eMAST is committed to advancing an open and collaborative approach to ecosystem science, and our successes are only possible thanks to the collaborative network that has built up around eMAST and who actively contribute to our work. Contact us if you'd like to get involved with eMAST, and read on below to find out more about some of the people who are already involved:
- Bradley Evans, eMAST Director
- Stuart Allen
- Ben Evans
- Michael Hutchinson
- Julie Pauwels
- David Porter
- I. Colin Prentice, eMAST Chair
- Luigi Renzullo
- Jingbo Wang
- Tingbao Xu
Dr Bradley Evans, eMAST Director
Brad is the Director of eMAST, and a Senior Lecturer in the Faculty of Agriculture and Environment at the University of Sydney.
Bradley leads the advance of developing community research infrastructure to support ecosystem science whilst maintaining his own research profile in land surface modelling and remote sensing. He contributes to a number of international open-source initiatives actively improving and sharing methodologies and tools for processing large scientific datasets.
Brad’s core research is in primary production modelling and data assimilation of TERN observations into national models. In addition to his management duties, Bradley developed the R-package “ePiSaT”, which constrained the gross primary production using OzFlux, AWAP, BoM and MODIS fAPAR data. He also provided significant contributions to the eMAST R-package and several data products. Read more about Brad here.
Stuart is an eResearch Analyst at INTERSECT and interested in the tools and techniques used to collect, generate, process, store and share data. At eMAST he plays a central role in the provision of the technical infrastructure. This includes the provision of 4 Virtual Machines hosted on INTERSECT servers, his assistance with the installation of software on those machines and the provisioning of 160TB of data storage on RDSI (Research Data Storage Infrastructure). The 4 Virtual Machines and allocated 160TB are exclusively used for eMAST’s computational work and storage of data.
Ben is Associate Director for ‘Research, Engagement and Initiatives’ at the National Computing Infrastructure (NCI). He is one of the project lead's for the eMAST facility. In addition to its well-known high-performance computational environment, NCI provides nation-wide gridded meteorology and satellite observations that are being used by the land surface models and for additional community analysis.
Prof Michael Hutchinson
Michael is Professor of Spatial and Temporal Analysis at ANU’s Fenner School of Environment and Society. His main interests in eMAST are to support spatially distributed dynamic modelling of land surface processes and provide a baseline for the assessment of the impacts of projected climate change. He is also modelling the spatial distribution of plants and animals to make long-term estimates of land surface processes for assessment of agriculture and biodiversity. He made significant contribution to the eMAST infrastructure by providing the ANUCLIM 6.1 and the new ANUClimate 1.0 gridded climate data. The production of ANUClimate 1.0 involved making significant extensions to the underpinning ANUSPLIN software. He was also involved in the development of the eMAST R-package that is used to calculate climatic and bioclimatic indices. Using the models, the eMAST R-package and daily and monthly temperature, precipitation, solar radiation, vapour pressure, evaporation and runoff, he provided various climatic and bioclimatic variables gridded on a 5km and 1km surface and covering the period 1970-2013.
Julie is a Master Student at Agrocampus Ouest in France interested in the application of modelling techniques to ecology. Currently she is conducting an internship at Macquarie University in Australia where she is involved in several eMAST activities. Her research interests in eMAST focus on the improvement of the eMAST R-package. In this context she is writing functions to calculate several bioclimatic variables defined by Michael Hutchinson and Tingbao Xu on a 1km and 5km grid for the period 1970 and 2010.
David is Software Engineer at the National Computing Infrastructure (NCI) currently working on building Virtual Laboratories in the NCI partner cloud, as well as implementing the NCI's data services infrastructure. Similarly to his colleagues Jingbo Wang and Ben Evans from the NCI, David’s main interest in relation to eMAST is helping to make large observational datasets accessible and processable by providing super computer facility, resources, and technical support. He has made significant contributions to set up the SPEDDEXES web interface and deploy it into the NCI’s partner cloud. David also provided significant support in the establishment of the THREEDS catalogue required for eMAST’s datasets.
I. Colin Prentice
Colin is a Professor in Ecology and Evolution at Macquarie University in Sydney, Australia and also holds the AXA Chair of Biosphere and Climate Impacts at Imperial College London, UK. His main research concern is the global terrestrial biosphere, and how plants react and interact with climate and environmental changes. His strategy is based on modelling, seeking to integrate process understanding in ecology and environmental physics with observations of all kinds, including atmospheric measurements and remote sensing with a view to developing sound theoretical and predictive frameworks. In his role as eMAST Chair, Colin is supporting the facility in every aspect to assimilate data for ecosystem model optimisation and drive advances in ecosystem science, impact assessment and land management.
Luigi is a Senior Research Scientist in CSIRO Land and Water and Research Team Leader of the Model Data Integration team of the Environmental Earth Observation program. His interests focus on improving our understanding of the Earth's terrestrial water, energy and carbon cycles, particularly through the integration of satellite remote sensing with land surface models. Luigi's area of expertise is in the methods of combining remotely-sensed satellite images with biophysical models, and making geospatial information products of relevance to policy and decision support. His skills include forward and inverse mathematical modelling of satellite signal of land surface variables. He employs sophisticated methods of analysis to combine model and observational information sources to gain greater insight into biophysical systems than would otherwise be achieved through the individual data alone. Dr Renzullo’s record for original research leading to impact is best illustrated by his leadership roles in the Water Information Research and Development Alliance (WIRADA) between the Bureau of Meteorology and CSIRO, specifically developing and testing the methods behind the remote sensing data assimilation system for the Bureau of Meteorology's National Australian Water Resources Assessment (AWRA) system. The AWRA data assimilation system methods and data are what Luigi brings to eMAST.
Jingbo is a Research Data Collection Manager at the National Computing Infrastructure (NCI) where she is leading the migration of data collections onto the RDSI (Research Data Storage Infrastructure) funded file systems. Her overall interest in eMAST is the support of the integration of gridded national observations into surface models by providing super computer facility (Raijin), resources and technical support. Jingbo’s focus is the data management, data citation, data ingest and publishing logistics.
Tingbao is a Senior Research Manager at the Fenner School of Environment and Society at ANU College of Medicine, Biology and Environment. His eMAST related interests and activities focus on the progress of software packages that are used to calculate surfaces of national (bio-)climatic variables with a 0.01° or 0.05° resolution. He developed the software package ANUCLIM 6.1. in collaboration with Michael Hutchinson and provided significant contributions to the ANUSPLIN 4.4 package (link to infrastructure), which Michael Hutchinson first authored. The ANUSPLIN 4.4. package is applied in the spatial model ANUClimate 1.0 to provide a facility for transparent analysis and interpolation of noisy multi-variate data.