algorithm atmospheric correction backscattering Barra Bonita bio-optical cascading clorophyl coefficient concentration dados hidroacústicos data quality datasets geoestatística imagens inland water landsat mapeamento nova avanhadava parametrization particle phytoplankton remote sensing reservoir São Paulo sentinel Submerged aquatic vegetation total suspended matter tropical reservoir TSM visual analytics
2016 |
![]() @article{Bernardo2016, title = {An investigation into the effectiveness of relative and absolute atmospheric correction for retrieval the TSM concentration in inland waters}, author = {Nariane Marselhe Ribeiro Bernardo and Fernanda Sayuri Yoshino Watanabe and Thanan Walesza Pequeno Rodrigues and Enner Herenio de Alcântara}, doi = {10.1007/s40808-016-0176-9}, issn = {2363-6211}, year = {2016}, date = {2016-06-21}, journal = {Modeling Earth Systems and Environment}, volume = {2}, number = {3}, pages = {114}, abstract = {The absolute atmospheric correction inputs are not always available, and then such parameters are assumed based on geographical location, acquisition time and sensor type. These assumptions can imply in errors in retrieving the remote-sensing reflectance (Rrs), and affects the optically active compounds estimates. As an alternative, relative atmospheric correction, i.e. radiometric normalization, can be used in cases where there is no information about atmospheric conditions. The main goal of this work was to perform a comparative analysis between absolute and relative atmospheric correction to estimate total suspended matter (TSM) concentrations in the Barra Bonita Hydroelectric Reservoir (São Paulo State, Brazil). The corrections were applied to the operational land imager, on-board Lansat-8 satellite. The Rrs errors from each correction were computed considering in situ data, and the lowest error was obtained for green spectral band (RMSEabsolute = 11.5 % and RMSErelative = 12.3 %). Using a regional algorithm that was developed using the in situ measurements (the model was TSM = 1742.7*B3 - 5.42, with R2 = 0.60}, keywords = {atmospheric correction, concentration, inland water, total suspended matter, TSM}, pubstate = {published}, tppubtype = {article} } The absolute atmospheric correction inputs are not always available, and then such parameters are assumed based on geographical location, acquisition time and sensor type. These assumptions can imply in errors in retrieving the remote-sensing reflectance (Rrs), and affects the optically active compounds estimates. As an alternative, relative atmospheric correction, i.e. radiometric normalization, can be used in cases where there is no information about atmospheric conditions. The main goal of this work was to perform a comparative analysis between absolute and relative atmospheric correction to estimate total suspended matter (TSM) concentrations in the Barra Bonita Hydroelectric Reservoir (São Paulo State, Brazil). The corrections were applied to the operational land imager, on-board Lansat-8 satellite. The Rrs errors from each correction were computed considering in situ data, and the lowest error was obtained for green spectral band (RMSEabsolute = 11.5 % and RMSErelative = 12.3 %). Using a regional algorithm that was developed using the in situ measurements (the model was TSM = 1742.7*B3 - 5.42, with R2 = 0.60 |
Rodrigues, T. W. P.; Alcântara, E. H. de; Watanabe, F. S. Y.; Rotta, L. H. da S.; Imai, N. N.; Curtarelli, M. P.; Barbosa, C. C. F.: COMPARAÇÃO ENTRE MÉTODOS EMPÍRICOS PARA ESTIMATIVA DA CONCENTRAÇÃO DE CLOROFILA-A EM RESERVATÓRIOS EM CASCATA (RIO TIETÊ, SÃO PAULO). Revista Brasileira de Cartografia, 68 (1), 2016. (Tipo: Journal Article | BibTeX | Tags: cascading, clorophyl, concentration, empíricos, reservoir, São Paulo, Tietê) @article{rodrigues2016comparaccao, title = {COMPARAÇÃO ENTRE MÉTODOS EMPÍRICOS PARA ESTIMATIVA DA CONCENTRAÇÃO DE CLOROFILA-A EM RESERVATÓRIOS EM CASCATA (RIO TIETÊ, SÃO PAULO)}, author = {Thanan Walesza Pequeno Rodrigues and Enner Herenio de Alcântara and Fernanda Sayuri Yoshino Watanabe and Luiz Henrique da Silva Rotta and Nilton Nobuhiro Imai and Marcelo Pedroso Curtarelli and Cláudio Clemente Faria Barbosa}, year = {2016}, date = {2016-01-01}, journal = {Revista Brasileira de Cartografia}, volume = {68}, number = {1}, keywords = {cascading, clorophyl, concentration, empíricos, reservoir, São Paulo, Tietê}, pubstate = {published}, tppubtype = {article} } |
2015 |
