Hyperspectral and Thermal Remote Sensing Laboratory (HyperSens)
The Hyperspectral and Thermal Remote Sensing Laboratory (HyperSens) is established jointly between the School of Agriculture, Food and Ecosystem Sciences (SAFES) in the Faculty of Science, and the Melbourne School of Engineering (MSE), Department of Infrastructure Engineering.
HyperSens focuses on quantitative methods for remote sensing, with main interests on vegetation stress detection, physiological condition and precision agriculture. HyperSens team members have experience with manned and unmanned airborne hyperspectral and thermal sensors to monitor plant traits, assessing biochemical and biophysical parameters through physical modelling.
Water and nutrient stress assessment, and the early detection – at pre-visual stages – of harmful diseases are the main focus of the research work carried out in the laboratory. Innovative technology and methods are used to retrieve chlorophyll fluorescence remotely, linking physiological indicators of vegetation condition with plant photosynthesis in the context of precision agriculture and natural resources.
The HyperSens Lab leads research projects with industry worldwide, with increasing emphasis on applied research, technology transfer and engagement with industry.
News and events
Contact the team
Professor Pablo Zarco-Tejada
Professor of Precision Agriculture
Group Leader
High-resolution Airborne Remote Sensing Facility
The University of Melbourne’s Remote Sensing Facility enables the acquisition of high-resolution imagery for agricultural applications, forestry and environmental purposes. The sensors comprise hyperspectral imaging in the visible and near infrared regions, a hyperspectral-fluorescence camera, and a high-resolution thermal camera.
At the typical flight altitudes, the Airborne Facility can collect imagery at 30cm–1.5m resolutions, from small fields up to several thousands of hectares.
Our researchers
Group members
Prof Pablo Zarco-Tejada
Pablo Zarco-Tejada’s research focuses on remote sensing, precision agriculture and vegetation stress detection using hyperspectral and thermal imagery acquired by manned and unmanned aircraft systems. Recent projects include the application of artificial intelligence methods for early disease detection and the use of enabling analytics for grain crop monitoring applications.
pablo.zarco@unimelb.edu.auDr Lola Suarez Barranco
Lola Suárez is an expert in hyperspectral remote sensing, imaging spectroscopy and radiative transfer modelling. She works in plant trait retrieval to assess crop stress in agricultural crops and forest inventory metrics for forest monitoring. She has experience working with varied crop species and ecosystem types at different scales. Her interest is the use of spectroscopy and physical models to understand and measure vegetation dynamics.
l.suarez@unimelb.edu.au +61383441633Dr Tomas Poblete Cisterna
Tomas Poblete is a bioinformatic engineer with a Bachelor in Bioinformatic Science and PhD in Agricultural Science. His research projects comprise multispectral and thermal sensors on board UAVs for agricultural applications, artificial neural networks for vineyard stress detection, and thermal sensor calibration. Research interests include the development of algorithms and computer vision for remotely sensed data in agriculture and forestry.
tomas.poblete@unimelb.edu.auDr Pangzhen Zhang
Pangzhen Zhang is a flavour chemist and viticulturist. His key research interest is to study plant secondary metabolites that contribute to the sensory attributes of food and wine.
pangzhen.zhang@unimelb.edu.au +61383446890Dr Gustavo Togeiro de Alckmin
Gustavo Togeiro de Alckmin is a lecturer in precision agriculture and remote sensing.
gustavo.alckmin@unimelb.edu.auHyperspectral and thermal imaging for precision agriculture and forestry applications – the University of Melbourne’s Airborne Remote Sensing Facility
The main research areas and projects of the HyperSens Laboratory are:
- High resolution hyperspectral, multispectral and thermal remote sensing methods for vegetation stress detection in precision agriculture and forestry
- Plant functioning and plant trait retrieval methods, including chlorophyll fluorescence and physiologically-based indicators of plant health using airborne imaging spectroscopy
- Pre-visual biotic stress detection of harmful diseases using deep learning algorithms linked to physically-retrieved plant traits
- Nutrient assessment of vegetation using VIS-NIR-SWIR airborne imaging spectroscopy and specific plant traits related to physiological condition
- Water stress detection and precision irrigation methods derived from thermal imaging and water-stress indicators obtained from airborne sensors
Our main areas of engagement with industry:
- Research contracts and advisory activities in the context of imaging spectroscopy, multispectral scanning, processing and calibration of remote sensing cameras using laboratory instrumentation
- Software designed for processing and image calibration can be adapted to the needs by industrial partners, particularly for RGB, CIR, multispectral and hyperspectral imaging sensors
- Advisory activities in the context of remote sensing for precision agriculture, both from manned and unmanned vehicles and platforms
- Research and service contracts in topics related to water and nutrient stress detection, large-scale imaging of farms and forestry areas, and monitoring activities using innovative cameras
- Image acquisition and algorithm development for plant breeding, plant trait retrievals and high-throughput data collection using high-resolution imaging spectroscopy and thermal cameras