Urban Observation: Integration of Remote Sensing and Social Media Data

Urban and regional research is crucial for many applications such as public participation, land use, disaster management, and environmental monitoring, but it is a time-consuming and expensive procedure to collect necessary data. Remote sensing is an effective technology for urban observation, however, the spatial, spectral, and temporal resolution of observation sensors limits many situations in which remote sensing data cannot be fully utilized, especially in the field of urban observation. Recently, with the popularity of internet and smart mobile devices, social media containing spatial information is evolving rapidly, such as tweets, Flickr photos, and geolocated posts. These location-based social media data are leading new research areas, new technologies and methods, and new insights into urban observation. In this paper, we provide an overview on the integration and joint analysis of remote sensing and social media data in urban observation applications. We describe four opportunities in exploiting social media data: to investigate the relationship among humans, environment and urban, to help urban planning, to manage urban disaster, and to monitor urban environment. Although significant possibilities for a combination of remote sensing and social media data can be seen, our survey suggests that the fusion of these data sources will continue to profoundly change these technologies.

[1]  Henrikki Tenkanen,et al.  User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey , 2017, ISPRS Int. J. Geo Inf..

[2]  João Porto de Albuquerque,et al.  Geo-social media as a proxy for hydrometeorological data for streamflow estimation and to improve flood monitoring , 2018, Comput. Geosci..

[3]  Gareth W. Peters,et al.  Participatory Sensing Data Tweets for Micro-Urban Real-Time Resiliency Monitoring and Risk Management , 2016, IEEE Access.

[4]  Lei Guo,et al.  Effective and Efficient Midlevel Visual Elements-Oriented Land-Use Classification Using VHR Remote Sensing Images , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[5]  David Fisher,et al.  Geolocated social media as a rapid indicator of park visitation and equitable park access , 2018, Comput. Environ. Urban Syst..

[6]  Zhenlong Li,et al.  A near real-time flood-mapping approach by integrating social media and post-event satellite imagery , 2018, Ann. GIS.

[7]  Cuizhen Wang,et al.  Reconstructing Flood Inundation Probability by Enhancing Near Real-Time Imagery With Real-Time Gauges and Tweets , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[8]  李超 Relationships between geographical cluster and cyberspace community: A case study on microblog , 2012 .

[9]  Tom W. Smith,et al.  Big Data and Survey Research: Supplement or Substitute? , 2017 .

[10]  Guanling Chen,et al.  Sharing location in online social networks , 2010, IEEE Network.

[11]  Bo Zhang,et al.  Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park , 2018 .

[12]  Seth E. Spielman The Potential for Big Data to Improve Neighborhood-Level Census Data , 2017 .

[13]  Diansheng Guo,et al.  A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods , 2018 .

[14]  Jon Atli Benediktsson,et al.  Big Data for Remote Sensing: Challenges and Opportunities , 2016, Proceedings of the IEEE.

[15]  Keith W. Miller,et al.  Big Data: New Opportunities and New Challenges [Guest editors' introduction] , 2013, Computer.

[16]  Yi Zhu,et al.  Spatial Morphing Kernel Regression for Feature Interpolation , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

[17]  Ruo-Qian Wang,et al.  Big Data of Urban Flooding: Dance with Social Media, Citizen Science, and Artificial Intelligence , 2018 .

[18]  Firoj Alam,et al.  Processing Social Media Images by Combining Human and Machine Computing during Crises , 2018, Int. J. Hum. Comput. Interact..

[19]  M. Brian Blake,et al.  Service-Oriented Computing and Cloud Computing: Challenges and Opportunities , 2010, IEEE Internet Computing.

[20]  Anthony Stefanidis,et al.  Geosocial gauge: a system prototype for knowledge discovery from social media , 2013, Int. J. Geogr. Inf. Sci..

[21]  H. Taubenböck,et al.  Detecting social groups from space – Assessment of remote sensing-based mapped morphological slums using income data , 2018 .

[22]  Alexander Zipf,et al.  Coupling maximum entropy modeling with geotagged social media data to determine the geographic distribution of tourists , 2018, Int. J. Geogr. Inf. Sci..

[23]  Antonio J. Plaza,et al.  This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1 Spectral–Spatial Classification of Hyperspectral Data Usi , 2022 .

[24]  Junwei Han,et al.  A Survey on Object Detection in Optical Remote Sensing Images , 2016, ArXiv.

[25]  Liang Zhao,et al.  Spatial Event Forecasting in Social Media With Geographically Hierarchical Regularization , 2017, Proceedings of the IEEE.

