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Digital Soil Mapping : Bridging Research, Environmental Application, and Operation

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Cover of 'Digital Soil Mapping : Bridging Research, Environmental Application, and Operation'

Table of Contents

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    Book Overview
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    Chapter 1 Current State of Digital Soil Mapping and What Is Next
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    Chapter 2 Environmental Covariates for Digital Soil Mapping in the Western USA
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    Chapter 3 A Generalized Additive Soil Depth Model for a Mountainous Semi-Arid Watershed Based Upon Topographic and Land Cover Attributes
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    Chapter 4 Applying Geochronology in Predictive Digital Mapping of Soils
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    Chapter 5 Scale Effects on Terrain Attribute Calculation and Their Use as Environmental Covariates for Digital Soil Mapping
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    Chapter 6 Conditioned Latin Hypercube Sampling: Optimal Sample Size for Digital Soil Mapping of Arid Rangelands in Utah, USA
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    Chapter 7 Using Proximal Soil Sensors for Digital Soil Mapping
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    Chapter 8 The Use of Hyperspectral Imagery for Digital Soil Mapping in Mediterranean Areas
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    Chapter 9 Automatic Interpretation of Quickbird Imagery for Digital Soil Mapping, North Caspian Region, Russia
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    Chapter 10 ASTER-Based Vegetation Map to Improve Soil Modeling in Remote Areas
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    Chapter 11 Digital Soil Boundary Detection Using Quantitative Hydrologic Remote Sensing
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    Chapter 12 Homosoil, a Methodology for Quantitative Extrapolation of Soil Information Across the Globe
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    Chapter 13 Artificial Neural Network and Decision Tree in Predictive Soil Mapping of Hoi Num Rin Sub-Watershed, Thailand
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    Chapter 14 Evaluation of the Transferability of a Knowledge-Based Soil-Landscape Model
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    Chapter 15 Random Forests Applied as a Soil Spatial Predictive Model in Arid Utah
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    Chapter 16 Two Methods for Using Legacy Data in Digital Soil Mapping
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    Chapter 17 Mapping Heavy Metal Content in Soils with Multi-Kernel SVR and LiDAR Derived Data
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    Chapter 18 Mapping the CN Ratio of the Forest Litters in Europe-Lessons for Global Digital Soil Mapping
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    Chapter 19 Spatial Prediction and Uncertainty Assessment of Soil Organic Carbon in Hebei Province, China
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    Chapter 20 Estimating Soil Organic Matter Content by Regression Kriging
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    Chapter 21 Digital Soil Mapping of Topsoil Organic Carbon Content of Rio de Janeiro State, Brazil
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    Chapter 22 Comparing Decision Tree Modeling and Indicator Kriging for Mapping the Extent of Organic Soils in Denmark
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    Chapter 23 Modeling Wind Erosion Events – Bridging the Gap Between Digital Soil Mapping and Digital Soil Risk Assessment
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    Chapter 24 Soilscapes Basis for Digital Soil Mapping in New Zealand
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    Chapter 25 Legacy Soil Data Harmonization and Database Development
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    Chapter 26 Toward Digital Soil Mapping in Canada: Existing Soil Survey Data and Related Expert Knowledge
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    Chapter 27 Predictive Ecosystem Mapping (PEM) for 8.2 Million ha of Forestland, British Columbia, Canada
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    Chapter 28 Building Digital Soil Mapping Capacity in the Natural Resources Conservation Service: Mojave Desert Operational Initiative
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    Chapter 29 A Qualitative Comparison of Conventional Soil Survey and Digital Soil Mapping Approaches
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    Chapter 30 Applying the Optimum Index Factor to Multiple Data Types in Soil Survey
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    Chapter 31 U.S. Department of Agriculture (USDA) TEUI Geospatial Toolkit: An Operational Ecosystem Inventory Application
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    Chapter 32 Predictive Soil Maps Based on Geomorphic Mapping, Remote Sensing, and Soil Databases in the Desert Southwest
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    Chapter 33 GlobalSoilMap.net – A New Digital Soil Map of the World
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    Chapter 34 Methodologies for Global Soil Mapping
Attention for Chapter 10: ASTER-Based Vegetation Map to Improve Soil Modeling in Remote Areas
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Citations

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Summary Dimensions citations
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Chapter title
ASTER-Based Vegetation Map to Improve Soil Modeling in Remote Areas
Chapter number 10
Book title
Digital Soil Mapping
Published by
Springer, Dordrecht, January 2010
DOI 10.1007/978-90-481-8863-5_10
Book ISBNs
978-9-04-818862-8, 978-9-04-818863-5
Authors

E. Meirik, B. Frazier, D. Brown, P. Roberts, R. Rupp, Meirik, E., Frazier, B., Brown, D., Roberts, P., Rupp, R.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 9%
Unknown 10 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 45%
Professor > Associate Professor 2 18%
Researcher 2 18%
Student > Bachelor 1 9%
Student > Master 1 9%
Other 0 0%
Readers by discipline Count As %
Environmental Science 4 36%
Earth and Planetary Sciences 3 27%
Agricultural and Biological Sciences 2 18%
Unknown 2 18%

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