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| Registros recuperados: 21 | |
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| OLDONI, L. V.; CATTANI, C. E. V.; MERCANTE, E.; JOHANN, J. A.; ANTUNES, J. F. G.; ALMEIDA, L.. |
| ABSTRACT: In the state of Paraná, Brazil, there are no major changes in areas cultivated with annual crops, mainly due to environmental laws that do not allow expansions to new areas. There is a great contribution of the annual crops to the domestic demand of food and economic demand in the exports. Thus, the area and distribution of annual crops are information of great importance. New methodologies, such as data mining, are being tested with the objective of analyzing and improving their potential use for classification of land use and land cover. This study used the classifiers decision tree and random forest with Normalized Difference Vegetation Index (NDVI) temporal metrics on images from Operational Land Imager (OLI)/Landsat-8. The results were... |
| Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Árvore de decisão; Métricas temporais de NDVI; Mineração de dados; Séries temporais; Decision tree; NDVI temporal metrics; Random forest; Data mining; Normalized difference vegetation index; Time series analysis. |
| Ano: 2019 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1114915 |
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| Oldoni,Lucas V.; Cattani,Carlos E. V.; Mercante,Erivelto; Johann,Jerry A.; Antunes,João F. G.; Almeida,Luiz. |
| ABSTRACT In the state of Paraná, Brazil, there are no major changes in areas cultivated with annual crops, mainly due to environmental laws that do not allow expansions to new areas. There is a great contribution of the annual crops to the domestic demand of food and economic demand in the exports. Thus, the area and distribution of annual crops are information of great importance. New methodologies, such as data mining, are being tested with the objective of analyzing and improving their potential use for classification of land use and land cover. This study used the classifiers decision tree and random forest with Normalized Difference Vegetation Index (NDVI) temporal metrics on images from Operational Land Imager (OLI)/Landsat-8. The results were... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Decision tree; Random forest; NDVI temporal metrics. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001200952 |
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| MOKRY, F. B.; LIMA, A. O. de; URBINATI, I.; TORRES JUNIOR, R. A. de A.; HIGA, R. H.; REGITANO, L. C. de A.. |
| Resumo: Foram genotipados 400 animais Canchim que apresentavam fenótipos para área de olho de lombo (AOL) e espessura de gordura subcutânea (EGS). Após o controle de qualidade, foi realizado análise de associação dos SNPs com AOL e EGS por meio da metodologia de RandomForest. Os 400 indivíduos foram também reamostrados 10 vezes formando grupos de 200 indivíduos mais representativos e menos aparentados. Foi criado um grupo de SNPs contendo apenas os SNPs que foram selecionados em todas as análises, considerados os SNPs mais robustos totalizando 197 SNPs para AOL e 162 SNPs para EGS. Após o ajuste de uma regressão selecionou-se um conjunto de 20 SNPs para AOL com R2=0,59 e um conjunto de 17 SNPs para EGS com R2=0,49. Esses SNPs ainda precisam ser validados... |
| Tipo: Artigo em anais de congresso (ALICE) |
Palavras-chave: Área de olho de lombo; Bovino de corte; Espessura de gordura subcutânea; Random forest; Ribeye area; Backfat; Single nucleotide polymorphism; Beef cattle. |
| Ano: 2012 |
URL: http://www.alice.cnptia.embrapa.br/handle/doc/946729 |
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| Goydaragh,Maryam Ghebleh; Jafarzadeh,Ali Asghar; Shahbazi,Farzin; Oustan,Shahin; Taghizadeh-Mehrjardi,Ruhollah; Lado,Marcos. |
| ABSTRACT Characterizing the elemental composition provides useful information about the weathering degree of soils. In Miandoab County, Northern Iran, this characterization was missing, and thus the objectives of this work were to evaluate the weathering degrees for the most typical soils in the area from their elemental compositions, and to estimate this elemental composition using Fourier transform infrared spectroscopy and Random Forest models. Five soil profiles, including Aridisols and Inceptisols, were selected as the most representative of the area. Major elemental oxides were determined in each genetic horizon by X-ray fluorescence, showing that these soils were at early developmental stages. Only Al2O3 and CaO were accurately estimated, with R2... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: FTIR spectra; Random forest; Weathering. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000600460 |
