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| SÁ, M. A. C. de; SHIRATSUCHI, L. S.; FRANZ, C. A. B.; SANTOS JÚNIOR, J. de D. G. dos. |
| RESUMO: A compactação do solo foi avaliada e correlacionada com a produtividade de soja irrigada (safra 2006) sob plantio direto em dois solos: Latossolo Vermelho Amarelo textura média (LV) e Neossolo Quartzarênico (RQ) na região de Luis Eduardo Magalhães, Bahia, Brasil. Ensaios de campo e laboratório para determinação do Índice de Cone (IC) foram conduzidos, sendo ajustados modelos de IC em função de (conteúdo de água volumétrico), Ds (densidade do solo) e argila. Ensaios de laboratório proporcionaram modelos com R2 mais elevados. Para caracterização da compactação do solo com base no IC, é importante estabelecer as relações matemáticas entre IC e atributos do solo, como Ds e teor de argila. Tanto o LV quanto o RQ sob Cerrado apresentaram valores mais... |
| Tipo: Folhetos |
Palavras-chave: Índice de cone; Soil mechanical resistance; Soil mapping; Agricultura de Precisão; Compactação do Solo; Glycine Max; Mapa; Manejo do Solo; Soja; Precision agriculture; Soybeans; Soil management. |
| Ano: 2007 |
URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/572302 |
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| Sarmento,Eliana Casco; Giasson,Elvio; Weber,Eliseu; Flores,Carlos Alberto; Hasenack,Heinrich. |
| The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Appellation of origin; Decision tree; Digital elevation model; Geographic information systems; Neural network; Soil mapping. |
| Ano: 2012 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2012000900025 |
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| Moura-Bueno,Jean Michel; Dalmolin,Ricardo Simão Diniz; ten Caten,Alexandre; Ruiz,Luis Fernando Chimelo; Ramos,Priscila Vogelei; Dotto,André Carnieletto. |
| ABSTRACT Terrain attributes (TAs) derived from digital elevation models (DEMs) are frequently used in digital soil mapping (DSM) as auxiliary covariates in the construction of prediction models. The DEMs and information extracted from it may be limited with regard to the spatial resolution and error magnitude, and can differ in the behavior of terrain features. The objective of this study was to evaluate the quality and limitations of free DEM data and to evaluate a topographic survey (TS) underlying the choice of a more appropriate model, for use in DSMs at a scale of 1:10,000. The study was conducted in an area of 937 ha in the watershed of Lajeado Giruá, in southern Brazil. The DEMs: DEM-TS, DEM-Topographic Map (TM), DEM-ASTER, DEM-SRTM, and... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Terrain modeling; DEM quality; DEM scale; Terrain attributes; Soil mapping. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832016000100304 |
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