This book contains papers presented at the 6th Global Workshop on Digital Soil Mapping, held 11-14 November 2014 at the Institute of Soil Science, Chinese Academy of Sciences of Nanjing, China. Digital soil mapping is advancing on different fronts at different paces throughout the world. The researches and applications on DSM are moving from method development to realizations in different scales and regions, serving the generation of national and continental to global soil grids. Meanwhile, new ideas and insights on mapping complex soil-landscapes such as flat plains,anthropogenically altered agriculture and urban spaces are emerging, with the help of new paradigms and models.The goal of the sixth workshop was to review and discuss the state of the art in digital soil mapping, and to explore strategies for bridging research, production, and environmental applications.
This book provides a very useful and comprehensive overview of the status of digital soil mapping, in which graduate students, scientists and specialists working within the field of geography can find the spatial prediction approaches and related theory.
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Part I Digital Soil Modelling |
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1 Digital Soil Mapping Across Paradigms, Scales, and Boundaries: A Review |
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3 | (8) |
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2 Spatial Prediction of Soil Antibiotics Based on High-Accuracy Surface Modeling |
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11 | (10) |
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3 Incorporating Probability Density Functions of Environmental Covariates Related to Soil Class Predictions |
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21 | (12) |
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4 Mapping Horizontal and Vertical Spatial Variability of Soil Salinity in Reclaimed Areas |
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33 | (14) |
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5 Mapping Soil Organic Matter in Low-Relief Areas Based on Time Series Land Surface Diurnal Temperature Difference |
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47 | (16) |
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6 Mapping Soil Thickness by Integrating Fuzzy C-Means with Decision Tree Approaches in a Complex Landscape Environment |
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63 | (14) |
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7 Multivariate Sampling Design Optimization for Digital Soil Mapping |
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77 | (12) |
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8 Applying Artificial Neural Networks Utilizing Geomorphons to Predict Soil Classes in a Brazilian Watershed |
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89 | (14) |
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9 Comparison of Traditional and Geostatistical Methods to Estimate and Map the Carbon Content of Scottish Soils |
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103 | (12) |
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Part II Environmental Application and Assessment |
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10 Digital Soil Mapping for Hydrological Modelling |
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115 | (16) |
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11 Some Challenges on Quantifying Soil Property Predictions Uncertainty for the GlobalSoilMap Using Legacy Data |
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131 | (10) |
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12 Spatial Assessment of Soil Organic Carbon Using Bayesian Maximum Entropy and Partial Least Square Regression Model |
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141 | (12) |
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13 Estimation of the Actual and Attainable Terrestrial Carbon Budget |
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153 | (12) |
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14 The Meta Soil Model---An Integrative Framework to Model Soil Carbon Across Various Ecosystems and Scales |
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165 | (16) |
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15 Example of Bayesian Uncertainty for Digital Soil Mapping |
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181 | (14) |
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16 An Unsupervised Fuzzy Clustering Approach for the Digital Mapping of Soil Organic Carbon in a Montaneous Region of China |
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195 | (10) |
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17 Application of Digital Soil Mapping Techniques to Refine Soil Map of Baringo District, Rift Valley Province, Kenya |
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205 | (14) |
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18 Predictive Mapping of Soil Organic Matter at a Regional Scale Using Local Topographic Variables: A Comparison of Different Polynomial Models |
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219 | (14) |
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19 Estimating Soil Carbon Sequestration Potential in Fine Particles of Top Soils in Hebei Province, China |
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233 | (16) |
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Part III Soil Sensors and Legacy Data |
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20 Digital Soil Morphometries via a Low-Cost Radiometer for Estimating Soil Organic Carbon and Texture |
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249 | (10) |
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Ricardo Simao Diniz Dalmolin |
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Bruno Fellipe Bottega Boesing |
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21 Transferability and Scaling of VNIR Prediction Models for Soil Total Carbon in Florida |
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259 | (16) |
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22 Digital Soil Resource Inventories: Status and Prospects in 2015 |
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275 | (12) |
