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Graphical abstract, Remote sensing data is a viable alternative for mapping pigment concentrations in water body, and consequently, the trophic. Chlorophyll-a (Chl-a) is present in all phytoplankton species. This study therefore uses laboratory fluorometric and remote sensing extraction methods for assessing chlorophyll-a concentration in the Lagos Lagoon. The fluorometer was calibrated with a commercially available chlorophyll-a standard before used in the laboratory to estimates chlorophyll-a concentration. Landsat 7 (ETM+) and Landsat 8 (OLI) were acquired for the remote sensing method. The Landsat data were first geometrically rectified. Then brightness values were converted to reflectance through the radiometric correction process. For the regression models, logarithmically transformed chlorophyll-a was used as the dependent variable. Single bands, band ratios and logarithmically transformed band ratios were the independent variables. R2 values were computed and evaluated. • Chlorophyll-a contributes to productive water bodies • laboratory fluorometric and remote sensing extraction methods • Landsat data acquired for the remote sensing method

Accurate calibration of oceanic LiDAR signals is essential for the accurate retrieval of ocean optical properties. Nowadays, there are many methods for aerosol LiDAR calibration, but fewer attempts have been made to implement specific calibration methods for oceanic LiDAR. Oceanic LiDAR often has higher vertical resolution, needs greater signal dynamic range, detects several orders of magnitude lower less depth of penetration, and suffers from the effects of the air-sea interface. Therefore the calibration methods for aerosol LiDAR may not be useful for oceanic LiDAR. In this paper, we present a new simple and feasible approach for oceanic LiDAR calibration via comparison of LiDAR backscatter against calculated scatter based on iteratively bio-optical models in clear, open ocean, Type 1 water. Compared with current aerosol LiDAR calibration methods, it particularly considers geometric losses and attenuation occurring in the atmosphere-sea interface. The mean relative error percentage (MREP) of LiDAR calibration constant at two different stations was all within 0.08%. The MREP between LiDAR-retrieved backscatter, chlorophyll after using LiDAR calibration constant with inversion results of measured data were within 0.18% and 1.39%, respectively. These findings indicate that the bio-optical methods for LiDAR calibration in clear ocean water are feasible and effective.

Made available in DSpace on 2022-04-29T07:50:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-10-01 The objective of this work was to evaluate the suitability of three remote sensors, namely, the Moderate Resolution Imaging Spectroradiometer (MODIS), the Operational Land Imager (OLI), and the Ocean Land Color Instrument (OLCI), for estimating total suspended matter (TSM) concentrations in the Barra Bonita reservoir. Although remote sensors have been widely explored for ocean and inland water applications in Brazilian reservoirs, a thorough comparison of sensors as a TSM monitoring tool has yet to be conducted. OLI data have been used for inland waters, but few studies on Brazilian aquatic systems have been performed. MODIS data were investigated due to their daily coverage, and OLCI data (scheduled for launch in December 2015) were analyzed because of their spatial (better than MODIS) and temporal (lower than OLI) resolution. In situ hyperspectral measurements were used as input to simulate MODIS, OLI and OLCI spectral bands while considering the spectral response function for each sensor. Simulated data and TSM concentrations were tuned to generate regional models using linear and non-linear regressions. The models were assessed using the coefficient of determination (R2), which had a range of between 0

Made available in DSpace on 2018-12-11T17:21:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-07-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The kd(490) is a vertical light attenuation coefficient and an important parameter for water quality. The kd estimates are often based on empirical and semi-analytical algorithms, designed for oceanic and coastal waters. However, there is a lack of information about the performances of these models to inland waters dominated by chromophoric dissolved organic matter (CDOM). Therefore, to contribute to this investigation, nine empirical models based on the blue-to-green and blue-to-red ratios and chlorophyll-a (Chl-a) concentration were evaluated, as well as three semi-analytical models using bands from the Operational Land Imager (OLI)/Landsat-8. The errors (mean absolute percentage error, MAPE > 80%) presented by the empirical