Professor Pablo J. Zarco-Tejada
Remote Sensing & Precision Agriculture – HyperSens Team Leader
Prof Zarco-Tejada is the Team Leader in Remote Sensing & Precision Agriculture – HyperSens Lab., jointly appointed between the Faculty of Science (FoS) and the Faculty of Engineering and Information Technology (FEIT).
His main focus lies on remote sensing technology and methods, precision agriculture and vegetation stress detection using hyperspectral and thermal imagery acquired by manned and unmanned aircraft systems. In particular, assessing the physiological condition of crops through physical modelling. These include the early detection of diseases, water and nutrient stress using advanced airborne imaging spectroscopy and fluorescence retrievals through radiative transfer modelling.
Dr Victoria Gonzalez-Dugo
Honorary Senior Fellow. Tenured Scientist – IAS-CSIC, Spain
Dr Victoria González-Dugo holds an Agricultural Engineering Degree from the University of Cordoba (Spain) and a PhD in Life Sciences from the University of Poitiers (France). Her work is based on crop physiology and its relationship with water productivity and crop water relations. The objective of her work focuses on the optimization of deficit irrigation strategies in fruit trees and the development of indicators derived from thermal, multi- and hyperspectral information for monitoring water status and irrigation scheduling.
Dr Pangzhen Zhang
Flavour Chemist and Viticulturist
Dr 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.
Dr Tomas Poblete
Lecturer & Research Fellow, Precision Agriculture & Remote Sensing
Tomas Poblete is a Bioinformatics Engineer, with a Bachelor in Bioinformatics Science, and a PhD in Agricultural Science. Tomas’s research projects have comprised the use of multispectral and thermal sensors onboard UAVs for agricultural applications. His current research is focused on the implementation of Machine/Deep Learning Algorithms using hyperspectral and thermal imagery in agricultural, biosecurity and forestry applications.
Dr Na Wang
Postdoctoral Research Fellow
Na Wang holds a BS in Geo-information Science, an MS in Remote Sensing of Agriculture, and a PhD in Remote Sensing of Fluorescence in Precision Agriculture. Her research interests revolve around sun-induced chlorophyll fluorescence (SIF), biotic/abiotic stress detection in crops/ fruit trees at different spatial scales (e.g., airborne, UAV, and proximal canopy), and multi-sensor synergy approaches. Her current research is focused on assessing the water stress status in orchards using advanced multi-sensor approaches, including SIF from both airborne sub-nanometre fluorescence imagery and narrow-band imagery as well as thermal data.
Dr Alberto Hornero
Honorary Research Fellow
Alberto Hornero holds a BS in Computer Systems Engineering, an MS in Computer Science and a PhD in Physical Geography. His main research interest lies on recent developments in Remote Sensing methods and technology. His current research is focused on the quantitative estimation of vegetation traits and dynamics using high-resolution hyperspectral and thermal data, medium-resolution satellite imagery, artificial intelligence and radiative transfer modelling.
Anne’s background is in GIS and Remote Sensing. Her main research interests are related to high-resolution Hyperspectral/Thermal Remote Sensing for crop monitoring and vegetation stress detection for precision agriculture. In particular, she is interested in assessing water and nutrient stress in fruit orchards using solar-induced fluorescence and leaf plant traits derived from airborne hyperspectral imaging and physical models.
Andrew R. Longmire
Andrew is interested in using information derived from remote sensing to guide precision agriculture. His diverse history includes a national scale modelling and GIS study of the potential for net-zero carbon emissions from land use and work as a ranger at Uluru-Kata Tjuta National Park.
Anirudh’s background is in Computer Science and Remote Sensing. His research interests are related to the incorporation of deep learning methodology for high resolution airborne hyperspectral imagery analysis. He is interested in linking the radiative transfer models to artificial intelligence for detecting pre-visual stress detection in vegetation using hyperspectral and thermal imaging.
James A. Gough
Jamie’s background is in Engineering and Environmental Science. Amongst other endeavours he has managed a small beef operation for over 20 years and is passionate about improving pasture production. His main research interests are related to exploring pasture canopy temperature to track plant water stress. He is using high resolution thermal remote sensing images to measure pasture temperature for soil moisture monitoring purposes.
