Digital Soil Mapping

Digital Soil Mapping is the creation and the population of a geographically referenced soil database. It is generated at a given resolution by using field and laboratory observation methods coupled with environmental data through quantitative relationships. Digital soil mapping is advancing on different fronts at different rates all across the world. This book presents the state-of-the art and explores strategies for bridging research, production, and environmental application of digital soil mapping.It includes examples from North America, South America, Europe, Asia, and Australia. The chapters address the following topics:- evaluating and using legacy soil data- exploring new environmental covariates and sampling schemes - using integrated sensors to infer soil properties or status - innovative inference systems predicting soil classes, properties, and estimating their uncertainties- using digital soil mapping and techniques for soil assessment and environmental application - protocol and capacity building for making digital soil mapping operational around the globe.

Introduction
Current State of Digital Soil Mapping and What Is Next	p. 3
Research
Environmental Covariates and Soil Sampling
Environmental Covariates for Digital Soil Mapping in the Western USA	p. 17
A Generalized Additive Soil Depth Model for a Mountainous Semi-Arid Watershed Based Upon Topographic and Land Cover Attributes	p. 29
Applying Geochronology in Predictive Digital Mapping of Soils	p. 43
Scale Effects on Terrain Attribute Calculation and Their Use as Environmental Covariates for Digital Soil Mapping	p. 55
Conditioned Latin Hypercube Sampling: Optimal Sample Size for Digital Soil Mapping of Arid Rangelands in Utah, USA	p. 67
Soil Sensors and Remote Sensing
Using Proximal Soil Sensors for Digital Soil Mapping	p. 79
The Use of Hyperspectral Imagery for Digital Soil Mapping in Mediterranean Areas	p. 93
Automatic Interpretation of Quickbird Imagery for Digital Soil Mapping, North Caspian Region, Russia	p. 103
ASTER-Based Vegetation Map to Improve Soil Modeling in Remote Areas	p. 113
Digital Soil Boundary Detection Using Quantitative Hydrologic Remote Sensing	p. 123
Soil Inference Systems
Homosoil, a Methodology for Quantitative Extrapolation of Soil Information Across the Globe	p. 137
Artificial Neural Network and Decision Tree in Predictive Soil Mapping of Hoi Num Rin Sub-Watershed, Thailand	p. 151
Evaluation of the Transferability of a Knowledge-Based Soil-Landscape Model	p. 165
Random Forests Applied as a Soil Spatial Predictive Model in Arid Utah	p. 179
Two Methods for Using Legacy Data in Digital Soil Mapping	p. 191
Environmental Application and Assessment
Mapping Heavy Metal Content in Soils with Multi-Kernel SVR and LiDAR Derived Data	p. 205
Mapping the CN Ratio of the Forest Litters in Europe-Lessons for Global Digital Soil Mapping	p. 217
Spatial Prediction and Uncertainty Assessment of Soil Organic Carbon in Hebei Province, China	p. 227
Estimating Soil Organic Matter Content by Regression Kriging	p. 241
Digital Soil Mapping of Topsoil Organic Carbon Content of Rio de Janeiro State, Brazil	p. 255
Comparing Decision Tree Modeling and Indicator Kriging for Mapping the Extent of Organic Soils in Denmark	p. 267
Modeling Wind Erosion Events - Bridging the Gap Between Digital Soil Mapping and Digital Soil Risk Assessment	p. 281
Making Digital Soil Mapping Operational
Soilscapes Basis for Digital Soil Mapping in New Zealand	p. 297
Legacy Soil Data Harmonization and Database Development	p. 309
Toward Digital Soil Mapping in Canada: Existing Soil Survey Data and Related Expert Knowledge	p. 325
Predictive Ecosystem Mapping (PEM) for 8.2 Million ha of Forestland, British Columbia, Canada	p. 337
Building Digital Soil Mapping Capacity in the Natural Resources Conservation Service: Mojave Desert Operational Initiative	p. 357
A Qualitative Comparison of Conventional Soil Survey and Digital Soil Mapping Approaches	p. 369
Applying the Optimum Index Factor to Multiple Data Types in Soil Survey	p. 385
US. Department of Agriculture (USDA) TEUI Geospatial Toolkit: An Operational Ecosystem Inventory Application	p. 399
Predictive Soil Maps Based on Geomorphic Mapping, Remote Sensing, and Soil Databases in the Desert Southwest	p. 411
GlobalSoilMap.net - A New Digital Soil Map of the World	p. 423
Methodologies for Global Soil Mapping	p. 429
Index	p. 437
Table of Contents provided by Ingram. All Rights Reserved.

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