models confirmed that the blue-to-green ratio failed in retrieving kd(490) in an environment dominated by CDOM. Similar failures occurred with the models using the Chl-a concentration (MAPE ~60%) as input. A semi-analytical approach showed the lowest error (MAPE = 41.04%) in the estimate of the inherent optical properties for complex waters in order to reduce the errors above. After retrieval of kd(490) using the semi-analytical model, seasonal patterns were observed, and high values of kd(490) were detected in the dry season possibly due to the increase of the concentration of the optically-significant substances (OSS). Department of Cartography São Paulo State University (Unesp) Federal Institute for Education Science and Technology of Pará State Department of Environmental Engineering São Paulo State University (Unesp) Department of Cartography São Paulo State University (Unesp) Department of Environmental Engineering São Paulo State University (Unesp)

Submitted by Ana Carolina Campos Gomes (carol.campos01@hotmail.com) on 2018-04-20T17:35:54Z No. of bitstreams: 1 AnaCarolina.pdf: 2801427 bytes, checksum: 1809e31f1376c275f1b3a1c9eca5cf6f (MD5) Approved for entry into archive by Claudia Adriana Spindola null (claudia@fct.unesp.br) on 2018-04-20T19:06:20Z (GMT) No. of bitstreams: 1 gomes_acc_me_prud.pdf: 2801427 bytes, checksum: 1809e31f1376c275f1b3a1c9eca5cf6f (MD5) Made available in DSpace on 2018-04-20T19:06:20Z (GMT). No. of bitstreams: 1 gomes_acc_me_prud.pdf: 2801427 bytes, checksum: 1809e31f1376c275f1b3a1c9eca5cf6f (MD5) Previous issue date: 2018-03-23 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) O presente trabalho teve como objetivo estimar as profundidades da zona eufótica (Zeu) e do disco de Secchi (ZSD) a partir do coeficiente de atenuação da luz (kd) utilizando dados do sensor Operational Land Imager (OLI)/Landsat-8 no reservatório de Bariri. Como importantes parâmetros de medida da claridade da água, kd, Zeu e ZSD são afetados pelas substâncias opticamente significativas (SOS). A caracterização óptica do reservatório foi realizada a partir de duas campanhas de campo realizadas no período seco, aqui nomeadas como BAR1 (agosto/2016) e BAR2 (junho/2017), que contaram com análises das propriedades ópticas inerentes (POIs), das SOS e da coleta de dados radiométricos para o cálculo da reflectância de sensoriamento remoto (Rsr). A localização do reservatório de Bariri como o segundo do Sistema de Reservatórios em Cascata (SRC) do Rio Tietê promove a heterogeneidade dos seus níveis de eutrofização na direção montante-jusante além de caracterizá-lo como altamente produtivo. As campanhas de campo foram marcadas por uma significativa diferença nos valores de concentração de clorofila-a ([Chl-a]) que apresentou variação média entre 7,99 e 119,76 μg L-1 com os maiores valores em BAR1, com decréscimo das SOS em BAR2 em relação a BAR1 e predomínio de material particulado orgânico (MPO) nas duas campanhas de campo; a turbidez variou entre 5,72 e 16,60 NTU. A absorção por matéria orgânica colorida dissolvida (aCDOM) foi predominante nas duas campanhas de campo, sendo mais expressiva em BAR2. Para as estimativas de kd, nove modelos empíricos e três modelos semi-analíticos baseados em dados radiométricos como razões entre as bandas azul/verde e azul/vermelho do sensor OLI/Landsat-8 e baseados em [Chl-a] foram avaliados. Considerando a propriedade óptica aparente (POA) do kd, um modelo semi-analítico baseado em POIs e na distribuição angular da luz apresentou os menores erros (erro médio percentual absoluto – MAPE) de 40% em relação aos modelos empíricos de [Chl-a] com 60% e de 80% para os modelos empíricos baseados em razões de bandas. A partir das estimativas de kd, modelos de estimativa de Zeu e ZSD foram avaliados. Para as estimativas de Zeu, cinco modelos empíricos, baseados na relação entre o coeficiente de atenuação da luz da radiação fotossinteticamente ativa [kd(PAR)] e de kd em 490 nm [kd(490)], e um modelo semi-analítico, baseado na equação de transferência radiativa, foram considerados; para as estimativas de ZSD, um modelo semi-analítico foi testado. Os resultados obtidos foram melhores para um modelo empírico (erro percentual absoluto – ε) de Zeu com 16% em relação ao modelo semi-analítico (ε 30%) e os erros nas estimativas de ZSD foram de 57%. Os erros nas estimativas de kd revelaram que a acurácia dos modelos empíricos foi comprometida devido à influência por CDOM e que o modelo semi-analítico, por considerar a natureza óptica de kd como uma POA, apresentou os melhores resultados. As estimativas de ZSD também foram afetadas pelas características ópticas de Bariri, não apresentando correlação com a matéria orgânica em BAR2, marcado pelo decréscimo de [Chl-a] e aumento dos valores de aCDOM. Zeu mostrou melhores resultados