2023

Trio of Penn State researchers tapped to lead AGU’s natural hazards section. Penn State News

New model provides improved air-quality predictions in fire-prone areas. Penn State News

Climate-related projects awarded seed grant funding through RISE support. Penn State News

New study finds early warning signs prior to 2002 Antarctic ice shelf collapse. Penn State News

Unusual warming played role in 2002 Antarctic ice shelf retreat: Study. Devdiscourse

Hiestand, M., Carlton, A., and Cervone, G.. Growing season convective systems in the US Corn Belt in relation to land use-land cover and synoptic patterns. Theoretical and Applied Climatology (2023): 1-21.

Alley, R. B., Cuffey, K. M., Bassis, J. N., Alley, K. E., Wang, S., Parizek, B. R., Anandakrishnan, S., Christianson, K., & DeConto, R. M. (2023). Iceberg Calving: Regimes and Transitions. Annual Review of Earth and Planetary Sciences, 51(1), null. https://doi.org/10.1146/annurev-earth-032320-110916

Hu, W., Cervone, G., Young, G., & Delle Monache, L. (2023). Machine Learning Weather Analogs for Near-Surface Variables. Boundary-Layer Meteorology, 186(3), 711–735. https://doi.org/10.1007/s10546-022-00779-6

Lu, M., Li, Y., Yu, M., Zhang, Q., Zhang, Y., Liu, B., & Wang, M. (2023). Spatiotemporal Prediction of Radar Echoes Based on ConvLSTM and Multisource Data. Remote Sensing, 15(5), 1279.

Sava, E., Cervone, G., & Kalyanapu, A. (2023). Multiscale Observation Product (MOP) for Temporal Flood Inundation Mapping of the 2015 Dallas Texas Flood. Remote Sensing, 15(6), Article 6. https://doi.org/10.3390/rs15061615

Wang, S., Liu, H., Alley, R. B., Jezek, K., Alexander, P., Alley, K. E., Huang, Z., & Wang, L. (2023). Multidecadal pre-and post-collapse dynamics of the northern Larsen Ice Shelf. Earth and Planetary Science Letters, 609, 118077.

Yu, M., Masrur, A., & Blaszczak-Boxe, C. (2023). Predicting hourly PM2. 5 concentrations in wildfire-prone areas using a SpatioTemporal Transformer model. Science of The Total Environment, 860, 160446.

2022

Cervone named to inaugural cohort of AGU Local Science Partners program. Penn State News

Model helps researchers choose wind farm locations, predicts output. NSF

Energy, environmental seed grants awarded to 21 interdisciplinary teams. Penn State News

Rahimian, M., Cervone, G., Duarte, J. P., & Iulo, L. D. (2022). A machine learning approach for mining the multidimensional impact of urban form on community scale energy consumption in cities. In Design Computing and Cognition’20 (pp. 607–624). Springer.

Yu, M., Shen, T., & Cervone, G. (2022). A comparative study of deep learning-based time-series forecasting techniques for fine-scale urban extreme heat prediction using Internet of Things observations. In Nanotechnology-Based Smart Remote Sensing Networks for Disaster Prevention (pp. 253–271). Elsevier.

Calovi, M., Hu, W., Clemente, L., & Cervone, G. (2022). Forecasting extreme weather events and associated impacts: Case studies. Extreme Weather Forecasting, 131.

Di, Y., Lu, M., Chen, M., Chen, Z., Ma, Z., & Yu, M. (2022). A quantitative method for the similarity assessment of typhoon tracks. Natural Hazards, 1–16.

Fanfarillo, A. (2022). Analog Ensemble Probabilistic Forecasting using Deep Generative Models. Authorea Preprints.

Hu, W., Cervone, G., Balasubramanian, V., Turilli, M., & Jha, S. (2022). A High-Performance Computing System for Probabilistic Weather Forecasts. Authorea Preprints.

Hu, W., Cervone, G., Merzky, A., Turilli, M., & Jha, S. (2022). A new hourly dataset for photovoltaic energy production for the continental USA. Data in Brief, 40, 107824.

Hu, W., Cervone, G., Turilli, M., Merzky, A., & Jha, S. (2022). A scalable solution for running ensemble simulations for photovoltaic energy. ArXiv Preprint ArXiv:2201.06962.

Hu, W., Laura, C.-H., George, Y., & Cervone, G. (2022). Empirical Inverse Transform Function for Ensemble Forecast Member Selection. Authorea Preprints.

Hu, W., Trusel, L., Yu, M., & Cervone, G. (2022). Quantifying Linkages between Navigational Conditions and Maritime Traffic in the Arctic Ocean. Authorea Preprints.

Huang, Y., Xu, J., Xu, J., Zhao, Y., Yu, B., Liu, H., Wang, S., Xu, W., Wu, J., & Zheng, Z. (2022). HMRFS–TP: long-term daily gap-free snow cover products over the Tibetan Plateau from 2002 to 2021 based on hidden Markov random field model. Earth System Science Data, 14(9), 4445–4462.

Huang, Z., & Wang, S. (2022). Multi-Link and AUV-Assisted Energy-Efficient Underwater Emergency Communications. IEEE Internet of Things Journal.

Jezek, K. C., Wang, S., Leduc-Leballeur, M., Johnson, J. T., Brogioni, M., Miller, J. Z., Long, D. G., & Macelloni, G. (2022). Relationships Between L-Band Brightness Temperature, Backscatter, and Physical Properties of the Ross Ice Shelf Antarctica. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–14.

Jezek, K., Johnson, J., Tsang, L., Brogioni, M., Macelloni, G., Aksoy, M., Kaleschke, L., Leduc-Leballeur, M., Yardim, C., & others. (2022). A review of recent developments in low-frequency ultra-wideband microwave radiometry for studies of the cryosphere. Frontiers in Earth Science, 10, 1029216.

Lu, M., Wang, M., Zhang, Q., Yu, M., He, C., Zhang, Y., & Li, Y. (2022). A vision transformer for lightning intensity estimation using 3D weather radar. Science of the Total Environment, 853, 158496.

Lu, M., Zhang, Y., Chen, M., Yu, M., & Wang, M. (2022). Monitoring Lightning Location Based on Deep Learning Combined with Multisource Spatial Data. Remote Sensing, 14(9), 2200.

Luo, W., Liu, Z., Zhou, Y., Zhao, Y., Li, Y. E., Masrur, A., Yu, M., & others. (2022). Investigating linkages between spatiotemporal patterns of the covid-19 delta variant and public health interventions in Southeast Asia: Prospective space-time scan statistical analysis method. JMIR Public Health and Surveillance, 8(8), e35840.

Masrur, A., Yu, M., Mitra, P., Peuquet, D., & Taylor, A. (2022). Interpretable machine learning for analysing heterogeneous drivers of geographic events in space-time. International Journal of Geographical Information Science, 36(4), 692–719.

Wang, S., Liu, H., Jezek, K., Alley, R. B., Wang, L., Alexander, P., & Huang, Y. (2022). Controls on Larsen C Ice Shelf Retreat From a 60-Year Satellite Data Record. Journal of Geophysical Research: Earth Surface, 127(3), e2021JF006346.

Xu, F., Cervone, G., & Salvador, M. (2022). Expanded Dimensionality for Image Spectroscopy via Machine Learning. Authorea Preprints.

Yang, J., Yu, M., Liu, Q., Li, Y., Duffy, D. Q., & Yang, C. (2022). A high spatiotemporal resolution framework for urban temperature prediction using IoT data. Computers & Geosciences, 159, 104991.

2021

Cervone elected to lead AGU natural hazards section, Penn State News.

Scientists turn to deep learning to improve air quality forecasts, Penn State News.

NASA's ICESat-2 satellite reveals shape, depth of Antarctic ice shelf fractures, EurekAlert!

Bodini, N., Hu, W., Optis, M., Cervone, G., & Alessandrini, S. (2021). Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble. Wind Energy Science, 6(6), 1363–1377.

Calovi, M., Hu, W., Cervone, G., & Delle Monache, L. (2021). NAM-NMM Temperature Downscaling Using Personal Weather Stations to Study Urban Heat Hazards. GeoHazards, 2(3), 257–276. https://doi.org/10.3390/geohazards2030014.

Diaz, J., Cervone, G., & Wauthier, C. (2021). Improving the Thermal Infrared Monitoring of Volcanoes: A Deep Learning Approach for Intermittent Image Series. ArXiv Preprint ArXiv:2109.12767.

Fanfarillo, A., Roozitalab, B., Hu, W., & Cervone, G. (2021). Probabilistic forecasting using deep generative models. GeoInformatica, 25, 127–147.

Hu, W., Cervone, G., Young, G., & Monache, L. D. (2021). Weather analogs with a machine learning similarity metric for renewable resource forecasting. ArXiv Preprint ArXiv:2103.04530.

Hultquist, C., Oravecz, Z., & Cervone, G. (2021). A Bayesian Approach to Estimate the Spatial Distribution of Crowdsourced Radiation Measurements around Fukushima. ISPRS International Journal of Geo-Information, 10(12), 822.

McGlinchy, J., Muller, B., Johnson, B., Joseph, M., and Diaz, J. Fully Convolutional Neural Network for Impervious Surface Segmentation in Mixed Urban Environment. ASPRS Photogrammetric Engineering & Remote Sensing, Volume 87, Number 2, February 2021, pp. 117-123(7). DOI: https://doi.org/10.14358/PERS.87.2.117.

