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.
In the News
Research Keywords
These keywords and phrases come from the publications and other research output of this person. See other researchers related to these topics by clicking on any keyword.
Projects
Recent Publications
Socioeconomic and sociodemographic correlations to COVID-19 variability in the United States in 2020
Golosov, N., Wang, S., Yu, M., Karle, N. N., Ideki, O., Abdul-Hamid, B. & Blaszczak-Boxe, C., 2024, In: Frontiers in Public Health. 12, 1359192.Research output: Contribution to journal › Article › peer-review
Impact of heat on emergency hospital admissions related to kidney diseases in Texas: Uncovering racial disparities
Guo, C., Ge, E., Yu, M., Li, C., Lao, X., Li, S., Glaser, J., He, Y., Almeida-Silva, M., Meng, S., Su, W. C., Zhang, J., Lin, S. & Zhang, K., Jan 20 2024, In: Science of the Total Environment. 909, 168377.Research output: Contribution to journal › Review article › peer-review
Arctic accessibility: recent trend in observed ship tracks and validation of arctic transport accessibility model
Hu, W., Cervone, G., Trusel, L. & Yu, M., 2024, In: Annals of GIS. 30, 4, p. 455-474 20 p.Research output: Contribution to journal › Article › peer-review
ER-MACG: An Extreme Precipitation Forecasting Model Integrating Self-Attention Based on FY4A Satellite Data
Lu, M., Zhang, J., Yu, M., Liu, H., He, C., Dong, T. & Mao, Y., Oct 2024, In: Remote Sensing. 16, 20, 3911.Research output: Contribution to journal › Article › peer-review
MCGLN: A multimodal ConvLSTM-GAN framework for lightning nowcasting utilizing multi-source spatiotemporal data
Lu, M., Jin, C., Yu, M., Zhang, Q., Liu, H., Huang, Z. & Dong, T., Jan 2024, In: Atmospheric Research. 297, 107093.Research output: Contribution to journal › Article › peer-review
MGCPN: An Efficient Deep Learning Model for Tibetan Plateau Precipitation Nowcasting Based on the IMERG Data
Lu, M., Huang, Z., Yu, M., Liu, H., He, C., Jin, C. & Zhang, J., Aug 2024, In: Journal of Meteorological Research. 38, 4, p. 693-707 15 p.Research output: Contribution to journal › Article › peer-review
Capturing and interpreting wildfire spread dynamics: attention-based spatiotemporal models using ConvLSTM networks
Masrur, A., Yu, M. & Taylor, A., Sep 2024, In: Ecological Informatics. 82, 102760.Research output: Contribution to journal › Article › peer-review
A Remote Sensing Spectral Index Guided Bitemporal Residual Attention Network for Wildfire Burn Severity Mapping
Wu, M., Huang, Q., Sui, T., Peng, B. & Yu, M., 2024, In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17, p. 17187-17206 20 p.Research output: Contribution to journal › Article › peer-review
Advancements in remote sensing for active fire detection: A review of datasets and methods
Yang, S., Huang, Q. & Yu, M., Sep 15 2024, In: Science of the Total Environment. 943, 173273.Research output: Contribution to journal › Review article › peer-review
Assessing the 2023 Canadian wildfire smoke impact in Northeastern US: Air quality, exposure and environmental justice
Yu, M., Zhang, S., Ning, H., Li, Z. & Zhang, K., May 20 2024, In: Science of the Total Environment. 926, 171853.Research output: Contribution to journal › Article › peer-review
Deep learning for spatiotemporal forecasting in Earth system science: a review
Yu, M., Huang, Q. & Li, Z., 2024, In: International Journal of Digital Earth. 17, 1, 2391952.Research output: Contribution to journal › Review article › peer-review
Enhanced urban PM2.5 prediction: Applying quadtree division and time-series transformer with WRF-chem
Zhang, S. & Yu, M., Nov 15 2024, In: Atmospheric Environment. 337, 120758.Research output: Contribution to journal › Article › peer-review
Environmental Assessment and Monitoring of Heavy Metals in New York City Potable Water Systems: Case Study at Medgar Evers College, Correlation Analysis, and Public Health Impacts
Blaszczak-Boxe, C. S., Karle, N. N., Wang, S., Yu, M., Golosov, N., Riyad, M., Smith, K., Hollet, T., Abdul-Hamid, B., St. Hillaire, D. & Sen, P., Dec 2023, In: Water (Switzerland). 15, 24, 4233.Research output: Contribution to journal › Article › peer-review
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