Publicações

@article{Alcântara2017,
title = {Regional-scale algorithm to estimate the particulate organic carbon (POC) in inland waters using Landsat-5/TM images},
author = {Enner Herenio de Alcântara},
doi = {10.1007/s40808-017-0314-z},
issn = {2363-6211},
year = {2017},
date = {2017-06-01},
journal = {Modeling Earth Systems and Environment},
volume = {3},
number = {2},
pages = {831--837},
abstract = {A regional-scale algorithm was developed in order to test if the Landsat-5/TM can be used to estimate the particulate organic carbon (POC) in oligotrophic-to-mesotrophic inland water. To develop the POC algorithm two fieldworks were conducted, the first in May and the second in September 2009. The algorithm was calibrated using the dataset from September and validated using the dataset from May. The results showed that the best calibration was obtained using a polynomial fitting function (R2 of 0.80, p<0.0001). This model was validated with a normalized root mean square error (NRMSE) of 6.21%. The algorithm was then applied in two Landsat-5/TM images from April and July 2009. The spatial distribution of POC obtained from the satellite images reveals a strong dependence of POC concentrations with the weather conditions. These results allowed us to conclude that there is a great potential to study the temporal dynamics of POC in inland waters using Landsat-5/TM images.},
keywords = {algorithm, inland water, landsat, particulate organic carbon, poc},
pubstate = {published},
tppubtype = {article}
}

@article{Bernardo2017,
title = {Comparing proximal remote sensing and orbital images to estimate the total suspended matter in inland water},
author = {Nariane Marselhe Ribeiro Bernardo and Enner Herenio de Alcântara},
doi = {10.1007/s40808-017-0285-0},
issn = {2363-6211},
year = {2017},
date = {2017-02-23},
journal = {Modeling Earth Systems and Environment},
volume = {3},
number = {1},
pages = {19},
abstract = {The main purpose of this work was to improve the remote sensing reflectance (R rs ) applications to estimate the total suspended matter (TSM) concentrations, since several studies using R rs retrieved from atmospherically corrected images did not match with in situ radiometric measurements. The goal was achieved by comparing two R rs datasets: one from atmospherically corrected image from Operational Land Imager (OLI)/ Landsat-8 and the R rs surface created by non-deterministic statistical approach. The R rs used to create the surface was computed by using samples gathered out in situ on 13--16 October 2014, and the OLI image used was taken in the first day of fieldwork. A reference surface from in situ TSM concentrations was also created to compare the estimates from both datasets (from statistical approach and image atmospherically corrected). The TSM estimates were made using empirical model, and the results demonstrate that non-statistical methods provide lowest errors to estimate the TSM concentration if compared to atmospheric corrected images.},
keywords = {inland water, orbital images, proximal remote sensing, total suspended matter},
pubstate = {published},
tppubtype = {article}
}

@article{BERNARDO20172335,
title = {Atmospheric correction issues for retrieving total suspended matter concentrations in inland waters using OLI/Landsat-8 image},
author = {Nariane Marselhe Ribeiro Bernardo and Fernanda Sayuri Yoshino Watanabe and Thanan Walesza Pequeno Rodrigues and Enner Herenio de Alcântara},
doi = {10.1016/j.asr.2017.02.017},
issn = {0273-1177},
year = {2017},
date = {2017-01-01},
journal = {Advances in Space Research},
volume = {59},
number = {9},
pages = {2335--2348},
abstract = {The atmospheric effects that influence on the signal registered by remote sensors might be minimized in order to provide reliable spectral information. In aquatic systems, the application of atmospheric correction aims to minimize such effects and avoid the under or overestimation of remote sensing reflectance (Rrs). Accurately Rrs provides better information about the state of aquatic system, it means, establishing the concentration of aquatic compounds more precisely. The aim of this study is to evaluate the outputs from several atmospheric correction methods (Dark Object Subtraction -- DOS; Quick Atmospheric Correction -- QUAC; Fast Line-of-sight Atmospheric Analysis of Hypercubes -- FLAASH; Atmospheric Correction for OLI `lite' -- ACOLITE, and Provisional Landsat-8 Surface Reflectance Algorithm -- L8SR) in order to investigate the suitability of Rrs for estimating total suspended matter concentrations (TSM) in the Barra Bonita Hydroelectrical Reservoir. To establish TSM concentrations via atmospherically corrected Operational Land Imager (OLI) scene, the TSM retrieval model was calibrated and validated with in situ data. Thereby, the achieved results from TSM retrieval model application demonstrated that L8SR is able to provide the most suitable Rrs values for green and red spectral bands, and consequently, the lowest TSM retrieval errors (Mean Absolute Percentage Error about 10},
keywords = {atmospheric correction, inland water, landsat, total suspended matter},
pubstate = {published},
tppubtype = {article}
}

