Unlocking ground-based imagery for habitat mapping

N. Morueta-Holme*, L. L. Iversen, D. Corcoran, C. Rahbek, S. Normand

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

1 Citation (Scopus)

Abstract

Fine-grained environmental data across large extents are needed to resolve the processes that impact species communities from local to global scales. Ground-based images (GBIs) have the potential to capture habitat complexity at biologically relevant spatial and temporal resolutions. Moving beyond existing applications of GBIs for species identification and monitoring ecological change from repeat photography, we describe promising approaches to habitat mapping, leveraging multimodal data and computer vision. We illustrate empirically how GBIs can be applied to predict distributions of species at fine scales along Street View routes, or to automatically classify and quantify habitat features. Further, we outline future research avenues using GBIs that can bring a leap forward in analyses for ecology and conservation with this underused resource.

Original languageEnglish
JournalTrends in Ecology & Evolution
Volume39
Issue number4
Pages (from-to)349-358
Number of pages10
ISSN0169-5347
DOIs
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

Keywords

  • biodiversity
  • habitat complexity
  • image recognition
  • remote sensing
  • Street View

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