Liu, Q., Gu, J., Yang, J., Li, Y., Sha, D., Xu, M., Shams, I., Yu, M., & Yang, C. (2021). Cloud, Edge, and Mobile Computing for Smart Cities. Urban Informatics, 757–795.

Liu, Q., Harris, J. T., Chiu, L. S., Sun, D., Houser, P. R., Yu, M., Duffy, D. Q., Little, M. M., & Yang, C. (2021). Spatiotemporal impacts of COVID-19 on air pollution in California, USA. Science of the Total Environment, 750, 141592.

Lu, M., Lao, T., Yu, M., Zhang, Y., Zheng, J., & Li, Y. (2021). PM2. 5 Concentration Forecasting over the Central Area of the Yangtze River Delta Based on Deep Learning Considering the Spatial Diffusion Process. Remote Sensing, 13(23), 4834.

Lu, M., Zhang, Y., Ma, Z., Yu, M., Chen, M., Zheng, J., & Wang, M. (2021). Lightning Strike Location Identification Based on 3D Weather Radar Data. Frontiers in Environmental Science, 9, 714067.

Scheele, C., Yu, M., & Huang, Q. (2021). Geographic context-aware text mining: Enhance social media message classification for situational awareness by integrating spatial and temporal features. International Journal of Digital Earth, 14(11), 1721–1743.

Sun, J., Xu, F., Cervone, G., Gervais, M., Wauthier, C., & Salvador, M. (2021). Automatic atmospheric correction for shortwave hyperspectral remote sensing data using a time-dependent deep neural network. ISPRS Journal of Photogrammetry and Remote Sensing, 174, 117–131.

Wang, S., Alexander, P., Wu, Q., Tedesco, M., & Shu, S. (2021). Characterization of ice shelf fracture features using ICESat-2–A case study over the Amery Ice Shelf. Remote Sensing of Environment, 255, 112266.

Wei, L., Zhaoyin, L., Yuxuan, Z., Yumin, Z., Elita, L. Y., Masrur, A., & Yu, M. (2021). Spatiotemporal patterns and progression of the Delta variant of COVID-19 and their health intervention linkages in Southeast Asia. MedRxiv, 2021–12.

Xu, F., Sun, J., Cervone, G., & Salvador, M. (2021). Ill-posed Surface Emissivity Retrieval from Multi-Geometry Hyperspectral Images using a Hybrid Deep Neural Network. ArXiv Preprint ArXiv:2107.04631.

Xu, M., Liu, H., Beck, R. A., Lekki, J., Yang, B., Liu, Y., Shu, S., Wang, S., Tokars, R., Anderson, R., & others. (2021). Implementation strategy and spatiotemporal extensibility of multipredictor ensemble model for water quality parameter retrieval with multispectral remote sensing data. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–16.

Yu, M., & Liu, Q. (2021). Deep learning-based downscaling of tropospheric nitrogen dioxide using ground-level and satellite observations. Science of the Total Environment, 773, 145145.

Yu, M., Xu, F., Hu, W., Sun, J., & Cervone, G. (2021). Using Long Short-Term Memory (LSTM) and Internet of Things (IoT) for Localized Surface Temperature Forecasting in an Urban Environment. IEEE Access, 9.

Zhan, Z., Zheng, L., Wei, M., Yu, M., & Jian, W. (2021). Aerial Image Color Balancing Based on Rank-Deficient Free Network. IEEE Access.

Hu, W., Del Vento, D., & Su, S. (Eds.). (2021). Proceedings of the 2021 Improving Scientific Software Conference (No. NCAR/TN-567+PROC). doi:10.26024/p6mv-en77

2020

COVID-19 SHUTDOWN EFFECT ON AIR QUALITY MIXED, University of Delaware News.

Li, Y., Yu, M., Xu, M., Yang, J., Sha, D., Liu, Q. and Yang, C., 2020. Big Data and Cloud Computing. Manual of Digital Earth, p.325.

Archer, C.L., Cervone, G., Golbazi, M., Al Fahel, N., Hultquist, C., Changes in air quality and human mobility in the USA during the COVID-19 pandemic. Bull. of Atmos. Sci.& Technol. https://doi.org/10.1007/s42865-020-00019-0, 2020.

Fanfarillo, Alessandro, Behrooz Roozitalab, Weiming Hu, and Guido Cervone. Probabilistic forecasting using deep generative models. GeoInformatica 1-21, 2020.

Xu, F., Cervone, G., Franch, G., Salvador, M., Multiple geometry atmospheric correction for image spectroscopy using deep learning, J. Appl. Remote Sens. 14(2), 024518 (2020), doi: 10.1117/1.JRS.14.024518, 2020.

Yu, M., Bambacus, M., Cervone, G., Clarke, K., Duffy, D., Huang, Q., Li, J., Li, W., Li, Z., Liu, Q., Resch, B., Yang, J., Yang, C., Spatiotemporal event detection: a review, International Journal of Digital Earth, DOI: 10.1080/17538947.2020.1738569, 2020.

Hultquist, C., Cervone, G. Integration of Crowdsourced Images, USGS Networks, Remote Sensing, and a Model to Assess Flood Depth during Hurricane Florence. Remote Sensing. Vol. 12, No. 5, pp. 834-851. doi: 10.3390/rs12050834, 2020.

Yang, C., Sha, D., Liu, Q., Li, Y., Lan, H., Guan, W.W., Hu, T., Li, Z., Zhang, Z., Thompson, J.H. and Wang, Z. Taking the pulse of COVID-19: A spatiotemporal perspective. International Journal of Digital Earth. doi: 10.1080/17538947.2020.1809723, pp.1-26, 2020.

Liu, Q., Harris, J.T., Chiu, L.S., Sun, D., Houser, P.R., Yu, M., Duffy, D.Q., Little, M.M. and Yang, C. Spatiotemporal impacts of COVID-19 on air pollution in California, USA. Science of The Total Environment. doi: 10.1016/j.scitotenv.2020.141592, 750, p.141592, 2020.

Li, Y., Jiang, Y., Yang, C., Yu, M., Kamal, L., Armstrong, E.M., Huang, T., Moroni, D. and McGibbney, L.J. Improving search ranking of geospatial data based on deep learning using user behavior data. Computers & Geosciences. doi: 10.1016/j.cageo.2020.104520, p.104520, 2020.

Yu, M. A Graph-Based Spatiotemporal Data Framework for 4D Natural Phenomena Representation and Quantification–An Example of Dust Events. ISPRS International Journal of Geo-Information. doi: 10.3390/ijgi9020127, 9(2), p.127, 2020.

Masrur, A., Yu, M., Luo, W. and Dewan, A. Space-time patterns, change, and propagation of COVID-19 risk relative to the intervention scenarios in Bangladesh. International journal of environmental research and public health. doi: 10.3390/ijerph17165911, 17(16), p.5911, 2020.

Xu, M., Liu, Q., Sha, D., Yu, M., Duffy, D.Q., Putman, W.M., Carroll, M., Lee, T. and Yang, C. PreciPatch: A Dictionary-based Precipitation Downscaling Method. Remote Sensing. doi: 10.3390/rs12061030, 12(6), p.1030, 2020.

Diaz, J., St. Denis, L.A., Joseph, M.B., Solvik, K., Balch, J.K. (2020). Classifying Twitter Users for Disaster Response: A Highly Multimodal or Simple Approach? In Proceedings of 17th International Conference on Information Systems for Crisis Response and Management.

St. Denis, L.A., Hughes, A.L., Diaz, J., Solvik, K., Joseph, M.B., Balch, J.K. (2020). 'What I Need to Know is What I Don't Know!': Filtering Disaster Twitter Data for Information from Local Individuals. In Proceedings of 17th International Conference on Information Systems for Crisis Response and Management.

Hu, W., Del Vento, D., & Su, S. (Eds.). (2020). Proceedings of the 2020 Improving Scientific Software Conference (No. NCAR/TN-564+PROC). doi:10.5065/p2jj-9878

2019

New Postdoctoral Scientist Joins CIESIN to Work Collaboratively on Flood Risk, News from CIESIN at Columbia University.

Model helps choose wind farm locations, predicts output, Penn State News.

Focusing computational power for more accurate, efficient weather forecasts, Penn State News.

Andris, C., Cavallo, S., Clemente-Harding, L., Dzwonczyk, E., Hultquist, C., and Ozanne, M. Towards crowdsourced gravity models for planners: A case study using Facebook. Connections, The Official Journal of the International Network for Social Network Analysis. Vol. 39, No. 1, pp. 1-17. doi: 10.21307/connections-2019-007, 2019

Kugler, T.A., Grace, K., Wrathall, D.J., de Sherbinin, A., Van Riper, D., Aubrecht, C., Comer, D., Adamo, S.B., Cervone, G., Engstrom, R., Hultquist, C., Gaughan, A.E., Linard, C., Moran, E., Stevens, F., Tatem, A.J., Tellman, B., Van Den Hoek, J. People & Pixels 20 years later: The current data landscape and research trends blending population and environmental data. Population and Environment. Vol. 41, No. 2, pp. 209–234. doi: 10.1007/s11111-019-00326-5, 2020.

