Urban resilience from the lens of social media data: Responses to urban flooding in Nanjing, China

Cities - Tập 106 - Trang 102884 - 2020
Bo Wang1,2, Becky P.Y. Loo3,4, Feng Zhen5, Guangliang Xi5
1School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China
2Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
3Department of Geography, The University of Hong Kong, Hong Kong, China
4HKU-Shenzhen Institute of Research and Innovation (HKU-SIRI), Shenzhen, China
5School of Architecture and Urban Planning, Nanjing University, Nanjing, China

Tài liệu tham khảo

Adger, 2005, Social-ecological resilience to coastal disasters, Science, 309, 1036, 10.1126/science.1112122 Burningham, 2008, “It”ll never happen to me’: Understanding public awareness of local flood risk, Disasters, 32, 216, 10.1111/j.1467-7717.2007.01036.x Burton, 2015, A validation of metrics for community resilience to natural hazards and disasters using the recovery from Hurricane Katrina as a case study, Annals of the Association of American Geographers, 105, 67, 10.1080/00045608.2014.960039 Campanella, 2006, Urban resilience and the recovery of New Orleans, Journal of the American Planning Association, 72, 141, 10.1080/01944360608976734 Chae, 2014, Public behavior response analysis in disaster events utilizing visual analytics of microblog data, Computers & Graphics, 38, 51, 10.1016/j.cag.2013.10.008 Chan, 2018, “Sponge City” in China—A breakthrough of planning and flood risk management in the urban context, Land Use Policy, 76, 772, 10.1016/j.landusepol.2018.03.005 Eilander, 2016, Harvesting social media for generation of near real-time flood maps, Procedia Engineering, 154, 176, 10.1016/j.proeng.2016.07.441 Fang, 2019, Assessing disaster impacts and response using social media data in China: A case study of 2016 Wuhan rainstorm, International Journal of Disaster Risk Reduction, 34, 275, 10.1016/j.ijdrr.2018.11.027 Galloway, 2018 Golder, 2011, Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures, Science, 333, 1878, 10.1126/science.1202775 Goodchild, 2007, Citizens as sensors: The world of volunteered geography, GeoJournal, 69, 211, 10.1007/s10708-007-9111-y Guan, 2014, Using social media data to understand and assess disasters, Natural Hazards, 74, 837, 10.1007/s11069-014-1217-1 Haworth, 2015, A review of volunteered geographic information for disaster management, Geography Compass, 9, 237, 10.1111/gec3.12213 Hensher, 2017, Future bus transport contracts under a mobility as a service (MaaS) regime in the digital age: Are they likely to change?, Transportation Research Part A: Policy and Practice, 98, 86 Holling, 1973, Resilience and stability of ecological systems, Annual Review of Ecogoly and Systematics, 4, 1, 10.1146/annurev.es.04.110173.000245 Houston, 2015, Social media and disasters: A functional framework for social media use in disaster planning, response, and research, Disasters, 39, 1, 10.1111/disa.12092 Huang, 2016, Activity patterns, socioeconomic status and urban spatial structure: What can social media data tell us?, International Journal of Geographical Information Science, 30, 1873, 10.1080/13658816.2016.1145225 Huang, 2015, Geographic situational awareness: Mining tweets for disaster preparedness, emergency response, impact, and recovery, ISPRS International Journal of Geo-Information, 4, 1549, 10.3390/ijgi4031549 Johnson, 2014, Advocacy for urban resilience: UNISDR’s making cities resilient campaign, Environment and Urbanization, 26, 29, 10.1177/0956247813518684 Jongman, 2015, Early flood detection for rapid humanitarian response: Harnessing near real-time satellite and Twitter signals, ISPRS International Journal of Geo-Information, 4, 2246, 10.3390/ijgi4042246 Kennedy, 2006, Sentiment classification of movie reviews using contextual valence shifters, Computational Intelligence, 22, 110, 10.1111/j.1467-8640.2006.00277.x Kryvasheyeu, 2016, Rapid assessment of disaster damage using social media activity, Science Advances, 2, 10.1126/sciadv.1500779 Kwan, 2016, Algorithmic geographies: Big data, algorithmic uncertainty, and the production of geographic knowledge, Annals of the American Association of Geographers, 106, 274 Lam, 2015, Measuring community resilience to coastal hazards along the northern Gulf of Mexico, Natural Hazards Review, 17 Lampos, 2016, Inferring the socioeconomic status of social media users based on behaviour and language, 689 Leichenko, 2011, Climate change and urban resilience, Current Opinion in Environmental Sustainability, 3, 164, 10.1016/j.cosust.2010.12.014 Liu, 2014, Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data, PLoS One, 9 Loo, 2012 Loo, 2017, Transport resilience: The occupy central movement in Hong Kong from anther perspective, Transportation Research Part A: Policy and Practice, 106, 100 Loo, 2019, “Mapping” smart cities, Journal of Urban Technology, 26, 129, 10.1080/10630732.2019.1576467 Loo, 2017, Progress of e-development in China since 1998, Telecommunications Policy, 41, 731, 10.1016/j.telpol.2017.03.001 