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| Meier,Martin; Souza,Eliana de; Francelino,Marcio Rocha; Fernandes Filho,Elpídio Inácio; Schaefer,Carlos Ernesto Gonçalves Reynaud. |
| ABSTRACT: Increasingly, applications of machine learning techniques for digital soil mapping (DSM) are being used for different soil mapping purposes. Considering the variety of models available, it is important to know their performance in relation to soil data and environmental variables involved in soil mapping. This paper investigated the performance of eight machine learning algorithms for soil mapping in a tropical mountainous area of an official rural settlement in the Zona da Mata region in Brazil. Morphometric maps generated from a digital elevation model, together with Landsat-8 satellite imagery, and climatic maps, were among the set of covariates to be selected by the Recursive Feature Elimination algorithm to predict soil types using machine... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil classification; Machine learning; Pedometrics; Land use planning; Agrarian reform. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832018000100313 |
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| Melo,Valdinar Ferreira; Francelino,Marcio Rocha; Uchôa,Sandra Cátia Pereira; Salamene,Samara; Santos,Célida Socorro Vieira dos. |
| Em Roraima, a distribuição espacial das populações indígenas identifica um cenário de busca constante de solos capazes de sustentar uma agricultura itinerante. Este trabalho teve como objetivo estabelecer relação entre a compreensão dos solos por parte dos Yanomami da região do médio Catrimani e o Sistema Brasileiro de Classificação de Solos, bem como avaliar o seu tipo de uso em função de análises químicas para diagnóstico da fertilidade do solo. O trabalho foi executado em duas etapas. A primeira consistiu em visitas a oito malocas para estudar os solos. Foram coletadas amostras em trincheiras até 1,50 m de profundidade para análise e classificação dos solos e (em prospecções com o trado) nas profundidades de 0-10 a 10-30 cm, em 21 tipos de uso agrícola,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Etnopedologia; Solos; Agricultura; Índio; Amazônia; Brasil. |
| Ano: 2010 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832010000200022 |
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| Moraes,André Geraldo de Lima; Francelino,Marcio Rocha; Carvalho Junior,Waldir de; Pereira,Marcos Gervasio; Thomazini,André; Schaefer,Carlos Ernesto Gonçalves Reynaud. |
| ABSTRACT: The pattern of variation in soil and landform properties in relation to environmental covariates are closely related to soil type distribution. The aim of this study was to apply digital soil mapping techniques to analysis of the pattern of soil property variation in relation to environmental covariates under periglacial conditions at Keller Peninsula, Maritime Antarctica. We considered the hypothesis that covariates normally used for environmental correlation elsewhere can be adequately employed in periglacial areas in Maritime Antarctica. For that purpose, 138 soil samples from 47 soil sites were collected for analysis of soil chemical and physical properties. We tested the correlation between soil properties (clay, potassium, sand, organic... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Kriging; Geostatistical methods; Soil variability. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832017000100316 |
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| CarvalhoJunior,Waldir de; Chagas,César da Silva; FernandesFilho,Elpídio Inácio; Vieira,Carlos Antonio Oliveira; Schaefer,Carlos Ernesto Gonçalves; Bhering,Silvio Barge; Francelino,Marcio Rocha. |
| Geomorphometric variables are applied in digital soil mapping because of their strong correlation with the disposition and distribution of pedological components of the landscapes. In this research, the relationship between environmental components of tropical hillslope areas in the Rio de Janeiro State, Brazil, artificial neural networks (ANN), and maximum likelihood algorithm (MaxLike) were evaluated with the aid of geoprocessing techniques. ANN and MaxLike were applied to soilscape mapping and the results were compared to the original map. The ANN architectures with seven and five neurons in the hidden layer produced the best classifications when using samples obtained systematically. When random samples were applied, the best neural net architectures... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Geomorphometric attribute; Digital soil mapping; Digital elevation model. |
| Ano: 2011 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162011000600014 |
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| Machado,Roriz Luciano; Ceddia,Marcos Bacis; Carvalho,Daniel Fonseca de; Cruz,Eleandro Silva da; Francelino,Marcio Rocha. |
| Knowledge of maximum daily rain and its return period in a region is an important tool to soil conservation, hydraulic engineering and preservation of road projects. The objective of this work was to evaluate the spatial variability of maximum annual daily rain considering different return periods, at the Rio de Janeiro State. The data set was composed by historical series of 119 rain gauges, for 36 years of observation. The return periods, estimated by Gumbel distribution, were 2, 5, 10, 25, 50 and 100 years. The spatial variability of the return periods was evaluated by semivariograms. All the return periods presented spatial dependence, with exponential and spherical model fitted to the experimental semivariograms. The parameters of the fitted... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Runoff; Extreme rainfall; Geostatistics; Kriging. |
| Ano: 2010 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052010000500009 |
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