(* indicates corresponding authors and + indicates the advisee authors)
Liu, S., Hu, H., Cao, G., Wang, S. and Guan, Q. (2019): Learning from data: A post classification method for annual land cover analysis in urban areas. ISPRS Journal of Photogrammetry and Remote Sensing 154, 202-215
Guo, M., Su, J. and Cao, G. (2019): Statistical Regression Analysis of Functional and Shape Data. Journal of Applied Statistics. (Accepted)
Su, Y-H.+, Tsou, M-H., Knapp, E., Rey, S. and Cao, G.(2019): How Do Cities Flow in an Emergency? Tracing Human Mobility Patterns during a Natural Disaster with Big Data and Geospatial Data Science. Urban Science, 3(2), 51.
Liu, Y.+, Zhao, N.+, Vanos, J., and Cao, G.* (2019): Revisiting the estimations of PM2.5-attributable mortality with advancements in PM2.5 mapping and mortality statistics. Science of the Total Environment, 666, 499-507.
Zhao, N.+, Zhang, W., Liu, Y.+, Samson, E., Chen, Y. and Cao, G.* (2019): Improving nighttime lights imagery with location-based social media data. IEEE Transactions on Geosciences and Remote Sensing. doi: 10.1109/TGRS.2018.2871788.
Jamali, M., Nejat, A., Ghosh, S., Jin, F. and Cao, G. (2019): Social media data and post-disaster recovery. International Journal of Information Management, 44, 25-37.
Zhao, N.+, Liu, Y. +, J. Vanos, and Cao, G.: Day-of-week and seasonal patterns of PM2.5 concentrations over the United States: Time-series analyses using the Prophet procedure. Atmospheric Environment 192, 116-127..
Herdt, A., Brown, R., Scott-Fleming, S., Cao, G., MacDonald, M., Henderson, D. and Vanos, J. (2018): Outdoor Thermal Comfort during Anomalous Heat at the 2015 Pan American Soccer Games in Toronto, Canada. Atmosphere, 9(8), 321.
Zhao, N.+, Cao, G., W. Zhang + and E. L. Samson (2018): Tweets or nighttime lights: comparison for preeminence in estimating socioeconomic factors. ISPRS Journal of Photogrammetry and Remote Sensing, 146, 1-10.
Liu, Y.+, Cao, G.*, Zhao, N., Mulligan, K. and Ye, X. (2018), Improve Ground-Level PM2.5 Concentration Mapping Using A Random Forests-Based Geostatistical Approach. Environmental Pollution, 235, 272-282. Note: A PM2.5 concentration dataset derived in this paper (1km resolution for the United States 2000-2015) is available.
Gao, Y., Wang, S., Padmanabhana, A., Yin, J. and Cao, G. (2018), Mapping spatiotemporal patterns of events using social media: a case study of influenza trends. International Journal of Geographical Information Science, 32(3), 425-449.
Liu, Y.+, Zhao, N., Vanos, J. and Cao, G. (2018), Visualizing changes in nationally averaged PM2.5 concentrations by an alluvial diagram. Environment and Planning A (Featured graphics), 50(2), 259-261.
Hardin, A., Liu, Y. +, Cao, G. and Vanos, J. (2018) Urban heat island intensity and spatial variability by synoptic weather type in the northeast US. Urban Climate, 24, 747-762.
Zhao, N. and Cao, G.* (2017), Quantifying and visualizing language diversity of Hong Kong using Twitter. Environment and Planning A (Featured graphics), 49 (12), 2698-2701.
Mehdipoor, H., Vanos, J., Zurita-Milla, R. and Cao, G. (2017) Short communication: Emerging technologies for biometeorology. International Journal of Biometeorology, 61(1), 81-88.
Fisher-Phelps, M.+, Cao, G, Wilson, R. and Kingston, T. (2017): Protecting bias: Across time and ecology, open-source bat locality data are heavily biased by distance to protected area. Ecological Informatics, 40, 22-34.
Zhao, N., Hsu, F., Cao, G and Samson, E. (2017), Improving accuracy of economic estimations with VIIRS DNB image products. International Journal of Remote Sensing, 38(21), 5899-5918.
Zhao, N., Cao, G*, Vanos, J. and Vecellio, D. (2017): Effects of synoptic weather on Influenza Infection Incidences: A retrospective study utilizing digital disease surveillance. International Journal of Biometeorology, 62(1), 69-84. Note: An ILI+ dataset derived in this paper (a combination of Google Flu Trends and CDC reports) is available.
