Sérgio Henrique Godinho Silva

Solum depth spatial prediction comparing conventional with knowledge-based digital soil mapping approaches

Solum depth and its spatial distribution play an important role in different types of environmental studies. Several approaches have been used for fitting quantitative relationships between soil properties and their environment in order to predict them spatially. This work aimed to present the steps required for solum depth spatial prediction from knowledge-based digital soil mapping, comparing the prediction to the conventional soil mapping approach through field validation, in a watershed located at Mantiqueira Range region, in the state of Minas Gerais, Brazil. Conventional soil mapping had aerial photo-interpretation as a basis. The knowledge-based digital soil mapping applied fuzzy logic and similarity vectors in an expert system. The knowledge-based digital soil mapping approach showed the advantages over the conventional soil mapping approach by applying the field expert-knowledge in order to enhance the quality of final results, predicting solum depth with suited accuracy in a continuous way, making the soil-landscape relationship explicit.

Digital soil mapping approach based on fuzzy logic and field expert knowledge

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 techniques. Such tools have reduced the inconsistency and costs associated with the traditional manual processes, relying on a relatively low density of soil samples. On the other hand, knowledge-based technique is not automatic, and just as the traditional soil survey, the knowledge of soil-landscape relationships is irreplaceable.

Spatial prediction of soil properties in two contrasting physiographic regions in Brazil

This study compared the performance of ordinary kriging (OK) and regression kriging (RK) to predict soil physical-chemical properties in topsoil (0-15 cm). Mean prediction of error and root mean square of prediction error were used to assess the prediction methods. Two watersheds with contrasting soil-landscape features were studied, for which the prediction methods were performed differently. A multiple linear stepwise regression model was performed with RK using digital terrain models (DTMs) and remote sensing images in order to choose the best auxiliary covariates. Different pedogenic factors and land uses control soil property distributions in each watershed, and soil properties often display contrasting scales of variability. Environmental covariables and predictive methods can be useful in one site study, but inappropriate in another one. A better linear correlation was found at Lavrinha Creek Watershed, suggesting a relationship between contemporaneous landforms and soil properties, and RK outperformed OK. In most cases, RK did not outperform OK at the Marcela Creek Watershed due to lack of linear correlation between covariates and soil properties. Since alternatives of simple OK have been sought, other prediction methods should also be tested, considering not only the linear relationships between covariate and soil properties, but also the systematic pattern of soil property distributions over that landscape.

Pedotransfer functions for water retention in different soil classes from the center-southern Rio Grande do Sul State

Water retention in soil is used in many agronomic and environmental applications, but its direct measurement is time-consuming and expensive. Therefore, pedotransfer functions (PTFs) are alternatives to obtain this information faster and more economically. The objectives of this study were to generate and validate PTFs to estimate the water content at potentials of -33 kPa (field capacity) and -1500 kPa (permanent wilting point) for different soil classes from the central-south portion of Rio Grande do Sul State. The physical and chemical analyses database from soil surveys of the Celulose Riograndense Corp were used. The database is composed of particle size distribution (coarse and fine sand, silt and clay), soil organic matter, and water content data at the above mentioned potentials, besides other information concerning the behavior of the soil classes at field conditions. Firstly, the data were stratified by soil classes and depths, and then 70% of the data were separated for PTF generation and 30% for validation. PTFs were generated for each specific soil class and also general PTFs which were not stratified by soil class, by means of stepwise multiple regression. In most situations, PTFs for a specific soil class showed a better fit than the general PTFs. Proper adjustment of the data showed that the water retention values at potentials of -33 kPa and -1500 kPa can be estimated for the soils from the central-south portion of Rio Grande do Sul State that do not have such analyses through the use of PTFs.