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| Picart, Stephane Saux; Tandeo, Pierre; Autret, Emmanuelle; Gausset, Blandine. |
| Machine learning techniques are attractive tools to establish statistical models with a high degree of non linearity. They require a large amount of data to be trained and are therefore particularly suited to analysing remote sensing data. This work is an attempt at using advanced statistical methods of machine learning to predict the bias between Sea Surface Temperature (SST) derived from infrared remote sensing and ground “truth” from drifting buoy measurements. A large dataset of collocation between satellite SST and in situ SST is explored. Four regression models are used: Simple multi-linear regression, Least Square Shrinkage and Selection Operator (LASSO), Generalised Additive Model (GAM) and random forest. In the case of geostationary satellites for... |
| Tipo: Text |
Palavras-chave: Machine learning; Systematic error; Sea surface temperature; Random forest. |
| Ano: 2018 |
URL: https://archimer.ifremer.fr/doc/00426/53797/54721.pdf |
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| CHAGAS, C. da S.; CARVALHO JUNIOR, W. de; BHERING, S. B.; PEREIRA, N. R.. |
| O planejamento de uso e o manejo sustentável da terra requerem informações confiáveis sobre a distribuição espacial de propriedades físicas e químicas do solo que afetam os processos e serviços na paisagem. Neste sentido, a capacidade de troca catiônica (CTC) é uma das propriedades do solo mais importantes, sendo considerada como um indicador vital da qualidade do solo, porém, sua obtenção é cara e demorada. Embora muitos estudos tenham sido conduzidos para identificar o padrão espacial da distribuição de propriedades do solo em várias escalas e várias paisagens, pouco se conhece sobre as relações existentes entre estas propriedades e diferentes covariáveis ambientais no semiárido brasileiro. Sendo assim, o objetivo desse estudo foi avaliar a eficiência... |
| Tipo: Artigo em anais de congresso (ALICE) |
Palavras-chave: Mapeamento digital de solos; Random forest; Cokrigagem. |
| Ano: 2015 |
URL: http://www.alice.cnptia.embrapa.br/handle/doc/1031631 |
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| TEIXEIRA,ANITA F.S.; SILVA,JACQUELINE S.; VILELA,LAÍZE A.F.; COSTA,PATRÍCIA F.; COSTA,ELAINE M. DA; GUIMARÃES,AMANDA A.; SANTOS,JESSÉ V. DOS; SILVA,SÉRGIO H.G.; CARNEIRO,MARCO AURÉLIO C.; MOREIRA,FATIMA M.S.. |
| Abstract: Several microbiological indicators of soil quality present high sensitivity, but little is known about the influence of topographic factors on them. This work aimed to evaluate variability of biological indicators of soil quality across a hillslope under native forest and the influence of topographic factors on them. Four positions on a hillslope were evaluated. Activity of the enzymes β-glucosidase, acid phosphatase, urease and fluorescein diacetate (FDA) hydrolysis were determined, as well as basal and substrate-induced respiration, and density of microorganisms: total bacteria, total fungi, actinobacteria, phosphate solubilizers, ammonifiers, native rhizobia, free-living N2-fixing bacteria, spores of arbuscular mycorrhizal fungi and percentage... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Biological indicators; Digital elevation model; Enzymes; Microbial activity; Random forest. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000700866 |
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| Silva,Sérgio Henrique Godinho; Silva,Elen Alvarenga; Poggere,Giovana Clarice; Pádua Junior,Alceu Linares; Gonçalves,Mariana Gabriele Marcolino; Guilherme,Luiz Roberto Guimarães; Curi,Nilton. |
| ABSTRACT Sulfuric acid digestion analyses (SAD) provide useful information to environmental studies, in terms of the geochemical balance of nutrients, parent material uniformity, nutrient reserves for perennial crops, and mineralogical composition of the soil clay fraction. Yet, these analyses are costly, time consuming, and generate chemical waste. This work aimed at predicting SAD results from portable X-ray fluorescence (pXRF) spectrometry, which is proposed as a “green chemistry” alternative to the current SAD method. Soil samples developed from different parent materials were analyzed for soil texture and SAD, and scanned with pXRF. The SAD results were predicted from pXRF elemental analyses through simple linear regressions, stepwise multiple linear... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil clay fraction; Weathering indices; Random forest; Proximal sensors; Green chemistry. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000401402 |