Hu, W., Cervone, G.. Dynamically Optimized Unstructured Grid (DOUG) for Analog Ensemble of numerical weather predictions using evolutionary algorithms, Computers and Geosciences, 2019

Shahriari, M., Cervone, G., Clemente-Harding L., Delle Monache L. Using the analog ensemble method as a proxy measurement for wind power predictability, Renewable Energy, 2019

Yang, L., Cervone, G. Analysis of remote sensing imagery for disaster assessment using deep learning: a case study of flooding, Soft Comput, 2019

Refereed Conference Proceedings

Hultquist, C. From the Sky to the Crowd: integrating geospatial big data for decision-making. In Proceedings of the 70th International Astronautical Congress (IAC), 2019. IAC-19/B1/4.

Hultquist, C. Is it secret? Is it safe?: Ethical Dimensions of Citizen Science Hazard Data. 1st International Workshop on Legal and Ethical Issues in Crowdsourced Geographic Information. CEUR Workshop Proceedings, 2019.

Presentations

Hu W., Cervone G., Empirical Inverse Transform Function for Ensemble Forecast Member Selection. American Geophysical Union (AGU) Fall Meeting. Poster. San Francisco, CA, December 2019

Calovi M., Cervone G., Clemente-Harding L., Extreme Heat Identification with High Spatio-Temporal Resolution Using the Analog Ensemble Technique. American Geophysical Union (AGU) Fall Meeting. Oral. San Francisco, CA, December 2019

Sun J., Wauthier C., Stephens K., Gervais M., Cervone G., Femina P., Higgins M., Deep Learning Application on Volcanic Deformation Detection and Blind Source Separation in InSAR Data. American Geophysical Union (AGU) Fall Meeting. Poster. San Francisco, CA, December 2019

Cervone G., Nittany Radiance 2019 Longwave Hyperspectral Experiment. American Geophysical Union (AGU) Fall Meeting. Oral. San Francisco, CA, December 2019

Fanfarillo A., Roozitalab B., Hu W., Cervone G., Analog Ensemble Probabilistic Forecasting using Deep Generative Models. American Geophysical Union (AGU) Fall Meeting. ePoster. San Francisco, CA, December 2019

Xu F., Cervone G., Salvador M., Expanded Dimensionality for Image Spectroscopy via Machine Learning. American Geophysical Union (AGU) Fall Meeting. Poster. San Francisco, CA, December 2019

Hultquist C., Cervone G., Harnessing networked citizen sensors during natural hazards. American Geophysical Union (AGU) Fall Meeting. San Francisco, CA, December 2019

Hultquist C., Cervone G., Assessing the Benefits and Limitations of Crowdsourced Data during Disasters. American Geophysical Union (AGU) Fall Meeting. San Francisco, CA, December 2019

Hultquist C., Cervone G., Modeling spatial uncertainty in opportunistically collected citizen science data. American Geophysical Union (AGU) Fall Meeting. San Francisco, CA, December 2019

Cervone G., Remote Sensing target detection using deep learning convolutional networks, Instituto Sant'Anna, Pisa, Italy, November 2019

Hultquist, C. From the Sky to the Crowd: integrating geospatial big data for decision-making. International Astronautical Congress (IAC). Washington, D.C. October 2019.

Hultquist, C. Is it secret? Is it safe?: Ethical Dimensions of Citizen Science Hazard Data. 1st International Workshop on Legal and Ethical Issues in Crowdsourced Geographic Information. Zurich, Switzerland. October, 2019.

Cervone G., Using deep learning convolutional networks to identify atmospheric gases, Universita' di Salerno, Italy, September 2019

Cervone, G., Hu, W., Calovi, M., Extreme values forecasting using an Analog Ensemble, SCRIPPS Institute, University of California, San Diego, August 2019

Hultquist, C. Representation in geosocial data: grappling with uncertainty in digital traces of human activity. UCGIS. Washington, D.C. June 2019.

Hultquist, C. Seeing with new eyes: a comparative geospatial analysis of citizen-contributed and government data during environmental hazards. Lamont-Doherty Earth Observatory, Palisades, NY. May 2019.

Hultquist, C. 1) Validation of Citizen Science Data during Hurricane Florence. Presented in Geospatial Methods and Tools for Disaster Risk Management and Hazards Mapping. 2) Invited panelist in Leveraging Crowdsourcing and Citizen Science to Produce Volunteered Geographic Information for Hazard Science, Disaster Research, and Emergency Management. 3) Invited discussant in Women in Geography, Building Leaders for Tomorrow. American Association of Geographers (AAG). Washington, D.C. April, 2019.

Hultquist, C., Cervone, G. Monitoring Radioactive Releases from Fukushima: a comparison of data and models. Institute for CyberScience Symposium. April 2019.

Cervone, G., Hultquist, C., Combining Remote Sensing and Social Media During Emergencies, Columbia University, April 2019

Hultquist, C. Seeing with new eyes: a comparative geospatial analysis of citizen-contributed and government data during environmental hazards. Department of Engineering Management & Systems Engineering Seminar Series, George Washington University (GWU), Washington, D.C. March 2019.

Jackson, C., Kalyanapu, A., Cervone, C. 2018, Use of Unmanned Aerial Systems (UAS) for Velocimetry Estimation, Geoscience Alliance Conference, Phoenix, AZ, 1 Feb 2019.

Workshops

Hu, W., , Clemente-Harding, L., Cervone, G. Parallel Analog Ensemble Forecasts with Ensemble Toolkit on HPC, Software Engineering Assembly (SEA) University Corporation for Atmospheric Research, Boulder, CO, April 2019.

2018

Researchers create tool to better geographic projections in atmospheric modeling, Penn State News.

GEOlab researchers shaping future of energy, disaster forecasting, Penn State News.

Book Chapters

Cervone, G., Dallmeyer, J., Lattner, A., Franzese, P., Waters, N. Coupling traffic simulation and gas dispersion simulation for atmospheric pollution estimation. In Wang, Shaowen und Goodchild, M. F., editor, CyberGIS: Fostering a New Wave of Geospatial Discovery and Innovation. Springer, 2018

Hultquist, C. Disaster Planning. Encyclopedia of Big Data. Eds Schintler, L. and McNeely, C. Springer International Publishing, http://doi.org/10.1007/978−3−319−32001−4338−1, 2018.

Journal Articles

Hultquist, C., Cervone, G., Comparison of simulated radioactive atmospheric releases to citizen science observations for the Fukushima nuclear accident. Atmospheric Environment. Vol. 198, pp. 478-488, 2018. doi: 10.1016/j.atmosenv.2018.10.018

Calovi M., Seghieri C., Using a GIS to support the spatialreorganization of outpatient care servicesdelivery in Italy, BMC Health Services Research 18: 883, 2018.

Seghieri C., Calovi M., Ferrè F, Proximity and waiting times in choice models for outpatient cardiological visits in Italy, PLoS ONE 13(8), https://doi.org/10.1371/journal.pone.0203018, 2018

Pan, Y., Zhang, X., Cervone, G., Yang, L., Detection of Asphalt Pavement Potholes and Cracks Based on the Unmanned Aerial Vehicle Multispectral Imagery, IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, pages 1-12, http://doi.org/10.1109/JSTARS.2018.2865528, 2018.

Wang, H., Skau, E., Krim, H., Cervone, G., Fusing heterogeneous data: A case for remote sensing and social media, IEEE Transactions on Geoscience and Remote Sensing, pages 1–13, 2018

Cervone, G. and Hultquist, C., Calibration of Safecast dose rate measurements. Journal of Environmental Radiactivity, Volumes 190–191, Pages 51-65, https://doi.org/10.1016/j.jenvrad.2018.04.018, 2018.

Brooks, R.P., Limpisathian, W.P., Gould, T., Mazurczyk, T., Sava, E., Mitsch, W.J. Does the Ohio river flow all the way to New Orleans? Journal of American Water Resources Association, JAWRA-17-0097-N.R1., 2018.

Panteras, G., Cervone, G. Enhancing the temporal resolution of satellite-based flood extent generation using crowdsourced data for disaster monitoring. International Journal of Remote Sensing, Volume 39(5), 2018.

Refereed Conference Proceedings

Carley, K. M., Cervone, G., Agarwal, N., Liu, H., Social cyber-security, In International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, pages 389–394. Springer, 2018

Cervone, G., Hultquist, C., Citizens as indispensable sensors during disasters, in Population-Environment Research Network Cyberseminar, People and Pixels Revisited, February 2018

Presentations

Jackson, C., Kalyanapu, A., Cervone, C. 2018, Use of Unmanned Aerial Systems (UAS) for Velocimetry Estimation, Annual Meeting of the American Geophysical Union, Washington, D.C. 11 Dec 2018.

Calovi M., Visualize the World, GIS Day 2018, PSU, University Park, PA, 13 Nov 2018

Calovi M., 11th Annual Postdoc Exhibition, PSU, University Park, PA, 28 Sep 2018

Calovi M., SMAK Talk - Computational Statistics Talk, PSU, University Park, PA, 14 Sept 2018

Hultquist, C. and Cervone, G. Validation of Citizen Science Environmental Monitoring: a case study of Fukushima Radiation Dose Rate Measurements, Pacific Northwest National Lab (PNNL), Richland, WA, August 2018.

