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Land use discovery based on Volunteer Geographic Information classification
16 references·5 citing·46 second hop
Land use discovery based on Volunteer Geographic Information classification (2019)Land use discovery based on Volunteer Geo…The Livehoods Project: Utilizing Social Media to Understand the Dynamics of a City (2021)The Livehoods Project: Utiliz…Describing and comparing landscapes using tags, texts, and free lists: an interdisciplinary approach (2018)Describing and comparing land…Beyond Spatial Proximity—Classifying Parks and Their Visitors in London Based on Spatiotemporal and Sentiment Analysis of Twitter Data (2018)Beyond Spatial Proximity—Clas…Extracting urban functional regions from points of interest and human activities on location‐based social networks (2017)Extracting urban functional r…City dynamics through Twitter: Relationships between land use and spatiotemporal demographics (2017)City dynamics through Twitter…The geography of Twitter topics in London (2016)The geography of Twitter topi…Participatory Cultural Mapping Based on Collective Behavior Data in Location-Based Social Networks (2016)Participatory Cultural Mappin…Crowdsourcing functions of the living city from Twitter and Foursquare data (2016)Crowdsourcing functions of th…Social Sensing: A New Approach to Understanding Our Socioeconomic Environments (2015)Social Sensing: A New Approac…Comparing and modelling land use organization in cities (2015)Comparing and modelling land …Spectral clustering for sensing urban land use using Twitter activity (2014)Spectral clustering for sensi…Mining Urban Deprivation from Foursquare: Implicit Crowdsourcing of City Land Use (2014)Mining Urban Deprivation from…Home Location Identification of Twitter Users (2014)Home Location Identification …Exploiting Foursquare and Cellular Data to Infer User Activity in Urban Environments (2013)Exploiting Foursquare and Cel…Exploring place through user-generated content: Using Flickr to describe city cores (2010)Exploring place through user-…Citizens as sensors: the world of volunteered geography (2007)Citizens as sensors: the worl…Providing climate change resilient land-use transport projects with green finance using Z extended numbers based decision-making model (2023)Providing climate change resi…Human mobility forecasting with region-based flows and geotagged Twitter data (2022)Human mobility forecasting wi…Application of Social Sensors in Natural Disasters Emergency Management: A Review (2022)Application of Social Sensors…A survey of location-based social networks: problems, methods, and future research directions (2021)A survey of location-based so…Predicting retail business success using urban social data mining (2020)Predicting retail business su…Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Discovering regions of different functions in a city using human mobility and POIs (2012)Computational socioeconomics (2019)Delineating urban functional use from points of interest data with neural network embedding: A case study in Greater London (2021)Find me if you can (2010)You are where you tweet (2010)Friendship and mobility (2011)Geotagging one hundred million Twitter accounts with total variation minimization (2014)A survey of location inference techniques on Twitter (2015)Crowd sourcing disaster management: The complex nature of Twitter usage in Padang Indonesia (2016)Why we tag (2007)Geographic Information Analysis (2010)Extracting and understanding urban areas of interest using geotagged photos (2015)Social media analytics for natural disaster management (2017)Social-media data for urban sustainability (2018)Space and Place: The Perspective of Experience. (1978)Crowdsourcing geographic information for disaster response: a research frontier (2010)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Measuring human perceptions of a large-scale urban region using machine learning (2018)GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond (2019)Mapping the world's photos (2009)Emotions in context: examining pervasive affective sensing systems, applications, and analyses (2015)Inferring individual daily activities from mobile phone traces: A Boston example (2015)Crowdsourced Data Mining for Urban Activity: Review of Data Sources, Applications, and Methods (2020)An Empirical Study of Geographic User Activity Patterns in Foursquare (2021)Bowling alone: the collapse and revival of American community (2000)Bowling Alone: The Collapse and Revival of American Community (2001)Discovering Urban Functional Zones Using Latent Activity Trajectories (2014)Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data (2014)Exploring Millions of Footprints in Location Sharing Services (2021)Science and Human Behavior (1953)Power-Law Distributions in Empirical Data (2009)Assessing social anxiety using gps trajectories and point-of-interest data (2016)Power-law distributions in empirical data (2018)Revisiting User Mobility and Social Relationships in LBSNs: A Hypergraph Embedding Approach (2019)A Methodological Analysis of Segregation Indexes (1955)Twitter mood predicts the stock market (2011)Identifying urban spatial structure and urban vibrancy in highly dense cities using georeferenced social media data (2019)The ghost map : the story of London's most terrifying epidemic--and how it changed science, cities, and the modern world (2007)How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets (2010)Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation (2012)Natural Scales in Geographical Patterns (2017)Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs (2018)Portraying the spatial dynamics of urban vibrancy using multisource urban big data (2019)Understanding house price appreciation using multi-source big geo-data and machine learning (2020)
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References

  • 2007Citizens as sensors: the world of volunteered geography4,544 cited
  • 2015Social Sensing: A New Approach to Understanding Our Socioeconomic Environments804 cited
  • 2021The Livehoods Project: Utilizing Social Media to Understand the Dynamics of a City565 cited
  • 2017Extracting urban functional regions from points of interest and human activities on location‐based social networks470 cited
  • 2010Exploring place through user-generated content: Using Flickr to describe city cores328 cited
  • 2016Participatory Cultural Mapping Based on Collective Behavior Data in Location-Based Social Networks313 cited
  • 2016The geography of Twitter topics in London211 cited
  • 2014Spectral clustering for sensing urban land use using Twitter activity205 cited
  • 2014Home Location Identification of Twitter Users202 cited
  • 2013Exploiting Foursquare and Cellular Data to Infer User Activity in Urban Environments133 cited
  • 2017City dynamics through Twitter: Relationships between land use and spatiotemporal demographics117 cited
  • 2015Comparing and modelling land use organization in cities94 cited
  • 2018Beyond Spatial Proximity—Classifying Parks and Their Visitors in London Based on Spatiotemporal and Sentiment Analysis of Twitter Data82 cited
  • 2014Mining Urban Deprivation from Foursquare: Implicit Crowdsourcing of City Land Use

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82 cited
  • 2018Describing and comparing landscapes using tags, texts, and free lists: an interdisciplinary approach69 cited
  • 2016Crowdsourcing functions of the living city from Twitter and Foursquare data63 cited
  • Cited by

    • 2023Providing climate change resilient land-use transport projects with green finance using Z extended numbers based decision-making model51 cited
    • 2022Application of Social Sensors in Natural Disasters Emergency Management: A Review46 cited
    • 2021A survey of location-based social networks: problems, methods, and future research directions29 cited
    • 2022Human mobility forecasting with region-based flows and geotagged Twitter data12 cited
    • 2020Predicting retail business success using urban social data mining3 cited