Integration of morphometric attributes and remote sensing in pedological cartography in the national park Brasilia, Federal District

Os levantamentos convencionais de solos requerem investimentos elevados em tempo e recursos. No entanto, o mapeamento do solo pode ser obtido por correlação com outros fatores ambientais, especialmente com o material de origem, o relevo e a vegetação. O presente artigo possui como objetivo desenvolver uma metodologia de mapeamento pedológico no Parque Nacional de Brasília, utilizando técnicas de sensoriamento remoto e sistema de informação geográfica. O mapa de solos foi obtido pela integração dos atributos de terreno e das classes de vegetação. A classificação das unidades de relevo foi feita pelo método de árvore de decisão, a partir dos atributos de terreno. A vegetação do Cerrado demonstrou uma alta correlação com os tipos de solo e são fundamentais para descrever zonas saturadas da paisagem e de seus solos correspondentes. A integração dos atributos do relevo e da vegetação obteve uma alta correlação com o mapa de solos existente. A metodologia utilizada permitiu um aprimoramento dos limites das unidades de solo. _________________________________________________________________________________ ABSTRACTThe conventional land surveying requires long time and high costs. However, the soil mapping can be obtained by correlation with other environmental factors, especially with the parent material, relief and vegetation. This paper aims to develop a methodology for pedological mapping in Brasilia National Park using remote sensing and geographic information system. The soil map was obtained by integration of terrain attributes and vegetation classes. The classification of relief units was made by the decision tree method, from terrain attributes. Cerrado vegetation showed a high correlation with the soil types and is essential to describe the saturation of the landscape areas and their corresponding soils. The integration of relief and vegetation attributes obtained a high correlation with the existing soil map. The methodology allowed an improvement for soil unit cartographic delimitation

INTEGRAÇÃO DE ATRIBUTOS MORFOMÉTRICOS E SENSORIAMENTO REMOTO NA CARTOGRAFIA PEDOLÓGICA DO PARQUE NACIONAL DE BRASÍLIA, DISTRITO FEDERAL

The conventional land surveying requires long time and high costs. However, the soil mapping can be obtained by correlation with other environmental factors, especially with the parent material, relief and vegetation. This paper aims to develop a methodology for pedological mapping in Brasilia National Park using remote sensing and geographic information system. The soil map was obtained by integration of terrain attributes and vegetation classes. The classification of relief units was made by the decision tree method, from terrain attributes. Cerrado vegetation showed a high correlation with the soil types and is essential to describe the saturation of the landscape areas and their corresponding soils. The integration of relief and vegetation attributes obtained a high correlation with the existing soil map. The methodology allowed an improvement for soil unit cartographic delimitation.Os levantamentos convencionais de solos requerem investimentos elevados em tempo e recursos. No entanto, o mapeamento do solo pode ser obtido por correlação com outros fatores ambientais, especialmente com o material de origem, o relevo e a vegetação. O presente artigo possui como objetivo desenvolver uma metodologia de mapeamento pedológico no Parque Nacional de Brasília, utilizando técnicas de sensoriamento remoto e sistema de informação geográfica. O mapa de solos foi obtido pela integração dos atributos de terreno e das classes de vegetação. A classificação das unidades de relevo foi feita pelo método de árvore de decisão, a partir dos atributos de terreno. A vegetação do Cerrado demonstrou uma alta correlação com os tipos de solo e são fundamentais para descrever zonas saturadas da paisagem e de seus solos correspondentes. A integração dos atributos do relevo e da vegetação obteve uma alta correlação com o mapa de solos existente. A metodologia utilizada permitiu um aprimoramento dos limites das unidades de solo

DIGITAL SOIL MAPPING FOR SMART AGRICULTURE: THE SOLIM METHOD AND SOFTWARE PLATFORMS

The key challenges faced by many of the existing digital soil mapping (DSM) techniques are the rigid requirements on the size of soil samples to extract the relationships needed and on the stationarity of the extracted relationships. These requirements limit the application of these DSM techniques. This paper provides an overview of the SoLIM approach and an introduction to the operation of SoLIM through the software platforms available. SoLIM is based on the Third Law of Geography, which calls for the comparison of similarity in geographic (environmental) configuration of a prototype and an unsampled location and then use this similarity to predict the value of a soil property at a given location. DSM under SoLIM approach removes requirements on the sample size and the stationarity assumption. In addition, the uncertainty computed based on the similarities can be used to improve the efficiency of error reduction efforts. The SoLIM approach has been implemented in two platforms: SoLIM Solutions and CyberSoLIM. The theoretical foundation and the availability of software platforms under SoLIM make DSM possible and convenient over large and complex geographic regions