Bernardo, N. M. R.; Alcântara, E. H. de; Watanabe, F. S. Y.; Rodrigues, T. W. P.; Imai, N. N.; Curtarelli, M.; Barbosa, C.: Bio-optical model tuning for retrieving the total suspended matter concentration in Barra Bonita Reservoir. Revista Brasileira de Cartografia, 67 (7), 2015. (Tipo: Journal Article | BibTeX | Tags: algorithm, Barra Bonita, bio-optical, concentration, models, total suspended matter, TSM) @article{bernardo2015bio, title = {Bio-optical model tuning for retrieving the total suspended matter concentration in Barra Bonita Reservoir}, author = {Nariane Marselhe Ribeiro Bernardo and Enner Herenio de Alcântara and Fernanda Sayuri Yoshino Watanabe and Thanan Walesza Pequeno Rodrigues and Nilton Nobuhiro Imai and Marcelo Curtarelli and Claudio Barbosa}, year = {2015}, date = {2015-01-01}, journal = {Revista Brasileira de Cartografia}, volume = {67}, number = {7}, keywords = {algorithm, Barra Bonita, bio-optical, concentration, models, total suspended matter, TSM}, pubstate = {published}, tppubtype = {article} } |
![]() @article{ijerph120910391, title = {Estimation of Chlorophyll-a Concentration and the Trophic State of the Barra Bonita Hydroelectric Reservoir Using OLI/Landsat-8 Images}, author = {Fernanda Sayuri Yoshino Watanabe and Enner Herenio de Alcântara and Thanan Walesza Pequeno Rodrigues and Nilton Nobuhiro Imai and Cláudio Clemente Faria Barbosa and Luiz Henrique da Silva Rotta}, doi = {10.3390/ijerph120910391}, issn = {1660-4601}, year = {2015}, date = {2015-01-01}, journal = {International Journal of Environmental Research and Public Health}, volume = {12}, number = {9}, pages = {10391--10417}, abstract = {Reservoirs are artificial environments built by humans, and the impacts of these environments are not completely known. Retention time and high nutrient availability in the water increases the eutrophic level. Eutrophication is directly correlated to primary productivity by phytoplankton. These organisms have an important role in the environment. However, high concentrations of determined species can lead to public health problems. Species of cyanobacteria produce toxins that in determined concentrations can cause serious diseases in the liver and nervous system, which could lead to death. Phytoplankton has photoactive pigments that can be used to identify these toxins. Thus, remote sensing data is a viable alternative for mapping these pigments, and consequently, the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton species. Therefore, the aim of this work was to evaluate the performance of images of the sensor Operational Land Imager (OLI) onboard the Landsat-8 satellite in determining Chl-a concentrations and estimating the trophic level in a tropical reservoir. Empirical models were fitted using data from two field surveys conducted in May and October 2014 (Austral Autumn and Austral Spring, respectively). Models were applied in a temporal series of OLI images from May 2013 to October 2014. The estimated Chl-a concentration was used to classify the trophic level from a trophic state index that adopted the concentration of this pigment-like parameter. The models of Chl-a concentration showed reasonable results, but their performance was likely impaired by the atmospheric correction. Consequently, the trophic level classification also did not obtain better results.}, keywords = {Barra Bonita, clorophyl, concentration, imagens, landsat, OLI, trophic state}, pubstate = {published}, tppubtype = {article} } Reservoirs are artificial environments built by humans, and the impacts of these environments are not completely known. Retention time and high nutrient availability in the water increases the eutrophic level. Eutrophication is directly correlated to primary productivity by phytoplankton. These organisms have an important role in the environment. However, high concentrations of determined species can lead to public health problems. Species of cyanobacteria produce toxins that in determined concentrations can cause serious diseases in the liver and nervous system, which could lead to death. Phytoplankton has photoactive pigments that can be used to identify these toxins. Thus, remote sensing data is a viable alternative for mapping these pigments, and consequently, the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton species. Therefore, the aim of this work was to evaluate the performance of images of the sensor Operational Land Imager (OLI) onboard the Landsat-8 satellite in determining Chl-a concentrations and estimating the trophic level in a tropical reservoir. Empirical models were fitted using data from two field surveys conducted in May and October 2014 (Austral Autumn and Austral Spring, respectively). Models were applied in a temporal series of OLI images from May 2013 to October 2014. The estimated Chl-a concentration was used to classify the trophic level from a trophic state index that adopted the concentration of this pigment-like parameter. The models of Chl-a concentration showed reasonable results, but their performance was likely impaired by the atmospheric correction. Consequently, the trophic level classification also did not obtain better results. |