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Refereed Academic Journal Articles

2024

Zhu, D. and G. Cao (2024). “Intelligent Spatial Prediction and Interpolation Methods”. In: Handbook of Geospatial Artificial Intelligence. CRC Press, pp. 121-150.

2023

Cong, Z., Z. Chen, D. Liang, W. Song, and G. Cao (2023). “Multidimensional tornado exposure and climate change risk perceptions”. In: APHA 2023 Annual Meeting and Expo. APHA.

Huang, L., M. J. Willis, G. Li, T. C. Lantz, K. Schaefer, E. Wig, G. Cao, and K. F. Tiampo (2023). “Identifying active retrogressive thaw slumps from ArcticDEM”. In: ISPRS Journal of Photogrammetry and Remote Sensing 205, pp. 301-316.

Xiao, W., J. Su, Y. Chen, and G. Cao (2023). “Cross-Scale Guided Fusion Transformer for Disaster Assessment Using Satellite Imagery”. In: IEEE Transactions on Geoscience and Remote Sensing.

Ye, S., Z. Zhu, and G. Cao (2023). “Object-based continuous monitoring of land disturbances from dense Landsat time series”. In: Remote Sensing of Environment 287, p. 113462.

2022

Cao, G. (2022). “Deep Learning of Big Geospatial Data: Challenges and Opportunities”. In: New Thinking in GIScience, pp. 159-169.

Cao, G. and B. Buttenfield (2022). “Pattern Recognition and Matching”. In: The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2022 Edition).

Coman, E. N., S. Steinbach, and G. Cao (2022). “Spatial perspectives in family health research”. In: Family Practice 39.3, pp. 556-562.

Liang, D., Z. Cong, and G. Cao (2022). “Examination of diffusion patterns of tornado warning using an agent-based model and simulation”. In: Weather, climate, and society 14.2, pp. 521-533.

Neupane, J., W. Guo, G. Cao, F. Zhang, L. Slaughter, and S. Deb (2022). “Spatial patterns of soil microbial communities and implications for precision soil management at the field scale”. In: Precision Agriculture 23.3, pp. 1008-1026.

Rabia, A. H., J. Neupane, Z. Lin, K. Lewis, G. Cao, and W. Guo (2022). “Principles and applications of topography in precision agriculture”. In: Advances in agronomy 171, pp. 143-189.

Zhu, D., S. Gao, and G. Cao (2022). “Towards the intelligent era of spatial analysis and modeling”. In: Proceedings of the 5th ACM SIGSPATIAL international workshop on AI for geographic knowledge discovery. , pp. 10-13.

2021

Cao, G. and N. Zhao (2021). “Integrating remote sensing and social sensing to examine socioeconomic dynamics: A case study of twitter and nighttime light imagery”. In: Urban Remote Sensing: Monitoring, Synthesis, and Modeling in the Urban Environment, pp. 131-150.

Chen, Z., Z. Cong, D. Liang, and G. Cao (2021). “Age Differences in Preparedness for the Continuation of COVID-19: Important Roles of Social Support”. In: Innovation in Aging 5.Suppl 1, p. 349.

Yazhou, S., G. Wenxuan, D. C. Weindorf, S. Fujun, D. Sanjit, C. Guofeng, J. Neupane, L. Zhe, and A. Raihan (2021). “Field-scale spatial variability of soil calcium in a semi-arid region: Implications for soil erosion and site-specific management”. In: Pedosphere 31.5, pp. 705-714.

Zhao, N., F. C. Hsu, G. Cao, and E. L. Samson (2021). “Improving accuracy of economic estimations with VIIRS DNB image products”. In: Remote Sensing of Night-time Light. Routledge, pp. 45-64.

2020

Guo, M., J. Su, L. Sun, and G. Cao (2020). “Statistical regression analysis of functional and shape data”. In: Journal of Applied Statistics 47.1, pp. 28-44.

Jamali, M., A. Nejat, S. Moradi, S. Ghosh, G. Cao, and F. Jin (2020). “Social media data and housing recovery following extreme natural hazards”. In: International Journal of Disaster Risk Reduction 51, p. 101788.

