Correction: Realistic characteristics and driving mechanisms of pseudo-human settlements in Chinese cities

[1]  Xiangming Xiao,et al.  Spatial-Temporal Patterns of Network Structure of Human Settlements Competitiveness in Resource-Based Urban Agglomerations , 2022, Frontiers in Environmental Science.

[2]  F. Sun,et al.  Global gridded GDP data set consistent with the shared socioeconomic pathways , 2022, Scientific data.

[3]  M. Song,et al.  Global 1 km × 1 km gridded revised real gross domestic product and electricity consumption during 1992–2019 based on calibrated nighttime light data , 2022, Scientific data.

[4]  Chaogui Kang,et al.  Understanding China’s urban system evolution from web search index data , 2022, EPJ Data Sci..

[5]  Xueming Li,et al.  Coupling Coordination of Urban Pseudo and Reality Human Settlements , 2022, Land.

[6]  Hyun-Woo Lim,et al.  How South Korean Internet users experienced the impacts of the COVID-19 pandemic: discourse on Instagram , 2022, Humanities and Social Sciences Communications.

[7]  Jin Liu,et al.  The impact of online education on carbon emissions in the context of the COVID-19 pandemic – Taking Chinese universities as examples , 2022, Applied Energy.

[8]  Xueming Li,et al.  Spatiotemporal evolution of pseudo human settlements: case study of 36 cities in the three provinces of Northeast China from 2011 to 2018 , 2022, Environment, Development and Sustainability.

[9]  Shaolong Sun,et al.  A novel multi-modal analysis model with Baidu Search Index for subway passenger flow forecasting , 2022, Eng. Appl. Artif. Intell..

[10]  T. Wei,et al.  Temporal–Spatial Evolution and Influencing Factors of Coordinated Development of the Population, Resources, Economy and Environment (PREE) System: Evidence from 31 Provinces in China , 2021, International journal of environmental research and public health.

[11]  Kaifang Shi,et al.  Remotely sensed nighttime lights reveal China's urbanization process restricted by haze pollution , 2021, Building and Environment.

[12]  Q. Han,et al.  Coordinated development of the economy, society and environment in urban China: a case study of 285 cities , 2021, Environment, Development and Sustainability.

[13]  Ming Zhang,et al.  Exploring the effect of air pollution on settlement intentions from migrants: Evidence from China , 2021, Environmental Impact Assessment Review.

[14]  Qiang Zhou,et al.  Quantitative Evaluation of Urban Expansion using NPP-VIIRS Nighttime Light and Landsat Spectral Data , 2021, Sustainable Cities and Society.

[15]  Jun Yang,et al.  Suitability of human settlements in mountainous areas from the perspective of ventilation: A case study of the main urban area of Chongqing , 2021 .

[16]  Yongwei Liu,et al.  Spatial Characteristics of the Tourism Flows in China: A Study Based on the Baidu Index , 2021, ISPRS Int. J. Geo Inf..

[17]  Guangfei Yang,et al.  Correlation between PM2.5 pollution and its public concern in China: Evidence from Baidu Index , 2021 .

[18]  Xun Zhu,et al.  Quantifying emotional differences in urban green spaces extracted from photos on social networking sites: A study of 34 parks in three cities in northern China , 2021, Urban Forestry & Urban Greening.

[19]  Santhosh Kumar,et al.  Research of Urban Area Structure Mixing and Human Activity Space from Citizen Activity Perspectives , 2021, 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS).

[20]  Yunsong Chen,et al.  PM2.5 exposure and anxiety in China: evidence from the prefectures , 2021, BMC Public Health.

[21]  Qihao Weng,et al.  Characterizing urban land changes of 30 global megacities using nighttime light time series stacks , 2021 .

[22]  Yutian Lu,et al.  Adaptability evaluation of human settlements in Chengdu based on 3S technology , 2021, Environmental Science and Pollution Research.

[23]  S. Qureshi,et al.  Fine-grained assessment of greenspace satisfaction at regional scale using content analysis of social media and machine learning. , 2021, The Science of the total environment.

[24]  Xiaohua Yang,et al.  A two-stage system analysis of real and pseudo urban human settlements in China , 2021 .

[25]  C. Bauch,et al.  Debates about vaccines and climate change on social media networks: a study in contrasts , 2020, Humanities and Social Sciences Communications.

[26]  Yulin Zhao,et al.  Analysis and Prediction of "AI + Education" Attention Based on Baidu Index - Taking Guizhou Province as an Example , 2021, Future Internet.

[27]  Xiaolei Zhang,et al.  Driving forces of carbon dioxide emissions in China’s cities: An empirical analysis based on the geodetector method , 2020 .

[28]  B. Surya,et al.  Spatial Transformation of a New City in 2006–2020: Perspectives on the Spatial Dynamics, Environmental Quality Degradation, and Socio—Economic Sustainability of Local Communities in Makassar City, Indonesia , 2020 .

[29]  Jiansheng Wu,et al.  Using DMSP/OLS nighttime light data and K–means method to identify urban–rural fringe of megacities , 2020 .

[30]  Dinesh Kumar Vishwakarma,et al.  Fake news, rumor, information pollution in social media and web: A contemporary survey of state-of-the-arts, challenges and opportunities , 2020, Expert Syst. Appl..

[31]  Guofeng Wu,et al.  Quantifying the bias in place emotion extracted from photos on social networking sites: A case study on a university campus , 2020, Cities.

