MDB tree stand condition monitoring tool description林分状况原文件监测

MURRAY-DARLINGBASINTREESTANDCONDTIONASSESSMENT(SCA)TOOL

Thisdocumentprovides:

alistofallproductsassociatedwiththisproject

contextandbackgroundtotheproject

aprojectdescription

Productsassociatedwiththisproject,includingaccessdetails

InformationType

Product

Format

Size

Distributionplatform

Report

DevelopmentofSCAtoolfinalreport

pdf

1.19MB

.au

Report

UserGuideforSCAtool

MSword

5.71MB

.au

Outputdata

Standconditiontimeseriesshapefiles(6epochsbetween2009-2016)forredgum,blackboxandcoolibah

geodatabaseofshapefiles

990MB

ForaccesscontactMDBAat

gis@.au

Outputdata

4bandsLandsatstandconditionoutputimagewithbands1to4containscrownextent(CE),plantareaindex(PAI),livebasalarea(LBA)andConditionscorerespectively:

floatingpointrasterimage

331GB(~50GBperepoch)

ForaccesscontactMDBAat

gis@.au

InputData

Fielddatausedformodelcalibrationandvalidation

commadelimitedcsvfile

~10MB

.au

InputData

6epochsincluding2009,2010,2012-2016Landsattimecompositeimages

floatingpointrasterimage

ForaccesscontactMDBAat

gis@.au

InputData

Basin-wideEnvironmentalWateringStrategy(BWS)Appendix3regions

geodatabase

1.95MB

.au

InputData

Cunningham2013treeclassificationlayerforredgum,blackboxandcoolibah

integerrasterimage

66.4MBzipped

.au

InputData

Murray-DarlingBasinmanagedfloodplain

shapefile

?

.au

SCAtool

SCAtoolsoftware

.exe

299MB

ForaccesscontactMDBAat

gis@.au

Context

ThefloodplainandriverineforestsoftheMurrayDarlingBasin(theBasin)areakeyindicatoroftheenvironmentalhealthoftheBasinandsupportimportantcultural,socialandeconomicvalues.

TheBasinPlananditssubordinateinstrumenttheBasin-wideEnvironmentalWateringStrategy(

.au/managing-water/environmental-water/basin-wide-environmental-watering-strategy

)identifytheexpectedoutcomesfromchangesinwatermanagementincludingfromtheuseofenvironmentalwater.Expectedchangesarequantifiedfortheredgum,blackboxandcoolibahforestsandwoodlandsofthelowlandfloodplainsoftheBasin.

TheMurrayDarlingBasinAuthority(MDBA)hasdevelopedarobustapproachtomonitoringtheconditionofriverineandfloodplainforestsandwoodlandsthatusesbothfielddataandcontemporaneoussummariesofsatelliteimagery(Newelletal2017).

AdescriptionofthedevelopmentoftheLandsat-basedtoolcanbefoundintheproject’sfinalreport(Newelletal2017)associatedwiththisrecord.Thedescriptionbelowisextractedfromthatreport.Pleaseseetheabovetableshowingtheresourcesthatareavailablethrough

.au

andthroughMDBA.

Introduction(fromNewelletal2017)

NotabledeclinesintheconditionofthefloodplainforestsandwoodlandshavebeenevidentacrosstheMurray-DarlingBasinovermanydecades(Cunninghametal.,2009b).Thesedetrimentalchangesareassociatedwithriverregulation,waterextractionforagriculturedeclinesinrainfallacrosstheBasin(Cunninghametal.inpress).

In2002thethenMurray-DarlingBasinCommission(MDBC)instituted‘TheLivingMurray’(TLM)programwhichaimedtorestorethehealthoftheBasinbyreturningwatertomanyofthenaturalfloodplainsacrosstheit(MDBC,2002).The‘TLM’programcomprisedavarietyofactivitiesataseriesofIconSitesincludingtheconstructionanddevelopmentofinfrastructuresupportingpositiveenvironmentaleffectsthroughwaterrecovery,environmentalwateringandmonitoring.Thephysicalandgeographicscaleoftheregionledtothedecisionin2008toundertakemonitoringofthechangesintheenvironmentalconditionofforestsandwoodlandsacrosstheMurrayregionthroughusingremotesensingtechnologies.

Previousstandconditionmodelling

SeveralapproacheshavebeentakentoassessandreportontheconditionorqualityofnativevegetationacrosstheBasin.TheinitialmodelsandmapsofstandconditionrelatedtoriverredgumandblackboxstandsacrossTLMIconSites,byusingacombinationoffielddata(175referencesites)andLandsatsatelliteimagery(Cunningham,etal.,2009a&b).Thisworksuggestedthatapproximately79%ofthesevegetationcommunitieswereinastressedstate.Thesemodelsweresuccessfullydevelopedusinganartificialneuralnetworkmodellingframework,usingstructuraldatafromtheremotesensedimageryandfielddata(R2=0.68).WhenthesemodelswereappliedretrospectivelytodatafortheIconSitesfrom2003to2008usinghistoricLandsatimagery,therewasadiscernibletrajectoryofincreasingstressontheseecosystems.Importantly,itwasrecognisedthatthisgeneralapproachwascapableofreportingonconditionstatesoverbothtimeandspace.Furthermore,itwaspossibletodetectanddocumentdecreasedlevelsofvegetationstressforregionsassociatedwithenvironmentalwateringeventsbetween2003and2009,aswellasacontinueddeclineforregionsacrosstheMurrayRiverfloodplainwherewaterwasmorerestricted(Cunninghametal.2009a).