Liu, Y., G. Cao, and N. Zhao (2020). “Integrate machine learning and geostatistics for high-resolution mapping of ground-level PM2. 5 concentrations”. In: Spatiotemporal Analysis of Air Pollution and Its Application in Public Health. Elsevier, pp. 135-151.

Zhao, N., G. Cao, W. Zhang, E. L. Samson, and Y. Chen (2020). “Remote sensing and social sensing for socioeconomic systems: A comparison study between nighttime lights and location-based social media at the 500 m spatial resolution”. In: International Journal of Applied Earth Observation and Geoinformation 87, p. 102058.

Zhao, N., Y. Liu, F. Hsu, E. L. Samson, H. Letu, D. Liang, and G. Cao (2020). “Time series analysis of VIIRS-DNB nighttime lights imagery for change detection in urban areas: A case study of devastation in Puerto Rico from hurricanes Irma and Maria”. In: Applied Geography 120, p. 102222.

2019

Du, H., L. Nguyen, Z. Yang, H. Abu-Gellban, X. Zhou, W. Xing, G. Cao, and F. Jin (2019). “Twitter vs news: Concern analysis of the 2018 california wildfire event”. In: 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). Vol. 2. IEEE. , pp. 207-212.

Han, S. Y., M. Tsou, E. Knaap, S. Rey, and G. Cao (2019). “How do cities flow in an emergency? Tracing human mobility patterns during a natural disaster with big data and geospatial data science”. In: Urban Science 3.2, p. 51.

Jamali, M., A. Nejat, S. Ghosh, F. Jin, and G. Cao (2019). “Social media data and post-disaster recovery”. In: International Journal of Information Management 44, pp. 25-37.

Liu, S., H. Su, G. Cao, S. Wang, and Q. Guan (2019). “Learning from data: A post classification method for annual land cover analysis in urban areas”. In: ISPRS Journal of Photogrammetry and Remote Sensing 154, pp. 202-215.

Liu, Y., N. Zhao, J. K. Vanos, and G. Cao (2019). “Revisiting the estimations of PM2. 5-attributable mortality with advancements in PM2. 5 mapping and mortality statistics”. In: Science of the Total Environment 666, pp. 499-507.

Nguyen, L., Z. Yang, J. Li, Z. Pan, G. Cao, and F. Jin (2019). “Forecasting people’s needs in hurricane events from social network”. In: IEEE Transactions on Big Data 8.1, pp. 229-240.

Tiffin, H. S., S. T. Peper, A. N. Wilson-Fallon, K. M. Haydett, G. Cao, and S. M. Presley (2019). “The influence of new surveillance data on predictive species distribution modeling of Aedes aegypti and Aedes albopictus in the United States”. In: Insects 10.11, p. 400.

2018

Gao, Y., S. Wang, A. Padmanabhan, J. Yin, and G. Cao (2018). “Mapping spatiotemporal patterns of events using social media: a case study of influenza trends”. In: International Journal of Geographical Information Science 32.3, pp. 425-449.

Hardin, A., Y. Liu, G. Cao, and J. Vanos (2018). “Urban heat island intensity and spatial variability by synoptic weather type in the northeast US”. In: Urban climate 24, pp. 747-762.

Herdt, A. J., R. D. Brown, I. Scott-Fleming, G. Cao, M. MacDonald, D. Henderson, and J. K. Vanos (2018). “Outdoor thermal comfort during anomalous heat at the 2015 Pan American games in Toronto, Canada”. In: Atmosphere 9.8, p. 321.

Liu, Y., G. Cao, N. Zhao, K. Mulligan, and X. Ye (2018). “Improve ground-level PM2. 5 concentration mapping using a random forests-based geostatistical approach”. In: Environmental pollution 235, pp. 272-282.

Liu, Y., N. Zhao, J. K. Vanos, and G. Cao (2018). “Visualizing changes in nationally averaged PM2. 5 concentrations by an alluvial diagram”. In: Environment and Planning A: Economy and Space 50.2, pp. 259-261.

Zhao, N., G. Cao, W. Zhang, and E. L. Samson (2018). “Tweets or nighttime lights: Comparison for preeminence in estimating socioeconomic factors”. In: ISPRS journal of photogrammetry and remote sensing 146, pp. 1-10.

Zhao, N., Y. Liu, J. K. Vanos, and G. Cao (2018). “Day-of-week and seasonal patterns of PM2. 5 concentrations over the United States: Time-series analyses using the Prophet procedure”. In: Atmospheric environment 192, pp. 116-127.