Santos, L., Cervone, G., Investigation Of Atmospheric Attenuation And Influences For Interpreting MSI Imagery Using Sentinel-2 (poster), Committee on Space Research (COSPAR), Pasadena, CA, July 2018

Cervone, G., Citizens as Essential Sensors During Hazards, International Research Institute for Disaster Science, Tohuku University, Japan, July 2018 (invited).

Hultquist, C. Validation and Use of Citizen Science Environmental Data, European Citizen Science Association (ECSA), Geneva, Switzerland, June 2018.

Hu W., Cervone G., Jha S., Balasubramanian V., and Turilli M., Automatic Unstructured Grid Refinement Using Machine Learning for the Analog Ensemble of Numeric Weather Prediction. 2018 All Hands Meeting for EarthCube. Washington, DC, June 2018.

Cervone, G., Calovi M., Temporal and Spatial Downscaling of GFS Forecasts using Personal Weather Stations, BASF, PA, June 2018

Cervone, G., Filling Gaps in Remote Sensing Data Using Social Media During CBRNE Emergencies, ONR HA/DR Operations Program Review, SEAWAR, Charleston, SC, June 2018.

Cervone, G., Citizens as Essential Sensors During Hazards, Department of Geography, University of Delaware, April 2018 (invited).

Hultquist, C. and Cervone, G. Monitoring Radioactive Releases from Fukushima: a comparison of data and models, USGIF Conference, Tampa, FL, April 2018.

Hultquist, C. A Greater Penn State for 21st Century Excellence campaign. Penn State Bryce Jordan Center audience of 2,000 and televised. April 2018.

Calovi M., Cervone G., Dynamic Downscaling of GFS Forecasts Using Personal Weather Stations for Extreme Heat Events, The ICS Symposium 2018: Harnessing the Power of Data. Poster presentation. Penn State, University Park, PA, March 2018.

Hu W., Cervone G., Jha S., Balasubramanian V., and Turilli M., Automatic Unstructured Grid Refinement Using Machine Learning for the Analog Ensemble of Numeric Weather Prediction. The ICS Symposium 2018: Harnessing the Power of Data. Poster presentation. Penn State, University Park, PA, March 2018.

Cervone, G., Stochastic Evolutionary Algorithms Guided by Machine Learning for Atmospheric Source Detection, Stochastic Modeling and Computational Statistics (SMAC), Department of Statistics, Penn State, February 2018.

Cervone, G., Grand Challenge: Combining Remote Sensing, Models and Citizen Science to Understand Sea Level Rise, Lamont-Doherty Earth Observatory, Columbia University, January 2018.

Workshops

Clemente-Harding L., Cervone G., Calovi M., Hu W., The Analog Ensemble (AnEn) technique for probabilistic forecasts, Software Engineering Assembly (SEA) University Corporation for Atmospheric Research, Boulder, Co, April 2018.

2017

Geography undergraduate researches tea plantation loss through Tea Institute, Penn State News.

Hultquist, C., Sava, E., Cervone, G., Waters, N. Damage assessment of the urban environment during disasters using volunteered geographic information. In: L. Shintler and Z. Chen (Eds.), Big Data for Regional Science. CRC Press, ch 18. 2017.

Hultquist, C. Satellite Imagery/Remote Sensing. Encyclopedia of Big Data. Eds Schintler, L. and McNeely, C. Springer International Publishing, http://dx.doi.org/10.1007/978−3−319−32001−4439−1.

Hultquist, C. Sensor Technologies. Encyclopedia of Big Data. Eds Schintler, L. and McNeely, C. Springer International Publishing. doi : 10.1007/978−3−319−32001−4442−1.

Hultquist, C. Data Fusion. Encyclopedia of Big Data. Eds Schintler, L. and McNeely, C. Springer International Publishing. doi : 10.1007/978−3−319−32001−4305−1.

Barkley, Z.R., Lauvaux, T., Davis, K.J., Deng, A., Miles, N.L., Richardson, S.J., Cao, Y., Sweeney, C., Karion, A., Smith, M. and Kort, E.A. Quantifying methane emissions from natural gas production in north-eastern Pennsylvania. Atmospheric Chemistry and Physics, 17(22), p.13941, 2017.

Cao, Y., Cervone, G., Barkley, Z., Lauvaux, T., Deng, A., Taylor, A. Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling. Geoscientific Model Development. Volume 10, 2017, Pages 3425–3440. https://doi.org/10.5194/gmd-10-3425-2017.

Huang, Q., Cervone, G., Zhang, G. 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, Volume 66, 2017, Pages 23-37, ISSN 0198-9715, http://dx.doi.org/10.1016/j.compenvurbsys.2017.06.004.

Cervone, G., Clemente-Harding, L., Alessandrini, S., Monache, L. D. Short-term photovoltaic power forecasting using Artificial Neural Networks and an Analog Ensemble. Renewable Energy, Volume 108, Pages 274-286, ISSN 0960-1481, http://doi.org/10.1016/j.renene.2017.02.052, August 2017.

Petrozziello, A., Cervone, G., Franzese, P., Haupt, S. E., Cerulli, R. Source Reconstruction of Atmospheric Release with Limited Meteorological Observations Using Genetic Algorithms. Applied Artificial Intelligence, 0(0):1–15, 0. http://doi.org/10.1080/08839514.2017.1300005. URLhttp://dx.doi.org/10.1080/08839514.2017.1300005.

Coletti, M., Hultquist, C., Kennedy, W. G., Cervone, G. Validating Safecast data by comparisons to a U. S. Department of Energy Fukushima Prefecture aerial survey. Journal of Environmental Radioactivity, 171, 9–20. http://doi.org/10.1016/j.jenvrad.2017.01.005, February 2017.

Hunter, H., Cervone, G. Analysing the influence of African dust storms on the prevalence of coral disease in the Caribbean Sea using remote sensing and association rule data mining, International Journal of Remote Sensing, 38:6, 1494-1521, January 2017.

Hultquist, C., Cervone, G. Citizen monitoring during hazards: validation of Fukushima radiation measurements. GeoJournal, http://doi.org/10.1007/s10708-017-9767-x, January 2017.

Shahriari M., Cervone G., Monache L., Using Analog Ensemble to generate spatially downscaled probabilistic wind power forecasts. American Geophysical Union (AGU) Fall Meeting. Oral presentation in session Renewable Energy: Wind. New Orleans, LA, December 2017.

Jackson C., Sava E. and Cervone G., Hurricane Harvey Riverine Flooding: Part 2: Integration of Heterogeneous Earth Observation Data for Comparative Analysis with High-Resolution Inundation Boundaries Reconstructed from Flood2D-GPU Model. American Geophysical Union (AGU) Fall Meeting. Poster Presentation. New Orleans, LA, December 2017.

Sava E., Cervone G., Kalyanapu A. J., and Sampson K. M., Integrating heterogeneous earth observation data for assessment of high-resolution inundation boundaries generated during flood emergencies. American Geophysical Union (AGU) Fall Meeting. Poster presentation. New Orleans, LA, December 2017.

Hultquist C. and Cervone G., Bayesian modelling to assess populated areas impacted by radiation from Fukushima. American Geophysical Union (AGU) Fall Meeting. Poster presentation. New Orleans, LA, December 2017.

Hu W., Cervone G., Jha S. Balasubramanian V. and Turilli M., Short-term temperature prediction using adaptive computing on dynamic scales. American Geophysical Union (AGU) Fall Meeting. Poster presentation. New Orleans, LA, December 2017.

Cervone, G., Hultquist, C., Analysis and calibration of Safecast data relative to the 2011 Fukushima Daiichi nuclear accident, American Geophysical Union (AGU) Fall Meeting. Oral presentation in Model, Tools, Techniques, and New Data Streams for Natural Hazards and Emergencies, New Orleans, LA, December 2017.

Cervone, G., The role of citizen science during the Fukushima-Dahichi nuclear accident, Instituto Sant’ Anna, Pisa, Italy, December 2017.

Hultquist, C. Systems view of the spatio-temporal resolution of information during hurricanes, 68th International Astronautical Congress. Oral presentation and conference paper in Space Assets and Disaster Management. Adelaide, Australia. September 2017.

Cervone, G., Using Remote Sensing and GIS to study and potentially prevent atrocities, Mass Atrocity Education Workshop (MAEW), United States National Holocaust Memorial Museum, Washington, D.C, September 2017 (invited).

Calovi, M., Cervone, G., Shahriari, M., A high resolution extreme heat forecasting product based on an Analog Ensemble of atmospheric model and volunteere geographic information. IDRiM2017, the 8th Conference of the International Society for Integrated Disaster Risk Management. Reykjavik, Iceland. August 23-25, 2017.

Sava, E., Thornton, J., Kalyanapu, A., Cervone, G. Integration of Contributed Data with HEC-RAS Hydrodynamic Model for Flood Inundation and Damage Assessment: 2015 Dallas, Texas, Case Study. 42nd Annual Natural Hazards Research and Applications Workshop. Broomfield, Colorado. July 2017.

Sava, E. Assessment of high-resolution inundation boundaries generated using WRF-Hydro during the 2013 Colorado Flood. NCAR SOARS Center for Higher Education: Undergraduate Leadership Program. Boulder, Colorado. July 2017.

Gochis, D., Sava, E. Integrated Hydrometeorological Predictions: A case study of the Colorado Front Range Flood of 2013. NCAR SOARS Center for Higher Education: Bridge to the Geosciences Program. Boulder, Colorado. June 2017.

