PhD scholarship – UC

World-leading biodiversity measurement in Aotearoa New Zealand: Machine learning for developing detection models of NZ ecosystem types and restoration, using remote sensing data.

Closes 31 March 2022.

Are you interested in using cutting-edge technology to advance biodiversity measurement in Aotearoa?

This project will utilise machine learning and high-fidelity remote sensing data to develop detection models for measuring biodiversity, through ecosystem type and cover. This information will inform a national-level biodiversity index (the Eco-index), which will calculate investment in and impact on biodiversity for Aotearoa New Zealand.

We are on the precipice of a new age of remote monitoring made possible through high resolution satellite imagery and technologies such as LiDaR and RADAR. Machine learning and artificial intelligence capabilities can augment these technologies to provide novel insights into the wellbeing of our environment, including our biodiversity.

This project will involve developing novel spectral and other signatures using computer vision and deep learning techniques across the remote sensing inputs to classify ecosystem types and areas undergoing native revegetation on production landscapes, across New Zealand. Using visible/near infrared reflectance to measure chlorophyll will also enable assessment of vegetation health and vigor, lake eutrophic levels and so forth.

This project will enable realisation of the potential value of these technologies coming together, to provide temporally and spatially accurate data on the extent of ecosystem restoration and revegetation, as a proxy for biodiversity investment outputs.

This research will be highly transdisciplinary, involving data science, GIS, machine learning, and ecology. The student will be located within the wider Eco-index team encompassing more diverse disciplines still, including indicator specialists, social science, data engineering, statistical modelling and engineering. This large and diverse network will ensure the student remains supported, engaged and excited about the work.

This PhD student will work in close conjunction with the Eco-index programme: a $3.1 million research programme (2020-2024) from the government-funded New Zealand’s Biological Heritage National Science Challenge – Ngā Koiora Tuku Iho. Our mandate is to create a biodiversity index for Aotearoa New Zealand, factoring in both investment in and impact on our terrestrial biodiversity.

Outline Vision Mātauranga

The Eco-index programme has taken a treaty-based approach in the development of its biodiversity targets and monitoring. It has strong connections and relationships with iwi, and in particular Ngāi Tahu and the Ngāi Tahu Research Centre.

The Eco-index involves the development of Eco-indices in partnership with iwi that permit Māori authorities to determine the current state of biodiversity in their takiwā using both conventional and mātauranga Māori derived indicators. Consequently, the project strongly aligns with vision mātauranga. Firstly, in terms of taiao through the development of tools that enable detection of environmental quality from a Māori perspective, and secondly through the innovation theme, where AI and remote sensing technologies are combined with matauranga Māori to generate novel approaches to environmental sensing.

Senior Supervisor (Project Co-Lead)

Dr John Reid, Ngāi Tahu Research Centre at the University of Canterbury

Other members of the supervision team

Professor Matthew Wilson, School of Earth and Environment at the University of Canterbury

Want to know more?

If you are interested in this position please email Penny Payne, Co-lead of the Eco-index programme, to discuss the opportunity further:

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