Updated Brazilian’s Georeferenced Soil Database – An Improvement for International Scientific Information Exchanging

The Brazilian soils represented by this database are denominated accordingly the available classification system which follows a hierarchy based on attributes and diagnostic horizons constituting the frame of the system. All the classes of soil present properties and characteristics determining a differential behavior due to the action of formation agents on the originating material. This heterogeneity has been studied for many years in order to permit a major understanding about Brazilian soils. The classification systems allow the information organization tracking knowledge development. The classification represents the art of designing systems with some intuitive ideas about their subdivisions and priorities. In this way, it can be understood why and how soil classification systems prepared by people with varied knowledge, techniques and practical expertise differ from each other. The soil classification is still away from the improved level of development reached by the botanical or zoological classification, but relevant progress has been achieved (Resende et al., 2007). Although there isn’t a worldwide unified system available yet, attempts have been made in that direction. Among the many systems of pedological classification, the Soil Taxonomy (United States, 1975, 1999) developed in the United States must be mentioned. It constitutes the most elaborated and comprehensive system; even though, it presents some problems regarding to tropical soils (Resende et al., 2007). To allow the classification of all kinds of soil in the planet, a system with special characteristics has been continuously developed by the FAO to elaborate the map of soils of the world (FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS, 1974). In this way, there is a tendency in many countries, including Brazil, to develop their own soil classification systems keeping a coherent relation with the FAO system and the Soil Taxonomy (Resende et al., 2007). During the most intensive period of soil surveys in Brazil, there was not a consolidated soil classification system available yet. In this way, maps and pedological surveys reports

Frações de carbono em topossequências de solos sob eucalipto com diferentes históricos de uso

In Brazil, most forest stands have been planted on soils with some degree of physical, chemical or biological degradation. The protection of the trees for the soil, depending on the litter deposition, is a driving force of the restoration process of degraded areas. Since organic matter is related to many of the physical, chemical and biological soil properties, it is characterized as a key factor for the maintenance of the environmental quality of forest systems. The purpose of this study was to characterize organic matter fractions in soils with eucalyptus under minimum tillage from positions in the landscape with different histories of soil use. The study was conducted in three forest stands (FST): Terra Dura, Canafistula and Sanga das Pedras with eucalyptus in the State of Rio Grande do Sul. The soils were sampled in the layers 0-5, 5-20 and 20-40 cm. In the 0-5 cm layer of the Ultisols, most FST studied had a higher organic carbon (OC) content than in adjacent native forest. In cultivated areas, the OC storage was greatest in FST Canafistula, with, in general, lower OC levels in the footslope in relation to the other toposequence positions. In general, the humification index was greater in forests than in the crop areas, but it varied according to the soil depth, the sampled toposequence position and the FST. In the 0-5 and 5-20 cm layer, the natural abundance of 13C in FSTs was similar to the native forests, however, the 13C levels were higher in the deepest layer of the cultivated soils, indicating the contribution to soil organic matter (SOM) of C derived from the pastures that preceded eucalyptus.

Detailed soil survey of an experimental watershed representative of the Brazilian Coastal Plains and its practical application

This paper presents a detailed soil survey of an experimental watershed with representative pedoclimatic characteristics of the Coastal Plains in Espirito Santo State and its practical applications. For the pedological survey, 35 observation sites and three soil profiles were sampled and described, which were morphologically characterized and subjected to physical (particle size) and chemical analyses (routine and sulfuric acid digestion). The soil map was made using the geographic information system ArcGIS 9.3. This GIS software was also used to generate the digital elevation model (DEM) for identifying the slope classes. SAGA software was used to calculate the topographic wetness index (WI) which aided in a more accurate separation of Haplic Organosol from other soils. The predominant soil class in the watershed was the dystrophic/dystrocohesive Yellow Argisol (97%), containing morphological, chemical and physical characteristics representative of the most expressive Coastal Plains soils. Geoprocessing tools and techniques aided to make the watershed soil map.

