PhD Studentship: Addressing ecosystem mapping challenges using machine learning and remote sensing

Project Title: Addressing ecosystem mapping challenges using machine learning and remote sensing

We are seeking a motivated PhD candidate to work at the nexus of landscape ecology, machine learning and remote sensing. The University of Exeter’s Centre for Doctoral Training in Environmental Intelligence, in partnership with RSK Biocensus, is inviting applications for a fully-funded PhD studentship to commence in September 2023.The successful applicant will join the UKRI CDT in Environmental Intelligence, and will be included in CDT cohort building and training activities.  The successful applicant will work on the below project under the supervision of Karen Anderson and Sareh Rowlands (University of Exeter), from the start of their PhD programme.

Project Description:

To address the urgent biodiversity crisis there is a need for timely information about ecological communities and their dynamics (spatially and temporally).  Traditionally the approach taken to deliver such information has been heavily reliant on field-based surveying techniques such as phase-1 habitat surveys or the National Vegetation Classification (NVC) system. Whilst remotely-sensed spatial data (e.g. lidar, satellite observations etc) and machine learning have proven great worth for ecological research and in the development of nature-based solutions, these approaches have yet to be employed to fulfil statutory ecological mapping requirements.  The broad goal of this PhD project is to investigate the use of these exciting and rapidly developing approaches for mapping habitats, vegetation community composition and structure. Using the results of those workflows, the successful candidate will then explore whether information about biodiversity and carbon storage characteristics of natural and semi-natural ecosystems can be inferred. 

This project will collate existing spatial data on habitats in the UK derived from ground-based surveys, and national open-source remote sensing datasets, to feed into machine learning pipelines, to investigate their potential to contribute to the production of maps that are routinely used in ecological consultancy and conservation.  If new workflows can deliver useful outputs, this could improve substantially the efficiency of habitat mapping which currently relies on expensive and time-consuming field surveys.  The project will also contribute to the development of tools for assessing changes in biodiversity and carbon storage in relation to habitat creation and restoration projects.

The project is a collaboration between the UKRI CDT in Environmental Intelligence at the University of Exeter and RSK Biocensus, a sector-leading and forward-thinking ecology and sustainability consultancy. RSK Biocensus will provide supporting technical knowledge in ecology, spatial data management and environmental mapping, and opportunities for the student to gain experience working in a commercial consultancy environment, including participating in the collection of data in the field.

The student will join the CDT Environmental Intelligence at University of Exeter where they will receive training in relevant methods before conducting their research project.

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