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Building predictive models of soil particle-size distribution Rev. Bras. Ciênc. Solo
Samuel-Rosa,Alessandro; Dalmolin,Ricardo Simão Diniz; Miguel,Pablo.
Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Digital soil mapping; Terrain attributes; Multiple linear regression; Cross-validation; Additive log-ratio.
Ano: 2013 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832013000200013
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Digital soil fertility mapping of the North, Northwest and Serrana state of Rio de Janeiro. Repositório Alice
ANDRADE, S. F. de; MENDONÇA-SANTOS, M. de L.; CARVALHO, C. N. de; DART, R. de O.; PARES, J. G..
Tipo: Anais e Proceedings de eventos Palavras-chave: Development of methods; Digital soil mapping; Study area.
Ano: 2010 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/873581
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Digital soil mapping approach based on fuzzy logic and field expert knowledge Ciência e Agrotecnologia
Menezes,Michele Duarte de; Silva,Sérgio Henrique Godinho; Owens,Phillip Ray; Curi,Nilton.
In Brazil, soil surveys in more detailed scale are still scarce and necessary to more adequately support the decision makers for planning soil and environment activities in small areas. Hence, this review addresses some digital soil mapping techniques that enable faster production of soil surveys, beyond fitting continuous spatial distribution of soil properties into discrete soil categories, in accordance with the inherent complexity of soil variation, increasing the accuracy of spatial information. The technique focused here is knowledge-based in expert systems, under fuzzy logic and vector of similarity. For that, a contextualization of each tool in the soil types and properties prediction is provided, as well as some options of knowledge extraction...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Digital soil mapping; Soil prediction; Conditioned Latin hypercube sampling; Knowledge miner.
Ano: 2013 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542013000400001
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Digital soilscape mapping of tropical hillslope areas by neural networks Scientia Agricola
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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Geomorphometric tool associated with soil types and properties spatial variability at watersheds under tropical conditions Scientia Agricola
Silva,Sérgio Henrique Godinho; Menezes,Michele Duarte de; Mello,Carlos Rogério de; Góes,Helen Thaís Pereira de; Owens,Phillip Ray; Curi,Nilton.
ABSTRACT The application of quantitative methods to digital soil and geomorphological mapping is becoming an increasing trend. One of these methods, Geomorphons, was developed to identify the ten most common landforms based on digital elevation models. This study aimed to make a quantitative assessment of the relationships between Geomorphons units, determined at three spatial resolutions and nine radii, and soil types and properties of two watersheds with different soil-landscape relationships in Brazil to help soil surveying and mapping under tropical conditions. The study was conducted at Lavrinha Creek (LCW) and Marcela Creek (MCW) watersheds, located in the state of Minas Gerais, Brazil. Spatial resolutions of 10, 20 and 30 m were the basis for...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Geomorphons; Soil-landscape relationships; Pedology; Landforms; Digital soil mapping.
Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000400363
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Geophysical data to modeling soil properties in tropical hillslope areas. Repositório Alice
BASTOS, B.; PINHEIRO, H.; CARVALHO JUNIOR, W. de.
Aero geophysical data is becoming an important source of environmental covariate in digital mapping. Airborne gamma-ray spectrometry is more common in digital soil mapping, because of the penetration potential of approximately 30-40 cm. However, the airborne magnetic method can be tested to add and improve the prediction of soil properties. Therefore, the objective of this work was to implement a preliminary study to model the spatial distribution of soil properties using pedological legacy data, aero geophysical data, and terrain covariates to discuss their importance to the digital soil mapping in Bom Jardim county, Rio de Janeiro, Brazil.
Tipo: Anais e Proceedings de eventos Palavras-chave: Digital soil mapping; Soil properties.
Ano: 2022 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1140014
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GlobalSoilMap.net: a new digital soil map of the world. Infoteca-e
HARTEMINK, A. E.; McBRATNEY, A. B.; HEMPEL, J.; MENDONÇA-SANTOS, M. de L.; McKENZIE, N.; SANCHEZ, P.; GAN-LIN, Z.; MONTANARELLA, L..
Knowledge of the world soil resources is fragmented and dated. There is a need for accurate, up-to-date and spatially referenced soil information as frequently expressed by the modelling community, farmers and land users, and policy and decision makers. This need coincides with an enormous leap in technologies that allow for accurately collecting and predicting soil properties. We are working on a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties. Our aim is to map the global land surface in 5 years ? the resulting maps will depict the primary functional soil properties at a grid resolution of 90×90 m. They will be freely available, web-accessible and widely distributed and...
Tipo: Artigo de divulgação na mídia (INFOTECA-E) Palavras-chave: Digital soil mapping; Mapeamento digital.
Ano: 2009 URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/696753
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Individualization of soil classes by disaggregation of physiographic map polygons PAB
Costa,José Janderson Ferreira; Giasson,Elvio; Silva,Elisângela Benedet da; Campos,Alcinei Ribeiro; Machado,Israel Rosa; Bonfatti,Benito Roberto; Bacic,Ivan Luiz Zilli.
