Current Lab Members
Justin Morgenroth
Urban forestry, forestry, Remote Sensing, geospatial science
Associate Professor Justin Morgenroth leads the ‘Remote Sensing and Geospatial Analysis Research Group’ at the School of Forestry. He’s interested in describing the spatial and temporal dynamics of New Zealand’s urban forests, indigenous forests, and exotic forest plantations using a range of quantitative techniques. He works extensively with remote sensing or earth observation techniques, including lidar, as well as aerial and satellite imagery. He holds a BSc in Computer Science (University of Western Ontario), a Masters in Forest Conservation (University of Toronto), and a PhD in Forestry (University of Canterbury).
Vega Xu
Small-scale plantation forests, optical satellite imagery, LiDAR, UAV
Vega Cong Xu is the WIDE Trust Lecturer in Geospatial Technologies and the co-director of the ‘Remote Sensing and Geospatial Analysis Research Group’ at the School of Forestry. She is interested in remote sensing applications in forestry and natural environment, through processing and analysing remote sensing data such as satellite imagery, LiDAR and UAV photogrammetry to classify forest types, assess forest growth, and monitor vegetation changes. She has recently been working on applying geospatial and remote sensing technologies to better describe New Zealand’s small-scale plantation forests.
Email: cong.xu@canterbury.ac.nz
Ning Ye
Optical satellite imagery, time series, LiDAR, machine learning, Google Earth Engine
Ning Ye is a postdoctoral researcher in Forestry at the University of Canterbury. She obtained a BSc degree in Geographical Information System from Wuhan University and an MSc degree in Geoinformation Science and Earth Observation from the University of Twente. For her PhD at the School of Forestry, her research focused on classifying New Zealand's native forests using optical satellite imagery. This research enabled accurate classification of the highly diverse native vegetation in New Zealand at a finer scale and at a lower cost. Currently, she is working on an NZDFI project that aims to use drone LiDAR data to generate a New Zealand-specific Eucalyptus biomass model.
Email: ning.ye@canterbury.ac.nz
Haotian (Joe) Zhao
Urban forestry, deep learning, Remote Sensing
Haotian (Joe) Zhao is a PhD candidate at the School of Forestry. His research is centered around the application of advanced artificial intelligence (AI) techniques to urban forestry monitoring. One of his current research projects involves the development of a convolutional neural network (CNN) for individual tree detection using aerial imagery. This project utilizes cutting-edge AI techniques, including self-supervised learning and synthetic data, to address the challenge of data scarcity and improve the training efficiency of the model. By leveraging these innovative techniques, it aims to significantly enhance the accuracy and generability of AI models in urban forest applications.
Supervisory team: Justin Morgenroth, Grant Pearse (Scion), Jan Schindler (Landcare Research)
Gunjan Sharma
Ecosystem service modelling, satellite Remote Sensing, LiDAR, i-tree eco
Gunjan is a PhD candidate at the School of Forestry, University of Canterbury, and is supervised by Dr. Justin Morgenroth. She has obtained a Master’s degree in Geography from India and an Erasmus Joint-Masters in Geo-information and Earth Observation for Environmental Modelling and Management from ITC-University of Twente, Netherlands, and Lund University, Sweden. Her current research focuses on exploring the potential of integrating remote sensing data with i-tree Eco for modelling urban tree benefits.
Supervisory team: Justin Morgenroth, Dan Richards (Landcare Research), Ning Ye
Shiva Pariyar
Forest Health and Vitality, Remote Sensing, Climate Change, Modelling
Shiva Pariyar is a PhD student in the GIS and Remote Sensing Lab Group within the School of Forestry, University of Canterbury. He is interested in assessing the forest health and vitality of plantation forests of New Zealand using remote sensing techniques. His research revolves around utilizing cutting-edge technologies such as UAVs, LiDAR, and satellite imageries to identify and analyze tree diseases at individual tree and forest stand levels. He received Master of Forest Ecosystem Science from the University of Melbourne in Australia and B.Sc. (Forestry) from the Tribhuvan University in Nepal.
