Signi?cant technological advances have been few and far between in the past approximately one hundred years of soil survey activities. Perhaps one of the most innovative techniques in the history of soil survey was the introduction of aerial photographs as base maps for ?eld mapping, which replaced the conventional base map laboriously prepared by planetable and alidade. Such a relatively simple idea by today’s standards revolutionized soil surveys by vastly increasing the accuracy and ef?ciently. Yet, even this innovative approach did not gain universal acceptance immediately and was hampered by a lack of aerial coverage of the world, funds to cover the costs, and in some cases a reluctance by some soil mappers and cartog- phers to change. Digital Soil Mapping (DSM), which is already being used and tested by groups of dedicated and innovative pedologists, is perhaps the next great advancement in delivering soil survey information. However, like many new technologies, it too has yet to gain universal acceptance and is hampered by ignorance on the part of some pedologists and other scientists. DSM is a spatial soil information system created by numerical models that – count for the spatial and temporal variations of soil properties based on soil – formation and related environmental variables (Lagacheric and Mc Bratney, 2007).
Зміст
Digital Soil Mapping: A State of the Art.- Digital Soil Mapping Technologies for Countries with Sparse Data Infrastructures.- A New Global Demand for Digital Soil Information.- Development and Application of Digital Soil Mapping Within Traditional Soil Survey: What will it Grow Into?.- Soil Map Density and a Nation’s Wealth and Income.- Dealing with Limited Spatial Data Infrastructures.- Digital Soil Mapping as a Component of Data Renewal for Areas with Sparse Soil Data Infrastructures.- Challenges to Digital Soil Mapping.- Mapping Potassium Availability from Limited Soil Profile Data in Brazil.- GIS as a Support to Soil Mapping in Southern Brazil.- Experiences with Applied DSM: Protocol, Availability, Quality and Capacity Building.- Towards a Data Quality Management Framework for Digital Soil Mapping with Limited Data.- Demand-Driven Land Evaluation.- Digital Soil Mapping – Methodologies.- Diffuse Reflectance Spectroscopy as a Tool for Digital Soil Mapping.- Digital Soil Mapping at a National Scale: A Knowledge and GIS Based Approach to Improving Parent Material and Property Information.- 3D Modelling of Geology and Soils – A Case Study from the UK.- Landsat Spectral Data for Digital Soil Mapping.- From a Large to a Small Scale Soil Map: Top-Down Against Bottom-Up Approaches.- An Approach to Removing Uncertainties in Nominal Environmental Covariates and Soil Class Maps.- Digital Soil Mapping Using Logistic Regression on Terrain Parameters for Several Ecological Regions in Southern Brazil.- Purposive Sampling for Digital Soil Mapping for Areas with Limited Data.- Assessment of Land Degradation Using NASA GIMMS: A Case Study in Kenya.- Digital Soil Mapping – Examples.- Spatial-Temporal Changes in Land Cover, Soil Properties and Carbon Stocks in Rio de Janeiro.-Broad-Scale Soil Monitoring Through a Nationwide Soil-Testing Database.- Online Soil Information Systems – Recent Australian Experience.- Digital Soil Mapping Using Legacy Data in the Eden Valley, UK.- Delineating Acidified Soils in the Jizera Mountains Region Using Fuzzy Classification.- Incorporating Legacy Soil p H Databases into Digital Soil Maps.- The Digital Terrain Model as a Tool for Improved Delineation of Alluvial Soils.- Building a Digital Soil Data Base of the Solimões River Region in the Brazilian Central Amazon.- Enhancing the Use of Remotely-Sensed Data and Information for Digital Soilscape Mapping.- The Use of GIS and Digital Elevation Model in Digital Soil Mapping – A Case Study from São Paulo, Brazil.- Geomorphometric Attributes Applied to Soil-Landscapes Supervised Classification of Mountainous Tropical Areas in Brazil: A Case Study.- Digital Soil Mapping of Soil Properties in Honduras Using Readily Available Biophysical Datasets and Gaussian Processes.- Digital Mapping of Soil Classes in Rio de Janeiro State, Brazil: Data, Modelling and Prediction.- Priorities in Digital Soil Mapping.- Synthesis and Priorities for Future Work in Digital Soil Mapping.
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