27
Mar

Mapping Land Cover with Machine Learning [Webinar]

  • Live Stream
  • 27 March 2020

Webinar: Mapping Land Cover with Machine Learning | Monitoring Land Cover Change Through Computer Vision

Friday 27 March, 10:00 - 11:00

Lynker Analytics is a privately-owned data science and analytics company based in Wellington. In this presentation, I will discuss and demonstrate how machine learning—a subfield of artificial intelligence (AI)—has progressed to the stage where computer vision and deep learning in image analysis and classification is now viable for geospatial data production.

I will explain what’s involved in successfully apply machine learning to accurately map land use, land cover and land activity. I will explain how iterative semi-supervised machine learning can be used to optimize and minimize the amount of data needed to train industrial artificial neural network models and then show how this method can be used to generate a range of high-resolution GIS features including vegetation, deforested land, buildings, roads, bare earth, water, impervious surfaces and more.

Finally, I will discuss the reliability of this approach and the resulting spatial data layers and what this could mean for organisations maintaining and managing geographic information systems.

Type: Live Stream Event

Members Rate: $FREE

Non-Members Rate: $50.00 + gst

Student Member Rate: $FREE


*Registrations will close on the 26 March, 16:00.

Presenters

  • Matt Lythe
    Matt Lythe

    Matt leads Wellington-based startup Lynker Analytics – a data science, analytics and machine learning consultancy. Providing industrial research and market-ready AI systems, Lynker Analytics is the AI centre of excellence for Lynker - a 480+ strong US science and technology company that provides services to the US federal government.

    Matt has worked in leadership roles across both the private and public sector in New Zealand including stints at Transpower, New Zealand Post, Eagle Technology and CoreLogic. Matt has a background in science, geospatial technology, data and analytics including scientific research roles in NZ and the UK. He has managed large multinational data, technology and analytics projects and product developments including the first comprehensive database and assessment of total ice volume on the Antarctic continent. He holds a Master of Science (Hons) from Auckland University and has over ten publications in peer-reviewed journals.

    https://www.linkedin.com/in/mattlythe