Spatial Big Data Analytics

*Underlined names are student advisees.

  1. Peng B., Meng Z., Huang Q., Wang C., 2019. Patch Similarity Convolutional Neural Network for Urban Flood Extent Mapping Using Bi-Temporal Satellite Multispectral Imagery. Remote Sensing, 11(21), 2492. DOI: 10.3390/rs11212492. 
  2. Yu M., Huang Q., Scheele C., Han Q., 2019. Deep Learning for Real-Time Social Media Text Classification for Situation Awareness – Using Hurricanes Sandy and Harvey as Case Studies. International Journal of Digital Earth, 12(11): 1230-1247.
  3. Liu X., Huang Q., Gao S., 2019. Exploring the Uncertainty of Activity Zone Detection Using Digital Footprints with Multi-Scaled DBSCAN. International Journal of Geographical Information Science, 33(6):1196-223. DOI: 1080/13658816.2018.1563301.
  4. Wong D., Huang Q., 2017. “Vote with Their Feet”: Delineating the Sphere of Influence Using Social Media Data. International Journal of Geo-Information, 2017, 6 (11), 325. DOI: 10.3390/ijgi6110325.
  5. Wang C., Pavlowsky R.T., Huang Q., Chang, 2016. Channel Bar Area Extraction for a Mining-Contaminated River Using High-Spatial Multispectral Remote Sensing Imagery. GIScience and Remote Sensing, 53(3): 283-302.
  6. Huang Q., Wong D., 2015. Modeling and Visualizing Regular Human Mobility Patterns with Uncertainty: An Example Using Twitter Data. Annals of the Association of American Geographers, 105(6): 1179-1197.
  7. Huang Q., Xiao Y., 2015. Geographic Situational Awareness: Mining Tweets for Disaster Preparedness, Emergency Response, Impact, and Recovery. International Journal of Geo-Information, 4(3): 1549-1568.
  8. Xiao Y., Huang Q., Wu K, 2015. Understanding Social Media Data for Disaster Management. Natural Hazards, 79(3):1663-1679.
  9. Huang Q., Xu C., 2014. A Data-Driven Framework for Archiving and Exploring Social Media Data, Annals of GIS, 20(4): 265-277.
  10. Li Z., Yang C., Huang Q., Liu K., Sun M., Xia J., et al., 2014. Building Model as a Service to Support Geosciences. Computers, Environment and Urban Systems. DOI: 10.1016/j.compenvurbsys.2014.06.004.
  11. Gui Z., Yang C., Xia J., Huang Q. et al., 2014. A Service Brokering and Recommendation Mechanism for Better Selecting Cloud Services. PLoS ONE, 9(8): e105297. DOI: 10.1371/journal.pone.0105297.

