Digital Soil Assessments and Beyond
Proceedings of the 5th Global Workshop on Digital Soil Mapping 2012, Sydney, Australia
By: Budiman Minasny (Editor), Brendan P. Malone (Editor), Alex B. McBratney (Editor)
Hardcover | 24 July 2012 | Edition Number 1
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482 Pages
25.4 x 17.8 x 3.81
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Digital soil assessments and beyond contains papers presented at the 5th Global Workshop on Digital Soil Mapping, held 10-13 April 2012 at the University of Sydney, Australia. The contributions demonstrate the latest developments in digital soil mapping as a discipline with a special focus on the use of map products to drive policy decisions particularly on climate change and food, water and soil security. The workshop and now this resulting publication have better united formerly disparate subdisciplines in soil science: pedology (study of the formation, distribution and potential use of soils) and pedometrics (quantitative and statistical analysis of soil variation in space and time). This book compiles papers covering a range of topics: digital soil assessment, digital soil modelling, operational soil mapping, soil and environmental covariates, soil sampling and monitoring and soil information modelling, artificial intelligence and cyber-infrastructure, and GlobalSoilMap. Digital soil assessments and beyond aims to encourage new mapping incentives and stimulate new ideas to make digital soil mapping practicable from local to national and ultimately global scales.
Foreword | p. xi |
Preface | p. xiii |
Sponsors | p. xv |
Digital soil assessments | |
Digital soil assessment: Guiding irrigation expansion in Tasmania, Australia | p. 3 |
Frameworks for digital soil assessment | p. 9 |
Soil natural capital definition using land evaluation principles | p. 15 |
Spatial modeling of human exposure to soil contamination-an example of digital soil assessment | p. 19 |
A pedometric approach to valuing the soil resource | p. 25 |
Development of terrons for the Lower Hunter Valley wine-growing region | p. 31 |
Spatial agricultural soil quality evaluation based on digital soil maps and uncertainty analysis | p. 37 |
Digital soil mapping in the environment | |
High resolution soil moisture mapping | p. 45 |
Soil carbon density under eucalypt forests in Australia | p. 53 |
Spatial prediction of biological soil crust classes: Value added DSM from soil survey | p. 57 |
Modelling the effect of soil type and grazing on nitrogen cycling in a tropical grazing system | p. 61 |
A digital soil map of Phytophthora cinnamomi in the Gondwana Rainforests of eastern Australia | p. 65 |
Modelling soil-regolith thickness in complex weathered landscapes of the central Mt Lofty Ranges, South Australia | p. 69 |
Exploring short-term soil landscape formation in the Hunter Valley, NSW, using gamma ray spectrometry | p. 77 |
Spatial variability of the active layer, permafrost, and soil profile depth in Alaskan soils | p. 83 |
Soil maps, legacy data & covariates | |
Updating legacy soil data for digital soil mapping | p. 91 |
Harmonization of legacy soil maps in North America: Status, trends, and implications for digital soil mapping efforts | p. 97 |
Cross-regional digital soil carbon modeling in two contrasting soil-ecological regions in the US | p. 103 |
Which covariates are needed for soil carbon models in Florida? | p. 109 |
A pragmatic quantitative model for soil organic carbon distribution in eastern Australia | p. 115 |
Spatial resolution effects of remote sensing images on digital soil models in aquatic ecosystems | p. 121 |
Digital soil modelling | |
The potential role of pedogenesis modelling in digital soil mapping | p. 129 |
Some methods regarding manipulations of scale for digital soil mapping | p. 135 |
Scale-specific control of soil water storage using multivariate empirical mode decomposition | p. 139 |
Mapping the occurrence and thickness of soil horizons within soil profiles | p. 145 |
Spatial prediction of soil organic carbon of Crete by using geostatistics | p. 149 |
Predicting soil organic carbon using mixed conceptual and geostatistical models | p. 155 |
Spatial stochastic modeling of topsoil organic carbon content over a cultivated peri-urban region, using soil properties, soil types and a digital elevation model | p. 161 |
Soil climate indicators from the Geographically Explicit Newhall Simulation Model (GEN) as potential environmental covariates in digital soil mapping applications | p. 167 |
Digital mapping of phosphorus status using soil test and geophysical data | p. 173 |
Uncertainty estimation for weighted-means digital soil maps | p. 179 |
Digital mapping of soil classes | |
Digital soil-class mapping across the Edgeroi district using numerical clustering and gamma-ray spectrometry data | p. 187 |
Digital soil mapping: Strategy for data pre-processing | p. 193 |