Zhao, N., W. Zhang, Y. Liu, E. L. Samson, Y. Chen, and G. Cao (2018). “Improving nighttime light imagery with location-based social media data”. In: IEEE Transactions on Geoscience and Remote Sensing 57.4, pp. 2161-2172.

2017

Fisher-Phelps, M., G. Cao, R. M. Wilson, and T. Kingston (2017). “Protecting bias: across time and ecology, open-source bat locality data are heavily biased by distance to protected area”. In: Ecological informatics 40, pp. 22-34.

Liu, Y., N. Zhao, J. K. Vanos, and G. Cao (2017). “Effects of synoptic weather on ground-level PM2. 5 concentrations in the United States”. In: Atmospheric Environment 148, pp. 297-305.

Mehdipoor, H., J. K. Vanos, R. Zurita-Milla, and G. Cao (2017). “emerging technologies for biometeorology”. In: International journal of biometeorology 61, pp. 81-88.

Yang, Z., L. H. Nguyen, J. Stuve, G. Cao, and F. Jin (2017). “Harvey flooding rescue in social media”. In: 2017 IEEE International Conference on Big Data (Big Data). IEEE. , pp. 2177-2185.

Zhao, N. and G. Cao (2017). “Quantifying and visualizing language diversity of Hong Kong using Twitter”. In: Environment and Planning A: Economy and Space 49.12, pp. 2698-2701.

Zhao, N., G. Cao, J. K. Vanos, and D. J. Vecellio (2017). “The effects of synoptic weather on influenza infection incidences: a retrospective study utilizing digital disease surveillance”. In: International Journal of Biometeorology, pp. 1-16.

Zhao, N., Y. Liu, G. Cao, E. L. Samson, and J. Zhang (2017). “Forecasting China’s GDP at the pixel level using nighttime lights time series and population images”. In: GIScience & Remote Sensing 54.3, pp. 407-425.

2016

Cao, G. (2016). “Modeling uncertainty in categorical fields”. In: International Encyclopedia of Geography: People, the Earth, Environment and Technology: People, the Earth, Environment and Technology, pp. 1-11.

Liu, Y., T. Delahunty, N. Zhao, and G. Cao (2016). “These lit areas are undeveloped: Delimiting China’s urban extents from thresholded nighttime light imagery”. In: International Journal of Applied Earth Observation and Geoinformation 50, pp. 39-50.

Luo, F., G. Cao, K. Mulligan, and X. Li (2016). “Explore Spatiotemporal and Demographic Characteristics of Human Mobility via Twitter: A Case Study of Chicago”. In: Applied Geography 70, pp. 11-25.

Wang, S., G. Cao, Z. Zhang, and Y. Zhao (2016). “8 A CyberGlS Environment for Analysis of”. In: Advanced Location-Based Technologies and Services, p. 187.

2015

Liu, Y., F. Luo, and G. Cao (2015). “Track Spatiotemporal Spread of Public Concerns on Ebloa in the US via Twitter”. In: Proceedings of The 13th International Conference on Geocomputation.

2014

Cao, G. (2014). “A Geostatistical Framework for Heterogeneous Spatial Data Fusion”. In: Proceedings of the 11th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences.

Cao, G., E. Yoo, and S. Wang (2014). “A statistical framework of data fusion for spatial prediction of categorical variables”. In: Stochastic Environmental Research and Risk Assessment 28, pp. 1785-1799.

Huang, Q., G. Cao, and C. Wang (2014). “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 networks. , pp. 1-8.

Luo, F., G. Cao, and X. Li (2014). “An interactive approach for deriving geometric network models in 3D indoor environments”. In: Proceedings of the Sixth ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness. , pp. 9-16.

Padmanabhan, A., S. Wang, G. Cao, M. Hwang, Z. Zhang, Y. Gao, K. Soltani, and Y. Liu (2014). “FluMapper: A cyberGIS application for interactive analysis of massive location-based social media”. In: Concurrency and Computation: Practice and Experience 26.13, pp. 2253-2265.

