Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/72903

TítuloRemote sensing depicts riparian vegetation responses to water stress in a humid Atlantic region
Autor(es)Pace, Giorgio
Cánovas, Cayetano Gutiérrez
Henriques, R.
Boeing, F.
Cássio, Fernanda
Pascoal, Cláudia
Palavras-chaveEcosystem
Environmental Monitoring
Humans
Portugal
Rivers
Dehydration
Remote Sensing Technology
NDVI
Primary productivity
Forestry
Sentinel 2
Climate change
Data10-Jun-2021
EditoraElsevier
RevistaScience of the Total Environment
CitaçãoPace, G., Gutiérrez-Cánovas, C., Henriques, R., Boeing, et al. (2021). Remote sensing depicts riparian vegetation responses to water stress in a humid Atlantic region. Science of The Total Environment, 772, 145526
Resumo(s)Riparian areas in the Cantabrian Atlantic ecoregion (northwest Portugal) play a key role in soil formation and conservation, regulation of nutrient and water cycle, creation of landscape aesthetic value and the preservation of biodiversity. The maintenance of their ecological integrity is crucial given the ever increase in multiple anthropogenic (water demand and agriculture) and climatic pressures (droughts and extreme events). We developed a transferable remote sensing approach, taking advantage of the latest freely available technologies (Sentinel-2 and Copernicus Land products), to detect intra-annual and inter-annual changes in riparian vegetation productivity at the river basin scale related to water stress. This study has used the normalized difference vegetation index (NDVI) to investigate riparian vegetation productivity dynamics on three different vegetation types (coniferous, broadleaved and grassland) over the past 5 years (2015-2019). Our results indicated that inter-annual seasonality differed between drier (2017) and wetter (2016) years. We found that intra-annual dynamics of NDVI were influenced by the longitudinal river zonation. Our model ranked first (r2m = 0.73) showed that the productivity of riparian vegetation during the dry season was positively influenced by annual rainfall and by the type of riparian vegetation. The emergent long lags between climatic variation and riparian plant productivity provides opportunities to forecast early warnings of climatically-driven impacts. In addition, the different average productivity levels among vegetation types should be considered when assessing climatic impacts on riparian vegetation. Future applications of Sentinel 2 products could seek to distinguish riparian areas that are likely to be more vulnerable to changes in the annual water balance from those that are more resistant under longer-term changes in climate.
TipoArtigo
URIhttps://hdl.handle.net/1822/72903
DOI10.1016/j.scitotenv.2021.145526
ISSN0048-9697
e-ISSN1879-1026
Versão da editorahttps://www.sciencedirect.com/science/article/pii/S0048969721005945
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CBMA - Artigos/Papers

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