Zhao, N., Liu, Y.+, and Cao, G, Samson, E. and Zhang, J. (2017): Forecasting China’s GDP at the pixel level using nighttime lights time series and population images. GIScience and Remote Sensing (54) 407-425. Note: A dataset of GDP projection of China at pixel levels derived in this paper is available.
Liu, Y.+, Zhao, N., Vanos, J., and Cao, G (2017): Effects of synoptic weather on ground-level PM2.5 concentrations in the United States. Atmospheric Environment (148) 297-305.
Liu, Y.+, Delahunty, T., Zhao, N. and Cao, G. (2016): These lit areas are undeveloped: China’s urban extents and urban development patterns from thresholded nighttime light imagery. International Journal of Applied Earth Observation and Geoinformation (50) 39-50. Note: A dataset of boundaries of Chinese urban areas derived in this paper) is available.
Luo, F.+, Cao, G*, Mulligan, K. and Li, X. (2016): Explore Spatiotemporal and Demographic Characteristics of Human Mobility via Twitter: A Case Study of Chicago. Applied Geography (70) 11-25. Note: This article is one of the top 25 most cited articles in Applied Geography since 2015. Accessed: 08/31/2018
Cao, G., Wang, S., Hwang, M., Padmanabhan, A., Zhang, Z., and Soltani, K. (2016). A Scalable Framework for Spatiotemporal Analysis of Location-based Social Media Data. Computers, Environment and Urban System, 51, 70-82. Note: This article is one of the top 25 most cited articles in Computers, Environment and Urban System since 2015. Accessed: 08/31/2018
Padmanabhan, A., Wang, S., Cao, G., Hwang, M., Zhang, Z., Gao, Y., Soltani, K., and Liu, Y.Y. (2014): FluMapper: A CyberGIS Application for Interactive Analysis of Massive Location-based Social Media. Concurrency and Computation: Practice and Experience, 26(13), 2253-2265.
Cao, G., Yoo, E.H., Wang, S. (2014): A Statistical Framework of Data Fusion for Spatial Prediction of Categorical Variables. Stochastic Environmental Research and Risk Assessment, 28: 1785-1799. A Matlab toolbox associated with this paper is available
Leetaru, K.,Wang, S., Cao, G., Padmananabhan, A., Shook, E. (2013): Mapping The Global Twitter HeartBeat: The Geography of Twitter. First Monday.
Yoo, E.H., Hoagland, B.W., Cao, G. and Fagin, T.D. (2013): Spatial distribution of trees and landscapes of the past: a mixed spatially correlated multinomial logit model approach for the analysis of the Public Land Survey data. Geographical Analysis, 45(4), pp.419-440.
Luo, F., Zhong, E., Cao, G., Tellez, R.D. and Gao, P. (2013): VGIS-AntiJitter: an effective framework of solving jitter problems in virtual geographic information systems International Journal of Digital Earth, 6(1), pp.28-50
Cao, G., Kyriakidis, P.C., and Goodchild, M.F. (2012): Response to ‘Comments on ‘Combining spatial transition probabilities for stochastic simulation of categorical fields’ with communications on some issues related to Markov chain geostatistics’, International Journal of Geographical Information Science, 26(10), pp.1741-1750. A Matlab toolbox associated with this paper is available
Cao, G., Kyriakidis, P.C. and Goodchild, M.F. (2011): A geostatistical framework for categorical spatial data modeling, The SIGSPATIAL Special, 2011, 3(3), pp.4-9. A Matlab toolbox associated with this paper is available
Cao, G., Kyriakidis, P.C. and Goodchild, M.F. (2011): A multinomial logistic mixed model for prediction of categorical spatial data, International Journal of Geographical Information Science, 25(12), pp.2071-2086. A Matlab toolbox associated with this paper is available
Cao, G., Kyriakidis, P.C. and Goodchild, M.F. (2011): Combining spatial transition probabilities for stochastic simulation of categorical fields, International Journal of Geographical Information Science, 25(11), pp.1773-1791. A Matlab toolbox associated with this paper is available
Li, K., Zhong, E., Zeng, Z. and Cao, G.(2006): An optimal path algorithm based on hierarchically structured topographical network, Journal of Images and Graphics (In Chinese), 11(07): 1004-1009.
Zhang, X., Zhang, L., Cao, G. and Zhong, E.(2006): A study on expressing techniques of battlefield situation evolution and variation based on GIS and its application, Geo-Information Science (In Chinese), 8(4).