Spatial Computing and Optimization

  1. Li Z., Huang Q., Jiang Y., Hu F., 2019. SOVAS: A Scalable Online Visual Analytic System for Big Climate Data Analysis. International Journal of Geographical Information Science, 34(6): 1188-1209.
  2. Huang Q., Li J., Li Z., 2018. A Hybrid Cloud Platform Based on Multi-sourced Computing and Model Resources for Geosciences. International Journal of Digital Earth. 11(12): 1184 – 1204.
  3. Huang Q., Cervone G., and Zhang G., 2017. A Cloud-enabled Automatic Disaster Analysis System of Multi-sourced Data Streams: An Example Synthesizing Social Media, Remote Sensing and Wikipedia Data. Computers, Environment and Urban Systems, 66: 23-37.
  4. Li Z., Huang Q., Carbone G.J., Hu F., 2017. A High Performance Query Analytical Framework for Supporting Data-Intensive Climate Studies. Computers, Environment and Urban Systems, 62: 210-221.
  5. Yang C., Huang Q., Li Z., Liu K., Hu F., 2017. Big Data and Cloud Computing: Innovation Opportunities and Challenges. International Journal of Digital Earth, 10: 13-53.
  6. Zhang G., Zhu AX., Huang Q., 2017. A GPU-Accelerated Adaptive Kernel Density Estimation Approach for Efficient Point Pattern Analysis on Spatial Big Data. International Journal of Geographical Information Science, 31(10): 2068-2097.
  7. Li R., Feng W., Wu H., Huang Q., 2017. A Replication Strategy for a Distributed High-Speed Caching System Based on Spatiotemporal Access Patterns of Geospatial Data. Computers, Environment and Urban Systems, 61: 163-171.
  8. Zhang G., Huang Q., Zhu A.X., Keel J. H., 2016. Enabling Point Pattern Analysis on Spatial Big Data Using Cloud Computing: Optimizing and Accelerating Ripley’s K Function. International Journal of Geographical Information Science, 30 (11): 2230-2252.
  9. Zhang T., Li J., Liu Q., Huang Q., 2016. A Cloud-Enabled Remote Visualization Tool for Time-Varying Climate Data Analytics. Environmental Modeling & Software, 75: 513-518.
  10. Gui Z, Yu M, Yang C, Jiang Y, Chen S, Xia J. Huang Q., Liu K., Li Z., Hassan M., Jin B., 2016. Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation. PLoS ONE, 11(4): e0152250. DOI:10.1371/journal.pone.0152250.
  11. Xia J., Yang C., Liu K., Gui Z., Li Z., Huang Q., Li, R., 2014. Adopting Cloud Computing to Optimize Spatial Web Portals for Better Performance to Support Digital Earth and Other Global Geospatial Initiatives. International Journal of Digital Earth, 8(6): 451-475.
  12. Huang Q., Yang C., Benedict K., Rezgui A., Xie J., Xia J., Chen, S., 2013. Using Adaptively Coupled Models and High-performance Computing for Enabling the Computability of Dust Storm Forecasting. International Journal of Geographic Information Science, 27(4): 765-784.
  13. Li J., Jiang Y., Yang C., Huang Q., Rice M., 2013. Visualizing 3D/4D Environmental Data Using Many-Core Graphics Processing Units (GPUs) and Multi-Core Central Processing Units (CPUs). Computers & Geosciences, 59 (2013): 78-89.
  14. Huang Q., Yang C., 2011. Optimizing Grid Configuration to Support Geospatial Processing – An Example with DEM Interpolation. Computer & Geosciences, and 37(2): 165-176.
  15. Yang C., Wu H., Huang Q., Li Z., Li J., 2011. Spatial Computing for Supporting Physical Sciences. Proceedings of National Academy of Sciences, 108(14):5498-5503.
  16. Yang C., Goodchild M., Huang Q., Nebert D., Raskin R., Bambacus M., Xu Y., Fay D., 2011. Spatial Cloud Computing – How Can Geospatial Sciences Use and Help to Shape Cloud Computing. International Journal of Digital Earth, 4(4): 305-329.

Spatial Data Science for Social Good

  1. Vincent K., Roth R. E, Moore S. A., Huang Q., Lally N., Sack C., Nost E., and Rosenfeld H., 2018. Improving Spatial Decision Making Using Interactive Maps: An Empirical Study on Interface and Decision Complexity in the North American Hazardous Waste Trade. Environment and Planning B, 2018: 2399808318764122.
  2. Cao K., Huang Q., 2018. Geo-Sensor for Potential Prediction of Earthquakes: Can Earthquake Be Predicted By Abnormal Animal Phenomena? Annals of GIS, 24(2): 125-138.
  3. Huang Q., Wong D., 2016. Activity Patterns, Socioeconomic Status and Urban Spatial Structure: What Can Social Media Data Tell Us? International Journal of Geographic Information Science, 30(9): 1873-1898.
  4. Ye X., Huang Q., Li W., 2016. Integrating Big Social Data, Computing and Modeling for Spatial Social Science. Cartography and Geographic Information Science, 43(5): 377-378.
  5. Cervone G., Sava E., Huang Q., Schnebele E., Harrison J., Waters N., 2016. Using Twitter for Tasking Remote-Sensing Data Collection and Damage Assessment: 2013 Boulder Flood Case Study. International Journal of Remote Sensing, 37(1): 100-124.
  6. Huang Q., Yang C., Liu K., Xia J., Xu C., Li J., Gui Z., Sun M., Li Z., 2013. Evaluating Open Source Cloud Computing Solutions for Geosciences. Computers & Geosciences, 59(9): 41-52.
  7. Huang Q., Yang C., Benedict K., Chen, S., Rezgui A., Xie J., 2013. Utilize Cloud Computing to Support Dust Storm Forecasting. International Journal of Digital Earth, 6(4): 338-355.
  8. Sun M., Li J., Yang C., Schmidt G.A., Bambacus M., Cahalan R., Huang Q., Xu C., Noble E.U., Li Z., 2012. A Web-based Geovisual Analytical Tool for Spatiotemporal Climate Data. Future Internet, 4(4): 1069-1085.
  9. Xie J., Yang C., Zhou B., Huang Q., 2010. High Performance Computing for the Simulation of Dust Storms. Computers, Environment, and Urban Systems, 34(4): 278-290.
  10. Huang Q., Mao S., Li M., Ru P., 2006. The Safety Assurance System for Coalmine Based on the Three-tiers B/S Architecture. Coal Engineering, 2006(11): 10-14. (Chinese)
  11. Zhao P., Mao S., Huang Q., Cheng L., 2007. Design on Intelligent Decision Support System for Mining and Excavation Connection in Mine. Coal Science and Technology, 2007(03): 55-60. (Chinese)