a partir de um modelo empírico calibrado com dados ópticos semelhantes aos do reservatório de Bariri em comparação ao modelo semi-analítico, desenvolvido para abranger as variações bio-ópticas sazonais e regionais. kd, Zeu e ZSD foram espacializados a partir de imagens do sensor OLI/Landsat-8 permitindo a avaliação espaçotemporal desses parâmetros que apresentaram um padrão sazonal quando analisados em relação aos dados de precipitação. kd apresentou variação entre 0,89 e 5,60 m-1 para o período analisado (2016) e Zeu e ZSD apresentaram variação entre 0,30 e 7,60 m e entre 0,32 e 2,95 m, respectivamente, para o período de 2014-2016. Pode-se concluir então, que apesar das estimativas de kd, Zeu e ZSD terem sido afetadas pela influência de CDOM no reservatório de Bariri, o esquema semi-analítico foi capaz de estimar kd com menor erro e permitiu as estimativas de Zeu e ZSD. The objective of this present work was estimate the euphotic zone (Zeu) and Secchi disk (ZSD) depths from the light attenuation coefficient (kd) using the Operational Land Imager (OLI)/Landsat-8 data in Bariri reservoir. The kd, Zeu and ZSD are important water clarity parameters and are influenced by the optically significant substances (OSS). The optical characterization was carried out with data collected in two field campaigns in the dry period, here called BAR1 (august/2016) and BAR2 (june/2017), that included analysis of the inherent optical properties (IOPs), of the OSS and radiometric data to calculate the remote sensing reflectance (Rrs). The location of Bariri reservoir as the second of the Cascading Reservoir System (CRS) of Tietê River promotes the heterogeneity of the eutrophication levels from upstream to downstream besides characterizes the reservoir as highly productive. The field campaigns presented a significant difference in chlorophyll-a concentrations ([Chl-a]) with mean variation between 7.99 and 119.76 μg L-1 with the highest values in BAR1, with reduce of the OSS in BAR2 in relation to BAR1 and predominance of organic particulate matter (OPM) in both field campaigns and variation in turbidity from 5.72 to 16.60 NTU. The absorption of chromophoric dissolved organic matter (CDOM) was dominant in both field campaigns and more expressive in BAR2. For the kd estimates, nine empirical models and three semi-analytical models based on radiometric data such as ratios of blue-green and blue-red bands of (OLI)/Landsat 8 sensor and based on [Chl-a] were evaluated. Considering the apparent optical property (AOP) of kd, a semi-analytical model based on IOPs and the light angular distribution presented the lowest errors (mean absolute percentage error – MAPE) of 40% in relation to the empirical models of [Chl-a] with 60% and of 80% for the empirical models based on the band ratios. Through the kd estimates, models to derive Zeu and ZSD were evaluated. For the Zeu estimates, five empirical models were considered based on the relation between the attenuation coefficient of the photosynthetically active radiation [kd(PAR)] and the kd at 490 nm [kd(490)], and one semi-analytical model, based on the radiative transfer equation; for the ZSD estimates, one semi-analytical model was tested. The empirical model of Zeu showed the better results with the (unbiased absolute percentage error – ε) 16% in relation to the semi-analytical model (ε 30%) and the estimates errors of ZSD were 57%. The errors in kd estimates revealed that the accuracy of the empirical models was affected by the CDOM influence in Bariri reservoir and the semi-analytical model presented a better performance when considering the optical nature of kd as an AOP. The ZSD estimates were also affected by the optical characteristics of Bariri with no correlation to the SPM in BAR2, where the [Chl-a] decreased and the aCDOM increased. Zeu showed better results from an empirical model calibrated with similar optical data to Bariri reservoir in relation to the semi-analytical model developed to be applied in a wide range of bio-optical seasonal and regional variations. The kd, Zeu and ZSD were spatially distributed through OLI/Landsat-8 images allowing the temporal-spatial assessment of theses parameters, which presented a seasonal pattern when analyzed in relation to rainfall data. kd presented variation from 0.89 to 5.60 m-1 to the analyzed period (2016) and Zeu and ZSD presented variations between 0.30 and 7.60 m and between 0.32 and 2.95 m, respectively, for 2014-2016 period. It can be concluded, therefore, that despite of the CDOM have affected the kd, Zeu and ZSD retrievals in Bariri reservoir, the semi-analytical scheme was able to estimate kd with lowest error and enable the Zeu and ZSD estimates. CNPq: 131737/2016-3 FAPESP: 2012/19821-1 e 2015/21586-9

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.

