Doctoral Degree Graduates

Forest entomology, entomology, biocontrol, chemical ecology, agronomy

I am currently employed at MPI as an adviser in Animal & Plant Health. As a student at the University of Canterbury, I undertook a PhD degree on quantifying variation in paropsine defoliation within Eucalyptus trees. As part of this research I used lidar data, collected from UAV and helicopter, to estimate crown defoliation. I received my master’s degree in biology (chemical ecology and sustainable agriculture) from the University of Neuchâtel in Switzerland.

Supervisory team: Steve Pawson, Justin Morgenroth

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.

Supervisory team: Justin Morgenroth, Vega Xu

Google Scholar 

Remote Sensing, forest modelling, geospatial science, forest management

Having worked as a senior remote sensing scientist at Scion I now work for Margules Groome Ltd. as a Senior Consultant based in the UK. In this role I lead remote sensing and forest modelling activities for projects around the world. As a student at the University of Canterbury, I undertook a PhD degree on monitoring and mapping invasive conifers in New Zealand using remote sensing. I was supervised by Dr Justin Morgenroth from UC and Dr Michael Watt and Dr Thomas Paul from Scion. I received my previous degrees in Forestry (MSc) from University of Wales, Bangor and Biology (BSc) from the University of Sheffield.

Supervisory team: Justin Morgenroth, Michael Watt (Scion), Thomas Paul (Scion)

Forest growth dynamics, silviculture, forest ecology, ecophysiology, geospatial science

I am currently employed at Scion Research (New Zealand Forest Research Institute Ltd) as a Senior forest scientist. As a student at the University of Canterbury, I undertook a PhD degree on “Hybrid growth models for Eucalyptus globoidea and E. bosistoana: Explaining within and between site variability”. I received my previous degrees BSc (hons.) in Forestry (Khulna University, Bangladesh) and MSc in Forestry and Natural resources management ( Khulna University, Bangladesh; University of Lleida, Spain; University of Lisbon, Portugal).

Supervisory team: Euan Mason, Justin Morgenroth, Mark Bloomberg, Dean Meason (Scion)

Google Scholar 

Land cover/use, Remote Sensing, Landsat, Large area mapping

I am currently employed at Copperbelt University in Zambia as a Lecturer of GIS and Remote Sensing. As a student at the University of Canterbury (2016 -2019), I undertook a PhD degree on Monitoring land cover dynamics for Zambia using remote sensing: 1972–2016. I was supervised by Associate Professor Justin Morgenroth and Dr. Cong Xu both from University of Canterbury. I received my master’s degrees in Forestry Science from Stellenbosch University in South Africa, and my Undergraduate degree (Forestry) from Copperbelt University in Zambia. My research interests include large area land cover mapping, open source geospatial tools and low-cost geospatial technology.

Supervisory team: Justin Morgenroth, Vega Xu

Google Scholar 

Urban forestry, urban planning, social impacts/outcomes

Tingdong Guo is currently employed at Auckland Council as a Senior Socio-Spatial Researcher. He focuses on using a mixed-method approach to research on issues (e.g. land use, housing, urban greenspace) in urban areas from a socio-spatial lens. As a student at the University of Canterbury, he undertook a PhD degree on the effect of residential property redevelopment on urban forest dynamics in Christchurch, New Zealand. His supervisor during this time was A/Prof. Justin Morgenroth. Prior to that, he obtained his Master's degree in Urban Forest Ecology from Northwest A&F University in China.

Supervisory team: Justin Morgenroth, Tenley Conway (University of Toronto), Matthew Hughes 

ResearchGate 

Remote Sensing, deep learning, geospatial data science, forestry

Dr Grant Pearse leads the Remote Sensing and GIS team at Scion Research. The team’s research covers a diverse range of topics including measuring forest growth and yield using lidar, satellite and UAV data. Using UAVs, aerial and satellite data to detect and manage forest biosecurity risks. The group also has an active tree phenotyping programme using state-of-the art hyperspectral, thermal and lidar sensors. Dr Pearse’s specific interests lie at the intersection of data science and remote sensing where he has developed and operationalized a range of tools based on deep learning. He obtained his BForSc from the School of Forestry in 2012 before completing his PhD in remote sensing at the University of Canterbury in 2016.

Supervisory team: Justin Morgenroth, Michael Watt (Scion)

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. 

Supervisory team: Bruce Manley, Justin Morgenroth

Research Profile 

Supervisory team: Justin Morgenroth, Michael Watt (Scion)