Lu, 2014, Network structure and community evolution on twitter: Human behavior change in response to the 2011 Japanese earthquake and tsunami, Scientific Reports, 4, 6773, 10.1038/srep06773 Mandel, 2012, A demographic analysis of online sentiment during Hurricane Irene, 27 Meerow, 2016, Defining urban resilience: A review, Landscape and Urban Planning, 147, 38, 10.1016/j.landurbplan.2015.11.011 Nahiduzzaman, 2015, Flood induced vulnerability in strategic plan making process of Riyadh city, Habitat International, 49, 375, 10.1016/j.habitatint.2015.05.034 Pregnolato, 2017, The impact of flooding on road transport: A depth-disruption function, Transportation Research Part D: Transport and Environment, 55, 67, 10.1016/j.trd.2017.06.020 Rizza, 2014, Building a resilient community through social network: Ethical considerations about the 2011 Genoa floods, 289 Schnebele, 2013, Improving remote sensing flood assessment using volunteered geographical data, Natural Hazards and Earth System Sciences, 13, 669, 10.5194/nhess-13-669-2013 Schnebele, 2014, Road assessment after flood events using non-authoritative data, Natural Hazards and Earth System Sciences, 14, 1007, 10.5194/nhess-14-1007-2014 Song, 2019, Resilience-vulnerability balance to urban flooding: A case study in a densely populated coastal city in China, Cities, 95, 102381, 10.1016/j.cities.2019.06.012 Statistical Bureau of Nanjing, 2017 Sun, 2016, Mapping floods due to Hurricane Sandy using NPP VIIRS and ATMS data and geotagged Flickr imagery, International Journal of Digital Earth, 9, 427, 10.1080/17538947.2015.1040474 The National Academies, 2012 Thumerer, 2000, A GIS based coastal management system for climate change associated flood risk assessment on the east coast of England, International Journal of Geographical Information Science, 14, 265, 10.1080/136588100240840 United Nations International Strategy for Disaster Reduction, 2009, 2009 global assessment report on disaster risk reduction: Risk and poverty United Nations International Strategy for Disaster Reduction, 2013 United NationsInternational Strategy for Disaster Reduction, 2004 Wang, 2019, The hierarchy of cities in Internet news media and Internet search: Some insights from China, Cities, 84, 121, 10.1016/j.cities.2018.07.013 Wang, 2018, The role of distance in online social networks: A case study of urban residents in Nanjing, China, Cities, 79, 37, 10.1016/j.cities.2018.02.020 Wang, 2017, GIS based social spatial behavior studies: A case study in Nanjing University utilizing mobile data, 320 Wang, 2015, A theoretical framework and methodolgy for urban activity spatial structure in E-society: Empirical evidence for Nanjing City, China, Chinese Geographical Science, 25, 672, 10.1007/s11769-015-0751-4 Wang, 2016, Using social media for emergency response and urban sustainability: A case study of the 2012 Beijing rainstorm, Sustainability, 8, 25, 10.3390/su8010025 Wang, 2018, Social media analytics for natural disaster management, International Journal of Geographical Information Science, 32, 49, 10.1080/13658816.2017.1367003 Weibo Data Center, 2016 Wu, 2018, Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China, Cities, 77, 104, 10.1016/j.cities.2018.01.017 Wu, 2015 Yan, 2019, Exploring the effect of air pollution on social activity in China using geotagged social media data, Cities, 91, 116, 10.1016/j.cities.2018.11.011 Yenneti, 2016, The truly disadvantaged? Assessing social vulnerability to climate change in urban India, Habitat International, 56, 124, 10.1016/j.habitatint.2016.05.001 Yi, 2014, Research trends of post disaster reconstruction: The past and the future, Habitat International, 42, 21, 10.1016/j.habitatint.2013.10.005 Yin, 2012, Using social media to enhance emergency situation awareness, IEEE Intelligent Systems, 27, 52, 10.1109/MIS.2012.6 Yuan, 2016, Nanjing-an ancient city rising in transitional China, Cities, 50, 82, 10.1016/j.cities.2015.08.015 Zhen, 2017, Delineation of an urban agglomeration boundary based on Sina Weibo microblog ‘check-in’ data: A case study of the Yangtze River Delta, Cities, 60, 180, 10.1016/j.cities.2016.08.014 Zheng, 2019, Air pollution lowers Chinese urbanites’ expressed happiness on social media, Nature Human Behaviour, 3, 237, 10.1038/s41562-018-0521-2 Zheng, 2017, Scaling laws of spatial visitation frequency: Applications for trip frequency prediction, Computers, Environment and Urban Systems, 64, 332, 10.1016/j.compenvurbsys.2017.04.004 Zhong, 2010, Study in performance analysis of China urban emergency response system based on Petri net, Safty Science, 48, 755, 10.1016/j.ssci.2010.02.017 Zhou, 2018, A commuting spectrum analysis of the jobs–housing balance and self-containment of employment with mobile phone location big data, Environment and Planning B: Urban Analytics and City Science, 45, 434 Zou, 2018, Mining Twitter data for improved understanding of disaster resilience, Annals of the American Association of Geographers, 108, 1422, 10.1080/24694452.2017.1421897