Submitted by SARAH CRISTINA ARAUJO MARTINS null (sarahca.martins@gmail.com) on 2017-08-27T12:54:53Z No. of bitstreams: 1 Dissertacao_MartinsSarah.pdf: 3974138 bytes, checksum: 73a1c2c28d4a0cbbde72b9e8a49211ce (MD5) Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-08-29T17:18:44Z (GMT) No. of bitstreams: 1 martins_sca_me_prud.pdf: 3974138 bytes, checksum: 73a1c2c28d4a0cbbde72b9e8a49211ce (MD5) Made available in DSpace on 2017-08-29T17:18:44Z (GMT). No. of bitstreams: 1 martins_sca_me_prud.pdf: 3974138 bytes, checksum: 73a1c2c28d4a0cbbde72b9e8a49211ce (MD5) Previous issue date: 2017-08-03 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) A matéria orgânica dissolvida (DOM) é a componente da água que pode ser usada como indicativo de sua qualidade, pois possui duas fontes: uma alóctone, relacionada com descargas de material terrestre, estando vinculada aos ácidos húmicos, e outra autóctone, associada às descargas fluviais ou produção própria do corpo hídrico estudado, estando relacionada aos ácidos fúlvicos. A matéria orgânica dissolvida colorida (CDOM) é a fração colorida da DOM, que pode ser usada como proxy para a observação desta última em águas interiores. O reservatório hidrelétrico de Funil (FHR) foi o corpo hídrico escolhido como área de estudo deste trabalho. Neste contexto, o objetivo geral desta pesquisa foi identificar e avaliar as mudanças no coeficiente de absorção da CDOM (aCDOM) na superfície da água ao longo do tempo (1995 – 2010), bem como entender a sua relação com mudanças no uso e cobertura da terra (LULC) na bacia de contribuição do FHR. Para alcançar tal objetivo foram realizados: (i) o mapeamento histórico de LULC (1995 – 2010, com 5 anos de intervalo) para detecção de mudanças; (ii) o estudo de um conjunto de modelos bio-ópticos baseados na literatura, bem como de um novo modelo empírico desenvolvido para estimar aCDOM via reflectância simulada (Rrs_simulated) para o sensor Thematic Mapper (TM); (iii) a distribuição espaço-temporal do aCDOM por meio da aplicação de um modelo bio-óptico em imagens TM/Landsat-5 de 1995 a 2010, e (iv) a análise das fontes possíveis de CDOM/DOM , assim como do comportamento/distribuição do aCDOM no FHR ao longo do tempo. Assim, o primeiro estudo desenvolvido nesta pesquisa foi o da parametrização do algoritmo maquinas de vetores de suporte (SVM) de acordo com as características da área de estudo para classificação supervisionada de LULC na bacia de contribuição do FHR. A detecção de mudança da classificação obtida para LULC demonstrou que a parametrização proposta para o SVM tornou o algoritmo capaz de diferenciar classes grandes e contínuas, classes estreitas e alongadas, além de áreas não contínuas e pequenas localizadas dentro de outra classe maior. A classificação obtida para o SVM apresentou boa avaliação estatística, com acurácia geral entre 86% e 96% para toda a série temporal, acurácia do produtor de 90%, acurácia do usuário maior do que 86% e índice Kappa entre 86% e 91%. Ainda, foi observado que o LULC desenvolvido na área de estudo se manteve relativamente estável ao longo da série histórica analisada. O segundo estudo realizado proporcionou o desenvolvimento de um modelo empírico em um comprimento de onda (485 nm) e uma razão de bandas (B4/B1) alternativos para estimativa de aCDOM via Rra_simulated para o TM/Landsat-5 (RMSE = 7%, Nash = 0.91). Este modelo também pôde identificar mesmo pequenas variações nos valores de reflectância via dados orbitais, assim como pode diferenciar variações sutis no aCDOM. Ainda, foram identificados dois padrões