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| Souza,Carlos H. Wachholz de; Mercante,Erivelto; Prudente,Victor H. R.; Justina,Diego D.D.. |
| C.H.W Souza, E. Mercante, V.H.R. Prudente and D.D.D. Justina. 2013. Methods of performance evaluation for the supervised classification of satellite imagery in determining land cover classes. Cien. Inv. Agr. 40(2): 419-428. Satellite imagery, in combination with remote sensing techniques, provides a new opportunity for monitoring and assessing crops with lower cost and greater objectivity than traditional surveys. The present research employed Landsat 5/TM satellite imagery to identify the land cover classes in Cafelândia (Paraná, Brasil), a predominantly agricultural town. Five supervised classification methods (parallelepiped (PL), minimum distance (MND), Mahalanobis distance (MHD), maximum likelihood classifier (MLC) and spectral angle mapper (SAM))... |
| Tipo: Journal article |
Palavras-chave: Accuracy indices; Agricultural landscape; Classifiers; Remote sensing. |
| Ano: 2013 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202013000200016 |
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| Prudente,Victor H. R.; Silva,Bruno B. da; Johann,Jerry A.; Mercante,Erivelto; Oldoni,Lucas V.. |
| ABSTRACT: The traditional per-pixel classification methods consider only spectral information, and may be limited. Object-based classifiers, however, also consider shape and texture, firstly segmenting the image, and then classifying individual objects. Thus, a Geographic Object-Based Image Analysis (GEOBIA) was compared in conjunction with data mining techniques and a traditional per-pixel method. A cut of Landsat-8, bands 2 to 7, orbit/point 223/77, located between the municipalities of Cascavel, Corbélia, Cafelândia and Tupãssi, in the west part of the state of Paraná, from 12/18/2013 was used. In the GEOBIA approach was realized image segmentation, spatial and spectral attribute extraction, and classification using the decision tree supervised... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: GeoDMA; Data mining; Decision tree. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000501015 |
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| Wrublack,Suzana C.; Mercante,Erivelto; Boas,Marcio A. Vilas; Prudente,Victor H. R.; Silva,Jefferson L. G.. |
| ABSTRACT This study demonstrates using remote sensing, geographic information systems and multivariate statistics to study water quality in an agricultural watershed. The monitoring of water quality in the watershed of Lontras's river in the southwestern region of the State of Paraná had been done in 2012 and 2013 with a multi-parameter probe in ten sites that were defined upstream and downstream watershed, during four different seasons. Mosaicked images were used from Google Earth, Digital Elevation Model and soil types of maps, defined as the explanatory variables. The definition of the areas of influence and multivariate statistical techniques, particularly the Redundancy Analysis (RDA), were used for the correlation between variables. In a spring area,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Geoprocessing; Mapping land use and occupation; Water quality. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100074 |
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| Prudente,Victor H. R.; Souza,Carlos H. W. de; Mercante,Erivelto; Johann,Jerry A.; Uribe-Opazo,Miguel A.. |
| In the current study, we performed a soybean production spatial distribution analysis in Paraná State. Seven crop-year data, from 2003-04 to 2009-10, obtained from the Paraná Department of Agriculture and Supply (SEAB) were used to develop a Boxmap for each crop-year, show soybean production throughout this time interval. Moran's index was used to measure spatial autocorrelation among municipalities at an aggregate level, while LISA index local correlation. For each index, different contiguity matrix and order were used and there was a significance level study. As a result, we have showed spatial relationship among cities regarding the production, which allowed the indication of high and low production clusters. Finally, identifying main soybean-producing... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Spatial correlation; Moran's Index; LISA index. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162014000400015 |
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| Remor,Marcelo B.; Sampaio,Silvio C.; Model,Kathleen J.; Falco,Thais D.; Prudente,Victor H. R.. |
| ABSTRACT Many studies have determined the concentration of trace elements in river sediments in Brazil. Notwithstanding, mercury assessments are scarce, especially because of exclusive extraction techniques and expensive analysis techniques. Still, this element is known for its toxicity, persistence, and bioaccumulation, making its presence in the environment an important factor for biota and human health. For this reason, the objective of this study was to determine the mercury concentration in the sediment of the Pelotas River basin, located on the border of the states of Santa Catarina and Rio Grande do Sul. The sediment was collected at eight locations of the Pelotas basin and, after drying, the mercury was quantified by atomic absorption spectrometry... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Heavy metal; Trace element; Multivariate statistics. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100117 |
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