexible remote sensing informationservice to customers, this satellite creates a new mode of real-time servicefor intelligent remote sensing satellites on the internet, breaks throughmission-driven high orientation and intelligent processing technology onorbit, and develops new generation remote sensing satellites withmultimode open intelligent interconnection.
Designing Future Cities Using Artificial Intelligence
Bio: Professor Michael Batty is Bartlett Professor of Planning, University College London; Chair, Centre for Advanced Spatial Analysis (CASA); Co-Founder & Chair of the Digital Task Force for Planning. Mike has worked on computer models of cities and their visualisation since the 1970s and his recent publications Cities and Complexity (2005), The New Science of Cities (2013), and Inventing Future Cities (2018) all from The MIT Press. His forthcoming book The Computable City (MIT Press, 2023) is a history of how computers and digital technologies have and are changing the form and function of cities. He is a Fellow of the British Academy (FBA), the Royal Society (FRS), the Academy of Social Sciences and the RTPI. He was awarded the CBE in the Birthday Honours List in 2004. He received the Gold Medal of the Royal Geographical Society (2015) and the Gold Medal of the Royal Town Planning Institute. He has been the editor of Environment and Planning B: Urban Analytics and City Science, since 1982.
Abstract: Figuring out the best locations for urban development has been the quest of urban planning for a century or more. The notion that the determinants of optimal development are based on conflicting degrees of land suitability which can be overlaid and integrated to determine the most suitable locations has been at the basis of plan-design methods since the late 19th century. These methods now represent the essence of GIS and geo-design. In this talk, I will illustrate how we can integrate a series of factors or features using various kinds of weighting structures which can be represented as networks, first linking these ideas to social networks where the factors can be associated with different actors or stakeholders who then resolve their differences between using averaging or pooling processes that can be formalised as recurrent Markov chains. These weighting structures can be thought of as neural nets but with the nets being fixed in advance to optimise the way the factors merge to produce optimal locations. The corollary to these design methods is to determine the weights by training the process of averaging to meet spatial patterns known in advance and we can thus exploit various algorithms based on deep learning to determine the best weighting structures through feedforward neural nets. The association between designing an optimal urban system and understanding an existing one through machine learning has considerable potential for enriching our understanding of how best designs might be accomplished.
Spatiotemporal Analytics, Human Mobility and Health Research
Bio: Professor Meipo Kwan is a Choh-Ming Li professor of Geography and Resource Management and a director of Institute of Space and Earth Information Science at The Chinese University of Hong Kong. Kwan is a Guggenheim Fellow and a Fellow of the U.K. Academy of Social Sciences, the American Association for the Advancement of Science (AAAS), and the American Association of Geographers (AAG). She was named to the 2019 Highly Cited Researchers List compiled by the Web of Science Group as one of the world's most influential researchers. She has received many prestigious honors and awards, including the Distinguished Scholarship Honors, the Wilbanks Prize for Transformational Research in Geography, and the Stanley Brunn Award for Creativity in Geography from the AAG. Kwan had served as an editor of Annals of the American Association of Geographers for 12 years. She has received over US$58.5 million grant support from sources including the U.S. National Institutes of Health, the U.S. National Science Foundation, the U.S. Department of Transportation, the National Natural Science Foundation of China, and the Hong Kong Research Grants Council. She has published over 330 books, journal articles and book chapters. She has delivered over 340 keynote addresses, invited lectures and other invited presentations in more than 20 countries.
Abstract: The rapid development and widespread use of advanced geospatial technologies such as GPS, remote sensing, mobile sensing, and location-aware devices in recent years have greatly facilitated the acquisition of enormous amounts of high-resolution space-time data. To build smart and healthy cities, we need to integrate these multi-source geospatial big data acquired by earth observation technologies and mobile sensing technologies to provide more accurate assessments of individual exposures to environmental or social risk factors, and to develop planning policies to improve health for all. In this presentation, I will discuss how these new developments can provide new insights into the relationships between people’s mobility, health behaviors, and the complex spatiotemporal dynamics of environmental influence Drawing upon my recent projects on individual exposures to green/blue spaces, light-at-night, and air and noise pollution, as well as on COVID-19, I explore how the collection, integration, and analysis of high-resolution space-time data enabled by advanced geospatial and mobile technologies (e.g., real-time mobile sensing and GPS tracking) can help identify the “truly relevant geographic context in space and time” and provide new insights into the relationships between human health, people’s daily mobility, and the complex spatiotemporal dynamics of environmental influences.
Digital Twins for Cities and Regions–An Opportunity, or a Distraction?
Bio: Professor Mark Birkin is Professor of Spatial Analysis and Policy in the School of Geography, Universityof Leeds, and is Programme Director for Urban Analytics and Fellow at The Alan Turing Institute. He has longstanding interests in mathematical modelling of urban and regional systems including geodemographic, microsimulation, agent-based modelling, and spatial decision-support systems.Mark has a notable track record of collaboration, including ten years as an executive directorof Geographical Modelling and Planning (GMAP) Limited. In this time, GMAP developed from occasional consulting projects into a market analytics business with 120 employees and global reach, working with household name partners such as Ford Motor Company, Asda-Walmart,HBoS, Exxon-Mobil and GSK. An ethos of collaboration with external partners in business andthe public sector continues in his current role as Director of the Consumer Data ResearchCentre (CDRC), a national investment within the UKRI Digital Footprints programme. He is also PI for the ESRC Centre for Doctoral Training in DataAnalytics, which coordinates more thaneighty postgraduate research projects intandem with external partners.Since 2014, Mark has been Director of the Leeds Institute for Data Analytics (LIDA). Having started as a partnership between CDRC and the MRC Medical Bioinformatics, LIDA now supportsover 90 projects and programmes with more than £60M of funded research,bringing together over 200 researchers from across all eight faculties at the University.He is a Fellow of the Academy of Social Sciences and a Fellow of the Royal Geographical Society.In 2019, Mark was the recipientto the RGS-IBG Murchison Award for ‘pioneering contributions to urban analytics’.
Abstract: From origins in applied science, digital twins have begun to attract attention within thegeoinformatics community. As with many scientific novelties, debatesregarding their value canquickly become polarised and a nascent backlash is already in evidence. In this talk I will provide a brief review of the digital twin concept, and contextualise the idea withinthe frame of ongoing research priorities in regionalscience and geoinformatics. I’ll provide someexamples from ongoing work at the Alan Turing Institute and across its network of partners, andcomment on the relative merits, actual and potential impact of the work.I will also suggest futurepathways andattempt an evaluation of the long-term importance of digital twins for our discipline.
