Soil Mapping
Mostrando 13-24 de 169 artigos, teses e dissertações.
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13. AlradSpectra: a Quantification Tool for Soil Properties Using Spectroscopic Data in R
ABSTRACT Soil reflectance spectroscopy has become an innovative method for soil property quantification supplying data for studies in soil fertility, soil classification, digital soil mapping, while reducing laboratory time and applying a clean technology. This paper describes the implementation of a Graphical User Interface (GUI) using R named AlradSpectra.
Rev. Bras. Ciênc. Solo. Publicado em: 29/07/2019
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14. Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
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 (surv
Sci. agric. (Piracicaba, Braz.). Publicado em: 01/07/2019
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15. TRANSITION FROM SYSTEMATIC TO DIRECTED SOIL SAMPLING DESIGNS IN AN AREA MANAGED WITH PRECISION AGRICULTURE
ABSTRACT In agricultural areas with a historical of systematic soil sampling, alternative methodologies such as directed sampling design based on management zones (MZ) have been proposed to reduce sampling costs. The aim of this study was to evaluate the technical and economic impacts of replacing a dense systematic soil sampling design (cell size of 0.5 ha)
Eng. Agríc.. Publicado em: 19/06/2019
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16. SPATIALIZATION OF ELECTRICAL CONDUCTIVITY AND PHYSICAL HYDRAULIC PARAMETERS OF SOILS UNDER DIFFERENT USES IN AN ALLUVIAL VALLEY
RESUMO A caracterização da estrutura de variabilidade espacial de propriedades hidráulicas e da salinidade do solo é de grande importância para um adequado manejo agrícola de vales aluviais e para proteção da vegetação ciliar. Dessa forma, o objetivo deste trabalho foi a verificação da precisão de medições indiretas da condutividade elétrica
Rev. Caatinga. Publicado em: 09/05/2019
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17. Mapping and characterization of intensity in land use by pasture using remote sensing
RESUMO A demanda atual por alimentos tem sido atendida por meio da exploração das reservas naturais. O Brasil apresenta 26% da sua extensão ocupada por usos agropecuários, sendo 62% desses, pastagens. Pastagens degradadas apresentam maior intensidade de uso da terra do que pastagens bem manejadas, levando à maior degradação do meio ambiente. Os sistem
Rev. bras. eng. agríc. ambient.. Publicado em: 06/05/2019
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18. Selection of Environmental Covariates for Classifier Training Applied in Digital Soil Mapping
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
Rev. Bras. Ciênc. Solo. Publicado em: 07/01/2019
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19. Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data
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 n
Rev. Bras. Ciênc. Solo. Publicado em: 07/01/2019
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20. Digital Soil Mapping Using Machine Learning Algorithms in a Tropical Mountainous Area
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
Rev. Bras. Ciênc. Solo. Publicado em: 14/11/2018
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21. Bibliometric Analysis for Pattern Exploration in Worldwide Digital Soil Mapping Publications
Abstract Bibliometric analyses provide a clear understanding of the scientific performance and relate them with standards of the global scientific production. Soil science is an outstanding and developing field among environmental sciences. Knowledge about soil characteristics and their distribution in the environment has been enriched by the use of new geot
An. Acad. Bras. Ciênc.. Publicado em: 25/10/2018
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22. Mapping Soil Cation Exchange Capacity in a Semiarid Region through Predictive Models and Covariates from Remote Sensing Data
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. Alth
Rev. Bras. Ciênc. Solo. Publicado em: 18/10/2018
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23. Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions
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) te
Rev. Bras. Ciênc. Solo. Publicado em: 17/09/2018
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24. Multinomial Logistic Regression and Random Forest Classifiers in Digital Mapping of Soil Classes in Western Haiti
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
Rev. Bras. Ciênc. Solo. Publicado em: 02/07/2018