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| Dalmolin,Ricardo Simão Diniz; Moura-Bueno,Jean Michel; Samuel-Rosa,Alessandro; Flores,Carlos Alberto. |
| ABSTRACT The use of new technologies, the development of new software, and the advances in the machines ability to process data have brought a new perspective to soil science and especially to pedology, with the advent of digital soil mapping (DSM). To meet the demand for soil surveys in Brazil, it will be necessary to popularize the techniques used in DSM. To identify and map the soil to generate maps of land use capability, we proposed a theoretical and practical course focused on the training in DSM for professionals involved in the management of land resources. The methodology was divided into five modules: I. Introduction to pedology, soil-landscape relationship, soil survey and soil classification (theory); II. Identification of soils in the field... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Expert knowledge; Pedometry; PronaSolos; Soil education; Soil survey. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832020000100600 |
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| Moura-Bueno,Jean Michel; Dalmolin,Ricardo Simão Diniz; Horst-Heinen,Taciara Zborowski; Cancian,Luciano Campos; Schenato,Ricardo Bergamo; Dotto,André Carnieletto; Flores,Carlos Alberto. |
| Abstract: The objective of this work was to evaluate the use of covariate selection by expert knowledge on the performance of soil class predictive models in a complex landscape, in order to identify the best predictive model for digital soil mapping in the Southern region of Brazil. A total of 164 points were sampled in the field using the conditioned Latin hypercube, considering the covariates elevation, slope, and aspect. From the digital elevation model, environmental covariates were extracted, composing three sets, made up of: 21 covariates, covariates after the exclusion of the multicollinear ones, and covariates chosen by expert knowledge. Prediction was performed with the following models: decision tree, random forest, multiple logistic regression,... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Digital soil mapping; Pedometry; Predictive covariates; Predictive models; Soil-landscape relationship. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2019000103808 |
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