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[1] Bridging Local Cyberinfrastructure and XSEDE with CyberGIS-Jupyter

Published in PEARC19, 2019

Padmanabhan, A., Yin, D., Lyu, F., Wang, S. (2019). Bridging Local Cyberinfrastructure and XSEDE with CyberGIS-Jupyter. In Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines learning. Association for Computing Machinery, New York, NY, USA, Article 95, 1–3.

[2] Reproducible Hydrological Modeling with CyberGIS-Jupyter: A Case Study on SUMMA

Published in PEARC19, 2019

Lyu, F., Yin, D., Padmanabhan, A., Choi, Y., Goodall, J., Castronova, A., Tarboton, D., Wang, S. (2019). Reproducible Hydrological Modeling with CyberGIS-Jupyter: A Case Study on SUMMA. In Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines learning. Association for Computing Machinery, New York, NY, USA, Article 95, 1–3.

[4] Integrating CyberGIS and Urban Sensing for Reproducible Streaming Analytics

Published in Urban Informatics. The Urban Book Series., 2021

Wang, S., Lyu, F., Wang, S., Catlett, C., Padmanabhan, A., Soltani, K. (2021). Integrating CyberGIS and Urban Sensing for Reproducible Streaming Analytics. In: Shi, W., Goodchild, M.F., Batty, M., Kwan, MP., Zhang, A. (eds) Urban Informatics. The Urban Book Series. Springer, Singapore.

[5] Multi-scale CyberGIS Analytics for Detecting Spatiotemporal Patterns of COVID-19

Published in Mapping COVID-19 in Space and Time. Human Dynamics in Smart Cities., 2021

Lyu, F., Kang, JY., Wang, S., Han, S.Y., Li, Y., Wang, S. (2021). Multi-scale CyberGIS Analytics for Detecting Spatiotemporal Patterns of COVID-19. In: Shaw, SL., Sui, D. (eds) Mapping COVID-19 in Space and Time. Human Dynamics in Smart Cities. Springer, Cham.

[8] CyberGIS for Scalable Remote Sensing Data Fusion

Published in PEARC22, 2022

Lyu, F., Yang, Z., Xiao, Z., Diao, C.,Park, J., Wang, S. (2022). CyberGIS for Scalable Remote Sensing Data Fusion. In Proceedings of the Practice and Experience in Advanced Research Computing. Association for Computing Machinery, New York, NY, USA, Article 35, 1–4. https://doi.org/10.1145/3491418.3535145

[9] Spatiotemporal assessments of nutrients and water quality in coastal areas using remote sensing and a spatiotemporal deep learning model

Published in International Journal of Applied Earth Observation and Geoinformation, 2022

Wu, S., Qi, Jin., Yan, Z., Lyu, F., Lin, T., Wang, Y., Du, Z. (2022). Spatiotemporal assessments of nutrients and water quality in coastal areas using remote sensing and a spatiotemporal deep learning model. International Journal of Applied Earth Observation and Geoinformation Volume 112, 2022, 102897, ISSN 1569-8432, https://doi.org/10.1016/j.jag.2022.102897

[12] Daily changes in spatial accessibility to intensive care unit (ICU) beds and their relationship with the case‑fatality ratio of COVID‑19 in the state of Texas, USA.

Published in Applied Geography, 2023

Park, J., Michels, A., Lyu, F., Han, S., Wang, S. (2023). Daily changes in spatial accessibility to intensive care unit (ICU) beds and their relationship with the case‑fatality ratio of COVID‑19 in the state of Texas, USA. Applied Geography, 102929, ISSN 0143‑6228, https://doi.org/10.1016/j.apgeog.2023.102929.

[14] From the coast to the interior: global economic evolution patterns and mechanisms

Published in Humanities and Social Sciences Communications, 2023

Jin, X., Yang, J., Yue, W., Wang, S., Yang, D., Xiao, X., Xue, B., Dou, Y., Lyu, F., Wang, S. (2023). From the coast to the interior: global economic evolution patterns and mechanisms. Humanities and Social Sciences Communications, 10, 723. https://doi.org/10.1057/s41599-023-02234-4

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