Digital Soil Mapping Across Paradigms, Scales and Boundaries

353 Pages·2016·11.74 MB·English

by  Gan-Lin Zhang

Springer Environmental Science and Engineering
Gan-Lin Zhang
Dick Brus
Feng Liu
Xiao-Dong Song
Philippe Lagacherie Editors
Digital Soil
Mapping Across
Paradigms,
Scales and
Boundaries
Springer Environmental Science
and Engineering
More information about this series at http://www.springer.com/series/10177
Gan-Lin Zhang Dick Brus Feng Liu
(cid:129) (cid:129)
Xiao-Dong Song Philippe Lagacherie
(cid:129)
Editors
Digital Soil Mapping
Across Paradigms,
Scales and Boundaries
123
Editors
Gan-Lin Zhang Xiao-DongSong
Institute of Soil Science Institute of Soil Science
ChineseAcademy of Sciences ChineseAcademy of Sciences
Nanjing Nanjing
China China
DickBrus Philippe Lagacherie
Soil Science National Institute for Agricultural Research
Alterra Paris
Wageningen France
TheNetherlands
FengLiu
Institute of Soil Science
ChineseAcademy of Sciences
Nanjing
China
ISSN 2194-3214 ISSN 2194-3222 (electronic)
SpringerEnvironmental ScienceandEngineering
ISBN978-981-10-0414-8 ISBN978-981-10-0415-5 (eBook)
DOI 10.1007/978-981-10-0415-5
LibraryofCongressControlNumber:2015960825
©SpringerScience+BusinessMediaSingapore2016
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Foreword
Unprecedenteddemandsarebeingplacedontheworld'ssoilresources(Kochetal.
2013). Responding to these challenging demands requires relevant, reliable, and
applicableinformation.Indeed,soilshavecriticalrelevancetoglobalissuessuchas
foodandwatersecurityandclimateregulationandtheyareincreasinglyrecognized
as major contributors to a wide range of ecosystem services. Mankind depends
upon soil for nearly everything. Our soil resource is being under threat, and we
must improve our knowledge about the current state and trend of soil condition.
Traditionalsoilsurveyinvolvesfieldreconnaissanceanddatacollectiontodraw
soil map unit boundaries (polygons) on maps. However, traditional soil survey
programsarecostandtime-consuming.Therefore,manypartsoftheworldhaveno,
or little, soil survey information. Also, as traditional soil survey mainly relies on
expert knowledge, it cannot be easily reproduced and the uncertainties of the
predictions are very difficult to estimate.
Digital soil mapping (DSM) has been proposed as a solution to increase
cost-effectiveness of mapping soil classes and soil properties (McBratney et al.
2003),includinganassessmentofuncertainties.Basically,thismethodisbasedon
thehypothesisthat soilclassesorpropertiescanbe predicted inaspatiallyexplicit
way,byusingsoilinformationand(1)spatiallyexhaustiveproxiesofsoilformation
factors and (2) spatially exhaustive sensors of some soil properties. Since the
seminal paper from McBratney et al. (2003), enormous advances in DSM have
beenachieved,mainlythankstotheIUSSWorkingGrouponDigitalSoilMapping.
Indeed, DSM has substantially matured and we have reached major advances
concerning suitable mapping and modelling procedure.
The DSM Working Group, currently led by Mogens Greve of Aarhus
University,Denmark,holdsbiennialglobalworkshops(Montpellierin2004,Riode
Janeiroin2006,Loganin2008,Romein2010,Sydneyin2012);thisbookpresents
selected papers presented at the 6th Global Workshop on Digital Soil Mapping. It
washeldinNovember2014inNanjing,China,skillfullyorganizedbyourChinese
colleagues. Prof. Zhang Ganlin and his colleagues were excellent hosts, and their
hospitality was highly appreciated.
v
vi Foreword
Theparticipationoftheworkshopwassuccessful,consideringthecontributions
of120attendees originating from 15countriesfrom allcontinents,having 58talks
and 17 posters. The full papers published in this book are a selection from these
presentations. They range from overviews of the DSM technology in general to
specificapplicationsinareashavingmoreorlessavailablesoilinformationorareas
where specific properties are investigated. In this book, recent findings are pre-
sented on the use of legacy data, soil sampling, covariates, soil spectroscopy, and
3D modelling in DSM. Particularly, sampling strategy and the uncertainty assess-
ment of DSM products are major issues that are addressed and which should be
accounted for in the future research. The coverages and scales of the applications
described in this book range from the field, to landscape, national, continental, or
