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TheAlgorithmsforQuantitativePedologyaqpPackage TheAlgorithmsforQuantitativePedologyaqpPackage

TheAlgorithmsforQuantitativePedologyaqpPackage - PDF document

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TheAlgorithmsforQuantitativePedologyaqpPackage - PPT Presentation

SoilPro12leVisualization sketchesdepictinghorizonsequencedepthcolor soilcolorstranslatedfromMunsellsystemtoRGBtriplets orderingofsketchesalongenvironmentalgradients SoilPro12leAggregation ID: 936323

lecollections list depth soilpro list lecollections soilpro depth mlra aggregaterepresentationofsoilpro library order slice plot cex lesketches componentrelationshipgraphs pair data

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TheAlgorithmsforQuantitativePedology(aqp)Package SoilPro leVisualization sketchesdepictinghorizonsequence,depth,color,... soilcolorstranslatedfromMunsellsystemtoRGBtriplets

orderingofsketchesalongenvironmentalgradients SoilPro leAggregation summaryofsoilpropertyormorphologyalongregulardepthslices transcendstypicalproblemswithsoilpro lecolle

ctions:!highvariabilityinhorizondescriptionstyleandhorizontypes/depths SoilPro leClassi cation similartoabove:distancemetriccomputedalongregulardepthslices canassistwith

similar/dissimilarevaluation Soil-Speci cClasses/Methods datastructures&vocabularyforworkingwithcollectionsofsoilpro les SoilPro leSketches (Digital)SoilPro leSk

etches:PedonKind library(soilDB)#loadpackage f�fetchNASIS()#loadpedonsfromNASIS new.order�order(f$pedon kind)#neworderingvector plot(f,name='hzname',plot.order=new.order)#

plotpedonsassketchs legend(...)#makealegend(detailsommited) AggregateRepresentationofSoilPro leCollections Slice-wiseaggregationofsoilproperties library(aqp) library(lattice

) #loadlabdatafromCSV le x�read.csv('MLRA 18 22�lab data.csv') #initSoilPro leCollectionobject depths(x)�pedon id~hztop+hzbot site(x)�~site id+lon+lat+mlra #

slice�wiseaggregationbyMLRAofn%BSatpH8.2 a�slab(x,mlra~bs82) #plot xyplot( top~p.q50,groups=mlra,data=a,lower=a$p.q25,upper=a$p.q75, ylim=c(160,�5),alpha=0.5,scales=lis

t(cex=1.25, y=list(tick.num=7,alternating=3),x=list(alternating=1)), panel=panel.depth function,prepanel=prepanel.depth function, ylab=list('Depth(cm)',cex=1.25), xlab=list('Bas

eSaturationatpH8.2',cex=1.25),par.settings=list( superpose.line=list(col=c('black','blue'),lty=c(1,2),lwd=2)), auto.key=list(columns=2,title='MLRA',points=FALSE,lines=TRUE) ) Ag

gregateRepresentationofSoilPro leCollections #loadpackage library(soilDB) #loadMVOsoilsfromlocalNASIS(querynational rst) f�fetchNASIS() #slice�wiseaggregationofsel

ectproperties a�slab(f,sampled as~clay+total frags pct+ph eld) #plottingdetailsommitted... AggregateRepresentationofSoilPro leCollections AggregateRepresentationofSoi

lPro leCollections Quantitative(pair-wise)ComparisonofSoils (a) (b) (c)\isamorelikeb,ascomparedtoc?"ideallytranscendinghorizonationanddescriptionstyle Pair-wisedissimilarity

alongdepth-slices(Mooreetal,1972) soilpropertiesatslice15clayvcsln_tccecA16.421.5-1.53.88.1210.617.6-1.55.94.938.810.5-0.27.56.049.112.6-0.85.65.956.816.2-0.55.08.2617.911.0-0.1

9.45.277.011.7-0.44.76.386.317.0-0.14.77.9 pair-wisedissimilarityatslice151234567242368464512919530464030696593045687484520162248832503937116424 Resultscansupportsimmilar/dissim

ilarevaluation ComponentRelationshipGraphs:CA630 ComponentRelationshipGraphs:MT637 ComponentRelationshipGraphs:SanJoaquinSeries PossibleApplicationandRelevancetoSDJR Visualizati

on:rapidevaluationofcomplexdata outliers/mistakestendtostick-out(pro lesketches/aggregatedata) dendrogramsdepictingsimilarity(similar/dissimilareval.) graph-networksdepictin

gconnectivity(associated/relatedsoils) Aggregation:data-drivensynthesisofa\representativesoilpro les" depth-slicescantranscendvariationsindescriptionstyle(withexpertreview!)

universallymeaningfulLow{RV{Highvalues:5th{50th{95thpctiles OSDs/DMUsviadirectaggregation:morphology+properties(datapermitting!) Slice-WiseSimilarity:property-driveneval.of\sim

ilarity" rapidIDofmistakes/outliers/missingdata(!) similar/dissimilardiscussionformapunitdesign/re-correlation/joins (semi-)automatedre-allocationofpro lestonewrevisedlegend

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