de comportamento da CDOM para o FHR: um associado ao LULC e à ocorrência de chuva/lixiviação, bem como outro relacionado à Clorofila-a (Chl-a) em situações de floração de algas. Os referidos estudos que compõe esta pesquisa foram padronizados como artigos científicos para a confecção deste documento. O primeiro estudo, sobre a parametrização do SVM, foi publicado na revista Modelling Earth Systems Environment – Springer (DOI 10.1007/s40808-016-0190-y). O segundo estudo, sobre a distribuição histórica do aCDOM está na etapa de revisão para futura submissão. The dissolved organic matter (DOM) is a water compound related to water quality, since it has two sources: one allochthonous, related to terrestrial discharges that can be linked to humic acids, and another autochthonous, associated with river input and itself production, so related to or fulvic acids. The colored dissolved organic carbon (CDOM) is the colored fraction of DOM that could be used as a proxy for its occurrence in inland waters. The Funil hydroelectric reservoir (FHR) was chosen as the study site for this work. In this context, the general aim of this research was to identify and to evaluate the changes in CDOM absorption coefficient (aCDOM) at the water surface over time (1995 – 2010), and to understand its relationship with land cover land use (LULC) changes in FHR watershed. For match this goal, (i) a LULC historical mapping (1995 – 2010, with 5 years of interval) was made to change detection, (ii) a bio-optical model set and a new model were studied in order to estimate aCDOM from simulated reflectance (Rrs_simulated) for Thematic Mapper (TM) sensor, (iii) a aCDOM spatial and temporal distribution was obtained by applying a bio-optical model in TM/Landsat-5 imagery from 1995 to 2010, and (iv) the possible CDOM/DOM sources in FHR were found, as well aCDOM historical behavior/distribution over time was analysed. Thus, the first study was the support vector machine algorithm (SVM) parameterization according to study area characteristics to LULC supervised classification in FHR watershed. The obtained LULC change detection analysis demonstrates that the proposed SVM parameterization made the algorithm able to differentiate large and continuous classes, lengthy and thin areas, and non-continuous small areas located inside wide classes. The obtained classification had great statistics with overall accuracy among 86% and 98% over the time series, the producer accuracy of 90%, the user accuracy higher than 86%, and the Kappa statistics ranged from 86% to 91%. In addition, no significant changes in LULC were identified in the study site over all time series. The second study provides a bio-optical model at alternatives wavelength (485 nm) and a band ratio (B4/B1) for aCDOM estimation using simulated Rrs for TM/Landsat-5 (RMSE = 7%, Nash = 0.91). This model could identify even small variations in reflectance values from orbital data, as well as differentiate even slight alterations in aCDOM. Two significantly different aCDOM behaviors were also identified for FHR: one associated with LULC and rainfall/runoff occurrence, and other correlated to Chlorophyll-a high concentrations (Chl-a) in algal blooms situations. The referred studies that compose this research ware standardized as academic articles in this document. The first study, about SVM parameterization, was published yet in Modeling Earth Systems Environment – Springer (DOI 10.1007/s40808-016-0190-y). The second study, about aCDOM historical distribution is in the revision step to future submission.