Tropical soils characterization at low cost and time using portable X-ray fluorescence spectrometer (pXRF): Effects of different sample preparation methods

Portable X-ray fluorescence spectrometer (pXRF) has been recently adopted by the Soil Science community for uses in both field and laboratory, obtaining the total content of several chemical elements in a few seconds. Sulfuric acid digestion is an expensive and time-consuming laboratory analysis that provides contents of Fe2O3, Al2O3, SiO2, TiO2 and P2O5, important for soil studies. Due to few pXRF studies in tropical soils, this work aimed to compare contents of Fe2O3, Al2O3, SiO2, TiO2 and P2O5 obtained by pXRF with sulfuric acid digestion results, and to evaluate the effects of varying forms of preparing soil samples and scanning with pXRF on the resulting values in Brazilian soils. Soils were scanned in five conditions in-field (in situ) and in laboratory, evaluating varying sample preparation methods, particle sizes and soil moisture. Four pXRF scanning operational modes were tested. Linear regressions were adjusted between results of pXRF and sulfuric acid digestion. Equations were validated with an independent set of samples. Statistical analyses compared the methods of preparing the samples. Adequate linear models reached R2 of 0.99 and 0.89 for Fe2O3 and TiO2, respectively. Validation promoted R 2 greater than 0.97 and RMSE and ME close to zero for both oxides. Statistical differences of pXRF results were found among the methods of preparing samples. pXRF spectrometer has great potential to obtain Fe2O3 and TiO2 content rapidly and economically with high correspondence with laboratory results of sulfuric acid digestion analysis. Varying methods of preparing the samples promote differences in the results of pXRF.

Multiple linear regression and random forest to predict and map soil properties using data from portable X-ray fluorescence spectrometer (pXRF)

A determinacao de atributos do solo auxilia no correto manejo da sua fertilidade. O equipamento portatil de fluorescencia de raios-X (pXRF) foi recentemente adotado para determinar o teor total de elementos quimicos em solos, permitindo inferencias sobre atributos do solo. No entanto, esses estudos ainda sao escassos no Brasil e em outros paises. Os objetivos deste trabalho foram prever atributos do solo a partir de dados do pXRF, comparando-se os metodos de regressao linear multipla stepwise (SMLR) e de random forest (RF), alem de mapear e validar atributos do solo. 120 amostras de solo foram coletadas em tres profundidades e submetidas a analises laboratoriais. Utilizou-se o pXRF para leitura das amostras e determinou-se o teor total de elementos. A partir dos dados do pXRF, foram utilizadas SMLR e RF para predizer resultados laboratoriais, que refletem atributos do solo, e os modelos foram validados. O melhor metodo foi utilizado para espacializar os atributos do solo. Utilizando SMLR, os modelos apresentaram valores elevados de R² (≥0,8), porem maior acuracia foi obtida na modelagem com RF. A capacidade de troca de cations potencial e efetiva, materia orgânica do solo, pH, saturacao por bases e teores trocaveis de Ca, Al e Mg apresentaram ajustes adequados e predicoes acuradas com RF. Dos dez atributos do solo preditos por RF a partir de dados do pXRF, sete apresentavam CaO como a variavel mais importante para auxiliar as predicoes, seguido por P2O5, Zn e Cr. Os mapas gerados a partir de dados do pXRF usando RF apresentaram adequados valores de R² para seis atributos do solo, atingindo R2 de ate 0,83. O pXRF em associacao com RF pode ser usado para prever atributos do solo com elevada acuracia, com rapidez e a baixo custo, alem de proporcionar variaveis que auxiliam o mapeamento digital de solos.

Geomorphometric tool associated with soil types and properties spatial variability at watersheds under tropical conditions

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 generating Geomorphons at 9 radii of calculation for the watersheds. They were overlapped to detailed soil maps of the watersheds and a chi-square test was carried out to assess their relationship with soil types. Observation points were compared with the most highly correlated Geomorphons to also assess relationships with soil properties. Geomorphons with resolution of 30-m and radii of 20 and 50 cells, respectively for LCW and MCW, were more highly correlated with the variability of soil types, in accordance with the terrain features of these watersheds. The majority of observation points for each soil type was located in the same Geomorphon unit that was dominant when analyzing soil maps. There was less variability in soil properties between Geomorphon units, which was probably due to the highly weathered-leached stage of soils. Geomorphons can help to improve soil maps in tropical conditions when assessing soil variability due to its high correlation with tropical soil types variability.