Afollow-upstudyin2010usinganupdatedfielddataandsimilarmodellingapproachesdisplayedpoorermodelperformance(R2=0.58;Cunninghametal.,2011),whichwasattributedtoimbalancesinstratificationofthefieldbaseddata,wheretheextremesoftheconditionstates(bothgoodandpoorcondition)werenotwidelysurveyed,andthatmajorityofthedata(77%)relatedtositesinpoortomoderatecondition.Theeffectofthedistributionoftrainingdatawasto‘flatten’themodel,decreasingmodelperformanceatthe‘tails’,andthiswasaddressedstatisticallybythelineartransformationofthepredictions(Cunninghametal.2014).Thisscaledandenforcedadirectrelationshipbetweenthestandconditionandfullrangeofconditionstatesobservedinthefieldandimprovedthestatisticalperformanceofthemodels.

Asubsequentmodellinginvestigationduring2013alteredtheapproachbyusingRapidEyeimagery,followingthedemiseoftheLandsat5satellite.Thiswasaccompaniedbydelaysinfielddataacquisitioninresponsetoextensivefloods,andtimeallowedforecologicalresponsestothisnaturalevent.ThismodellingstudycoincidedwiththedevelopmentoftheoriginalBasin-wideStandConditionModellingTool(Cunninghametal.2013a),andthereforenecessitatedtheneedtore-modelstandconditionforthethreeprecedingyearstoensureconsistentmodelperformancewithinthetool.ThesestandconditionmodelsprovidedrelativelystrongmodelfitforTLMIconSites(R2=0.75and0.61;2009and2010respectively).Buildingamulti-yearmodelfromsurveysrecordedduringtwodroughtyears,andtheyearfollowingextensivefloodsprovidedsubstantialimprovementsforthepredictionsofcondition(R2=0.87),whencomparedwithmodelsbasedonindividualyears(R2=0.60-0.75).TheStandConditionToolbuiltfromthemulti-yearmodelprovidedstrongpredictions(R2=0.84)forasurveyof50sitesnotusedformodellingstandcondition.TogethertheseresultssuggestedthattheStandConditionToolwouldbeabletopredictstandconditionunderarangeofenvironmentalsettingandconditions.Thecombinationofthesestudiesdemonstratedthatthestandconditionmodellingapproachprovidedarobustframeworkforassessing,understandingandreportingonstandconditionovertime,andacrossextensivespatialextents.

Thiscurrentreportdetailstheapproachestakentoupdatethemodelsofstandcondition,andthesoftwaretoolsthatenabletheMDBAtodevelopmappedoutputsofstandconditionacrosstheMurray-DarlingBasin.ThiswasachievedbyincorporatingadditionalfieldobservationsrecentlyacquiredacrosstheBasinin2014,2015andlate2016/early2017,inconjunctionwithupdatestothelibraryofremote-senseddataavailabletodevelopmodels.Incontrasttopreviousdocuments,thisreportdoesnotreportoncurrentstandcondition,butontheproductionofasoftwaretoolthatenablestheMDBAtoproduceup-to-dateappraisalsofstandconditiononanas-needsbasis,andthereforeprovidestheabilitytomonitorstandconditionovertime.Thismonitoringtoolwillprovideusefulexpressionsofstandcondition,untilthemodelscanberevisedwithnewfielddatainthefuture.Thissoftwareisprovidedwithaninstallationmanual,andanadditionaltoolthatallowsuserstoviewinputimageryandmodelledoutputs.

References

Cunningham,S.C.,Griffioen,P.,White,M.&MacNally,R.(Inpress)Assessmentofecosystems:asystemforrigorousandrapidmappingoffloodplainforestconditionforAustralia’smostimportantriver.LandDegradation&Development.

Cunningham,S.C.,MacNally,R.,Griffioen,P.&White,M.(2009a)MappingtheConditionofRiverRedGumandBlackBoxStandsinTheLivingMurrayIconSites.StandConditionReport2009(withmodelledresultsfor2003and2008).Murray-DarlingBasinAuthority,Canberra.

CunninghamS.C.,MacNallyR.,ReadJ.,BakerP.J.,WhiteM.,ThomsonJ.R.,&GriffioenP.(2009b)Arobusttechniqueformappingvegetationconditionacrossamajorriversystem.Ecosystems,12,207-219.

Cunningham,S.C.,Griffioen,P.,White,M.&MacNally,R.(2011)MappingtheConditionofRiverRedGum(EucalyptuscamaldulensisDehnh.)andBlackBox(Eucalyptuslargiflorens