[26]  Amit P. Sheth,et al.  Citizen Sensing, Social Signals, and Enriching Human Experience , 2009, IEEE Internet Computing.

[27]  S. Cox,et al.  Citizen-based sensing of crisis events: sensor web enablement for volunteered geographic information , 2013 .

[28]  Stuart E. Middleton,et al.  Real-Time Crisis Mapping of Natural Disasters Using Social Media , 2014, IEEE Intelligent Systems.

[29]  Jason Hong,et al.  Using User-Generated Content to Understand Cities , 2017 .

[30]  Lun Wu,et al.  Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data , 2014, PloS one.

[31]  Teng Wang,et al.  Inferring urban air quality based on social media , 2017, Comput. Environ. Urban Syst..

[32]  Chein-I Chang,et al.  High Performance Computing in Remote Sensing , 2007, HiPC 2007.

[33]  David J. Crandall,et al.  Where have all the people gone? Enhancing global conservation using night lights and social media. , 2015, Ecological applications : a publication of the Ecological Society of America.

[34]  James Llinas,et al.  An introduction to multisensor data fusion , 1997, Proc. IEEE.

[35]  Jon Atli Benediktsson,et al.  Land-Cover Mapping by Markov Modeling of Spatial–Contextual Information in Very-High-Resolution Remote Sensing Images , 2013, Proceedings of the IEEE.

[36]  Satish V. Ukkusuri,et al.  Inferring Urban Land Use Using Large-Scale Social Media Check-in Data , 2014 .

[37]  D. Leibovici,et al.  Rapid flood inundation mapping using social media, remote sensing and topographic data , 2017, Natural Hazards.

[38]  Lev Manovich,et al.  Zooming into an Instagram City: Reading the local through social media , 2013, First Monday.

[39]  Qunying Huang,et al.  Using Twitter for tasking remote-sensing data collection and damage assessment: 2013 Boulder flood case study , 2016 .

[40]  Marcel Worring,et al.  Learning Visual Contexts for Image Annotation From Flickr Groups , 2011, IEEE Transactions on Multimedia.

[41]  Luke S. Smith,et al.  Assessing the utility of social media as a data source for flood risk management using a real‐time modelling framework , 2017 .

[42]  Gui-Song Xia,et al.  AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[43]  Bin Jiang,et al.  Volunteered Geographic Information: Towards the establishment of a new paradigm , 2015, Comput. Environ. Urban Syst..

[44]  Enrique Herrera-Viedma,et al.  Quantifying the emotional impact of events on locations with social media , 2018, Knowl. Based Syst..

[45]  Paul D. Bates,et al.  Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: A case study , 2012 .

[46]  Xiao Xiang Zhu,et al.  Are the Poor Digitally Left Behind? Indications of Urban Divides Based on Remote Sensing and Twitter Data , 2018, ISPRS Int. J. Geo Inf..

[47]  Yuan Wang,et al.  Hyper-resolution monitoring of urban flooding with social media and crowdsourcing data , 2018, Comput. Geosci..

[48]  Christopher M. Danforth,et al.  Exposure to urban parks improves affect and reduces negativity on Twitter , 2018, ArXiv.

[49]  Jianghao Wang,et al.  Urban Land Use Mapping by Combining Remote Sensing Imagery and Mobile Phone Positioning Data , 2018, Remote. Sens..

[50]  Serge Fdida,et al.  Sensing Pollution on Online Social Networks: A Transportation Perspective , 2016, Mobile Networks and Applications.

[51]  Yao Yao,et al.  Mapping fine‐scale urban housing prices by fusing remotely sensed imagery and social media data , 2018, Trans. GIS.

[52]  O. K. Gowrishankar,et al.  Personalized Travel Sequence Recommendation on Multi-Source Big Social Media , 2016, IEEE Transactions on Big Data.

[53]  Xianfeng Yang,et al.  An Integrated Evacuation Decision Support System Framework with Social Perception Analysis and Dynamic Population Estimation , 2017, Human Dynamics in Smart Cities.

[54]  Jun Li,et al.  Social Media: New Perspectives to Improve Remote Sensing for Emergency Response , 2017, Proceedings of the IEEE.

[55]  Carole E. Nahum,et al.  Airborne SAR-Efficient Signal Processing for Very High Resolution , 2013, Proceedings of the IEEE.

[56]  YingLonga,et al.  Understanding Uneven Urban Expansion with Natural Cities using Open Data , 2018 .

[57]  Daniel Gayo-Avello,et al.  No, You Cannot Predict Elections with Twitter , 2012, IEEE Internet Comput..

[58]  Iman Saleh,et al.  Social-Network-Sourced Big Data Analytics , 2013, IEEE Internet Computing.

