IDEAS home Printed from https://ideas.repec.org/a/taf/nzecpp/v60y2026i1p24-47.html

Mapping solar adoption: integrating aerial image analysis with Bayesian spatial modelling in Aotearoa New Zealand

Author

Listed:
  • Y. S. Matthews
  • C. S. Harland

Abstract

This study examines household solar photovoltaic (PV) adoption in Aotearoa New Zealand, addressing a major research gap in a country with strong renewable energy potential but low residential uptake. In the absence of official data, we developed a new nationwide dataset by applying deep learning techniques to high-resolution aerial imagery. We identify 12,010 solar-equipped residential rooftops across urban areas, covering 51% of all residential properties nationwide. A property-level regression within a Bayesian spatial framework reveals that solar uptake is positively associated with solar potential, property wealth, newer and larger homes, and steel roofing, but lower in urban cores, multi-unit dwellings and semi-rural areas. Spatial clustering persists after controlling for observable factors, suggesting localised influences. Uptake is higher on Māori-owned and lower on company-owned properties. This study introduces a novel, publicly available dataset and provides new evidence on physical and governance-related factors to inform energy policy and strategies.

Suggested Citation

  • Y. S. Matthews & C. S. Harland, 2026. "Mapping solar adoption: integrating aerial image analysis with Bayesian spatial modelling in Aotearoa New Zealand," New Zealand Economic Papers, Taylor & Francis Journals, vol. 60(1), pages 24-47, January.
    • Handle: RePEc:taf:nzecpp:v:60:y:2026:i:1:p:24-47
    DOI: 10.1080/00779954.2025.2543274
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00779954.2025.2543274
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00779954.2025.2543274?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:nzecpp:v:60:y:2026:i:1:p:24-47. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/RNZP20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.