| 词条 | Digital soil mapping |
| 释义 |
Digital Soil Mapping (DSM) in soil science, also referred to as predictive soil mapping[1] or pedometric mapping, is the computer-assisted production of digital maps of soil types and soil properties. Soil mapping, in general, involves the creation and population of spatial soil information by the use of field and laboratory observational methods coupled with spatial and non-spatial soil inference systems. The international WORKING GROUP ON DIGITAL SOIL MAPPING (WG-DSM) defines digital soil mapping as "the creation and the population of a geographically referenced soil databases generated at a given resolution by using field and laboratory observation methods coupled with environmental data through quantitative relationships." [2][3][4][5] AmbiguitiesDSM can rely upon, but is considered to be distinct from traditional soil mapping, which involves manual delineation of soil boundaries by field soil scientists. Soil maps (paper sheets) produced as result of manual delineation of soil mapping units may also be digitized or surveyors may draw boundaries using field computers, hence both traditional, knowledge-based and technology and data-driven soil mapping frameworks are in essence digital. Unlike traditional soil mapping, Digital Soil Mapping is, however, considered to make an extensive use of:
In digital soil mapping, semi-automated techniques and technologies are used to acquire, process and visualize information on soils and auxiliary information, so that the end result can be obtained at cheaper costs. Products of the data-driven or statistical soil mapping are commonly assessed for the accuracy and uncertainty and can be more easily updated when new information comes available.[6] Digital Soil Mapping tries to overcome some of the drawbacks of the traditional soil maps that are often only focused on delineating soil-classes i.e. soil types.[5] Such traditional soil maps:
An example of successful digital soil mapping application is the physical properties[7] (soil texture, bulk density) developed in the European Union with around 20,000 topsoil samples of LUCAS database[8]. ScorpanScorpan is a mnemonic for an empirical quantitative descriptions of relationships between soil and environmental factors with a view to using these as soil spatial prediction functions for the purpose of Digital soil mapping. It is an adaptation of Hans Jenny’s five factors not for explanation of soil formation, but for empirical descriptions of relationships between soil and other spatially referenced factors. [6] S = f(s,c,o,r,p,a,n), where
See also
References1. ^{{cite journal | last = Scull | first = P. |author2=J. Franklin |author3=O.A. Chadwick |author4=D. McArthur | title = Predictive soil mapping - a review | journal = Progress in Physical Geography | volume = 27 | issue = 2 | pages = 171–197 |date=June 2003 | doi = 10.1191/0309133303pp366ra | citeseerx = 10.1.1.137.3441 }} 2. ^{{cite book|title=Digital soil mapping: an introductory perspective|year=2006|publisher=Elsevier|location=Amsterdam|isbn=978-0-444-52958-9|pages=600|url=http://www.elsevier.com/wps/find/bookdescription.cws_home/709809/description#description|editor1=Lagacherie, P. |editor2=McBratney, A. B. |editor3=Voltz, M. }} 3. ^{{cite book|title=Digital Soil Mapping as a support to production of functional maps|year=2006|publisher=Office for Official Publications of the European Communities|location=Luxemburg|pages=68|url=http://eusoils.jrc.ec.europa.eu/esdb_archive/eusoils_docs/other/EUR22123.pdf|editor1=Dobos, E. |editor2=Carré, F. |editor3=Hengl, T. |editor4=Reuter, H.I. |editor5=Tóth, G. |quote=EUR 22123 EN}} 4. ^{{cite book|title=Digital Soil Mapping: Bridging Research, Environmental Application, and Operation|year=2010|publisher=Springer|isbn=978-90-481-8862-8|pages=473|url=https://www.springer.com/series/8746|editor1=Boettinger, J.L. |editor2=Howell, D.W. |editor3=Moore, A.C. |editor4=Hartemink, A.E. |editor5=Kienast-Brown, S. }} 5. ^1 {{cite journal|author-last1=Hengl|author-first1=Tom|author-last2=Mendes de Jesus|author-first2=Jorge|author-last3=McMillan|author-first3= R.A.|author-last4=Batjes|author-first4=Niels H.|author-last5=Heuvelink|author-first5= G.B.M.|author-last6=Ribeiro|author-first6= Eloi C.|author-last7=Samuel-Rosa|author-first7= Allesandro | author-last8=Kempen|author-first8=Bas|author-last9=Leenaars|author-first9=J.G.B.|author-last10=Walsh|author-first10=M.G.|author-last11=Ruiperez Gonzalez|author-first11= Maria G.|year=2014|title=SoilGrids1km — global soil information based on automated mapping|journal=PLOS ONE|volume=9|issue=8|pages= e105992 |doi=10.1371/journal.pone.0105992|pmid=25171179|pmc=4149475}} 6. ^1 2 {{cite journal | last = McBratney | first = A.B. | authorlink = | author2 = M.L. Mendonça Santos |author3 = B. Minasny | title = On digital soil mapping | journal = Geoderma | volume = 117 | issue = 1–2 | pages = 3–52 | date = 1 November 2003 | doi = 10.1016/S0016-7061(03)00223-4 }} 7. ^{{Cite journal|last=Ballabio|first=Cristiano|last2=Panagos|first2=Panos|last3=Monatanarella|first3=Luca|title=Mapping topsoil physical properties at European scale using the LUCAS database|journal=Geoderma|volume=261|pages=110–123|doi=10.1016/j.geoderma.2015.07.006|year=2016}} 8. ^{{Cite journal|last=Orgiazzi|first=A.|last2=Ballabio|first2=C.|last3=Panagos|first3=P.|last4=Jones|first4=A.|last5=Fernández-Ugalde|first5=O.|title=LUCAS Soil, the largest expandable soil dataset for Europe: a review|journal=European Journal of Soil Science|volume=69|language=en|pages=140–153|doi=10.1111/ejss.12499|issn=1365-2389|year=2018}} External links
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