Hultquist, C., Cervone, G. Unsteady source term estimation of the Fukushima Dai-ichi release using contributed radiological measurements. Japan Geoscience Union (JpGU). Session on Dynamics of radionuclides emitted from Fukushima Dai-ichi Nuclear Power Plant in the environment. Chiba, Japan. May 2017.

Calovi, M., Cervone, G., Dynamic Downscaling of Extreme Temperature. University of Salerno, Italy, May 2017 (invited).

Hu W., Cervone G., Calovi M., Probabilistic Temperature Prediction Using Analog Ensemble Modeling, The 2017 AAG Annual Meeting. Boston, MA, April 2017.

Hultquist, C., Cervone, G. Radiation from Fukushima: Policy, Information, and Technology, American Association of Geographers (AAG). All Things Nuclear. Boston, MA. April 2017.

Clemente-Harding, L., Cervone, G., Monache, L. D., Haupt, S. E., Examination of Spatial Relationships Using Machine Learning. American Meteorological Society Annual Conference. Oral presentation at 15th Conference on Artificial and Computational Intelligence and its Applications to Environmental Sciences, January 2017.

Clemente-Harding, L., Fisher, A., Lewis, M., Smith, C., Eylander, J., Use of the Cosmic-Ray Soil Moisture Observing System to Verify and ImproveLand Surface Model Output. American Meteorological Society Annual Conference. Oral presentation at 31st Conference on Hydrology, Innovative Water Cycle Observations, January 2017.

Hultquist, C., Cervone, G., Geoinformatics and Earth Observation for Understanding Human-Environment Processes, American Meteorological Society (AMS). 12th Symposium on Societal Applications: Policy, Research and Practice - Uses of Earth Observations and Geospatial Information to Support Progress on the Sustainable Development Goals. January 2017.

2016

Geography student wins ICS poster competition, Penn State Institute for CyberScience News.

Mining social media to task satellite data collection during emergencies, SPIE newsroom.

Mining social media can help improve disaster response efforts, Penn State news.

Cervone, G., Schnebele, E., Waters, N., Moccaldi, M., Sicignano, R. Using Social Media and Satellite Data for Damage Assessment in Urban Areas During Emergencies. In: P. THakuriah et al. (eds.), Seeing Cities Through Big Data. Springer Geography, pp. 443-457, 2016.

Huang, Q., Cervone, G. Usage of Social Media and Cloud Computing During Natural Hazards. In: Vance, T.C., Merati, N., Yang, C., Yuan, M. (Eds.), Cloud Computing in Ocean and Atmospheric Sciences. Academic Press, pp. 297-324, 2016.

Sava, E., Clemente-Harding, L., Cervone, G. Supervised classification of civil air patrol (CAP). Natural Hazards, 1-22, 2016.

Leone, V., Cervone, G., Iovino, P., Impact assessment of PM10 cement plants emissions on urban air quality using the SCIPUFF dispersion model. Environmental Modeling and Assessment, 188:499. http://doi.org/10.1007/s10661-016-5519-5, 2016.

Medina, R. M., Cervone, G., Waters, N. M. Characterizing and predicting traffic accidents in extreme weather environments. The Professional Geographer, 6, 1–12, 2016.

Ferruzzi, G., Cervone, G., Delle Monache, L., Graditi, G., Jacobone, F., Optimal bidding in a Day-Ahead energy market for Micro Grid under uncertainty in renewable energy production. Energy, 106, 194-202, 2016.

Cervone, G., Sava, E., Huang, Q., Schnebele, E., Harrison, J., Waters, N., 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, 2016.

Clemente-Harding, L., Cervone, G., Monache, L. D., Haupt, S. E., Alessandrini, S., Analog Ensemble: Optimal Predictor Weighting and Exploitation of Spatial Characteristics in AnEn Generation. American Geophysical Union (AGU) Fall Meeting. Poster presentation in Stochastic and Coupled Modeling for Seamless Earth System Prediction Capabilities II. San Francisco, CA, December 2016.

Hultquist, C., Cervone, G., Situation Awareness of Hazards: Validation of Multi-source Radiation Measurements, American Geophysical Union (AGU) Fall Meeting. Oral presentation in Model, Tools, Techniques, and New Data Streams for Natural Hazards and Emergencies I. San Francisco, CA, December 2016.

Sava, E., Thornton, J., Kalyanapu, A., Cervone, G., Integration of Contributed Data with HEC-RAS Hydrodynamic Model for Flood Inundation and Damage Assessment: 2015 Dallas Texas Case Study (poster), American Geophysical Union (AGU) Fall Meeting, San Francisco, CA, December 2016.

Hultquist, C., Cervone, G., Citizen Monitoring During Hazards: Validation of Fukushima Radiation Measurements (poster). Research Day Penn State, Institute for CyberScience, University Park, PA, October 2016.

Sava, E., Thornton, J., Kalyanapu, A., Cervone, G., Integration of Contributed Data with HEC-RAS Hydrodynamic Model for Flood Inundation and Damage Assessment: 2015 Dallas Texas Case Study (poster), Research Day Penn State, Institute for CyberScience, University Park, PA, October 2016.

Cervone, G., Hultquist, C., Using Volunteer Geographical Information for Situation Awareness during Hazards, CRS4, Cagliari, Italy, June 2016 (invited).

Cervone, G., Clemente-Harding, L., Alessandrini, S., Delle Monache, L., Analog Ensemble for Renewable Energy Forecasts, University of Salerno, Italy, June 2016 (invited).

Cervone, G., Clemente-Harding, L., Alessandrini, S., Delle Monache, L., Photovoltaic Power Forecast Using Neural Networks and Analog Ensemble, The Second University of Naples, Caserta, Italy, June 2016 (keynote).

Cervone, G., Filling the Gaps in Remote Sensing Data using Twitter, Flickr and Instagram, NASA SEDAC User Working Group, Washington D.C., June 2016 (invited).

Hultquist, C., Cervone, G., Citizen Monitoring during Hazards: The Case of Fukushima Radiation. Session chair and presenter: Citizen Science for Environmental Monitoring and Hazards. Session chair: Spatiotemporal Symposium: New Data Sources Technologies and Tools for Disaster Management. Association of American Geographers (AAG) Annual Meeting. San Francisco, CA, March 2016.

Sava, E., Cervone, G., Fusion of Remote Sensing Data and Social Media for Damage Assessment during Emergencies: 2015 Texas Flood Case Study (oral), Association of American Geographers AAG Annual Meeting, San Francisco, CA, March 2016.

Cao Y., Cervone G., Lauvaux T., Barkley Z.,Aijun D.. The Impact of Geographic Coordinate System on Weather Numerical Model, Association of American Geographers (AAG) Annual Meeting, San Francisco, CA, April 2016.

Cervone, G. Fusion of Remote Sensing and Social Media during Emergencies, Lamont-Doherty Earth Observatory, Columbia University, March 2016 (invited).

Alessandrini S., Delle Monache, L., Cervone, G., Harding, L., and Haupt, S. E., Gridded Probabilistic Forecasts of Weather Parameters with an Analog Ensemble, AMS, Seattle, WA, January 2016.

Workshops

Cervone, G., Sava, E., Hultquist, C., Using R for Spatial Analytics. Software Engineering Assembly (SEA) University Corporation for Atmospheric Research, Boulder, Co, April 2016.

2015

Penn State, NCAR researchers aim to better predict renewable energy production, Penn State news.

Schnebele, E., Oxendine, C., Cervone, G., Ferreira, C. M., Waters, N. Using Non-authoritative Sources During Emergencies in Urban Areas. In Computational Approaches for Urban Environments (pp. 337-361). Springer International Publishing, 2015.

Alessandrini, S., Delle Monache, L., Sperati, S., Cervone, G., An analog ensemble for short-term probabilistic solar power forecast, Applied Energy, http://doi.org/10.1016/j.apenergy.2015.08.011, 157:95-110, 2015.

Sava, E., Twardy, C., Koester, R., Sonwalkar, M., Evaluating Lost Person Behavior Models. Transactions in GIS, 2015.

Costantin, J., Delle Monache, L., Alessandrini, S., Cervone, G., Predictor-weighting strategies for probabilistic wind power forecasting with an analog ensemble. Energy Meteorology, http://doi.org/10.1127/metz/2015/0659

Schnebele, E., Tanyu, B., Cervone, G., Waters, N. Review of remote sensing methodologies for pavement management and assessment. European Transport Research Review, 7(2):1–19, 2015.

Ferruzzi, G., Cervone, G., Bidding Strategy of a MicroGrid in the Deregulated Market under Uncertain Photovoltaic Production, ACM SIGSPATIAL International Workshop onSmart Cities and Urban Analytics, Seattle, WA, USA, November 2015.

Hultquist, C., Simpson, M., Cervone, G., Huang, Q., Using Nightlight Remote Sensing Imagery and Twitter Data to Study Power Outages, ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management (EM-GIS), Seattle, WA, USA, November 2015.

Huang, Q., Cervone, G., Jing, D., Chang, C., DisasterMapper: A CyberGIS framework for disaster management using social media data, ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data 2015, Seattle, WA, USA, November 2015.