Supervisory team: Vega Xu, Justin Morgenroth, Steve Pawson, Ning Ye
Priyanganie Samarasinghe Yapa Mudiyanselage
Urban Greening, Ecological Risk Modelling, Satellite Remote Sensing, LiDAR
Priya is a PhD student in the GIS and Remote Sensing Lab Group within the School of Forestry, University of Canterbury, and supervised by Associate Professor Justin Morgenroth. She holds a BSc degree in Agricultural Technology and Management from the University of Peradeniya in Sri Lanka, as well as a Master's degree in geoinformatics from the same university. Her current research focuses on urban greening for reduction of ecological risk and minimization of the urban heat island effect.
Supervisory team: Justin Morgenroth, Ning Ye
Email: priyanganiesamarasinghe.yapamudiyanselage@pg.canterbury.ac.nz
Robin Hartley
Forestry, Remote Sensing, proximal sensing, phenotyping, automation
Robin is currently a Masters student in the GIS and Remote Sensing Lab Group within the School of Forestry, University of Canterbury. He is working on research looking at deriving branch phenotypes from the point clouds of mobile laser scanners. Robin also works full time at Scion as a geospatial scientist in the Autonomous Systems team, where his research focuses on UAVs, proximal sensing, phenotyping and democratising technology for the forest industry. Robin has a BSc Hons in Geography and Environmental Management from the University of the West of England in the UK. He’s also a keen surfer and spends as much time at the beach as his three-year-old will allow!
Supervisory team: Justin Morgenroth, Grant Pearse (Scion), Sadeepa Jayathunga (Scion)
David Pedley
Urban forestry, Remote Sensing, geospatial analysis, urban planning
I am currently a PhD student in the GIS and Remote Sensing Lab Group within the School of Forestry and am part of the University of Canterbury Geospatial Research Institute. I am working on research looking at the relationship between urban trees and housing intensification, with a focus on the loss of trees on private residential land. I received my previous degrees in law (LLB) and science (BSc in Biological Science and Geography) from the University of Canterbury and spent 11 years working as an environmental lawyer. I recently completed my Master of Landscape Architecture at Lincoln University.
Supervisory team: Justin Morgenroth, Grant Pearse (Scion)
Blake Singleton
Forestry, remote sensing, geospatial science, statistical modelling
Blake Singleton is currently an Honours student at the University of Canterbury, New Zealand, pursuing a Bachelor of Forestry Science degree. His honours dissertation focuses on practical applications of UAV imagery for assessing survival and health in New Zealand plantation forestry. Prior to this, Blake completed research with Scion as part of the Tools for Foresters initiative, utilising multispectral imagery for survival and health assessments using machine learning processes. Blake is committed to leveraging technology for meaningful insights into forestry. His interest lies in making remote sensing tools more accessible and useful for on-the-ground applications.
Supervisory team: Justin Morgenroth, Vega Xu, Ning Ye
Email: bsi68@uclive.ac.nz
Dengqiu Li
Visiting period: 11/2023 ~ 10/2024
Time-series remote sensing, forest disturbance detection, carbon source/sink estimation, ecosystem model simulation
Dr. Dengqiu Li is a visiting scholar from the School of Geographical Sciences and the School of Carbon Neutrality Future Technology at Fujian Normal University. His research interests include the classification of forest types and the monitoring of disturbances using dense time-series satellite remote sensing data and UAV Lidar. He specializes in evaluating the impacts of forest management and disturbances on the carbon cycle through the use of process-based ecosystem models and remote sensing data. Dr. Li holds BSc and MSc degrees in Land Resources Management from Shandong Agriculture University, and a PhD in Geography from Nanjing University.
Email: dengqiu.li@canterbury.ac.nz
Joseph Avis
Remote sensing, species classification, image analysis
Joseph is a PhD Student at the University of Canterbury's, School of Forestry, under the supervision of Dr Vega Xu. His research will focus on developing innovative remote sensing techniques to identify, classify, and monitor minor tree species throughout New Zealand. Through the combination of advanced image analysis and machine learning/deep learning methods, Joseph aims to provide an accurate and efficient tool to monitor and manage these valuable resources. Joseph holds an MSc in Remote Sensing and GIS and has spent the last 5 years working on Earth Observation projects commissioned by the European Space Agency.
Supervisory team: Vega Xu