[59]  Peng Yue,et al.  Discovering spread mode of public opinions in incidents and mapping it with GIS: A case on big geospatial data analytics , 2014, 2014 The Third International Conference on Agro-Geoinformatics.

[60]  Luca Calderoni,et al.  From Sensing to Action: Quick and Reliable Access to Information in Cities Vulnerable to Heavy Rain , 2014, IEEE Sensors Journal.

[61]  Yiannis Kompatsiaris,et al.  Sensing Trending Topics in Twitter , 2013, IEEE Transactions on Multimedia.

[62]  P. Thakuriah,et al.  Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery , 2017 .

[63]  Mihai Datcu,et al.  The Semantic Gap: An Exploration of User and Computer Perspectives in Earth Observation Images , 2015, IEEE Geoscience and Remote Sensing Letters.

[64]  Huiji Gao,et al.  Harnessing the Crowdsourcing Power of Social Media for Disaster Relief , 2011, IEEE Intelligent Systems.

[65]  Zhen Qian,et al.  Road Traffic Congestion Monitoring in Social Media with Hinge-Loss Markov Random Fields , 2014, 2014 IEEE International Conference on Data Mining.

[66]  Xuelong Li,et al.  On Combining Social Media and Spatial Technology for POI Cognition and Image Localization , 2017, Proceedings of the IEEE.

[67]  Xin Du,et al.  The Combined Use of Remote Sensing and Social Sensing Data in Fine-Grained Urban Land Use Mapping: A Case Study in Beijing, China , 2017, Remote. Sens..

[68]  Jon Atli Benediktsson,et al.  Spatial Technology and Social Media in Remote Sensing: A Survey , 2017, Proceedings of the IEEE.

[69]  Jingsong Deng,et al.  “Ghost cities” identification using multi-source remote sensing datasets: A case study in Yangtze River Delta , 2017 .

[70]  Xindong Wu,et al.  Data mining with big data , 2014, IEEE Transactions on Knowledge and Data Engineering.

[71]  Tao Wang,et al.  Social media: A new vehicle for city marketing in China , 2014 .

[72]  Jan Dirk Wegner,et al.  Toward Seamless Multiview Scene Analysis From Satellite to Street Level , 2017, Proceedings of the IEEE.

[73]  Wei Tu,et al.  Integrating Aerial and Street View Images for Urban Land Use Classification , 2018, Remote. Sens..

[74]  David J. Crandall,et al.  Utilizing remote sensing and big data to quantify conflict intensity: The Arab Spring as a case study , 2018 .

[75]  Robert A. Schowengerdt,et al.  Remote sensing, models, and methods for image processing , 1997 .

[76]  Bhartendu Pandey,et al.  Mapping Floods and Assessing Flood Vulnerability for Disaster Decision-Making: A Case Study Remote Sensing Application in Senegal , 2018 .

[77]  Yu Liu,et al.  Building a Spatially-Embedded Network of Tourism Hotspots From Geotagged Social Media Data , 2018, IEEE Access.

[78]  E. Marcheggiani,et al.  Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy , 2016 .

[79]  Xiaoqiang Lu,et al.  Remote Sensing Image Scene Classification: Benchmark and State of the Art , 2017, Proceedings of the IEEE.

[80]  Jing Ma,et al.  The socio-spatial dimension of behavior analysis: Frontiers and progress in Chinese behavioral geography , 2016, Journal of Geographical Sciences.

[81]  Paolo Gamba,et al.  Human Settlements: A Global Challenge for EO Data Processing and Interpretation , 2013, Proceedings of the IEEE.

[82]  Wei Tu,et al.  Portraying Urban Functional Zones by Coupling Remote Sensing Imagery and Human Sensing Data , 2018, Remote. Sens..

[83]  Yong Gao,et al.  Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data , 2013, PloS one.

[84]  Birgit Kirsch,et al.  E2mC: Improving Emergency Management Service Practice through Social Media and Crowdsourcing Analysis in Near Real Time , 2017, Sensors.

[85]  A. Soliman,et al.  Social sensing of urban land use based on analysis of Twitter users’ mobility patterns , 2017, PloS one.

[86]  Nigel Waters,et al.  Using Social Media and Satellite Data for Damage Assessment in Urban Areas During Emergencies , 2017 .

[87]  Erik Skau,et al.  Fusing Heterogeneous Data: A Case for Remote Sensing and Social Media , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[88]  Krzysztof Janowicz,et al.  Using Semantic Signatures for Social Sensing in Urban Environments , 2019, Mobility Patterns, Big Data and Transport Analytics.

