Pedometrics in Brazil

Pedometrics in Brazil

Saraiva Koenow Pinheiro, Helena; Bacis Ceddia, Marcos; Souza Valladares, Gustavo; de Carvalho Junior, Waldir

Springer International Publishing AG

09/2024

286

Dura

9783031645785

15 a 20 dias

Descrição não disponível.
Preface.- MultiSoils: a digital platform for information search and project management in soil science.- Multiscalar geomorphometric generalization to delineate soil textural paterns on amazon watersheds landscapes.- Applying machine learning techniques to model and map soil surface texture using limited legacy data.- Predicting soil physical-hydric attributes based on pedotransfer functions and algorithms for quantitative pedology.- Spatial dependence of organic carbon and granulometry in archaeological soils of lagoa grande das queimadas, northeastern brazil.- Application of electrical conductivity profiling for the characterization and textural discretization of a Technosol.- Soil porosity differences among grass-covered and exposed soils measured by high resolution X-ray computed microtomography (microCT).- Using legacy soil data to plan new data collection: Study case of Rio de Janeiro state Brazil.- Exploratory Analysis from Harmonized Legacy Soil Data to Support Digital Soil Mapping in Brazilian Midwest.- Soil organic carbon stock estimation using legacy data: a case study of north fluminense region BR.- Aerogeophysical data to modeling soil properties: a study case in Bom Jardim RJ.- Predicting and mapping of soil carbon and nitrogen stocks by diffuse reflectance spectroscopy and magnetic susceptibility in Western Plateau of Sao Paulo.- Iron rods as markers for soil horizon depths and point scatterers for estimating pulse velocity in GPR imagery.- Random forest-based fusion of proximal and orbital remote sensor data for soil salinity mapping in a brazilian semi-arid region.- The particle size causes a change in the determination of soil color via the Nix Pro 2 sensor.- Mapping soil salinity: a case study from Marajo Island, Brazilian Amazonia.- Applied Morphometry To Digital Soil Mapping In Detailed Scale.- Prediction of soil carbon stock in the Piaui State coast by remote sensing.- Methods and challenges in digital soil mapping: Applied modelling with R examples.
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Digital Soil Mapping;Pedometrics;Pedotransfer Functions;Soil Attributes;Soil Classes;Soil Surveys;Machine Learning Applied to Soil Sciences