Abstract: The objective of this work was to disaggregate the polygons of physiographic map units in order to individualize the soil classes in each one, representing them as simple soil map units and generating a more detailed soil map than the original one, making these data more useful for future reference. A physiographic map, on a 1:25,000 scale, of the Tarumãzinho watershed, located in the municipality of Águas Frias, in the state of Santa Catarina, Brazil, was used. For disaggregation, three geomorphometric parameters were applied: slope and landforms, both derived from the digital terrain model; and an elevation map. The boundaries of the physiographic units and the elevation, slope, and landform maps were subjected to cross tabulation to identify...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Decision trees; Digital soil mapping; Pedology; Soil class prediction.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2019000103807
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Is It Possible to Classify Topsoil Texture Using a Sensor Located 800 km Away from the Surface? Rev. Bras. Ciênc. Solo
Demattê,José Alexandre Melo; Alves,Marcelo Rodrigo; Terra,Fabricio da Silva; Bosquilia,Raoni Wainer Duarte; Fongaro,Caio Troula; Barros,Pedro Paulo da Silva.
ABSTRACT It is often difficult for pedologists to “see” topsoils indicating differences in properties such as soil particle size. Satellite images are important for obtaining quick information for large areas. However, mapping extensive areas of bare soil using a single image is difficult since most areas are usually covered by vegetation. Thus, the aim of this study was to develop a strategy to determine bare soil areas by fusing multi-temporal satellite images and classifying them according to soil textures. Three different areas located in two states in Brazil, with a total of 65,000 ha, were evaluated. Landsat images of a specific dry month (September) over five consecutive years were collected, processed, and subjected to atmospheric correction...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Bare soils; Satellite images; Spectral sensing; Multi-temporal images; Digital soil mapping; Soil remote sensing.
Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832016000100311
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Mapping a hydrophysical soil property through a comparative analysis of local and global scale approximations Scientia Agricola
Araujo-Carrillo,Gustavo Alfonso; Varón-Ramirez,Viviana Marcela; Gómez-Latorre,Douglas Andrés; Estupiñan-Casallas,Jhon Mauricio; Rodríguez-Roa,Andrea Onelia; Deantonio-Florido,Leidy Yibeth; Martínez-Maldonado,Fabio Ernesto.
ABSTRACT: Current available soil information allows building baselines to improve research, such as sustainable resource management; however, its use requires analysis of accuracy and precision that describes specific variables on local and global scales. Therefore, this study evaluated differences in the spatial distribution of water retention capacity (WRC) of the soil at a depth of 0.3 m, calculated from local general soil surveys and the global gridded soil information system (SoilGrids), using detailed or semi-detailed soil surveys as a reference, in two regions of Colombia (A and B). The qualitative and statistical analyses evaluated differences in WRC surfaces generated by the information sources. Neither information sources described WRC...
Tipo: Info:eu-repo/semantics/article Palavras-chave: SoilGrids; Digital soil mapping; General soil study; Water retention capacity.
Ano: 2021 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000201401
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Mapping soil carbon, particle-size fractions, and water retention in tropical dry forest in Brazil PAB
Vasques,Gustavo Mattos; Coelho,Maurício Rizzato; Dart,Ricardo Oliveira; Oliveira,Ronaldo Pereira; Teixeira,Wenceslau Geraldes.
Abstract The objective of this work was to compare ordinary kriging with regression kriging to map soil properties at different depths in a tropical dry forest area in Brazil. The 11 soil properties evaluated were: organic carbon content and stock; bulk density; clay, sand, and silt contents; cation exchange capacity; pH; water retention at field capacity and at permanent wilting point; and available water. Samples were taken from 327 sites at 0.0-0.10, 0.10-0.20, and 0.20-0.40-m depths, in a tropical dry forest area of 102 km2. Stepwise linear regression models for particle-size fractions and water retention properties had the best fit. Relief and parent material covariates were selected in 31 of the 33 models (11 properties at three depths) and...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Caatinga; Digital soil mapping; Gamma radiometric survey; Geostatistics; Pedometrics.
Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2016000901371
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Multinomial Logistic Regression and Random Forest Classifiers in Digital Mapping of Soil Classes in Western Haiti Rev. Bras. Ciênc. Solo
Jeune,Wesly; Francelino,Márcio Rocha; Souza,Eliana de; Fernandes Filho,Elpídio Inácio; Rocha,Genelício Crusoé.