world levels. Case studies in different parts of the world provide an excellent
opportunity to evaluate DSM technique and test its utility.
These proceedings give a useful overview of the state of the art in DSM. I am
convinced that it will be of broad interest for people involved in soil information
delivery and utilization. It will be a valuable resource for many years to come for
scientists, students, soil surveyors, and end users.
Dominique Arrouays
INRA-InfoSol Unit, France
References
Kochetal.,Soilsecurity:solvingtheglobalsoilcrisis.GlobalPolicy.4,434-441(2013).
McBratneyetal.,Ondigitalsoilmapping.Geoderma.117,1-2,3-52(2003).
Preface
Digital Soil Mapping Across Paradigms, Scales and Boundaries contains papers
presented at the 6th Global Workshop on Digital Soil Mapping, held November
11–14, 2014, at the Institute of Soil Science, Chinese Academy of Sciences of
Nanjing, China. The organizing committee was chaired by Dr. Gan-Lin Zhang,
professor of Institute of Soil Science, Chinese Academy of Sciences.
Approximately 120 participants from 15 countries presented and discussed nearly
60 papers during the four-day session, demonstrating the global engagement in
digital soil mapping.
Digital soil mapping is advancing on different fronts at different paces
throughout the world, facilitating the development of digital soil information with
increasing precision for many areas. To map the soils of the world to the every
detail, we need is a glorious task of soil scientists, especially when it is done in a
modern and fashionable way—mapping soils digitally. The goal of the sixth
workshopistoreviewanddiscussthestateoftheartindigitalsoilmappingandto
explore the strategies for bridging research, methodologies, and environmental
applications. The contents of predictive soil mapping, including the concepts,
paradigms, models, and mathematical and computational tools, develop continu-
ouslyandmoreandmoreresearchesandprojects,invarioussizes,resolutions,and
geographic regions, are running in the world. There are also more and more sci-
entists and users who are working in and shaping the frontiers of the field. It is
certainly necessary once again to bring people together to exchange and share
research results and to discuss the future of digital soil mapping, and we hope to
recognize these distinct foci within the realm of digital soil mapping.
We have selected 29 papers from the workshop that focus on digital soil map-
ping research, environmental application, and operation. Part I is an introductory
chapter which provides context for the whole book. The remaining papers are
organized into thefollowing parts: (II) Digital Soil Modelling; (III) Environmental
vii
viii Preface
Application and Assessment; and (IV) Soil Sensors and Legacy Data. The
CD-ROMaccompanyingthisbookcontainsthedigitalversionsofallcontributions
with full colour. Whenever reference is made in the book to colour images, the
reader is kindly requested to consult the CD-ROM.
Nanjing Gan-Lin Zhang
November 2014 Dick Brus
Feng Liu
Xiao-Dong Song
Philippe Lagacherie
Contents
Part I Digital Soil Modelling
1 Digital Soil Mapping Across Paradigms, Scales,
and Boundaries: A Review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Gan-Lin Zhang, Feng Liu, Xiao-Dong Song and Yu-Guo Zhao
2 Spatial Prediction of Soil Antibiotics Based on High-Accuracy
Surface Modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Wenjiao Shi, Tianxiang Yue, Xuewen Li and Zhengping Du
3 Incorporating Probability Density Functions
of Environmental Covariates Related to Soil Class Predictions. . . . 21
Jenette M. Ashtekar, Phillip R. Owens, Zamir Libohova
and Ankur Ashtekar
4 Mapping Horizontal and Vertical Spatial Variability
of Soil Salinity in Reclaimed Areas. . . . . . . . . . . . . . . . . . . . . . . . 33
Yan Guo, Zhou Shi, Jingyi Huang, Laigang Wang,
Yongzheng Cheng and Guoqing Zheng
5 Mapping Soil Organic Matter in Low-Relief Areas
Based on Time Series Land Surface Diurnal Temperature
Difference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Ming-Song Zhao, Gan-Lin Zhang, Feng Liu, De-Cheng Li
and Yu-Guo Zhao
6 Mapping Soil Thickness by Integrating Fuzzy C-Means with
Decision Tree Approaches in a Complex Landscape
Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Yuanyuan Lu, Ganlin Zhang, Yuguo Zhao, Decheng Li,
Jinling Yang and Feng Liu
ix