Chlorophyll-a (chl-a) is a central water quality parameter that has been estimated through remote sensing bio-optical models. This work evaluated the performance of three well established reflectance based bio-optical algorithms to retrieve chl-a from in situ hyperspectral remote sensing reflectance datasets collected during three field campaigns in the Funil reservoir (Rio de Janeiro, Brazil). A Monte Carlo simulation was applied for all the algorithms to achieve the best calibration. The Normalized Difference Chlorophyll Index (NDCI) got the lowest error (17.85%). The in situ hyperspectral dataset was used to simulate the Ocean Land Color Instrument (OLCI) spectral bands by applying its spectral response function. Therefore, we evaluated its applicability to monitor water quality in tropical turbid inland waters using algorithms developed for MEdium Resolution Imaging Spectrometer (MERIS) data. The application of OLCI simulated spectral bands to the algorithms generated results similar to the in situ hyperspectral: an error of 17.64% was found for NDCI. Thus, OLCI data will be suitable for inland water quality monitoring using MERIS reflectance based bio-optical algorithms.

Ocean color algorithms have been successfully developed to estimate chlorophyll a and total suspended solids concentrations in coastal and estuarine waters but few have been created to estimate light absorption due to colored dissolved inorganic matter (CDOM) and salinity from the spectral signatures of these waters. In this study, we used remotely sensed reflectances in the red and blue-green portions of the visible spectrum retrieved from Medium Resolution Imaging Spectrometer (MERIS) and the International Space Station (ISS) Hyperspectral Imager for the Coastal Ocean (HICO) images to create a model to estimate CDOM absorption. CDOM absorption results were then used to develop an algorithm to predict the surface salinities of coastal bays and estuaries in New England, Middle Atlantic, and Gulf of Mexico regions. Algorithm-derived CDOM absorptions and salinities were successfully validated using laboratory measured absorption values over magnitudes of ~0.1 to 7.0 m−1 and field collected CTD data from oligohaline to polyhaline (S less than 5 to 18–30) environments in Narragansett Bay (Rhode Island); the Neuse River Estuary (North Carolina); Pensacola Bay (Florida); Choctawhatchee Bay (Florida); St. Andrews Bay (Florida); St. Joseph Bay (Florida); and inner continental shelf waters of the Gulf of Mexico.

The aim of the study is to test the suitability of Sentinel-2 MSI for mapping phytoplankton in turbid extremely productive inland waters with recurrent cyanobacterial bloom that represent a major concern. These blooms can have an influence on health care costs, on the costs associated with the treatment of water intended for human consumption and on the tourism business. The study sites investigated in this work include the three lakes of Mantua (Italy), a system of fluvial lakes characterised by a patchy distribution of phytoplankton. These shallow, nutrient-enriched and turbid waters host different primary producers and undergo pronounced discharge variations. The other site is the Curonian lagoon (Lithuania and Russian Federation) and with a surface of 1584 km2 is largest lagoon of Europe. It is also very shallow with waters readily mixed by wind action, although weak stratification can occur temporarily during the summer. The system is also highly eutrophic due to external nutrient loads from the tributary Nemunas River. The presence of cyanobacterial toxic metabolites, is a major concern for water quality and human health in the region. The study areas are part of two research projects (FP-7 INFORM (copernicus-inform.eu) and BLASCO (projectblasco.it)) which have been supporting field activities in the last three years gathering fundamental data for evaluating Sentinel-2 data. Five days match-ups with satellite acquisitions resulted available for evaluating satellite products in terms of concentrations of chlorophyll-a (chl-a), as proxy of phytoplankton. Field measurements include aquatic optical properties and limnological data that allowed the development of semi-empirical adaptive algorithms and of spectral inversion techniques of bio-optical modelling to retrieve chl-a. Depending on water leaving reflectance the approaches were integrated because bio-optical modelling inversion performed better for lower chl-a concentrations (

Quantifying Colored Detrital Matter (CDM) from satellite observations can improve our knowledge of carbon dynamics in coastal areas and the open oceans. Several bio-optical inversion models have been developed for this purpose. However, care must be taken when they are applied to waters where optical properties significantly differ from model assumptions, which is the case in the Mediterranean Sea. Algorithm testing and validation are thus required before routine use. Here, in situ radiometric measurements collected in the NW Mediterranean Sea (BOUSSOLE site) are used to evaluate three bio-optical inversion models that retrieve the CDM light absorption coefficients at 443 nm (a(cdm)(443)). Although all methods reproduced the CDM seasonal cycles at the surface, comparisons of predicted and in situ acdm(443) coefficients showed that the Quasi-Analytical Algorithm version 6 (QAAv6) and a locally-adapted version of the Garver-Siegel-Maritorena model (GSM-Med) were the two best algorithms. Applying these two models to SeaWiFS remote sensing reflectances, collected between 2003 and 2010, reproduced with good accuracy the acdm(443) coefficients retrieved from field radiometric measurements at the BOUSSOLE site, with seasonal patterns consistent with previous observations. Finally, bio-optical relationships derived from satellite-retrieved a(cdm)(443) and chlorophyll values confirmed the higher-than-average CDM contribution for a given chlorophyll concentration in the Mediterranean Sea as compared to many oceanic regions. (C) 2016 Elsevier Inc. All rights reserved.