Zhang,L., Zhu,J., Zeng,Z., and Cao, G.(2006): GRID services for large scale elevation derivatives computation, Geo-Information Science (In Chinese), 8(2), pp.14-29.
Cao, G., Zhang, L. and Zhong, E. (2005): A discussion on key techniques in 3D GIS rendering engine, Geo-Information Science (In Chinese), 7(1), pp.87-91.
Cao, G.: Modeling uncertainty in categorical fields, International Encyclopedia of Geography. (in press)
Wang, S. and Cao, G., Zhang, Z., Zhao, Y., Padmanabhan, A. and Wu, K. (2013): A CyberGIS environment for analysis of location-based social media data, in Location-Based Computing and Services,2nd Edition, (edited by A.K.Hassan and H. Amin), CRC Press.
Yang, Z., Nguyen, L.H., Cao, G. and Jin, F.: Harvey flooding rescue in social media, in Proceedings of the IEEE Big Data conference 2017, Boston, December 2017.
Huang, Q., Cao, G., Wang, C.: From where do tweets originate? - A GIS approach for user location inference, in Proceedings of the 7th ACM SIGSPATIAL International Workshop on Location-Based Social Network, Dallas, November 2014.
Luo, F., Cao, G., Li, X.: An interactive approach for deriving geometric network models in 3D indoor environments, in Proceedings of the 6th ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness, Dallas, November 2014.
Zhang, Z., Wang, S., Cao, G., Padmanabhan, A., Wu, K.: A scalable approach to extracting mobility patterns from social media data, in Proceedings of the 22nd International Conference on Geoinformatics, Kaohsiung, June 2014.
Cao, G.: A Geostatistical Framework for Heterogeneous Spatatial Data Fusion, in: A. Shortridge, J. Messina, S. Kravchenko and A. Finley (Eds.), \emph{Proceedings of the 11th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences}, Lansing, Michigan, July 2014.
Hwang, M., Wang, S., Cao, G., Padmanabhan, A, and Zhang, Z.: Spatiotemporal Transformation of Social Media: A Case Study of Twitter for Exploration of Flu Risk Indicators. International Conference on Advances in Geographic Information Systems, Orlando, Florida, November 2013.
Padmanabhan, A, Wang, S., Cao, G., Hwang, M., Zhao, Y., Zhang, Z. and Gao, Y.: FluMapper: An interactive CyberGIS environment for massive location-based social media data analysis, XSEDE 13 Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery, July 2013, San Diego.
Shook, E. Leetaru, K, Cao, G., Padmanabhan, A and Wang, S. (2012): Happy or not : Generating topic-based geospatial emotional heatmaps for Culturomics using CyberGIS. IEEE 8th International Conference on E-Science, pp.1-6.
Cao, G.,Wang, S., and Guan, Q. (2012): A state-space model for understanding spatial dynamics represented by areal data. Proceedings of the Seventh International Conference, GIScience 2012, Columbus, Ohio, September 2012.
Cao, G., Kyriakidis, P.C., and Goodchild, M.F. (2011): A geostatistical framework for categorical spatial data modeling, in Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Chicago, Illinois, November 2011.
Kyriakidis, P.C. and Cao, G (2010): Generating fine resolution area class maps subject to coarser resolution data constraints, in Proceedings of the Sixth International Conference, GIScience 2010 Zurich, Switzerland, Sep.14-17,2010.
Cao, G., Kyriakidis, P.C., and Goodchild, M.F. (2009): Prediction and simulation in categorical fields: a transition probability combination approach, in Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle,Washington, November 2009, pp.496-499.
Cao, G., and Kyriakidis, P.C. (2008): Combining transition probabilities in the prediction and simulation of categorical fields, in: J. Zhang, and M.F. Goodchild (Eds.), Proceedings of the International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Shanghai, China, June 2008, pp.25-32.
Li, K., Zhong, E., Song, G., Cao, G., Zhang, L. and Wu, Q. (2007): NDF: An effective mobile GIS physical storage model, in Proceedings of the SPIE 6754, Geoinformatics 2007: Geospatial Information Technology and Applications 67541W (August 07, 2007) DOI:10.1117/12.764932
Zhang, X., Cao, G. and Zhang, L. (2006): Research and improvement on optimal path analysis algorithm based on cost-distance grid, in Proceedings of the IEEE International Conference on Geoscience and Remote Sensing Symposium, Denver, Colorado, Aug 2006, pp.869-871.