Manzhu Yu’s research focuses on spatiotemporal theories and applications, atmospheric modeling, environmental analytics, big data and cloud computing, and the ability of using the above to solve pressing issues in natural hazards and sustainability. She hopes to continue to combat the life and economic costs associated with natural hazards by facilitating more accurate and timely analyses for extreme weather events. She has collaborated actively with researchers in several other disciplines of Geography, Environmental Science, and Computer Science, particularly on the interdisciplinary solutions for natural hazard management and the contributing physical and social factors of these natural hazards.
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Projects
Recent Publications
Spatiotemporal Prediction of Radar Echoes Based on ConvLSTM and Multisource Data
Lu, M., Li, Y., Yu, M., Zhang, Q., Zhang, Y., Liu, B. & Wang, M., Mar 2023, In: Remote Sensing. 15, 5, 1279.Research output: Contribution to journal › Article › peer-review
Developing high-resolution PM2.5 exposure models by integrating low-cost sensors, automated machine learning, and big human mobility data
Yu, M., Zhang, S., Zhang, K., Yin, J., Varela, M. & Miao, J., 2023, In: Frontiers in Environmental Science. 11, 1223160.Research output: Contribution to journal › Article › peer-review
Predicting hourly PM2.5 concentrations in wildfire-prone areas using a SpatioTemporal Transformer model
Yu, M., Masrur, A. & Blaszczak-Boxe, C., Feb 20 2023, In: Science of the Total Environment. 860, 160446.Research output: Contribution to journal › Article › peer-review
Aerial Image Color Balancing Based on Rank-Deficient Free Network
Zhan, Z., Zheng, L., Wei, M., Yu, M. & Jian, W., 2023, In: IEEE Access. 11, p. 18838-18854 17 p.Research output: Contribution to journal › Article › peer-review
A quantitative method for the similarity assessment of typhoon tracks
Di, Y., Lu, M., Chen, M., Chen, Z., Ma, Z. & Yu, M., May 2022, In: Natural Hazards. 112, 1, p. 587-602 16 p.Research output: Contribution to journal › Article › peer-review
A vision transformer for lightning intensity estimation using 3D weather radar
Lu, M., Wang, M., Zhang, Q., Yu, M., He, C., Zhang, Y. & Li, Y., Dec 20 2022, In: Science of the Total Environment. 853, 158496.Research output: Contribution to journal › Article › peer-review
Monitoring Lightning Location Based on Deep Learning Combined with Multisource Spatial Data
Lu, M., Zhang, Y., Chen, M., Yu, M. & Wang, M., May 1 2022, In: Remote Sensing. 14, 9, 2200.Research output: Contribution to journal › Article › peer-review
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
Luo, W., Liu, Z., Zhou, Y., Zhao, Y., Li, Y. E., Masrur, A. & Yu, M., Aug 1 2022, In: JMIR Public Health and Surveillance. 8, 8, e35840.Research output: Contribution to journal › Article › peer-review
Interpretable machine learning for analysing heterogeneous drivers of geographic events in space-time
Masrur, A., Yu, M., Mitra, P., Peuquet, D. & Taylor, A., 2022, In: International Journal of Geographical Information Science. 36, 4, p. 692-719 28 p.Research output: Contribution to journal › Article › peer-review
A high spatiotemporal resolution framework for urban temperature prediction using IoT data
Yang, J., Yu, M., Liu, Q., Li, Y., Duffy, D. Q. & Yang, C., Feb 2022, In: Computers and Geosciences. 159, 104991.Research output: Contribution to journal › Article › peer-review
Spatiotemporal impacts of COVID-19 on air pollution in California, USA
Liu, Q., Harris, J. T., Chiu, L. S., Sun, D., Houser, P. R., Yu, M., Duffy, D. Q., Little, M. M. & Yang, C., Jan 1 2021, In: Science of the Total Environment. 750, 141592.Research output: Contribution to journal › Article › peer-review
Lightning Strike Location Identification Based on 3D Weather Radar Data
Lu, M., Zhang, Y., Ma, Z., Yu, M., Chen, M., Zheng, J. & Wang, M., Aug 4 2021, In: Frontiers in Environmental Science. 9, 714067.Research output: Contribution to journal › Article › peer-review
Pm2.5 concentration forecasting over the central area of the yangtze river delta based on deep learning considering the spatial diffusion process
Lu, M., Lao, T., Yu, M., Zhang, Y., Zheng, J. & Li, Y., Dec 1 2021, In: Remote Sensing. 13, 23, 4834.Research output: Contribution to journal › Article › peer-review
Geographic context-aware text mining: enhance social media message classification for situational awareness by integrating spatial and temporal features
Scheele, C., Yu, M. & Huang, Q., 2021, In: International Journal of Digital Earth. 14, 11, p. 1721-1743 23 p.Research output: Contribution to journal › Article › peer-review
Deep learning-based downscaling of tropospheric nitrogen dioxide using ground-level and satellite observations
Yu, M. & Liu, Q., Jun 15 2021, In: Science of the Total Environment. 773, 145145.Research output: Contribution to journal › Article › peer-review