Digital soil mapping of soil classes using decision trees in central Iran | p. 197 |
Fuzzy disaggregation of conventional soil maps using database knowledge extraction to produce soil property maps | p. 203 |
Towards a model for predicting soil classes in low relief and deeply weathered landscapes of the Northern Territory | p. 209 |
Use of weights of evidence statistics to define inference rules to disaggregate soil survey maps | p. 215 |
Sampling and monitoring in DSM | |
The effect of preferential sampling on sampling variance | p. 223 |
A conditioned Latin hypercube sampling algorithm incorporating operational constraints | p. 227 |
Soil survey design for management-scale digital soil mapping in a mountainous southern Philippine catchment | p. 233 |
Spatial and temporal prediction of soil properties from legacy data | p. 239 |
Mapping the temporal change of soil carbon: A case study from northern New South Wales, Australia | p. 245 |
Number of sampling points influences the parameters of soil properties spatial distribution and kriged maps | p. 251 |
Digital Soil Mapping to inform design-based sampling strategies for estimating total organic carbon stocks at the farm scale | p. 257 |
Cyber infrastructure & expert system in DSM | |
OneGeology-Improving global access to geoscience | p. 265 |
Multi-scale feature data and landscape analysis toolkit for predictive soil mapping | p. 271 |
The LIFE+ SOILCONSWEB project: A web based spatial decision support system embedding DSM engines | p. 277 |
The role of soil inference systems in digital soil assessments | p. 281 |
Worldgrids-a public repository of global soil covariates | p. 287 |
Digital Soil Map data in an on-line, on-demand world | p. 293 |
Operational DSM | |
Digital Soil Mapping in a changing world | p. 301 |
Digital soil mapping in Ontario, Canada: An example using high resolution LiDAR | p. 307 |
Using Pedotransfer functions for estimating soil pH and bulk density at regional scale | p. 313 |
Soil-landscape models to predict soil pH variation in the Subang region of West Java, Indonesia | p. 317 |
Mapping the presence of red clay subsoil in the Driftless area of Wisconsin, USA | p. 325 |
Modelling the distribution of organic carbon in the soils of Chile | p. 329 |
Rapid soil mapping under restrictive conditions in Tete, Mozambique | p. 335 |
High resolution 3D mapping for soil organic carbon assessment in a rural landscape | p. 341 |
Seasonal soil salinity monitoring in oasis ecosystems by EM conductivity | p. 347 |
Downscaling for site-specific crop management needs? | p. 353 |
Estimation of soil organic carbon stock in subtropical forest region based on digital soil map in Taiwan | p. 357 |
Proximal, remote sensing and spectroscopy of soil | |
Mapping surface soil mineralogy using hyperspectral and ASTER imagery: An example from Mullewa, Western Australia | p. 365 |
Retrieval of composite mineralogy by VNIR spectroscopy | p. 373 |
Organic matter prediction for Korean soils using visible-near infrared reflectance spectroscopy | p. 377 |
A novel spectro-temporal approach for predicting soil physical properties | p. 381 |
Using Vis-NIR hyperspectral data to map topsoil properties over bare soils in the Cap Bon region, Tunisia | p. 387 |
Co-kriging of soil properties with Vis-NIR hyperspectral covariates in the Cap Bon region (Tunisia) | p. 393 |
Soil Classification based calibration of Visible and Near Infrared Diffuse Reflectance Spectroscopy (VNIR-DRS) for predicting soil properties | p. 399 |
Development of a Danish national Vis-NIR soil spectral library for soil organic carbon determination | p. 403 |
Soil profile organic carbon prediction with visible-near infrared reflectance spectroscopy based on a national database | p. 409 |
Sampling for field measurement of soil carbon using Vis-NIR spectroscopy | p. 415 |
Prediction of field capacity and permanent wilting point using rapid soil sensing approaches | p. 421 |
Global Soil Map. net | |
Versioning of GlobalSoilMap.net raster property maps for the North American Node | p. 429 |
Digital soil mapping of soil properties for Korean soils | p. 435 |
Documenting GlobalSoilMap.net grid cells from legacy measured soil profile and global available covariates in Northern Tunisia | p. 439 |
Progress towards GlobalSoilMap.net soil database of Denmark | p. 445 |
The challenges of collating legacy data for digital mapping of Nigerian soils | p. 453 |
An Australian soil grid: Infrastructure and function | p. 459 |
Author index | p. 465 |
Table of Contents provided by Ingram. All Rights Reserved. |
ISBN: 9780415621557
ISBN-10: 0415621550
Published: 24th July 2012
Format: Hardcover
Language: English
Number of Pages: 482
Audience: Professional and Scholarly
Publisher: Taylor & Francis Ltd
Country of Publication: GB
Edition Number: 1
Dimensions (cm): 25.4 x 17.8 x 3.81
Weight (kg): 1.02
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