Advancing pollen-induced health risk assessment with geospatial big data

Professor Chen, Bin   (Principal Investigator (PI))

Dr Wu Shengbiao   (Co-Investigator)

Professor Ren Chao   (Co-Investigator)

48

2024-01-01

1196323

Advancing pollen-induced health risk assessment with geospatial big data

Satellite observations, Tree specie,; Phenology, Pollen, Environmental exposure.

Urban Studies and PlanningEnvironmental Studies and Science

Physical Sciences (P)

N_HKU722/23

NSFC/RGC Joint Research Scheme 2023/24

2023

On-going

1. To generate spatially, temporally, and spectrally consistent seamless data cubes (SDCs) by fusing satellite-based Landsat and Sentinel imagery and derive high-resolution tree species mappings.2. Through the integration of the generated SDCs, tree species maps, and in-situ pollen observations, to investigate the association between vegetation phenology and pollen dynamics, and then generate the baseline mapping of pollen concentrations.3. To enable the Weather Research Forecasting (WRF-based) model of pollens’ spatiotemporal transmission by accounting for the influence of meteorological conditions, and realize near real-time forecasting of pollen concentrations.4. Based on the Intergovernmental Panel on Climate Change (IPCC) ""Hazard-Exposure-Vulnerability"" conceptual framework, to assess urban pollen risks by considering both population and pollen dynamics.5. Based on the composition and distribution of pollen risk assessment, to couple medical allergy incidence data for quantifying the response relationship between pollen risk and health outcome, and develop spatiotemporal optimization strategies for guiding interventions on pollen alleviation.