Dr Luigi Renzullo
Areas of expertise
- Simulation And Modelling 080110
- Image Processing 080106
- Environmental Monitoring 050206
- Surfacewater Hydrology 040608
- Numerical And Computational Mathematics 0103
- Pattern Recognition And Data Mining 080109
Research interests
Dr Luigi Renzullo is a senior research scientist with over 14 years experience in areas such as: atmospheric correction of satellite data, hyperspectral sensing in the viticulture industry, landscape carbon and water balance modelling, and satellite rainfall and soil moisture applications for water resources assessments.
His interests are best summarised as “exploring the role that earth observations can play in land management decision support, especially as constraints on biophysical models through techniques of model-data fusion and data assimilation”.
Keywords: satellite data; radiative transfer modelling; spectrometry; water cycle science; data assimilation
Publications
- Tian, S, Renzullo, L, Van Dijk, A et al 2019, 'Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response', Hydrology and Earth System Sciences, vol. 23, no. 2, pp. 1067-1081.
- Tian, S, Van Dijk, A, Tregoning, P et al. 2019, 'Forecasting dryland vegetation condition months in advance through satellite data assimilation', Nature Communications, vol. 10, no. 469, pp. 1-7.
- Gevaert, A, Renzullo, L, Van Dijk, A et al. 2018, 'Joint assimilation of soil moisture retrieved from multiple passive microwave frequencies increases robustness of soil moisture state estimation', Hydrology and Earth System Sciences, vol. 22, no. 9, pp. 4605-4619.
- Sabaghy, S, Walker, J, Renzullo, L et al. 2018, 'Spatially enhanced passive microwave derived soil moisture: Capabilities and opportunities', Remote Sensing of Environment, vol. 209, pp. 551-580pp.
- Hou, J, Van Dijk, A, Renzullo, L et al. 2018, 'Using modelled discharge to develop satellite-based river gauging: A case study for the Amazon Basin', Hydrology and Earth System Sciences, vol. 22, no. 12, pp. 6435-6448.
Projects and Grants
Grants information is drawn from ARIES. To add or update Projects or Grants information please contact your College Research Office.
- Terrestrial Ecosystem Observatory: Landscapes platform as defined in TERN Landscapes Business Plan 2019-2023 (Primary Investigator)
- Soil water nowcasting for the grains industry (Secondary Investigator)
- Multi-source ensemble rainfall analyses (MERA): enhanced real-time precipitation productsthrough the blending of gauge, radar, satellite and NWP data (Primary Investigator)
- TERN VII - Landscapes (Secondary Investigator)
- Data Assimilation into the AWRA-CMS for improved operational and forecast modelling (Primary Investigator)
- BoM Himawari-8 rainfall evaluation (Primary Investigator)