Ciaramella, A., Staiano, A., Cervone, G., Alessandrini, S., Bayesian Based Neural Network Models for Solar Photovoltaic Forecasting, 25th Italian Workshop on Neural Networks (WIRN-2015), Vietri sul Mare, Salerno, Italy, May 20-22 2015

Harding, L., Cervone, G., Delle Monache, L., GC53D-1240: Analog Ensemble Methodology: Expansion and Optimization for Renewable Energy Applications (poster), AGU Fall Meeting, San Francisco, December 2015.

Hultquist, C., Cervone, G., ED53B-0855: Citizen Monitoring during Hazards: The Case of Fukushima Radiation after the 2011 Japanese Earthquake (poster), AGU Fall Meeting, San Francisco, December 2015.

Cao, Y., Barkley, Z., Cervone G., Lauvaux, T., A11M-0239: Fusion Geographic Information System Data with State-of-the-art Atmospheric Systems: Application to Methane Source Mapping over the Marcellus Shale formation (poster), AGU Fall Meeting, San Francisco, December, 2015.

Sava, E.,, Harding, L., Cervone, G., NH52A-03: Supervised classification of aerial imagery and multi- source data fusion for flood assessment (oral), AGU Fall Meeting, San Francisco, December 2015.

Ferruzzi, G., Cervone, G., Bidding Strategy of a MicroGrid in the Deregulated Market under Uncertain Photovoltaic Production, ACM SIGSPATIAL International Workshop onSmart Cities and Urban Analytics, Seattle, WA, USA, November 2015.

Hultquist, C., Simpson, M., Cervone, G., Huang, Q., Using Nightlight Remote Sensing Imagery and Twitter Data to Study Power Outages, ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management (EM-GIS), Seattle, WA, USA, November 2015.

Huang, Q., Cervone, G., Jing, D., Chang, C., DisasterMapper: A CyberGIS framework for disaster management using social media data, ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data 2015, Seattle, WA, USA, November 2015.

Cervone, G., Sava, E., Huang, Q., A CyberGIS framework for the study of Environmental Hazards, CyberGIS Meeting, USGS, Reston VA, September 2015.

Cervone, G., Data fusion of remote sensing and volunteer geographical information, Workshop on Disaster Tools, Carnegie Mellon University, Pittsburg PA, August 2015.

Cervone, G., Filling Gaps in Remote Sensing Data Using Social Media During CBRNE Emergencies, ONR HA/DR Operations Program Review, Carnegie Mellon University, Pittsburg PA, July 2015.

Hultquist, C., Simpson, M. Real-time Detection and Tracking of Power Outages via Social Media, Natural Hazards Center Annual Workshop. Boulder, CO, July 2015.

Hultquist, C., Coletti, M., Cervone, G., Citizen Monitoring during Hazards: The Case of Fukushima Radiation after the 2011 Japanese Earthquake, University Consortium for Geographic Information Science (UCGIS) Annual Meeting. Alexandria, VA. May 2015.

Hultquist, C., Machine Learning for Post-fire Burn Severity Assessment in Diseased Forests, Association of American Geographers (AAG) Annual Meeting. Chicago, IL, April 2015.

Sava. E., Harding-Clemente L., Cervone, G., Classification of Civil Air Patrol Imagery for Flood Damage Assessment, Association of American Geographers (AAG) Annual Meeting, Chicago, IL, April 2015.

Harding, L., Cervone, G., Application of the Analog Ensemble Methodology Using Predictor Weighting for Renewable Energy, Association of American Geographers (AAG) Annual Meeting. Session: Energy Transitions I: Analysis, Chicago, IL, April 2015.

Harding, L., Cervone, G., Brothers, M., Application of the Analog Ensemble Methodology to Renewable Energy: Visualization of Optimized Parameter Weighting, Spatial Cognition Symposium, March 2015.

Cervone G., Geoinformatics approaches for environmental hazards damage assessment and renewable energy optimization, University of Wisconsin at Madison, February 27, 2015

Cervone G., Power Metered Forecasts for Renewable Energy, Department of Mathematics, University of Salerno, Italy, January 2015.

Workshops

Coletti, M., Cervone, G., A python QGIS plugin for twitter analysis during emergencies, Software Engineering Application Conference (SEA-2015) (invited), Boulder Co, April 2015.

2014

Penn State Department of Geography newletter

Cervone, G., Lin, J., Waters, N. Data Mining for Geoinformatics: Methods and Applications, volume ISBN-13: 978-1-4614-7668-9. Springer, 2014.

Cervone, G., Franzese, P. Source term estimation for the 2011 Fukushima nuclear accident. In Data Mining for Geoinformatics, pages 49–64. Springer, 2014

Sava E., Edwards B., and Cervone G.: Chlorophyll increases off the coasts of Japan after the 2011 tsunami using NASA/MODIS data, Nat. Hazards Earth Syst. Sci., 14, 1999–2008, http://doi.org/10.5194/nhess-14-1999-2014, 2014

Schnebele, E., Cervone, G., and Waters, N.: Road assessment after flood events using non-authoritative data, Nat. Hazards Earth Syst. Sci., 14, 1007-1015, http://doi.org/10.5194/nhess-14-1007-2014, 2014.

Manca, G., Cervone, G., Klarke, K. Combined approach of a couple fire model with atmospheric releases: the case of the 2003 Glacier wildfires, European Journal of Remote Sen sing, 47:181–193, 2014.

Schnebele, E., Cervone, G., Kumar, S., Waters, N. Real time estimation of the Calgary floods using limited remote sensing data, Water, 6:381-398, 2014.

Hultquist, C., Chen, G., Zhao, K. A comparison of Gaussian process regression, random forests and support vector regression for burn severity assessment in diseased forests. Remote Sensing Letters, 5(8):723–732, September 2014.

Cervone, G., Schnebele, E., Waters, N., Harrison, J., Moccaldi, M., Sicignano, R. Using social media to task data collection and augment observations in urban areas during emergencies: 2013 Boulder floods case study. In Proceedings of Big Data for Urban Informatics Conference (BDUIC), Chicago, IL, August 11-12 2014.

Oxendine, C. E., Schnebele, E., Cervone, G., Waters, N. Fusing non-authoritative data to improve situational awareness in emergencies. In Proceedings of the 11th Information Systems for Crisis Response and Management (ISCRAM) Conference, pages 762–766. University Park, PA, May 19-21 2014.

Presentations

Clemente-Harding, L., American Meteorological Society (AMS) Annual Meeting. 13th Conference on Artificial Intelligence, Phoenix, AZ, December 2014.

Cervone G., High Performance Computation for Probabilistic Forecasts, NSF Workshop on Polar CyberInfrastructure, Rutgers University, New Brunswick NJ, December 2014.

Hultquist, C., Criminalization of Indian Politics in Uttar Pradesh, Pennsylvania Geographical Society. State College, PA, November 2014.

Hultquist, C., Machine Learning for Post-fire Burn Severity Assessment in Diseased Forests, Pennsylvania Geographical Society. State College, PA, November 2014.

Hultquist, C., Machine Learning for Post-fire Burn Severity Assessment in Diseased Forests, Middle States Division of the Association of American Geographers. York, PA, October 2014.

Cervone, G., From Big Data to Big Knowledge: The Revolution of CyberScience and GeoInformatics, National Center for Atmospheric Research, Boulder CO, July 2014.

Cervone, G., Rocco, G., Radzikowski, J., Assessing the potential impact of shale gas extraction on rattlesnakes in rural areas using UAVs, Boulder Linux User Group, Boulder CO, July 2014.

Cervone, G., Schnebele, E., GeoInformatics Approach for the Analysis of Big Data from Atmospheric Models, Remote Sensing and Social Media, National Center for Atmospheric Research, Boulder CO, July 2014.

Cervone, G., Using Geoinformatics for the analysis of remote sensing, model and social media ’big data’ to study environmental hazards, Department of Environmental Engineering, University of Caserta, Italy, June 2014.

Cervone, G., Fusing Remote Sensing and Social Media for Situation Awareness During Emergencies, ONR Science Meeting, Washington D.C., May 2014.

Workshops

Cervone, G., Code Testing in a Distributed Environment: Lessons Learned from a Joint University-NCAR project, Software Engineering Application Conference (SEA-2014) (invited), Boulder Co, April 2014.

2013

Journal Articles

Manca, G., Cervone, G. The case of arsenic contamination in the Sardinian geopark, italy, analyzed using symbolic machine learning, Environmetrics, http://doi.org/10.1002/env.2222, 2013.

Schnebele, E., Cervone, G. Improving remote sensing flood assessment using volunteered geographical data, Natural Hazards Earth System Science, 13:669–677, 2013.

Owusu A., Cervone G., Beach S., Analysis of Desertification in the Upper East Region (UER) of Ghana Using Remote Sensing, Field Study, and Local Knowledge, Carthographica, 48(1), pp22-37, 2013.

Conferences Proceedings

Dallmeyer, J., Lattner, A. D., Cervone, G., Timm, I. J. Simulation von Schadstoffemissionsverteilungen auf Basis multimodalen, akteursorientierten Verkehrs. In Proceedings of ASIM Simulation in den Umwelt- und Geowissenshaften, Leipzig, Germany, April 10-12 2013. ASIM.

Technical Report

Goolsby, R., Cervone, G. Using social media to fill the gaps in observations during emergencies. In Innovation, volume 11, pages 19–22. Office of Naval Research, Winter 2013.