Modeling the spatial distribution of soil organic carbon and carbon stocks in the Casanare flooded savannas of the Colombian Llanos

Abstract Flooded savannas are valuable and extensive ecosystems in South America, but not widely studied. In this study, we quantify the spatial distribution of soil organic carbon (SOC) content and stocks in the Casanare flooded savannas. We sampled 80 sites at two soil-depth intervals (0-10 and 10-30 cm), where SOC values ranged from 0.41% in the surface and 0.23% in the sub-surface of drier soils to over 14.50% and 7.51%, in soils that experienced seasonal flooding. Spatial predictions of SOC were done through two digital soil mapping (DSM) approaches: Expert-Knowledge (EK) and Random-Forest (RF). Although both approaches performed well, EK was slightly superior at predicting SOC. Covariates derived from vegetation cover, topography, and soil properties were identified as key drivers in controlling its distribution. Total SOC stocks were 55.07 Mt with a mean density of 83.1±24.3 t·ha -1 in the first 30 cm of soil, with 12.3% of this located in areas that experience long periods of flooding (semi-seasonal savannas) , which represented only 7.9% of the study area (664,752 ha). Although the study area represents only 15% of the total area of the Casanare department, the intensive pressure of human development could result in the reduction of its SOC stocks and the release of important amounts of greenhouse gases into the atmosphere. At regional level, the impact of a large-scale land use conversions of the flooded Llanos del Orinoco ecosystem area (15 Mha) could transform this area in a future source of important global emissions if correct decisions are not taken regarding the land management of the region

Digital soil mapping, downscaling and updating conventional soil maps using GIS, RS, statistics and auxiliary data

Spatial distribution of soil types and soil properties in the landscape are important in many environmental researches. Conventional soil surveys are not designed to provide the high-resolution soil information required in environmental modelling and site-specific farm management. The objectives of this study were to investigate the relationship between soil development, soil evolution in the landscape, updating legacy soil maps and pedodiversity in an arid and semi-arid region. The application of Digital Soil Mapping (DSM) techniques was investigated with a particular focus to predict soil taxonomic classes and spatial distribution of soil types by soil observations and covariate sets representative of s,c,o,r,p,a,n factors. In the first study, focus is on establishing relationships between pedodiversity and landform evolution in a 86,000 ha region in Borujen, Chaharmahal-Va-Bakhtiari Province, Central Iran. From an overview study, we could conclude that landform evolution was mainly affected by topography and its components. A second study compares various DSM-methods and a conventional soil mapping approach for soil class maps in terms of accuracy, information value and cost in central Iran. Also, the effects of different sample sizes were investigated. Our results demonstrated that in most predicted maps, in DSM approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map. Furthermore, results showed that the conventional soil mapping approach was not as effective as DSM approach. In the third study, different models of the DSM approach were compared to predict the spatial distribution of some important soil properties such as clay content, soil organic carbon and calcium carbonate content. Among all studied models, the terrain attribute “elevation” is the most important variable to predict soil properties. Random forest had promising performance to predict soil organic carbon. But results revealed that all models could not predict the spatial distributions of clay content properly. The minimum area of land that can be legibly delineated in a traditional (printed) map is highly dependent upon mapping scale. For example, this area at a mapping scale of 1:24,000 is about 2.3 ha but at a mapping scale of 1:1,000,000 it is about 1000 ha. A mapping scale of 1:1,000,000 is just too coarse to show a fine-scale pattern or soil type with any degree of legibility, but finer-scale soil maps are more expensive and time-consuming to produce. Thus, spatial variation is often unavoidably obscured. The fourth study of this dissertation focuses on downscaling and updating soil map methods. Thus, the objectives were to apply supervised and unsupervised disaggregation approaches to disaggregate soil polygons of conventional soil map at a scale of 1: 1,000,000 in the selected area. Therefore, soil subgroups and great groups were selected because it is a basic taxonomic level in regional and national soil maps in Iran. In general, we conclude that DSM approach and also disaggregation approach are capable to predict soil types and properties, produce and update legacy soil maps. However, still a number of challenges need to be evaluated e.g. influence of expert knowledge on CSM approach, resolution of ancillary data, georeferenced legacy soil samples data to validate disaggregated soil maps

Status and Prospect of Soil Information in South-eastern Europe: Soil Databases, Projects and Applications

This report was produced as a summary report of the JRC’s European Soil Bureau Network workshop that was held at the Faculty of Agriculture in Zagreb, Croatia in period from 28-30 of September 2006. The objective of this workshop was to gather key players in the development and/or implementation of soil protection policy, soil survey, soil monitoring and soil information systems and discuss further strengthening of collaborations between the countries of south-eastern Europe and JRC.JRC.H.7-Land management and natural hazard