@article{fdi:010073604, title = {{A} multivariate analysis framework to detect key environmental factors affecting spatiotemporal variability of chlorophyll-a in a tropical productive estuarine-lagoon system}, author = {{L}ins, {R}. {C}. and {M}artinez, {J}ean-{M}ichel and {M}arques, {D}. {D}. and {C}irilo, {J}. {A}. and {M}edeiros, {P}. {R}. {P}. and {F}ragoso, {C}. {R}.}, editor = {}, language = {{ENG}}, abstract = {{H}ere, we demonstrate how a combination of three multivariate statistic techniques can identify key environmental factors affecting the seasonal and spatial variability of chlorophyll-a ({C}hl-a) in a productive tropical estuarine-lagoon system. {R}emote estimation of {C}hl-a was carried out using a {NIR}-{R}ed model based on {MODIS} bands, which is highly consistent with the in situ measurement of {C}hl-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. {O}ur findings suggest that the river discharges and hydraulic residence time of the lagoons promote a stronger effect on the spatial variability of {C}hl-a in the coastal lagoons, while wind, solar radiation and temperature have a secondary importance. {T}he results also indicate a slight seasonal variability of {C}hl-a in {M}undau lagoon, which are different the from {M}anguaba lagoon. {T}he multivariate approach was able to fully understand the relative importance of key environmental factors on the spatiotemporal variability of {C}hl-a of the aquatic ecosystem, providing a powerful tool for reducing dimensionality and analyzing large amounts of satellite-derived {C}hl-a data.}, keywords = {{MODIS} ; {M}undau lagoon ; {M}anguaba lagoon ; {BRESIL} ; {ATLANTIQUE} ; {MANGUABA} {LAGON} ; {MUNDAU} {BASSIN}}, booktitle = {}, journal = {{R}emote {S}ensing}, volume = {10}, numero = {6}, pages = {art. 853 [17 p.]}, ISSN = {2072-4292}, year = {2018}, DOI = {10.3390/rs10060853}, URL = {https://www.documentation.ird.fr/hor/fdi:010073604}, }