Presentation

Non-Steady Source Term Estimation for the 2011 Fukushima Nuclear Accident, ISSNAF Meeting, Embassy of the Republic of Italy (invited), Washington, D.C., October 2013.

A Geoinformatics Approach for the Analysis of Remote Sensing, Model and Social Media Big Data to Study Environmental Hazards, offered as part of the ‘Taming the Data’ series, North Carolina State University, Durham NC, October 2013.

Filling the Gaps in Remote Sensing Data using Social Media, ONR Workshop at NATO Headquarters, Brussels, Belgium, October 2013.

Spatio-Temporal Data Mining for Geoinformatics, Department of Computer Science, University of Salerno, Italy, July 2013.

Using Social Media for Filling the Gaps in Remote Sensing Data, Department of Machine Learning, Carnegie Mellon University, May 2013.

Application of Geoinformatics and Remote Sensing to Study Environmental Hazards, Department of Geography, the Pennsylvania State University, University Park PA, March 2013.

2012

Articles and Interviews About Me and My Work

Rhodesia at George Mason University, by Chris Whitehead, Rhodesians Worldwide, 27(4) pp. 22, 2012.

Measuring Sea Surface Temperature Can Help Sailors Safely and Swiftly Cross the Gulf Stream, Scientist Find, Mason News.

Mainsim: Frankfurt develop computer traffic simulation system (in German). You can read an English translation thanks to Google Translate.

Journal Articles

Cervone G., Haack B., Supervised Machine Learning Classification for Land Cover Using Combined RADAR and Electro-optical Data, Journal of Applied Remote Sensing, Volume 6(1), 18 pages, 2012.

J. Welsh-Thomas, Cervone G., Agouris P., Manca G., Further evidence of impacts of large-scale wind farms on land surface temperature, Renewable & Sustainable Energy Reviews 16(8) pp6432-6437, 2012.

Cervone G., Combined Remote Sensing, Model and In Situ Measurements of Sea Surface Temperature as Aid to Recreational Navigation: Crossing the Gulf Stream, International Journal of Remote Sensing 34(2) pp434-450, 2012.

Lattner A. and Cervone G., Ensemble Modeling of Transport and Dispersion Simulations guided by Machine Learning Hypotheses Generation, Computers & Geosciences, 48, pp267-279, http://doi.org/10.1016/j.cageo.2012.01.017, 2012./p>

Conferences Proceedings

Coletti M., Cervone G., Analysis of Emergent Selection Pressure in Evolutionary Algorithm and Machine Learner Offspring Filtering Hybrids, Proceedings of the third Swarm, Evolutionary and Memetic Computing Conference (SEMCCO), pp9-15, 2012.

Manca G., Cervone G., Clark, K., Atmospheric Releases During the 2003 Glacier Wildfires: Mapping, Analysis and Modeling, Proceedings of the 2009 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 22-27, Munich Germany, 2012

Presentations

Cervone G., and Franzese P., Source Term Estimation for the 2011 Fukushima Nuclear Accident, Workshop: Methods for Estimating Radiation Release from Fukushima Daiichi, NCAR Boulder, CO, February 2012.

Cervone G., Machine Learning for Source Detection, University of Salerno, Italy, July 2012.

Presentation

Machine Learning Based Evolution for Optimization and Anomaly Detection, Department of Computer Science, University of Salerno, Italy, July 2012.

Source Term Estimation for the 2011 Fukushima Nuclear Accident, NSF Workshop on Methods for Estimating Radiation Release from Fukushima Daiichi, National Center for Atmospheric Research, Boulder CO, February 2012.

2011

Articles and Interviews About Me and My Work

Data Analysis of the damages from the March 11 Japanese Tsunami are on the disasterscharter.org website

Broadside article about my work

Interview about my work with Germana Manca on the Japanese Earthquake, (Alternative) ABC News Channel 7, March 22 18:00, 2011

GMU article about my work

Simulation of Japanese Earthquake Radioactive Plume, used by Bob Ryan, ABC News Channel 7, March 13 23:00, 2011

Landsat Satellite Images Before and After the Japanese Earthquake, used by Topper Shutt, WUSA Channel 9, March 13 17:00, 2011

Japanese Tsunami Flooding from Space, CNN iReport, March 12, 2011

Journal Articles

Cervone G., Franzese P., Non-Darwinian Evolution For The Source Detection Of Atmospheric Releases, Atmospheric Environment, http://doi.org/10.1016/j.atmosenv.2011.04.054, 2011

Cervone G., Manca G., Damaga Assessment of the 2011 Japanese Tsunami Using High Resolution Satellite Data, Carthographica, 2011.

Conference Articles

Cervone G., Franzese P., Non-Darwinian Evolution For Source Estimation, Proceedings of the 9th Conference on Artificial Intelligence Applications to Environmental Science, Code J1.5, Seattle, WA, January 2011.

Cervone G., Lin J., Franzese P., Addressing Wind Direction Uncertainty in Source Estimation Through Dynamic Time Warping, Proceedings of the 91st American Meteorological Society Annual Meeting, Session 2: Computational intelligence methods and their applications to environmental science , Code J2.5, Seattle, WA, January 2011.

Presentation

Research Activities in Geospatial Analysis at the Department of Geography and Geoinformation Science, Annual BAE GXP conference, Chantilly, VA, May 2011.

2010

Book Proceedings

Lin J., Cervone G., Waters N., Proceedings of the 1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics (DMG) 2010, 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACMGIS), ISBN: 978-1-4503-0430-6, San Jose, CA, November 2, 2010.

Refereed Journal Articles

Cervone G., Franzese P., Gradjeanu, A., Characterization of atmospheric contaminant sources using adaptive evolutionary algorithms, Atmospheric Environment, http://doi.org/10.1016/j.atmosenv.2010.06.046, 2010.

Cervone G., Franzese P., Monte carlo source detection of atmospheric emissions and error functions analysis, Computers & Geosciences, 36(7), 902-909, http://doi.org/10.1016/j.cageo.2010.01.007,2010.

Cervone G., Franzese P., Keesee A., Algorithm Quasi-Optimal (AQ) learning, WIREs: Computational Statistics, 2 pp 218-236, 2010.

Conference Articles

Lin J., Cervone G., Franzese P., Assessment of Error in Air Quality Models Using Dynamic Time Warping, Proceedings of the 1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics (DMG) 2010, pp38-44, San Jose, CA, November 2, 2010.

Cervone G., Franzese P., Machine Learning for the Source Detection of Atmospheric Emissions, Proceedings of the 8th Conference on Artificial Intelligence Applications to Environmental Science, Code J1.7, Atlanta, GA, January 2010

Presentations

Cervone G., Atmospheric Source Detection Through Machine Learning, Johann Wolfgang Goethe Universitat Frankfurt, Germany

Cervone G., Geoinformatics and Machine Learning, Johann Wolfgang Goethe Universitat Frankfurt, Germany

2009

US Patent

Guido Cervone et al. Wavelet maxima curves of surface latent heat flux Application number: 11/108,115, Publication number: US 2005/0229508 A1, Filing date: Apr 18, 2005

Conference Articles

Cervone G., Stefanidis A., Franzese P., Agouris P., Spatiotemporal Modeling and Monitoring of Atmospheric Hazardous Emissions using Sensor Networks, Proceedings of the 2009 IEEE International Conference on Data Mining Workshops, Spatial and Spatiotemporal Data Mining (SSTDM), pp571-576, Miami, FL, December 2009

Bowman M., Cervone G., The next generation of remote sensing for natural hazard and environmental monitoring: National Polar-orbiting Operational Environmental Satellite System (NPOESS), Proceedings of the 33rd International Symposium on Remote Sensing of Environment (ISRSE), May 4-8, 2009, Stresa, Italy

Bowman M., Cervone G., Franzese P., Source Detection of Atmospheric Releases Using Symbolic Machine Learning Classification and Remote Sensing, Proceedings of the 2009 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) July 12-17, Cape Town, South Africa, 2009.

2008

Articles and Interviews About Me and My Work

Anche questa e' America, Oscar Bartoli, LUISS University Press, 2008

Don't Rebuild on China Quake Faults, Experts Warn, National Geographics, By Kevin Holden Platt, June 17, 2008

Journal Articles

Cervone G., Franzese P., Ezber Y., Boybeyi Z., Risk Assessment of Atmospheric Emissions Using Machine Learning, Natural Hazards and Earth System Sciences, 8, 991-1000, 2008.

Conference Articles

Cervone G., Franzese P., Ezber Y., Boybeyi Z., Risk Assessment of Atmospheric Emissions Using K-means Clustering, Proceedings of the 2008 Workshop on Spatial and Spatio-Temporal Data Mining, SSTDM-08, International Conference on Data Mining (ICDM-08), Pisa, Italy, 2008.