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23 Evaluating the Relative Importance of Legacy Soil Sampling and Spatial Models in Digital Soil Mapping Performances: A Case Study in Languedoc-Roussillon (Southern France) |
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287 | (4) |
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24 Improved Soil Mapping in British Columbia, Canada, with Legacy Soil Data and Random Forest |
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291 | (14) |
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25 Disaggregation of Legacy Soil Maps to Produce a Digital Soil Attribute Map for the Okanagan Basin, British Columbia, Canada |
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305 | (14) |
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26 Comparison of Different Strategies for Predicting Soil Organic Matter of a Local Site from a Regional Vis-NIR Soil Spectral Library |
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319 | (12) |
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27 Variations for the Implementation of SCORPAN's "S" |
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331 | (12) |
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28 Monitoring Ecological Environment in Nansi Lake Area Using Remote Sensing |
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343 | (8) |
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29 Extraction and Integration of Different Soil Nutrient Grading Systems for Soil Nutrient Mapping |
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351 | |
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Dr. Gan-Lin Zhang graduated from Huazhong Agricultural University in 1987, with the Bachelor of Agronomy and obtained his PhD of Soil Science from Institute of Soil Science, Chinese Academy of Sciences in 1993. He was promoted as professor of soil science in 2001. His research fields cover soil genesis, soil classification, soil mapping and soil evaluation. He is a grantee of the Distinguished Young Scientist Fund of the National Natural Science Foundation. He served as the Vice-Chair and the Chair of the Commission of Soil Genesis, International Union of Soil Science (C1.3, IUSS) during 2002 and 2014. He is now the vice-chair of the Working Group of Soils of Urban, Industrial, Traffic and Mining Areas (SUITMA), IUSS. He also served the Chair of the Committee of Soil Genesis, Classification and Geography (2004-2012), Soil Science Society of China. He is currently on the editorial board of Geoderma, Soil Use and Management, Science China (Earth Science), Acta Pedologica Sinica and Arid Zone Research. He is the leader of the East Asian Node of GlobalSoilMap.net Project and a member of the FAO Intergovernmental Technical Panel on Soil (ITPS). He has authored (co-authored) a number of books and book chapters as well as more than 300 papers in Chinese and international peer-reviewed journals, covering soil genesis, soil classification, soil mapping, soil information system and soil quality evaluation, as well as urban soil and environment.
Dick J. Brus has studied geology and physical geography. He works at Wageningen University and Research Centre for 32 years. After his work on the geomorphological mapping of the Netherlands at scale 1:50,000 and on the Dutch Soil Classification System, in 1990 he moved to the field of pedometrics. His main fields of interest are sampling theory, geostatistics, (generalized) linear regression analysis and uncertainty analysis. He has rich research experiences in developing and applying statistical methods fornatural resources inventory and monitoring. He has published numerous papers in peer-reviewed, international journals on these topics. He is second co-author of the book Sampling for Natural Resource Monitoring, published in 2006 by Springer. This book is widely acclaimed in soil, earth, environmental, agriculture, and statistical sciences. He was the Vice-chair of the International Union of Soil Science commission Pedometrics. He was awarded Best Paper on Pedometrics in 1996, 2004 and 2011 by the Pedometrics Commission of the International Union for Soil Science (IUSS). In 2014 he was granted by the Chinese Academy of Science a Visiting Professorship for Senior International Scientists.
Dr. Feng Liu is working as an associate professor in soil geography, Department of Soil Resources and Remote Sensing Applications, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China. His work on soils started with his PhD thesis on predictivesoil mapping over low relief areas such as plains and gently undulating terrains. His research interest and projects focus on this topic. He is a member of the advisory board for the Pedometrics Commission, for the period of 2014-2018. He obtained his MSc degree from the Department of Geography, University of Lanzhou, and his PhD degree from the Institute of Geographical Sciences and Natural resources, Chinese Academy of Sciences. He had done one-year soil mapping work as a visiting scholar in the group of Canadian Soil Information System (CanSIS) at Ottawa.
Dr. Xiao-Dong Song is working as an assistant professor in soil geography, Department of Soil Resources and Remote Sensing Applications, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China. He completed his PhD in soil science in 2013 at Nanjing Normal University. He was awarded Doctoral National Scholarship in 2013.
Philippe Lagacherie trained as an Agronomist and completed his PhD in soil science in 1992. He obtained his senior scientist degree from Montpellier 2 University in 2002 for his researches on digital soil mapping methods. He is currently senior researcher at INRA Montpellier (France) and lead a research team of the LISAH research unit entitled spatial structures and dynamics of the cultivated landscapes. Dr Philippe Lagacherie has been involved in research dealing with Digital Soil Mapping, remote sensing and spatial modelling of cultivated landscapes. He developed spatial approaches that associated field knowledge, GIS, remote sensing, geostatistics, and fuzzy logic. He organised the first international workshop on Digital Soil mapping in Montpellier (2004) and is the co-editor of the first book on Digital Soil Mapping published in 2007. He has conducted several research projects at the crossroad of soil, agronomy and hydrology. Dr Philippe Lagacherie has been nominated in the editorial boards of Geoderma and Int. J. of Earth Observation and Geo-information.