Unlocking ground-based imagery for habitat mapping
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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.
Originalsprog | Engelsk |
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Tidsskrift | Trends in Ecology & Evolution |
Vol/bind | 39 |
Udgave nummer | 4 |
Sider (fra-til) | 349-358 |
Antal sider | 10 |
ISSN | 0169-5347 |
DOI | |
Status | Udgivet - 2024 |
Bibliografisk note
Funding Information:
This research was supported by the Carlsberg Foundation via grant CF16-0942 to N.M-H. L.L.I. received support from the Natural Sciences and Engineering Research Council (grant DGECR-2022-00328 ). D.C. and S.N. were supported by SustainScapes – Center for Sustainable Landscapes under Global Change, funded by the Novo Nordisk Foundation (grant NNF20OC0059595 to S.N.). C.R. was supported by research grant no. 25925 from VILLUM FONDEN.
Publisher Copyright:
© 2023 Elsevier Ltd
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