2007

Articles and Interviews About Me and My Work

NBC 4 News, by Bob Ryan, May 15, 2007

NBC 4 News, by Bob Ryan, May 14, 2007

NBC 4 News, by Bob Ryan, May 11, 2007

Erdbeben-Alarm Was taugen die neuen Methoden? Pages 46-47, Bild der Wissenschat, Deustchland, by Alex Tillemans, March, 2007

Journal Articles

Ouzounov D., Liu D., Chunili K., Cervone G., Kafatos M., Taylor P., Outgoing long wave radiation variability from IR satellite data prior to major earthquakes, Tectonophysics, Volume 431, Issues 1-4, 20,Pages 211-220, 2007

Singh R. P., Cervone G., Kafatos M., Prasad A. K., Sahoo A. K., Sun D., Tang D. L., Yang R., Multi-sensor studies of the Sumatra earthquake and tsunami of 26 December 2004, International Journal of Remote Sensing
Special Issue: Satellite Observations Related to Sumatra Tsunami and Earthquake of 26 December 2004, Volume 28 Issue 13 & 14 Print ISSN: 0143-1161 Online ISSN: 1366-5901, 2007

Kayetha V. K., Senthilkumar J., Prasad A. K., Cervone G., Singh R. P., Effect of Dust Storm on Ocean Color and Snow Parameters, Journal of the Indian Society of Remote Sensing, Vol 35, 1, 2007

Singh R. P., Cervone G., Singh V. P., Kafatos M., Generic Precursors to coastal earthquakes: Inferences from Denali fault earthquake, Tectonophysics, Volume 431, Issues 1-4, 20, Pages 231-240, February 2007

Sun, D., Kafatos M., Cervone, G., Boybeyi Z., Yang R., Satellite Microwave Detected SST Anomalies and Hurricane Intensification, Natural Hazards, DOI 10.1007/s11069-006-9099-5, 2007

Presentations

Cervone, G., Using Remote Sensing to Study the Earth, Barrett Elementary School, Arlington, VA, November 16 2007

Cervone, G., Using Google Earth for Near Real Time Natural Hazard Monitoring, Google Santa Monica, Santa Monica, February 23, 2007

2006

Articles and Interviews About Me and My Work

Hurricane Ernesto making landfall in Florida, Fox News@5, Washington D.C., August 29, 2006

George Mason Scientists prepare for busy hurricane season, Fox News@5, Washington D.C., June 1, 2006

An Antenna to track hurricanes? ABC News, Washington D.C., by Peggy Fox, May 31, 2006

Storm Tracker, Mason Spirit, George Mason University, October 24, 2006

Quake Forecast, The Globe and Mail, Canada, October 1, 2006

Spotlight on Research: Global Change Scientists Use New Technology to Predict Intensity of Hurricanes, Mason Gazette, by Tara Laskowski (http://gazette.gmu.edu/articles/8994), September 19, 2006

Journal Articles

Cervone G., Kafatos M., Napoletani D., R.P. Singh, An early warning system for coastal earthquakes, Advances in Space Research, Volume 37, Issue 4, pages 636-642, 2006

Cervone G., Maekawa S., Singh R., Hayakawa M., Kafatos M., and Shavets A., Surface Latent Heat Flux and Nighttime LF Anomalies prior to the Mw=8.3 Tokachi-Oki Earthquake, Natural Hazards and Earth System Sciences, 6, 109-114, 2006

Pulinets S., Ouzounov D., Ciraolo L., Singh R. P., Cervone G., Leyva S., Dunajecka M., Karelin A. V., Boyarchuk K. A., and Kotsarenko A., Thermal, atmospheric and ionospheric anomalies around the time of the Colima M7.8 earthquake of 21 January 2003, Ann. Geophys., 24, pages 835-849, 2006

Singh R. P., Dey P., Bhoi S., Sun D., Cervone G. and Kafatos M., Anomalous increase of chlorophyll concentrations associated with earthquakes, Advances in Space Research, Volume 37, Issue 4, pages 636-642, 2006

Sarkar S., Choknagmwong R., Cervone G., Singh R.P., Kafatos M., Variablity of Aerosols Optical Depth and Aerosol Forcing over India, Advances in Space Research, 37, pages 671–680, 2006

Papasimakis N., Cervone G., Pallikari F., Kafatos M., Multifractal character of surface latent heat flux, Physica A: Statistical and Theoretical Physics, Volume 372, Issue 2, pp 703-718, 15 November 2006 (http://dx.doi.org/10.1016/j.physa.2006.03.053)

M. Kafatos, D. L. Sun, R. Gautam, Z. Boybeyi, R. Yang, and G. Cervone, The role of warm Gulf waters in the intensification of Hurricane Katrina, Geophysical Research Letters, VOL. 33, L17802, http://doi.org/10.1029/2006GL026623, 2006

Sun D. L., R. Gautam, G. Cervone, Z. Boybeyi, and M. Kafatos, Comments on "Satellite Altimetry and the Intensification of Hurricane Katrina", EOS, Vol. 87, No. 8., 2006

Invited Articles

Cervone, G., Urban Environment: Challenges for Sustainability, Development Gateway, Special Report, June 5, 2006

2005

Articles and Interviews About Me and My Work

Local Scientists detect anomalies prior to the October 10, 2005 Pakistan Earthquakes, Fox News@5, Washington D.C., October 11, 2005.

Can Earthquakes be Forecasted?, NBC New, Baltimore, MD, October 11, 2005.

Warm Gulf Waters Fueling Busy Hurricane Season, ABC News, September 22, 2005

Did warm waters fuel Hurricane Katrina?, Physics Web, http://physicsweb.org/articles/news/9/10/2/1

Can Software Predict Earthquakes?, Washington Insider October 21, 2005, by Josh Drobnyk
http://www.dcexaminer.com/articles/2005/10/11/news/n_virginia_news/02newsv12quakes.txt

From the Ground Up, Mason Spirit, By Robin Herron
http://www.gmu.edu/alumni/spirit/spring05/groundup.html

Journal Articles

Gautam R., Cervone G., Singh R.P., Kafatos M., Characteristics of Meteorological Parameters Associated with Hurricane Isabel, Geophysical Res. Letters, 32, L04801, http://doi.org/10.1029/2004GL021559, 2005

Cervone G., Singh R. P., Kafatos M., Yu. C.., Wavelet maxima curves of surface latent heat flux anomalies associated with Indian earthquakes, Natural Hazards and earth System Sciences, 5: 87–99. SRef-ID: 1684-9981/nhess/2005-5-87, 2005

Presentations

Kafatos M., Boybeyi Z., Cervone G., Di L., Sun D, Yang C., Web-based Services for Earth Observing and Model Data in National Applications and Hazards, AGU-2005, American Geophysical Union (invited), San Francisco, December 2005

Presentations

Kafatos M., Cervone G., Earthquake Forecasting and Risk Mitigation Using Space Remote Sensing Data, Georgetown University, Center for the Environment, School of Foreign Service (invited), December 2005

2004

Refereed Journal Articles

Cervone G., Kafatos M., Napoletani D., Singh R.P., Wavelet Maxima Curves Associated with Two Recent Greek Earthquakes, Natural Hazards and Earth System Sciences, European Geophysical Society, 4:359-374, 2004

Refereed Conference Articles

Cervone G., Panait L., Singh R., Kafatos M., Luke S., An Application of Evolutionary Algorithms to Predict the Extent of SLHF Anomaly Associated with Coastal Earthquakes, Proceedings of GECCO-2004, Genetic and Evolutionary Computation Conference, Seattle, WA, June 26-30 2004

Presentations

Singh R. P., Cervone G., Dey S., Kafatos M., Surface Latent Heat Flux Associated with Indian Coastal Earthquakes, AOGS 2004, Asia-Oceania Geoscience Society, Singapore, July 5-9 2004

Chokngamwong R., Cervone G., Singh R. P., Kafatos M. Effect of the populated and industrial cities on the aerosol optical depth, COSPAR-2004, Committee on Space Research, Paris, France, July 18-25 2004

2003

Refereed Conference Articles

Lattner A. D., Kim S., Cervone G., Grefenstette J.J., Experimental comparison of symbolic learning programs for the classification of gene network topology models, FGML 2003 Workshop, Annual Meeting of the GI Working Group "Machine Learning, Knowledge Discovery, Data Mining" Karlsruhe, Germany

2002

Presentations

Cervone G., Scorcioni, R., El Askari, H., Gao, L., Machine learning to categorize dendritic classes, KIAS, Computational Neuroanatomy Group, Krasnow Institute for Advanced Studies, Fairfax, VA, June 2002

Refereed Conference Articles

Scorcioni R., Cervone G. and Ascoli G. A., Machine learning derived rules for the quantitative definition of neuromorphological classes, Program No. 312.15. 2002 Poster Session Washington DC, Society for Neuroscience

Cervone, G., et Al., Recent Results from the Experimental Evaluation of the Learnable Evolution Model, Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2002, 2002

2001

Presentations

Cervone, G., The Learnable Evolution Model, TZI, Bremen, Germany, July 2001

Refereed Conference Articles

Cervone G. and Zucchelli M., An Application of Machine Learning to the Optimization of Disparity Maps, Proceedings of IASTED-01, 2001

Cervone, G., Panait, L. A. et Al., The Development of the AQ20 Learning System and Initial Experiments, Tenth International Symposium on Intelligent Information Systems, Zakopane, Poland, June, 2001

2000

Refereed Conference Articles

Cervone, G., et Al., and Panait, L. A., Combining Machine Learning with Evolutionary Computation Recent Results on LEM, Proceedings of the Fifth International Workshop on Multistrategy Learning (MSL-2000), Guimaraes, Portugal, pp 41-58, June 2000

Cervone, G., et Al., Experimental Validations of the Learnable Evolution Model, 2000 Congress on Evolutionary Computation, San Diego CA, pp 1064-1071, July 2000