Digital soil mapping : bridging research, production, and environmental application
著者
書誌事項
Digital soil mapping : bridging research, production, and environmental application
(Progress in soil science / series editors: Alfred E. Hartemink and Alex B. McBratney, 2)
Springer, 2010
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
Other editors: D.W. Howell, A.C.Moore, A.E.Hartemink and S. Kienast-Brown
内容説明・目次
内容説明
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.
目次
Current State of Digital Soil Mapping and What Is Next.- Research.- Environmental Covariates for Digital Soil Mapping in the Western USA.- A Generalized Additive Soil Depth Model for a Mountainous Semi-Arid Watershed Based Upon Topographic and Land Cover Attributes.- Applying Geochronology in Predictive Digital Mapping of Soils.- Scale Effects on Terrain Attribute Calculation and Their Use as Environmental Covariates for Digital Soil Mapping.- Conditioned Latin Hypercube Sampling: Optimal Sample Size for Digital Soil Mapping of Arid Rangelands in Utah, USA.- Using Proximal Soil Sensors for Digital Soil Mapping.- The Use of Hyperspectral Imagery for Digital Soil Mapping in Mediterranean Areas.- Automatic Interpretation of Quickbird Imagery for Digital Soil Mapping, North Caspian Region, Russia.- ASTER-Based Vegetation Map to Improve Soil Modeling in Remote Areas.- Digital Soil Boundary Detection Using Quantitative Hydrologic Remote Sensing.- Homosoil, a Methodology for Quantitative Extrapolation of Soil Information Across the Globe.- Artificial Neural Network and Decision Tree in Predictive Soil Mapping of Hoi Num Rin Sub-Watershed, Thailand.- Evaluation of the Transferability of a Knowledge-Based Soil-Landscape Model.- Random Forests Applied as a Soil Spatial Predictive Model in Arid Utah.- Two Methods for Using Legacy Data in Digital Soil Mapping.- Environmental Application and Assessment.- Mapping Heavy Metal Content in Soils with Multi-Kernel SVR and LiDAR Derived Data.- Mapping the CN Ratio of the Forest Litters in Europe-Lessons for Global Digital Soil Mapping.- Spatial Prediction and Uncertainty Assessment of Soil Organic Carbon in Hebei Province, China.- Estimating Soil Organic Matter Content by Regression Kriging.- Digital Soil Mapping of Topsoil Organic Carbon Content of Rio de Janeiro State, Brazil.- Comparing Decision Tree Modeling and Indicator Kriging for Mapping the Extent of Organic Soils in Denmark.- Modeling Wind Erosion Events - Bridging the Gap Between Digital Soil Mapping and Digital Soil Risk Assessment.- Making Digital Soil Mapping Operational.- Soilscapes Basis for Digital Soil Mapping in New Zealand.- Legacy Soil Data Harmonization and Database Development.- Toward Digital Soil Mapping in Canada: Existing Soil Survey Data and Related Expert Knowledge.- Predictive Ecosystem Mapping (PEM) for 8.2 Million ha of Forestland, British Columbia, Canada.- Building Digital Soil Mapping Capacity in the Natural Resources Conservation Service: Mojave Desert Operational Initiative.- A Qualitative Comparison of Conventional Soil Survey and Digital Soil Mapping Approaches.- Applying the Optimum Index Factor to Multiple Data Types in Soil Survey.- U.S. Department of Agriculture (USDA) TEUI Geospatial Toolkit: An Operational Ecosystem Inventory Application.- Predictive Soil Maps Based on Geomorphic Mapping, Remote Sensing, and Soil Databases in the Desert Southwest.- GlobalSoilMap.net - A New Digital Soil Map of the World.- Methodologies for Global Soil Mapping.
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