[89]  Antonio J. Plaza,et al.  Parallel Hyperspectral Image and Signal Processing [Applications Corner] , 2011, IEEE Signal Processing Magazine.

[90]  C. Havas,et al.  Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment , 2018 .

[91]  Xiaoping Liu,et al.  Classifying urban land use by integrating remote sensing and social media data , 2017, Int. J. Geogr. Inf. Sci..

[92]  Xizhao Wang,et al.  Learning from big data with uncertainty - editorial , 2015, J. Intell. Fuzzy Syst..

[93]  Jean-Claude Thill,et al.  Social Media Discourse in Disaster Situations: A Study of the Deadly July 21, 2012 Beijing Rainstorm , 2017, EM-GIS.

[94]  Wei Jiang,et al.  Using Social Media to Detect Outdoor Air Pollution and Monitor Air Quality Index (AQI): A Geo-Targeted Spatiotemporal Analysis Framework with Sina Weibo (Chinese Twitter) , 2015, PloS one.

[95]  Xiao Huang,et al.  Geospatial Assessment of Wetness Dynamics in the October 2015 SC Flood with Remote Sensing and Social Media , 2018 .

[96]  Ting Ma,et al.  Delineating Spatial Patterns in Human Settlements Using VIIRS Nighttime Light Data: A Watershed-Based Partition Approach , 2018, Remote. Sens..

[97]  Alexander Zipf,et al.  Monitoring and Assessing Post-Disaster Tourism Recovery Using Geotagged Social Media Data , 2017, ISPRS Int. J. Geo Inf..

[98]  Jon Atli Benediktsson,et al.  On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[99]  Xing Xie,et al.  User-Service Rating Prediction by Exploring Social Users' Rating Behaviors , 2016, IEEE Transactions on Multimedia.

[100]  Xiaoping Liu,et al.  Delineating urban functional areas with building-level social media data: A dynamic time warping (DTW) distance based k-medoids method , 2017 .

[101]  Lars Backstrom,et al.  Find me if you can: improving geographical prediction with social and spatial proximity , 2010, WWW '10.

[102]  Norman M. Sadeh,et al.  The Livehoods Project: Utilizing Social Media to Understand the Dynamics of a City , 2012, ICWSM.

[103]  Yao Yao,et al.  Sensing Urban Land-Use Patterns By Integrating Google Tensorflow And Scene-Classification Models , 2017, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

[104]  Francesca Bovolo,et al.  A Novel Framework for the Design of Change-Detection Systems for Very-High-Resolution Remote Sensing Images , 2013, Proceedings of the IEEE.

[105]  Jianghao Wang,et al.  Spatial-Temporal Analysis of Human Dynamics on Urban Land Use Patterns Using Social Media Data by Gender , 2018, ISPRS Int. J. Geo Inf..

[106]  Satish V. Ukkusuri,et al.  Understanding urban human activity and mobility patterns using large-scale location-based data from online social media , 2013, UrbComp '13.

[107]  Aji Putra Perdana,et al.  Urban Spatial Pattern and Interaction based on Analysis of Nighttime Remote Sensing Data and Geo-social Media Information , 2016 .

[108]  Heidi Kreibich,et al.  Social media as an information source for rapid flood inundation mapping , 2015 .

[109]  Tao Mei,et al.  Service Quality Evaluation by Exploring Social Users’ Contextual Information , 2016, IEEE Transactions on Knowledge and Data Engineering.

[110]  K. Mcdougall,et al.  The use of LiDAR and volunteered geographic information to map flood extents and inundation , 2012 .

[111]  D. Dransch,et al.  Volunteered Geographic Information for Disaster Management with Application to Rapid Flood Damage Estimation , 2019 .

[112]  Hang Zheng,et al.  Monitoring surface water quality using social media in the context of citizen science , 2016 .

[113]  Xuelong Li,et al.  Manifold Regularized Sparse NMF for Hyperspectral Unmixing , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[114]  Giovanni Pau,et al.  Using geosocial search for urban air pollution monitoring , 2017, Pervasive Mob. Comput..

[115]  Juraj Lieskovský,et al.  Appreciation of landscape aesthetic values in Slovakia assessed by social media photographs , 2017 .

[116]  Rozenn Dahyot,et al.  Automatic Discovery and Geotagging of Objects from Street View Imagery , 2017, Remote. Sens..

[117]  Xiaozhi Qu,et al.  Landmark based localization in urban environment , 2017 .

[118]  Shivam Gupta,et al.  Big data in humanitarian supply chain management: a review and further research directions , 2017, Annals of Operations Research.

[119]  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..