Lins R. C., Martinez Jean-Michel, Marques D. D., Cirilo J. A., Medeiros P. R. P., Fragoso C. R. (2018). A multivariate analysis framework to detect key environmental factors affecting spatiotemporal variability of chlorophyll-a in a tropical productive estuarine-lagoon system. Remote Sensing, 10 (6), p. art. 853 [17 p.]. ISSN 2072-4292.
Titre du document
A multivariate analysis framework to detect key environmental factors affecting spatiotemporal variability of chlorophyll-a in a tropical productive estuarine-lagoon system
Here, we demonstrate how a combination of three multivariate statistic techniques can identify key environmental factors affecting the seasonal and spatial variability of chlorophyll-a (Chl-a) in a productive tropical estuarine-lagoon system. Remote estimation of Chl-a was carried out using a NIR-Red model based on MODIS bands, which is highly consistent with the in situ measurement of Chl-a with root mean square error (RMSE) of 15.24 mg m(-3) and 13.43 mg m(-3) for two independent datasets used for the model's calibration and validation, respectively. Our findings suggest that the river discharges and hydraulic residence time of the lagoons promote a stronger effect on the spatial variability of Chl-a in the coastal lagoons, while wind, solar radiation and temperature have a secondary importance. The results also indicate a slight seasonal variability of Chl-a in Mundau lagoon, which are different the from Manguaba lagoon. The multivariate approach was able to fully understand the relative importance of key environmental factors on the spatiotemporal variability of Chl-a of the aquatic ecosystem, providing a powerful tool for reducing dimensionality and analyzing large amounts of satellite-derived Chl-a data.
