Author(s) |
Brinkhoff, James
Backhouse, Gillian
Saunders, Manu E
Bower, Deborah S
Hunter, John T
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Publication Date |
2022-01-27
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Abstract |
<p>Understanding broad trends in the distribution and composition of wetlands is essential for making evidence-based management decisions. Determining temporal change in the extent of inundation in wetlands using remote sensing remains challenging and requires on-ground verification to determine accuracy and precision. Therefore, optimization and validation of remote sensing methods in threatened wetlands is a high priority for their conservation. Despite their ecological importance in the landscape, we have little knowledge of the variation in the spatial extent of inundation in upland lagoons, a threatened ecological community in New South Wales, Australia. Our project developed locally trained algorithms to predict the extent of water and emergent vegetation using imagery from the Landsat-5, -7, and -8 satellites. The best model for upland lagoons used shortwave infrared reflectance (performing better than normalized difference spectral indices), with model accuracy against validation transects greater than 95%. We applied the model to images from 1988 to 2020 across 58 lagoons to generate a dataset that demonstrates the variable water regime and vegetation change in response to local rainfall over 32 years such as in the lagoons. Our results reduce threats to a dynamic threatened ecological community by filling an important knowledge gap and demonstrate a valuable method to understand historical and current changes in the hydrology of dynamic wetland systems more broadly.</p>
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Citation |
Ecosphere, 13(1), p. 1-13
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ISSN |
2150-8925
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Link | |
Publisher |
Ecological Society of America
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Rights |
Attribution 4.0 International
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Title |
Remote sensing to characterize inundation and vegetation dynamics of upland lagoons
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Type of document |
Journal Article
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Entity Type |
Publication
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Name | Size | format | Description | Link |
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openpublished/RemoteBrinkhoffBackhouseSaundersBowerHunter2022JournalArticle.pdf | 8225.423 KB | application/pdf | Published version | View document |