- UAV-borne sensing of crop water stress and agricultural water use
- Optical remote sensing of land cover dynamics of floods in hydrology and evapotranspiration losses
- Multi-sensor remote sensing of soil water and vegetation vigour
- Quantifying large-scale hydrological cycles and land surface processes using satellite remote sensing and coupled earth system modelling
- Investigating impacts of agricultural water use on local-to-regional water circulation
- Assessment of water scarcity and sustainable water use using a global earth systems model
- Bayesian predictive framework for the assessment of water quality behaviours at the Great Barrier Reef catchments
- Stochastic data assimilation for hydrological prediction models
The Environmental Sensing and Modelling Lab integrates various ground and remote sensing techniques into process-based (physical and biophysical) and statistical models to predict land and atmosphere interaction via water and energy exchanges.
For the latest opportunities contact:
Assoc Prof Dongryeol Ryu
Assoc Prof Dongryeol Ryu
Dr Lola Suarez
Ms Anne (Yue) Wang
Ms Danuta Kucharska, Remote sensing of long-term flood inundation events in the Cooper Creek Catchment, Australia
Mr Abbas Mohammadi, Characterizing Flow Regime in Anastomosing Rivers of Arid Regions
Ms Kate (Suyoung) Park, Estimation on crop water status (CWSI and ET) derived from canopy temperature using very high resolution remote sensed imagery
Mr Chihchung Chou, Investigating the impact of irrigation development on the Indian Monsoon Rainfall using a coupled land-atmosphere system model
Mr Naveen Joseph, Investigation of sustainable water resources management of India in a changing climate
Mr Shuci Liu, Predicting water quality at catchment scale
Ms Jie Jian, Streamflow prediction in the ungauged basins using water level data from ground and space
Facilities & resources
We use various ground and airborne sensing equipment, including:
- Phoenix AL3-32 32-beam LiDAR system
- Resonon Pika-IIg hyperspectral system
- MicaSense RedEdge multispectral 5-channel imager
- Tetracam MiniMCA 6-channel imager
- FLIR A65 thermal infrared imager
- FLIR DJI Zenmuse XT, Tau 2, FV-640-13MM, Fast 30Hz
- DJI D-RTK, GNSS-G & A3 Pro
We use commercial image processing software such as Pix4DMapper Pro, PhotoScan of Agisoft, ENVI, and ER Mapper of ERDAS, ArcGIS, Flir Tools, SpectrononPro, as well as remotely sensed geospatial scripting in Python, R and MATLAB.
Along with the University’s Spartan HPC system, we use DELL PowerEdge R430/R630 systems to accommodate the high computation demands for the image/point clouds processing and the Community Earth System Model (CESM).
Most of the hardware and software systems of ESML are maintained via Melbourne Unmanned Aircraft Systems Integration Platform (MUASIP).