Zhang, Z., S. Wang, G. Cao, A. Padmanabhan, and K. Wu (2014). “A scalable approach to extracting mobility patterns from social media data”. In: 2014 22nd International Conference on Geoinformatics. IEEE. , pp. 1-6.

2013

Cao, G., P. Kyriakidis, and M. Goodchild (2013). “On spatial transition probabilities as continuity measures in categorical fields”. In: arXiv preprint arXiv:1312.5391.

Hwang, M., S. Wang, G. Cao, A. Padmanabhan, and Z. Zhang (2013). “Spatiotemporal transformation of social media geostreams: a case study of twitter for flu risk analysis”. In: Proceedings of the 4th ACM SIGSPATIAL International Workshop on GeoStreaming. , pp. 12-21.

Leetaru, K., S. Wang, G. Cao, A. Padmanabhan, and E. Shook (2013). “Mapping the global Twitter heartbeat: The geography of Twitter”. In: First Monday.

Luo, F., E. Zhong, G. Cao, R. D. Tellez, and P. Gao (2013). “VGIS-AntiJitter: an effective framework for solving jitter problems in virtual geographic information systems”. In: International Journal of Digital Earth 6.1, pp. 28-50.

Padmanabhan, A., S. Wang, G. Cao, M. Hwang, Y. Zhao, Z. Zhang, and Y. Gao (2013). “FluMapper: an interactive CyberGIS environment for massive location-based social media data analysis”. In: Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery. , pp. 1-2.

Wang, S., G. Cao, Z. Zhang, and Y. Zhao (2013). “A CyberGlS Environment for Analysis of Location-based Social Media Data”. In: Advanced Location-based Technologies and Services, p. 187.

Yoo, E., B. W. Hoagland, G. Cao, and T. Fagin (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”. In: Geographical Analysis 45.4, pp. 419-440.

2012

Cao, G., P. C. Kyriakidis, and M. F. Goodchild (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’”. In: International Journal of Geographical Information Science 26.10, pp. 1741-1750.

Cao, G., S. Wang, and Q. Guan (2012). “A State-Space Model for Understanding Spatial Dynamics Represented by Areal Data”. In: Proceedings of The 7th International Conference on Geographic Information Science.

Shook, E., K. Leetaru, G. Cao, A. Padmanabhan, and S. Wang (2012). “Happy or not: Generating topic-based emotional heatmaps for Culturomics using CyberGIS”. In: 2012 IEEE 8th International Conference on E-Science. IEEE. , pp. 1-6.

2011

Cao, G., P. C. Kyriakidis, and M. F. Goodchild (2011a). “A multinomial logistic mixed model for the prediction of categorical spatial data”. In: International Journal of Geographical Information Science 25.12, pp. 2071-2086.

Cao, G., P. C. Kyriakidis, and M. F. Goodchild (2011b). “Combining spatial transition probabilities for stochastic simulation of categorical fields”. In: International Journal of Geographical Information Science 25.11, pp. 1773-1791.

Cao, G., P. Kyriakidis, and M. Goodchild (2011c). “A geostatistical framework for categorical spatial data modeling”. In: SIGSPATIAL Special 3.3, pp. 4-9.

2010

Kyriakidis, P. and G. Cao (2010). “Generating Fine Resolution Area Class Maps Subject to Coarser Resolution Data Constraints”. In: Proceedings of The 6th International Conference on GIScience.

2009

Cao, G., P. Kyriakidis, and M. Goodchild (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. , pp. 496-499.

2008

Cao, G. and P. Kyriakidis (2008). “Combining transition probabilities in the prediction and simulation of categorical fields”. In: Proceedings of the 8th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Shanghai.

2007

Li, K., E. Zhong, G. Song, G. Cao, L. Zhang, and Q. Wu (2007). “NDF: an effective mobile GIS physical storage model”. In: Geoinformatics 2007. Vol. 6754. International Society for Optics and Photonics. , p. 67541W.

2006

LI, K., E. ZHONG, Z. ZENG, and G. CAO (2006). “An Optimal Path Algorithm Based on Hierarchically Structured Topographical Network [J]”. In: Journal of Image and Graphics 7, p. 016.

ZHANG, L., J. ZHU, Z. ZENG, and G. CAO (2006). “GRID Services for large scale elevation derivatives computation”. In: Geoinformation Science 8.2, pp. 14-16.

Thesis