Luis Manuel Guadarrama Escobar
Luis holds a Bachelor degree in Biotechnology Engineering and a Master degree in Agricultural Sciences. His research interests are related to the re-domestication of wild relatives of cereals as a promising alternative to improve abiotic stress tolerance. Using high-throughput techniques, such as thermal infrared imagery, will enable him to screen a large amount of wild germplasm material with the potential of drought tolerance.
Peiye completed her Master’s degree in Environmental Engineering at the University of Melbourne. She is particularly interested in applying hyperspectral and thermal imagery for vegetation functional traits retrieval and stress detection. Her current research at HyperSens focuses on evaluating atmospheric correction modelling methods for hyperspectral images acquired by the University of Melbourne’s Airborne Remote Sensing Facility.
Hafez holds a BS in Surveying Engineering and an MS in Remote Sensing Engineering. His research interests primarily focus on the application of remote sensing techniques in precision agriculture. His current research is focused on harnessing the potential of hyperspectral and thermal imaging for the detection of plant stress symptoms at the pre-visual stage. Specifically, he aims to investigate the combination of solar-induced chlorophyll fluorescence, thermal and spectral indices, and plant traits retrieved from radiative transfer models to assess biotic and abiotic sources of stress.
Zhonghua Ma is a PhD student involved in data-driven research on precision agriculture, climate resilience, and environmental benefits in collaboration with the University of Melbourne and the University of Manchester. His work is focused on advancing process-based modeling in agricultural nitrogen management using machine learning and remote sensing techniques. He was recipient of the Dean’s International Science Excellence Scholarship at ANU in 2018 and won the first prize in a physical science and technology innovation competition for his work on the laser feedback principle at SDU in 2017. Additionally, he achieved the third prize in SRTP for his research on coronal holes and solar wind. As an ICM faculty advisor in 2021, he provides valuable mentorship and expertise in mathematical modeling and interdisciplinary problem-solving.
Isabelle J. Gartside, Ryan J. Dossetor
Master of Engineering (Spatial) student team working in the Capstone Project “GIS-based mapping of object-based traits quantified by hyperspectral imagery”. Their work is based around improving the accuracy of self-segmenting methods on pre-collected hyperspectral and thermal mosaics. Whereby the final aim is to have a learned program which can extract information for each individual tree crown over a varied dataset.
Yau Ming Ng, Godofredo Chiu Castro, Murray Peh
Master of Mechatronics Engineering student team working in the Capstone Project “Real-time monitoring of the cameras onboard the Airborne Remote Sensing Facility”. Their goal is to evaluate different options for the design of the control system of the Airborne Remote Sensing Facility, develop the protocols for communicating with the ground control station, and code the software that receives data from the aircraft to monitor the imagery acquisition.
Alumni and former Academics
Dr Lola Suarez
Plant Physiology and Remote Sensing
Lola holds a degree in GIS and Remote Sensing, and a PhD in remote sensing of vegetation stress detection. She has worked with remote sensing data applied to vegetation science since 2006. Her research interests include vegetation health assessment and monitoring and modelling the link of vegetation physiology to hyper/multispectral remote sensing at different scales, including approaches based on radiative transfer and model inversion methods.
Dr Gustavo Togeiro de Alckmin
Lecturer, Research Fellow
Gustavo was Lecturer & Research Fellow in Precision Agriculture and Remote Sensing. He holds a degree in Agricultural Engineering, an M.Sc. and a Ph.D. in Remote Sensing, investigating the use of drones and spectral data for pastures and crop biophysical parameter retrieval. He was interested in developing robust methods and effective spectral instruments to enable optimal crop and animal production. As a Lecturer, he aimed to teach students about the cornerstone concepts of spectroscopy and its relations with crop physiology.
Visiting PhD Student
Xiaojin is a PhD student in the Aerospace Information Research Institute, Chinese Academy of Sciences. Her main research is about the retrieval of vegetation parameters. She was visiting the University of Melbourne to learn more about the estimation of leaf chlorophyll content and Vcmax from satellite remote sensing.
