Andrew Michaelis

Staff Engineer, Infrastructure and Software Engineering
NASA Earth eXchange (NEX)
Advanced Computing Branch (TNC)
Business Email: andrew.r.michaelis@nasa.gov

Publications

• Bingham, A., Mitchell, A., Gentemann, C., Dahl, L., Stavros, N. E., Sayfi, E., Michaelis, A., Ho, E., Ott, L., Bienstock, B., Hua, H., Yue, Q., Su, W., Harkin, S., Parker, A., Engebretson, C., Lubkin, S., & Yuen, K. (2023, March 31). Final report of the open source science for earth system observatory mission data processing architecture study. NASA. https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=doi%3A10.48577%2Fjpl.AXZSUY 
• Thrasher, B., Wang, W., Michaelis, A., Melton, F., Lee, T. and Nemani, R., 2022. NASA Global Daily Downscaled Projections, CMIP6. Scientific Data, 9(1), pp.1-6.
• T. J. Vandal, D. McDuff, W. Wang, K. Duffy, A. Michaelis and R. R. Nemani, “Spectral Synthesis for Geostationary Satellite-to-Satellite Translation,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-11, 2022, Art no. 4702611, doi: 10.1109/TGRS.2021.3088686.                                               
• Natasha Stavros, Elias Sayfi, Andrew Michaelis, Bernie Bienstock, Wenying Su, Hook Hua, Evelyn Ho, Karen Yuen, Qing Yue, Curt Tilmes, Lesley Ott, Chris Engebretson, Adrian Parker, Sean Harkins, Mike Chepurin “Workshop# 2 Report; ESO Mission Data Processing Study: Summary of State-of-the-Practice and State-of-the- Art Mission Data Processing System Architectures” 2022 https://trs.jpl.nasa.gov/handle/2014/54626                          
• Jon Jenkins, Peter Tenenbaum, Yohei Shinozuka, et al. Progress in Developing a Prototype Science Pipeline and Full-Volume, Global Hyperspectral Synthetic Data Sets for NASA’s Earth System Observatory’s Upcoming Surface, Biology and Geology Mission. Authorea. December 31, 2021.
• Hashimoto, H., Wang, W., Dungan, J.L., Li, S., Michaelis, A.R., Takenaka, H., Higuchi, A., Myneni, R.B. and Nemani, R.R., 2021. New generation geostationary satellite observations support seasonality in greenness of the Amazon evergreen forests. Nature communications, 12(1), pp.1-11.
• Stavros, E. Natasha; Sayfi, Elias; Bienstock, Bernie; Su, Wenying; Hua, Hook; Michaelis, Andrew; Ho, Evelyn; Yuen, Karen; Yue, Qing; Tilmes, Curt; Ott, Lesley; Engebretson, Chris; Parker, Adrian; Harkins, Sean; Chepurin, Mike, 2021, “ESO Mission Data Processing Study – Summary of NASA Program Offices and ESO Missions Requirements, Constraints, Recommendations, and Opportunities” 2021, https://hdl.handle.net/2014/53042
• Collier, E., Duffy, K., Ganguly, S., Madanguit, G., Kalia, S., Shreekant, G., Nemani, R., Michaelis, A., et al., 2018, November. Progressively growing generative adversarial networks for high resolution semantic segmentation of satellite images. In 2018 IEEE International Conference on Data Mining Workshops (ICDMW) (pp. 763-769). IEEE
• Boyda, E., Basu, S., Ganguly, S., Michaelis, A., Mukhopadhyay, S. and Nemani, R.R., 2017. Deploying a quantum annealing processor to detect tree cover in aerial imagery of California. PloS one, 12(2), p.e0172505
• Vandal, T., Kodra, E., Ganguly, S., Michaelis, A., Nemani, R. and Ganguly, A.R., 2017, August. Deepsd: Generating high resolution climate change projections through single image super-resolution. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1663-1672). ACM.
• K. Schleeweis, S. N. Goward, C. Huang, J. L. Dwyer, J. L. Dungan, M. A. Lindsey, A. Michaelis, K. Rishmawi, and J. G. Masek, Selection and quality assessment of Land- sat data for the North American forest dynamics forest history maps of the US, International Journal of Digital Earth 9 (2016), 963–980.       
• S. Basu, S. Ganguly, R. R. Nemani, S. Mukhopadhyay, G. Zhang, C. Milesi, A. Michaelis, et al., A Semiautomated Probabilistic Framework for Tree-Cover Delineation From 1-m NAIP Imagery Using a High- Performance Computing Architecture, IEEE Transactions on Geoscience and Remote Sensing 53 (2015), 5690– 5708.
• B. Thrasher, J. Xiong, W. Wang, F. Melton, A. Michaelis, and R. Nemani, Downscaled Climate Projections Suitable for Resource Management, EOS Transactions 94 (2013), 321– 323.
• Nemani, R., Votava, P., Michaelis, A., Melton, F. and Milesi, C., 2011. Collaborative supercomputing for global change science. Eos, Transactions American Geophysical Union, 92(13), pp.109-110.
• A. Michaelis, W. Wang, F. Melton, P Votava, C. Milesi, H. Hashimoto, R. Nemani, S. Hiatt (2009), Building A Community Focused Data and Modeling Collaborative platform with Hardware Virtualization Technology, Abstract IN41A-1119, presented at 2009 AGU Fall Meeting, 14-18 Dec.
• Nemani, R., Hashimoto, H., Votava, P., Melton, F., Wang, W., Michaelis, A., Mutch, L., Milesi, C., Hiatt, S. and White, M., 2009. Monitoring and forecasting ecosystem dynamics using the Terrestrial Observation and Prediction System (TOPS). Remote Sensing of Environment, 113(7), pp.1497-1509.
• Jolly, W.M., Graham, J.M., Michaelis, A., Nemani, R. and Running, S.W., 2005. A flexible, integrated system for generating meteorological surfaces derived from point sources across multiple geographic scales. Environmental modelling & software, 20(7), pp.873-882.
• Yang, F., Ichii, K., White, M.A., Hashimoto, H., Michaelis, A.R., Votava, P., Zhu, A.X., Huete, A., Running, S.W. and Nemani, R.R., 2007. Developing a continental-scale measure of gross primary production by combining MODIS and AmeriFlux data through Support Vector Machine approach. Remote Sensing of Environment, 110(1), pp.109-122.