Made available in DSpace on 2018-11-26T17:55:16Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-09-04 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Several quasi-analytical algorithm (QAA) versions were developed to make it suitable for different inland water systems. QAA(BBHR) and QAA(OMW) were reparameterized based on two reservoirs from the Tiete River cascading system (Sao Paulo State, Brazil), which present widely differing compositions. Considering the purpose of monitoring the entire cascade through a unique QAA version, we aimed to assess the suitability of these two QAA versions and, in addition, another two QAA native forms (versions 5 and 6), for retrieving inherent optical properties (IOPs) in Ibitinga hydroelectric reservoir (IHR), situated in the same cascading system. In addition to that, we addressed bio-optical characterization of IHR, using spectral and water quality data collected in a field campaign conducted in July 2016. Wide spatial variability of optically significant constituent (OSC) in IHR and colored dissolved organic matter predominance in its absorption budget was observed. None of the tested QAA versions were completely suitable in retrieving absorption coefficients for IHR in all wavelengths. However, results for wavelengths commonly used as proxy for OSC concentration retrieval were satisfactory in some of the models. Therefore, the results obtained in this study shows that QAAs versions can be used for specific purposes (e.g., chlorophyll-a mapping), by employing the best model for IOPs retrieval at a specific wavelength. This highlights the challenge of copying with high optical variability in cascading systems. In this sense, further research is necessary, for either achieving a QAA reparameterized version appropriate for aquatic systems with widely differing optical properties or another analytical scheme. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) Sao Paulo State Univ, Dept Cartog, Presidente Prudente, Brazil Sao Paulo State Univ, Dept Environm Engn, Sao Jose Dos Campos, Brazil Natl Inst Space Res, Remote Sensing Div, Sao Jose Dos Campos, Brazil Sao Paulo State Univ, Dept Cartog, Presidente Prudente, Brazil Sao Paulo State Univ, Dept Environm Engn, Sao Jose Dos Campos, Brazil FAPESP: 2012/19821-1 FAPESP: 2015/21586-9

Semi-analytical models for remote sensing of water quality parameters need to be parameterized with specific inherent optical properties. In this thesis, data on specific inherent optical properties of Swedish lakes and coastal waters is presented. Also, the problems of measuring in situ spectral backscattering are addressed. It is shown how measured specific inherent optical properties are used to parameterize semi-analytical bio-optical models. The models are then used to produce large synthetic data sets based on the distribution of water quality parameters, and from these data sets, band ratio or single band ratio algorithms for remote estimation of water quality parameters are constructed. A similar model was also used to calculate under water PAR from measured water quality parameters. The specific inherent optical properties of Swedish lakes and coastal waters are very similar to earlier reported data from the oceanic environment. However, different relations of the water quality parameters will affect the inherent optical properties absorption and backscattering. The absorption spectra are dominated by yellow substance with terrestrial origin. Phytoplankton absorption is low, and account in general only for about 10 % of the total absorption in regions where phytoplankton pigments are active. The spectral backscattering is dominated by suspended particulate inorganic matter. Phytoplankton backscattering is almost negligible, except in cases where the phytoplankton community is dominated by highly scattering cyanobacteria. Experiences from remote sensing campaigns and modeling shows that remote chlorophyll estimation is most effective at longer wavelengths, where the absorption of yellow substance is low. However, modeling also predicts that large uncertainties have to be expected in the estimation of chlorophyll, both from variation in the specific phytoplankton absorption and from influences of other optically active water quality parameters.