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Research Project
Feeding ecology of declining seahorse populations of Ria Formosa lagoon
Funder
Authors
Publications
Mapping saltmarsh vertical distribution communities in southern Portugal using high spatiotemporal resolution satellite imagery
Publication . Martins, Márcio; Parreira, Filipe; Ito, Paula; Santos, Rui; Gotha, Simon von sachsen-Coburg Und; Barrena de los Santos, Carmen
Saltmarshes, transitional coastal habitats between terrestrial and marine ecosystems, offer crucial ecological benefits, including coastal protection, biodiversity enhancement, water purification and carbon sequestration. However, saltmarsh areas are shrinking, primarily due to human activities. Traditional monitoring approaches for saltmarsh coverage are often costly and restricted in spatial scope, prompting a shift towards remote sensing techniques. While remote sensing has proven effective for studies that cover large spatial areas, its application for smaller areas remains challenging. In this study, we trained classification models to identify saltmarsh vegetation communities in southern Portugal. We utilized high-resolution (3-metre) and high-frequency (near-daily) imagery to optimize image selection according to tidal conditions at the time of capture and developed an elevation proxy for the intertidal zone. Our model achieved an overall accuracy of 67%, estimating a total of 4,572 ha of saltmarsh in southern Portugal, 85% located in the Ria Formosa lagoon. The middle saltmarsh zone, dominated by Atriplex portulacoides, Salicornia perennis and Salicornia fruticosa, covered the largest area. The approach presented here holds promise for further refinement, enabling automated, high-resolution monitoring of saltmarsh communities, which is essential for conservation and management initiatives.
Organizational Units
Description
Keywords
, Natural sciences ,Natural sciences/Biological sciences
Contributors
Funders
Funding agency
Fundação para a Ciência e a Tecnologia, I.P.
Fundação para a Ciência e a Tecnologia, I.P.
Fundação para a Ciência e a Tecnologia, I.P.
Funding programme
OE
Funding Award Number
2022.11198.BD