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| SCHIKOWSKI,ANA B.; CORTE,ANA P.D.; RUZA,MARIELI S.; SANQUETTA,CARLOS R.; MONTAÑO,RAZER A.N.R.. |
| Abstract Taper functions and volume equations are essential for estimation of the individual volume, which have consolidated theory. On the other hand, mathematical innovation is dynamic, and may improve the forestry modeling. The objective was analyzing the accuracy of machine learning (ML) techniques in relation to a volumetric model and a taper function for acácia negra. We used cubing data, and fit equations with Schumacher and Hall volumetric model and with Hradetzky taper function, compared to the algorithms: k nearest neighbor (k-NN), Random Forest (RF) and Artificial Neural Networks (ANN) for estimation of total volume and diameter to the relative height. Models were ranked according to error statistics, as well as their dispersion was verified.... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Artificial intelligence; Data mining; Random forest; ANN. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000703389 |
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| REIS, A. A. dos; WERNER, J. P. S.; SILVA, B. C.; FIGUEIREDO, G. K. D. A.; ANTUNES, J. F. G.; ESQUERDO, J. C. D. M.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; ROCHA, J. V.; MAGALHÃES, P. S. G.. |
| Abstract: Fast and accurate quantification of the available pasture biomass is essential to support grazing management decisions in intensively managed fields. The increasing temporal and spatial resolutions oered by the new generation of orbital platforms, such as Planet CubeSat satellites, have improved the capability of monitoring pasture biomass using remotely sensed data. Here, we assessed the feasibility of using spectral and textural information derived from PlanetScope imagery for estimating pasture aboveground biomass (AGB) and canopy height (CH) in intensively managed fields and the potential for enhanced accuracy by applying the extreme gradient boosting (XGBoost) algorithm. Our results demonstrated that the texture measures enhanced AGB and CH... |
| Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Pasto; Pastagem tropical; Floresta aleatória; Random forest; Mixed pastures; Integrated systems; Texture measures; Extreme gradient boosting; Biomassa; Pastagem Mista; Sensoriamento Remoto; Pastures; Tropical pastures; Biomass; Aboveground biomass; Remote sensing. |
| Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1125026 |
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| VALADARES, A. P.; COELHO, R. M.; OLIVEIRA, S. R. de M.. |
| ABSTRACT:Data Mining techniques play an important role in the prediction of soil spatial distribution in systematic soil surveying, though existing methodologies still lack standardization and a full understanding of their capabilities. The aim of this work was to evaluate the performance of preprocessing procedures and supervised classification approaches for predicting map units from 1:100,000-scale conventional semi-detailed soil surveys. Sheets of the Brazilian National Cartographic System on the 1:50,000 scale, ?Dois Córregos? (?Brotas? 1:100,000-scale sheet), ?São Pedro? and ?Laras? (?Piracicaba? 1:100,000-scale sheet) were used for developing models. Soil map information and predictive environmental covariates for the dataset were obtained from the... |
| Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Aprendizado de máquina; Pré-processamento; Classificação de solos; Random forest; Machine learning algorithms; Tacit soil-landscape relationships; Digital soil mapping; Solo; Soil; Soil classification. |
| Ano: 2019 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1118563 |
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| Valadares,Alan Pessoa; Coelho,Ricardo Marques; Oliveira,Stanley Robson de Medeiros. |
