Publicações

@article{Martins2016,
title = {Support Vector Machine algorithm optimal parameterization for change detection mapping in Funil Hydroelectric Reservoir (Rio de Janeiro State, Brazil)},
author = {Sarah Cristina Araujo Martins and Nariane Marselhe Ribeiro Bernardo and Igor Ogashawara and Enner Herenio de Alcântara},
doi = {10.1007/s40808-016-0190-y},
issn = {2363-6211},
year = {2016},
date = {2016-07-21},
journal = {Modeling Earth Systems and Environment},
volume = {2},
number = {3},
pages = {138},
abstract = {Change detection in Land Use and Land Cover (LULC) using Support Vector Machines (SVM) to mapping a geographic area is a way that has been studded and improved because of its advantages as low costs in terms of computing, field research and staff team. To use SVM, it is needed firstly to define the most efficient function to be used (linear, polynomial, and radial base function---RBF) and secondly to establish the most appropriate input parameters of them, based on the study area, which was the main challenge of using SVM algorithm. The main goal of this work was to test the performance of polynomial function and RBF, and to identify which input parameters combination are the best to use SVM algorithm for Funil Hydroelectric Reservoir (FHR) sub-watershed LULC mapping, using TM/Landsat-5 time-series images. After several tests and based on the obtained results, the RBF was identified as the best SVM's function, which was used to classify the time-series images. The referred SVM function has the following parameters to be defined: the error tolerance (ξ or C), the pyramid depths (P), the radial basis function parameter (γ), and the threshold. The most effective combination of input parameters to RBF was C = 100; P = 2, γ = 0.1},
keywords = {algorithm, change detection, Funil, parametrization, reservoir, Rio de Janeiro, Support vector machine, SVM},
pubstate = {published},
tppubtype = {article}
}

@article{doi:10.1080/01431161.2016.1204027,
title = {Analyzing the status of submerged aquatic vegetation using novel optical parameters},
author = {Luiz Henrique da Silva Rotta and Deepak R Mishra and Enner Herenio de Alcântara and Nilton Nobuhiro Imai},
doi = {10.1080/01431161.2016.1204027},
year = {2016},
date = {2016-01-01},
journal = {International Journal of Remote Sensing},
volume = {37},
number = {16},
pages = {3786--3810},
abstract = {ABSTRACTThe reservoirs constructed throughout Brazil for electrical power generation following its industrial and socioeconomic development now favour abundant aquatic macrophyte growth. Nova Avanhandava Reservoir is fully inhabited by submerged aquatic vegetation (SAV) that poses serious ecological and economic threats. The overall goal of this study was to assess the radiation availability in the water column in the Nova Avanhandava Reservoir and analyse its influence on SAV development and growth. In addition to the diffuse attenuation coefficient (Kd) and euphotic zone depth (ZEZ), optical parameters such as percentage light through the water (PLW) were computed and analysed to achieve the objective. Nineteen sampling locations were considered for both spectroradiometer measurements and water sampling for analytical determination of total suspended solids (TSS) and chlorophyll-a concentration. Depth, SAV height, and precise position were also collected through hydro-acoustic measurements. The upstream region showed the highest TSS and Kd levels compared to the downstream. SAV heights were found to be lower upstream compared to downstream. The growth of tall SAV was favoured by low PLW, which grew taller to intercept required radiation. Locations with high transparency (lower Kd) also favoured the development of tall SAV compared to areas of high Kd. This may mean that low PLW values favour tall SAV growth if Kd is low enough not to hinder this. An inverse relationship between SAV height and attenuation of photosynthetic active radiation (Kd,PAR) was observed with a coefficient of determination of R2 = 0.56 (p < 0.001), demonstrating that SAV height can be estimated using Kd,PAR with significant accuracy.},
keywords = {optical, parametrization, Submerged aquatic vegetation, water},
pubstate = {published},
tppubtype = {article}
}

@article{WATANABE201628,
title = {Parametrization and calibration of a quasi-analytical algorithm for tropical eutrophic waters},
author = {Fernanda Sayuri Yoshino Watanabe and Deepak R Mishra and Ike Astuti and Thanan Walesza Pequeno Rodrigues and Enner Herenio de Alcântara and Nilton Nobuhiro Imai and Cláudio Barbosa},
doi = {10.1016/j.isprsjprs.2016.08.009},
issn = {0924-2716},
year = {2016},
date = {2016-01-01},
journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
volume = {121},
pages = {28--47},
abstract = {Quasi-analytical algorithm (QAA) was designed to derive the inherent optical properties (IOPs) of water bodies from above-surface remote sensing reflectance (Rrs). Several variants of QAA have been developed for environments with different bio-optical characteristics. However, most variants of QAA suffer from moderate to high negative IOP prediction when applied to tropical eutrophic waters. This research is aimed at parametrizing a QAA for tropical eutrophic water dominated by cyanobacteria. The alterations proposed in the algorithm yielded accurate absorption coefficients and chlorophyll-a (Chl-a) concentration. The main changes accomplished were the selection of wavelengths representative of the optically relevant constituents (ORCs) and calibration of values directly associated with the pigments and detritus plus colored dissolved organic material (CDM) absorption coefficients. The re-parametrized QAA eliminated the retrieval of negative values, commonly identified in other variants of QAA. The calibrated model generated a normalized root mean square error (NRMSE) of 21.88},
keywords = {algorithm, calibration, parametrization, quasi-analytical, 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}
}