@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}
}

@article{doi:10.1080/2150704X.2016.1177242,
title = {Estimating the CDOM absorption coefficient in tropical inland waters using OLI/Landsat-8 images},
author = {Enner Herenio de Alcântara and Nariane Marselhe Ribeiro Bernardo and Fernanda Sayuri Yoshino Watanabe and Thanan Walesza Pequeno Rodrigues and Luiz Henrique da Silva Rotta and Alisson Fernando Coelho do Carmo and Milton Hirokazu Shimabukuro and Stela Rosa Amaral Gonçalves and Nilton Nobuhiro Imai},
doi = {10.1080/2150704X.2016.1177242},
year = {2016},
date = {2016-01-01},
journal = {Remote Sensing Letters},
volume = {7},
number = {7},
pages = {661--670},
abstract = {ABSTRACTColoured dissolved organic matter (CDOM) is the most abundant dissolved organic matter (DOM) in many natural waters and can affect the water quality, such as the light penetration and the thermal properties of water system. So the objective of this letter was to estimate the CDOM absorption coefficient at 440 nm, aCDOM(440), in Barra Bonita Reservoir (São Paulo State, Brazil) using operational land imager (OLI)/Landsat-8 images. For this two field campaigns were conducted in May and October 2014. During the field campaigns remote sensing reflectance (Rrs) were measured using a TriOS hyperspectral radiometer. Water samples were collected and analysed to obtain the aCDOM(440). To predict the aCDOM(440) from Rrs at two key wavelengths (650 and 480 nm) were regressed against laboratory-derived aCDOM(440) values. The validation using in situ data of aCDOM(440) algorithm indicated a goodness of fit},
keywords = {absorption, cdom, coefficient, imagens, inland water, landsat, tropical reservoir},
pubstate = {published},
tppubtype = {article}
}

@article{OGASHAWARA2016128,
title = {Re-parameterization of a quasi-analytical algorithm for colored dissolved organic matter dominant inland waters},
author = {Igor Ogashawara and Deepak R Mishra and Renata F F Nascimento and Enner Herenio de Alcântara and Milton Kampel and Jose L Stech},
doi = {10.1016/j.jag.2016.09.001},
issn = {0303-2434},
year = {2016},
date = {2016-01-01},
journal = {International Journal of Applied Earth Observation and Geoinformation},
volume = {53},
pages = {128--145},
abstract = {Quasi-Analytical Algorithms (QAAs) are based on radiative transfer equations and have been used to derive inherent optical properties (IOPs) from the above surface remote sensing reflectance (Rrs) in aquatic systems in which phytoplankton is the dominant optically active constituents (OACs). However, Colored Dissolved Organic Matter (CDOM) and Non Algal Particles (NAP) can also be dominant OACs in water bodies and till now a QAA has not been parametrized for these aquatic systems. In this study, we compared the performance of three widely used QAAs in two CDOM dominated aquatic systems which were unsuccessful in retrieving the spectral shape of IOPS and produced minimum errors of 350},
keywords = {algorithm, cdom, inland water, parametrization, quasi-analytical},
pubstate = {published},
tppubtype = {article}
}

@article{CICERELLI2015,
title = {Sensoriamento remoto multifonte aplicado na detecção do fitoplâncton em Águas interiores},
author = {Rejane E Cicerelli and Maria de Lourdes Bueno Trindade Galo},
issn = {1415-4366},
year = {2015},
date = {2015-03-01},
journal = {Revista Brasileira de Engenharia AgrÃcola e Ambiental},
volume = {19},
pages = {259--265},
publisher = {scielo},
keywords = {detecção fitoplâncton, inland water, phytoplankton, remote sensing, Sensoriamento Remoto},
pubstate = {published},
tppubtype = {article}
}

@article{isprs-archives-XL-7-W3-1439-2015,
title = {Brazilian inland water bio-optical dataset to support carbon budget studies in reservoirs as well as anthropogenic impacts in Amazon floodplain lakes: Preliminary results},
author = {C Barbosa and E Novo and R Ferreira and L Carvalho and C Cairo and F Lopes and J Stech and Enner Herenio de Alcântara},
doi = {10.5194/isprsarchives-XL-7-W3-1439-2015},
year = {2015},
date = {2015-01-01},
journal = {ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
volume = {XL-7/W3},
pages = {1439--1446},
keywords = {amazon, anthropogenic impacts, bio-optical, carbon budget, datasets, floodplain, inland water, lakes},
pubstate = {published},
tppubtype = {article}
}