[32]  Linchuan Yang,et al.  A geographically weighted regression model augmented by Geodetector analysis and principal component analysis for the spatial distribution of PM2.5 , 2020 .

[33]  Yongqing Zhao,et al.  Correlation Studies between Land Cover Change and Baidu Index: A Case Study of Hubei Province , 2020, ISPRS Int. J. Geo Inf..

[34]  Yingcheng Li,et al.  Towards concentration and decentralization: The evolution of urban spatial structure of Chinese cities, 2001-2016 , 2020, Comput. Environ. Urban Syst..

[35]  Ali A. Ghorbani,et al.  An overview of online fake news: Characterization, detection, and discussion , 2020, Inf. Process. Manag..

[36]  Yangli Zhang,et al.  The Application of the Fuzzy Analytic Hierarchy Process in the Assessment and Improvement of the Human Settlement Environment , 2020, Sustainability.

[37]  Norjihan Abdul Ghani,et al.  Social media big data analytics: A survey , 2019, Comput. Hum. Behav..

[38]  C. Ratti,et al.  Exploring the effect of air pollution on social activity in China using geotagged social media check-in data , 2019, Cities.

[39]  Xun Li,et al.  Identifying urban spatial structure and urban vibrancy in highly dense cities using georeferenced social media data , 2019, Habitat International.

[40]  Shaohua Wang,et al.  Extraction and monitoring approach of dynamic urban commercial area using check-in data from Weibo , 2019, Sustainable Cities and Society.

[41]  Matthew E. Kahn,et al.  Air pollution lowers Chinese urbanites’ expressed happiness on social media , 2019, Nature Human Behaviour.

[42]  Jorge E. Patiño,et al.  Spatiotemporal dynamics of urban growth in Latin American cities: An analysis using nighttime light imagery , 2019, Landscape and Urban Planning.

[43]  Becky P.Y. Loo,et al.  The hierarchy of cities in Internet news media and Internet search: Some insights from China , 2019, Cities.

[44]  N. Gavin.  Media definitely do matter: Brexit, immigration, climate change and beyond , 2018, The British Journal of Politics and International Relations.

[45]  David W. S. Wong,et al.  Comparing implementations of global and local indicators of spatial association , 2018, TEST.

[46]  Lei Wang,et al.  Comparative Analysis of Urban Competitiveness in the Yangtze River Delta and Pearl River Delta Regions of China, 2000–2010 , 2017 .

[47]  Wei Song,et al.  A New Approach for Detecting Urban Centers and Their Spatial Structure With Nighttime Light Remote Sensing , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[48]  Michael Jendryke,et al.  Putting people in the picture: Combining big location-based social media data and remote sensing imagery for enhanced contextual urban information in Shanghai , 2017, Comput. Environ. Urban Syst..

[49]  Xueming Li,et al.  Initial Evaluation of Provincial-Level Environmental Risks from the Perspective of Human Settlements , 2016 .

[50]  Xiangfeng Luo,et al.  Discovering the core semantics of event from social media , 2016, Future Gener. Comput. Syst..

[51]  Tonglin Zhang,et al.  A measure of spatial stratified heterogeneity , 2016 .

[52]  Yinghua Huang,et al.  Big Data Analytics on Aviation Social Media: The Case of China Southern Airlines on Sina Weibo , 2016, 2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService).

[53]  Wenwu Tang,et al.  Analysis of spatial patterns of public attention on housing prices in Chinese cities: A web search engine approach , 2016 .

[54]  Parsa Ghaffari,et al.  Opinion Mining and Sentiment Polarity on Twitter and Correlation between Events and Sentiment , 2016, 2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService).

[55]  Michael S. Bernstein,et al.  Empath: Understanding Topic Signals in Large-Scale Text , 2016, CHI.

[56]  M. Tsou,et al.  Research challenges and opportunities in mapping social media and Big Data , 2015 .

[57]  Jianping Wu,et al.  Poverty Evaluation Using NPP-VIIRS Nighttime Light Composite Data at the County Level in China , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[58]  Elizabeth C. Delmelle,et al.  Five decades of neighborhood classifications and their transitions: A comparison of four US cities, 1970–2010 , 2015 .

[59]  Pascal Frossard,et al.  Multiscale event detection in social media , 2014, Data Mining and Knowledge Discovery.

[60]  Jianfa Shen,et al.  Analyzing Urban Competitiveness Changes in Major Chinese Cities 1995–2008 , 2014 .

[61]  Zhigang Cao,et al.  Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events , 2013, 1304.3898.

[62]  Shixin Wang,et al.  Population spatialization in China based on night-time imagery and land use data , 2011 .

[63]  Maarten van Zalk,et al.  How the internet is changing the implementation of traditional research methods, people’s daily lives, and the way in which developmental scientists conduct research , 2010 .

[64]  D. Bruce,et al.  The use of night-time lights satellite imagery as a measure of Australia's regional electricity consumption and population distribution , 2010 .

[65]  Xiaoying Zheng,et al.  Geographical Detectors‐Based Health Risk Assessment and its Application in the Neural Tube Defects Study of the Heshun Region, China , 2010, Int. J. Geogr. Inf. Sci..

[66]  Piet Schenelaars,et al.  Public opinion , 2013, BDJ.

[67]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[68]  W. Tobler.  A Computer Movie Simulating Urban Growth in the Detroit Region , 1970 .