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65 results

Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data

Patrícia Morais da Matta Campbell, Elpídio Inácio Fernandes Filho, Márcio Rocha Francelino, José Alexandre Melo Demattê, Marcos Gervasio Pereira, Clécia Cristina Barbosa Guimarães and, [...]

08/Nov/2018

ABSTRACT Quantification of soil properties is essential for better understanding of the environment and better soil management. The conventional techniques of laboratory analysis are sometimes costly and detrimental to the environment. Thus, development of new techniques for soil analysis that do not generate residues, such as spectroscopy, is increasingly necessary as a viable way to estimate a wide range of soil properties. The objective of this study was to predict the levels of organic carbon (OC), clay, and extractable phosphorus […]

Selection of Environmental Covariates for Classifier Training Applied in Digital Soil Mapping

Alcinei Ribeiro Campos, Elvio Giasson, José Janderson Ferreira Costa, Israel Rosa Machado, Elisângela Benedet da Silva, Benito Roberto Bonfatti

08/Nov/2018

ABSTRACT A large number of predictor variables can be used in digital soil mapping; however, the presence of irrelevant covariables may compromise the prediction of soil types. Thus, algorithms can be applied to select the most relevant predictors. This study aimed to compare three covariable selection systems (two filter algorithms and one wrapper algorithm) and assess their impacts on the predictive model. The study area was the Lajeado River Watershed in the state of Rio Grande do Sul, Brazil. We […]

Paleoenvironmental Characterization of a High-Mountain Environment in the Atlantic Forest in Southeastern Brazil

Eduardo Carvalho da Silva Neto, Jaqueline Jesus Santana dos Santos, Marcos Gervasio Pereira, Deyvid Diego Carvalho Maranhão, Fabiana da Costa Barros, Lúcia Helena Cunha dos Anjos

02/Nov/2018

ABSTRACT: Records of changes in the phytosociological structure of vegetation can be observed more clearly in soils that have more significant accumulation of organic matter, like those occurring in high-mountain environments. The aim of this study was to characterize soils formed in high-mountain environments in the Itatiaia National Park (INP), state of Rio de Janeiro, southeastern Brazil, and to discuss the potential of preserved phytoliths as markers of vegetative history and environmental factors. Four profiles were selected, which were morphologically […]

Digital Soil Mapping Using Machine Learning Algorithms in a Tropical Mountainous Area

Martin Meier, Eliana de Souza, Marcio Rocha Francelino, Elpídio Inácio Fernandes Filho, Carlos Ernesto Gonçalves Reynaud Schaefer

02/Nov/2018

ABSTRACT: Increasingly, applications of machine learning techniques for digital soil mapping (DSM) are being used for different soil mapping purposes. Considering the variety of models available, it is important to know their performance in relation to soil data and environmental variables involved in soil mapping. This paper investigated the performance of eight machine learning algorithms for soil mapping in a tropical mountainous area of an official rural settlement in the Zona da Mata region in Brazil. Morphometric maps generated from […]

Mapping Soil Cation Exchange Capacity in a Semiarid Region through Predictive Models and Covariates from Remote Sensing Data

César da Silva Chagas, Waldir de Carvalho Júnior, Helena Saraiva Koenow Pinheiro, Pedro Armentano Mudado Xavier, Silvio Barge Bhering, Nilson Rendeiro Pereira, [...]

15/Oct/2018

ABSTRACT: Planning sustainable use of land resources requires reliable information about spatial distribution of soil physical and chemical properties related to environmental processes and ecosystemic functions. In this context, cation exchange capacity (CEC) is a fundamental soil quality indicator; however, it takes money and time to obtain this data. Although many studies have been conducted to spatially quantify soil properties on various scales and in different environments, not much is known about interactions between soil properties and environmental covariates in […]

Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions

José Alexandre Melo Demattê, Clécia Cristina Barbosa Guimarães, Caio Troula Fongaro, Emmily Larissa Felipe Vidoy, Veridiana Maria Sayão, André Carnieletto Dotto, [...]

12/Sep/2018

ABSTRACT: The study of soils, including their physical and chemical properties, is essential for agricultural management. Soil quality must be maintained to ensure sustainable production of food and conservation of natural resources. In this context, soil mapping is important to provide spatial information, which can be performed using remote sensing (RS) techniques. Modeling through use of satellite data is uncertain regarding the amplitude of replicability of the models. The aim of this study was to develop a quantification model for […]

Pedogenesis in an Archaeological Dark Earth – Mulatto Earth Catena over Volcanic Rocks in Western Amazonia, Brazil

Luís Antônio Coutrim dos Santos, Jane Kelly Silva Araujo, Valdomiro Severino de Souza Júnior, Milton César Costa Campos, Marcelo Metri Corrêa, Regilene Angélica da Silva Souza

31/Jul/2018

ABSTRACT Archaeological Dark Earth (ADE) pedogenesis and pre-Columbian history are fundamental for understanding the biodiversity and pedodiversity of the Neotropical rainforest in the Amazon region. This study aimed to evaluate the morphological, physical, chemical, and mineralogical properties as well as NaOH-extractable organic matter [OM(NaOH)] in ADE and Mulatto Earth (ME) overlying volcanic rocks along a toposequence (four soil profiles) in western Amazonia, Brazil. The soil profiles show anthropic A horizons over an argic horizon (Bt) in the ADE (Humic, Pretic […]

Mineralogy, Micromorphology, and Genesis of Soils with Varying Drainage Along a Hillslope on Granitic Rocks of the Atlantic Forest Biome, Brazil

Anderson Almeida Pacheco, João Carlos Ker, Carlos Ernesto Gonçalves Reynaud Schaefer, Mauricio Paulo Ferreira Fontes, Felipe Vaz Andrade, Eder de Souza Martins, [...]

06/Jul/2018

ABSTRACT Although the physical environment of the Atlantic Forest realm is well known, studies on the soil-landform relationships are fundamental to improve the management of soil resources to facilitate sustainable development. The purpose of this study was to evaluate a representative topossequence on the “Mares de Morros” landscape of deeply weathered regolith on leucocratic granite rocks and demi-orange convex slopes. The soils varied along the topossequence according to drainage and were classified as Acrudox, Pseudogleysol, and Epiaquent. The clay fraction […]

Reversibility of the Hardening Process of Plinthite and Petroplinthite in Soils of the Araguaia River Floodplain under Different Treatments

Angélica Pires Batista Martins, Glenio Guimarães Santos, Virlei Álvaro de Oliveira, Deyvid Diego Carvalho Maranhão, Leonardo Santos Collier

18/Jun/2018

ABSTRACT Although ferruginous materials occur frequently in soils of tropical regions, information about the reversal of the hardening process of these materials is scarce. This study assessed the influence of different chemical treatments and periods of immersion on the reversibility of the hardening process of plinthite and petroplinthite in soils of the Araguaia River plain. Soil samples were collected from the plinthic horizons in 0.10 m high and 0.15 m diameter PVC cylinders and divided into subsamples with a rock […]

Multinomial Logistic Regression and Random Forest Classifiers in Digital Mapping of Soil Classes in Western Haiti

Wesly Jeune, Márcio Rocha Francelino, Eliana de Souza, Elpídio Inácio Fernandes Filho, Genelício Crusoé Rocha

18/Jun/2018

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 […]

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