@Article{AmoreKampFrou:2018:GeApMe,
author = "Amore, Diogo de Jesus and Kampel, Milton and Frouin, Robert",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Scripps Institution
of Oceanography}",
title = "Geostatistical approach for meteo-oceanographic variables
evaluation at the Brazilian coast",
journal = "Proceedings of SPIE",
year = "2018",
volume = "10778",
pages = "107780v",
keywords = "GWR, geostatistics, sea surface temperature, photosynthetically
active radiation, chlorophyll-a.",
abstract = "MODIS chlorophyll-a concentration (chla), sea surface temperature
(SST), and photosynthetically active radiation (PAR) were used to
perform a geographically weighted regression (GWR) analysis within
a 150-km buffer of the Brazilian coast. The correlation was
between chla as the regressed variable and SST or PAR as the
predictors. Both a GWR and a Bayesian GWR (BGWR) were used for
evaluating the variables. Colored matrices were plotted for
displaying beta values, significance, residuals, and t-statistics.
Coefficients of determination (R2 ) were computed for all months.
Also, the ratio of the GWR beta estimates and the 95% confidence
interval BGWR estimates was computed. Results showed overall
better R2 for SST than for PAR regression but also better beta
estimates for PAR than for SST in relation to BGWR beta
significance range. Northern regions of the Brazilian coast
exhibited lower statistical significance. July had lowest GWR beta
values and best significance, January highest beta values and
worst significance, and April and October highly variable
results.",
doi = "10.1117/12.2500574",
url = "http://dx.doi.org/10.1117/12.2500574",
issn = "1018-4732",
language = "en",
targetfile = "amore_geostatistical.pdf",
urlaccessdate = "27 abr. 2024"
}