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| Registros recuperados: 32 | |
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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 de periódico |
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: Anais e Proceedings de eventos |
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/alice/handle/doc/946729 |
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| KUCHLER, P. C.; SIMÕES, M.; BÉGUÉ, A.; FERRAZ, R. P. D.; ARVOR, D.. |
| A implementação do iLP, ou seja, a diversificação, rotação, consorcio e/ou sucessão das atividades agrícolas e de pecuária na mesma área formando um único sistema, é considerada uma importante estratégia de intensificação agrícola sustentável para brasil, com diversos impactos positivos com destaque na conservação do solo e rentabilidade e viabilidade econômica. O acompanhamento da implantação desta iniciativa é fundamental como instrumento de gestão pública, porém ainda é um desafio. Nesta direção, este trabalho discute a aplicação dos conceitos de BIG DATA e aprendizado de máquina para o sensoriamento remoto. Como teste foi utilizado o classificador Random Forest (RF) aplicado a séries temporais MODIS para analisar a capacidade de detecção de certos... |
| Tipo: Parte de livro |
Palavras-chave: Séries temporais; Random forest; Mato Grosso; Sistemas integrados; Big Earth Observation Data; Aprendizado de máquina; Sensoriamento Remoto; Remote sensing. |
| Ano: 2021 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1135867 |
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| SANO, E. E.; BOLFE, E. L.; PARREIRAS, T. C.; BETTIOL, G. M.; VICENTE, L. E.; DEL'ARCO SANCHES, I.; VICTORIA, D. de C.. |
| Abstract: Farmers in the Brazilian Cerrado are increasing grain production by cultivating second crops during the same crop growing season. The release of PlanetScope (PS) satellite images represents an innovative opportunity to monitor double cropping production. In this study, we analyzed the potential of six PS monthly mosaics from the 2021/2022 crop growing season to discriminate double cropping areas in the municipality of Goiatuba, Goiás State, Brazil. The four multispectral bands of the PS images were converted into normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), green-red normalized difference index (GRNDI), and textural features derived from the gray-level co-occurrence matrix (GLCM). The ten most important... |
| Tipo: Artigo de periódico |
Palavras-chave: Floresta aleatória; Mapeamento do uso da terra; Mapeamento de cobertura da terra; Cobertura da terra; Constelação de satélites; Matriz de coocorrência em nível de cinza; Savana tropical; Random forest; Gray-level co-occurrence matrix; GRNDI; Land use and land cover mapping; Satellite constellation; Tropical savanna; Uso da Terra; Land use; Land cover. |
| Ano: 2023 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1152103 |
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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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| TORO, A. P. S. G. D.; WERNER, J. P. S.; REIS, A. A. dos; ESQUERDO, J. C. D. M.; ANTUNES, J. F. G.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G.; FIGUEIREDO, G. K. D. A.. |
| ABSTRACT. Various approaches were developed considering the need to increase agricultural productivity in cultivated areas without more deforestation, such as the Integrated Crop livestock systems (ICLS). The ICLS could be composed of annual crops followed by pastureland with the presence of cattle. Due to the high temporal dynamic of rotation between crops over the season, monitoring these areas is a big challenge. Also, agricultural organizations worldwide highlight the need for early-season maps for this kind of work. In this context, this study evaluated the potential of open data (Sentinel-2) data to map ICLS areas. The performance of two classifiers was evaluated: one of Machine Learning (random forest) and the other of Deep Learning (LSTM). Three... |
| Tipo: Artigo de periódico |
Palavras-chave: Agricultura regenerativa; Identificação de culturas; Floresta aleatória; Aprendizado profundo; LSTM; Regenerative agriculture; Crop identification; Random forest; Sensoriamento Remoto; Remote sensing. |
| Ano: 2022 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1145714 |
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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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| Kopf, R. Keller; Yen, Jian D. L.; Nimmo, Dale G.; Brosse, Sébastien; Villeger, Sébastien; Tittensor, Derek. |
| Aim The aim of this study was test whether maximum body mass and jaw length are reliable predictors of trophic position (TP) in fishes, and to compare linear and nonlinear machine‐learning (ML) models incorporating biogeography, habitat and other morphological traits. Location Global. Time period Modern. Major taxa studied Fishes. Methods We compiled a global database of TP (2.0–4.5), maximum body mass, jaw length, order, ecoregion, habitat and other morphological traits of freshwater, estuarine and diadromous fishes (n = 1,991). We used Bayesian linear mixed effects and ML, with r2 analogues and 10‐fold cross‐validation, to explain and predict TP. Results Random forest models outperformed Bayesian models in all comparisons. Jaw length was the most... |
| Tipo: Text |
Palavras-chave: Allometric trophic network models; Allometry; Body mass; Gape limitation; Machine learning; Predator– Prey; Random forest; Trophic network theory. |
| Ano: 2021 |
URL: https://archimer.ifremer.fr/doc/00661/77349/78823.pdf |
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| MACARRINGUE, L. S.; BOLFE, E. L.; DUVERGER, S. G.; SANO, E. E.; CALDAS, M. M.; FERREIRA, M. C.; ZULLO JUNIOR, J.; MATIAS, L. F.. |
| Accurate land use and land cover (LULC) mapping is essential for scientific and decision-making purposes. The objective of this paper was to map LULC classes in the northern region of Mozambique between 2011 and 2020 based on Landsat time series processed by the Random Forest classifier in the Google Earth Engine platform. The feature selection method was used to reduce redundant data. The final maps comprised five LULC classes (non-vegetated areas, built-up areas, croplands, open evergreen and deciduous forests, and dense vegetation) with an overall accuracy ranging from 80.5% to 88.7%. LULC change detection between 2011 and 2020 revealed that non-vegetated areas had increased by 0.7%, built-up by 2.0%, and dense vegetation by 1.3%. On the other hand,... |
| Tipo: Artigo de periódico |
Palavras-chave: Cobertura da terra; Floresta aleatória; Séries temporais; Aprendizado de máquina; Google Earth Engine; Feature selection; Miombo; Random forest; Machine learning; Desmatamento; Uso da Terra; Deforestation; Land use; Land cover. |
| Ano: 2023 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1155979 |
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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: Separatas |
Palavras-chave: Mapeamento digital de solos; Random forest; Cokrigagem. |
| Ano: 2015 |
URL: http://www.alice.cnptia.embrapa.br/alice/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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| Registros recuperados: 32 | |
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