ABSTRACT Digital soil mapping (DSM) has been increasingly used to provide quick and accurate spatial information to support decision-makers in agricultural and environmental planning programs. In this study, we used a DSM approach to map soils in western Haiti and compare the performance of the Multinomial Logistic Regression (MLR) with Random Forest (RF) to classify the soils. The study area of 4,300 km2 is mostly composed of diverse limestone rocks, alluvial deposits, and, to a lesser extent, basalt. A soil survey was conducted whereby soils were described and classified at 258 sites. Soil samples were collected and subjected to physical and chemical analyses. Recursive Feature Elimination (RFE) was used to select the most important covariates from...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Auxiliary data; Digital soil mapping; Soil survey; Data-mining.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832018000100306
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Multiple logistic regressions: controlling factors in applications to soil class prediction. Repositório Alice
CATEN, A. Ten; DALMOLIN, R. S. D.; PEDRON, F. A.; MENDONÇA-SANTOS, M. de L..
Métodos mais eficazes para determinação do padrão de distribuição de classes de solo na paisagem precisam ser avaliados visando suprir a demanda por mapas de solo em escalas regional e global. Neste estudo, Regressões Logísticas Múltiplas foram utilizadas como modelos preditores em uma aplicação de Mapeamento Digital de Solos. Os modelos foram gerados utilizando um mapa de solos existente como variável dependente e atributos de terreno como variáveis independentes, o que possibilitou determinar a probabilidade de encontrar classes de solo na paisagem no primeiro e no segundo nível categórico do SiBCS. A qualidade dos mapas preditos foi verificada por meio da matriz de contingência. A classe dos Argissolos foi predita corretamente, em relação ao mapa...
Tipo: Separatas Palavras-chave: Digital soil mapping; Generalized linear models; Pedometry.
Ano: 2011 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/890090
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Open legacy soil survey data in Brazil: geospatial data quality and how to improve it. Repositório Alice
SAMUEL-ROSA, A.; DALMOLIN, R. S. D.; MOURA-BRUNO, J. M.; TEIXEIRA, W. G.; FILIPPINI ALBA, J. M..
Spatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil...
Tipo: Artigo de periódico Palavras-chave: Free Brazilian Repository for Open Soil Data; PronaSolos; Pedometrics; Soil data recovery; Digital soil mapping; Mapeamento digital do solo; Base de Dados; Solo; Databases; Soil.
Ano: 2019 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1114070
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Open legacy soil survey data in Brazil: geospatial data quality and how to improve it Scientia Agricola
Samuel-Rosa,Alessandro; Dalmolin,Ricardo Simão Diniz; Moura-Bueno,Jean Michel; Teixeira,Wenceslau Geraldes; Alba,José Maria Filippini.
ABSTRACT: Spatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Free Brazilian Repository for Open Soil Data; PronaSolos; Pedometrics; Soil data recovery; Digital soil mapping.
Ano: 2020 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101401
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Pedological mapping through integration of digital terrain models spectral sensing and photopedology Rev. Ciênc. Agron.
Demattê,José A. M.; Rizzo,Rodnei; Botteon,Victor Wilson.
ABSTRACTNew tools for soil mapping are needed to increase speed and accuracy of pedological mapping processes. This study integrated various technologies to map soils of the Piracicaba region in São Paulo State, Brazil. Each technology was expected to provide different information to design a detailed map. We carried out field survey and soil sampling for laboratory analysis. Initially, we conducted field visits to obtain soil patterns of a reference site. We applied the acquired patterns to an validation site, based solely on information obtained from remote sensing and cartographic databases, namely LANDSAT 7/ETM, digital elevation models (DEM) and aerial photographs. We integrated the information from each product to generate the map of the validation...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Aerial photographs; Digital terrain models; Satellite images; Digital soil mapping.
Ano: 2015 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902015000400669
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Prediction of soil classes in a complex landscape in Southern Brazil PAB
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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Prediction of Topsoil Texture Through Regression Trees and Multiple Linear Regressions Rev. Bras. Ciênc. Solo
Pinheiro,Helena Saraiva Koenow; Carvalho Junior,Waldir de; Chagas,César da Silva; Anjos,Lúcia Helena Cunha dos; Owens,Phillip Ray.
ABSTRACT: Users of soil survey products are mostly interested in understanding how soil properties vary in space and time. The aim of digital soil mapping (DSM) is to represent the spatial variability of soil properties quantitatively to support decision-making. The goal of this study is to evaluate DSM techniques (Regression Trees - RT and Multiple Linear Regressions - MLR) and the ability of these tools to predict mineral fraction content under a wide variability of landscapes. The study site was the entire Guapi-Macacu watershed (1,250.78 km2) in the state of Rio de Janeiro in the Southeast region of Brazil. Terrain attributes and remote sensing data (with 30 m of spatial resolution) were used to represent landscape co-variables selected as an input in...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Terrain attributes; Soil depth functions; Digital soil mapping; Regression models.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832018000100304
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Preprocessing procedures and supervised classification applied to a database of systematic soil survey. Repositório Alice
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 de periódico 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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Preprocessing procedures and supervised classification applied to a database of systematic soil survey Scientia Agricola
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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