| ABSTRACT: Data Mining techniques play an important role in the prediction of soil spatial distribution in systematic soil surveying, though existing methodologies still lack standardization and a full understanding of their capabilities. The aim of this work was to evaluate the performance of preprocessing procedures and supervised classification approaches for predicting map units from 1:100,000-scale conventional semi-detailed soil surveys. Sheets of the Brazilian National Cartographic System on the 1:50,000 scale, “Dois Córregos” (“Brotas” 1:100,000-scale sheet), “São Pedro” and “Laras” (“Piracicaba” 1:100,000-scale sheet) were used for developing models. Soil map information and predictive environmental covariates for the dataset were obtained from the... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Machine learning algorithms; Random forest; Tacit soil-landscape relationships; Digital soil mapping. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162019001500439 |
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| CARVALHO JUNIOR, W. de; PEREIRA, N. R.; FERNANDES FILHO, E. I.; CALDERANO FILHO, B.; PINHEIRO, H. S. K.; CHAGAS, C. da S.; BHERING, S. B.; PEREIRA, V. R.; LAWALL, S.. |
| Notwithstanding the importance of soil surveys, advances in digital soil mapping have mainly focused on mapping soil attributes or properties rather than developing digital maps of soil units or soil classes. The purpose of this research was to develop digital soil unit maps based on primary soil data collection in areas without previously collected soil information. The covariate variability, the random effect across the data subset and the map outputs were the focuses of this study. We used five datasets with four models (Random Forest - RF, Gradient Boosted Machine - GBM, C5.0, and multinomial log-linear model - MLR). The covariates were grouped into five datasets, where four were grouped by Region Of Interest per Class (ROIC) and one was not grouped by... |
| Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Mapeamento digital de solos; Tree learners models; Hillslope areas; Random forest; Mapa; Solo; Soil map. |
| Ano: 2020 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1124458 |
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| SCHULTZ, B.; IMMITZER, M.; FORMAGGIO, A. R.; SANCHES, I. D. A.; LUIZ, A. J. B.; ATZBERGER, C.. |
| Abstract: Only well-chosen segmentation parameters ensure optimum results of object-based image analysis (OBIA). Manually defining suitable parameter sets can be a time-consuming approach, not necessarily leading to optimum results; the subjectivity of the manual approach is also obvious. For this reason, in supervised segmentation as proposed by Stefanski et al. (2013) one integrates the segmentation and classification tasks. The segmentation is optimized directly with respect to the subsequent classification. In this contribution, we build on this work and developed a fully autonomous workflow for supervised object-based classification, combining image segmentation and random forest (RF) classification. Starting from a fixed set of randomly selected and... |
| Tipo: Artigo em periódico indexado (ALICE) |
Palavras-chave: Mapeamento agrícola; Segmentação multirresolução; OBIA; Crop mapping; Brazil; Multi-resolution segmentation; OLI; Random forest; Sensoriamento remoto; Remote sensing. |
| Ano: 2015 |
URL: http://dx.doi.org/10.3390/rs71114482 |
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| KUCHLER, P. C.; SIMÕES, M.; FERRAZ, R. P. D.; BÉGUÉ, A.. |
| A implementação dos Sistemas Integrados de produção agropecuária (SI), ou seja, a integração lavoura-pecuária-floresta (ILPFs), constitui uma importante estratégia de intensificação agrícola sustentável para o Brasil. Estados, como Mato Grosso (MT), tradicionalmente grandes produtores agrícolas já vem adotando esta estratégia e potencializando a sua capacidade produtiva. O Governo Federal vem, desde 2009, promovendo a disseminação e adoção dos sistemas integrados, entretanto ainda não existe uma metodologia de monitoramento desta tendência. Nossa hipótese é que técnicas de classificação Random Forest (RF) aplicadas a Séries Temporais (ST) do satélite MODIS sejam capazes de detectar determinados SI no MT. Para isso, avaliamos a acurácia do RF aplicado a ST... |
| Tipo: Artigo em anais de congresso (ALICE) |
Palavras-chave: Séries temporais; Random forest; Mato Grosso; Sistemas integrados; Sensoriamento Remoto; Remote sensing. |
| Ano: 2018 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1100305 |
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| Registros recuperados: 21 | |
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