Adrian Gracia Romero
Visiting PhD Student
Adrian was developing his PhD in Plant Phenotyping and Remote Sensing at the Integrative Crop Ecophysiology Group of the University of Barcelona. Adrian’s research is focused in the application of UAVs including thermal sensors, imaging spectral cameras and conventional RGB cameras as high-throughput phenotyping systems. He is a graduate in Environmental Science and holds a Msc in Environmental Agrobiology, both from the University of Barcelona. He was visiting the University of Melbourne to learn more about high-resolution hyperspectral data for vegetation stress detection.
Johann completed a Bachelor’s degree in Mathematics and Economics and has been recently graduated from a Master’s degree in Statistics and Econometrics. He developed a strong interest in Data Science for Agriculture after having worked with Syngenta as Data Analyst for one year.
Johann will start a PhD in France in September and his main subject would be to develop a model to predict the phenological stages for Corn and Barley crops using multispectral and hyperspectral images. He visited the University of Melbourne to learn more about remote sensing for precision agriculture.
James holds a Bachelor’s degree in Mathematics from the UoM and was studying for a Master of Earth Sciences. The aim of his thesis was to identify and quantify the impact of remote sensing sub-pixel heterogeneity on plant parameter satellite retrieval estimates, with the view of improving our knowledge of the global carbon cycle.
Sarah Dan Ni Chia
Sarah completed a Bachelor’s degree in Science (Agri-food biotechnology) and was in her final year of the Masters’ of Food Science at UoM. She has a passion for sustainable food and agricultural innovations in order to accommodate for a growing population. Her research project was investigating the effects of LED and fluorescent lighting recipes through analysing chlorophyll fluorescence, spectral reflectance and root development in cannabis plants.
Navneet completed her bachelors in Agricultural Science and was pursuing Masters in Agricultural science (Specialisation: Crop Production) at the University of Melbourne. Her research interest is to deduce sustainable agriculture measures with the help of Precision agriculture as she believes it holds the potential to revolutionise the agriculture sector. Her research project was to identify almond varieties in a commercial orchard using airborne hyperspectral images in the Mallee region.
Jiajia holds a Bachelor’s degree in Environmental Science and now studies a Master of Environmental Engineering at the University of Melbourne. She has research interests in environmental modelling and hyperspectral remote sensing. Her project topic was ‘Vcmax Estimation from Hyperspectral Data using the Scope Model and Deep-Learning Algorithms’.
Qiwei completed his Bachelor’s degree in Environmental Engineering in Shandong University in 2018, and now he is focusing on the Master degree of Environmental Engineering in University of Melbourne. He has a strong background in data analysis, modelling and plant physiology, which are his main research interests. He worked on the project ‘Vcmax Estimation from Hyperspectral Data using the Scope Model and Deep-Learning Algorithms’.
Wey Yao Wong
Wey is a student from the Bachelor of Science, majoring in Plant Science. His research interests are mainly in plant pathology and precision agriculture, but also with an ongoing interest in palaeobotany. Wey was working on his honours project, titled ‘Distinguishing abiotic and biotic water stress symptoms in physiology-related hyperspectral indicators with Verticillium wilt in tomatoes’.
Lily Aoi Fujii
Lily was in her final year of a Bachelor’s degree in Data Science at the University of Melbourne. She is interested in applying her programming, analytical and visualisation skills to data processing in the agricultural field. She was working on the development of an interactive tool to handle the hyperspectral remote sensing images collected by the airborne remote sensing facility.
Completion of Capstone Projects
Jiahang Lu, Haoming Tian, Chen Qi, Jinyao Zhai
Master of Engineering (Electrical) student team worked in the Capstone Project “Real-time assessment of the Airborne Remote Sensing Facility flights for accurate image acquisition”. Their work was based on the UoM Airborne Remote Sensing Facility to develop hardware and software for real-time tracking purposes, improving the quality of the hyperspectral and thermal imagery collected.