Self-Levelling Feller-Buncher Productivity Based on Lidar

Originalscientificpaper–Izvorni znanstveni rad

Croat. j. for. eng. 34(2013)2 273

Self-Levelling Feller-Buncher Productivity

Based on Lidar-Derived SlopeMuhammad Alam, Mauricio Acuna, Mark Brown

Abstract – Nacrtak

The purpose of the study was to examine the ability of LiDAR (Light Detection and Ranging) to derive terrain slope over large areas and to use the derived slope data to model the effect of slope on the productivity of a self-levelling feller-buncher in order to predict its productivity for a wide range of slopes.The study was carried out for a self-levelling tracked feller-buncher in a 24-year old radiata pine (Pinus radiata) plantation near Port Arthur, Tasmania, Australia undertaking a clear felling operation. Tree heights and diameter at breast height were measured prior to the harvest-ing operation. Low intensity LiDAR (>3 points m-2) flown in 2011 over the study site was used to derive slope classes. A time and motion study carried out for the harvesting operation was used to evaluate the impact of tree volume and slope on the feller-buncher productivity.The results showed the ability of LiDAR to derive terrain slope classes. The study found that for an average tree volume of 0.53 m3, productivities of 97 m3 PMH0

-1 (Productive Machine Hours excluding delays) and 73 m3 PMH0

-1 were predicted for the moderate slope (11–18°) and steep slope (18–27°), respectively. The difference in feller-buncher productivity between the two slope classes was found to result from operator technique differences related to felling. The productivity models were tested with trees within the study area not used in model devel-opment and were found to be able to predict the productivity of the feller-buncher.

Keywords: Tasmania, productivity, self-levelling feller-buncher, LiDAR, mechanised harvest-ing system, slope

fectingtheproductivityofforestharvestingmachines(e.g.Brunbergetal.1989,KelloggandBettinger1994,AcunaandKellogg2009).However,slopeisthepri-marydeterminantoftravelspeedandstabilityofhar-vestingmachines(DavisandReisinger1990).Increas-ingslopehasbeenshowntobeasignificantfactorindecreasingtheproductivityofarangeofforesthar-vesting equipment (Stampfer 1999, Stampfer andSteinmüller2001,SimõesandFenner2010,ZimbalattiandProto2010).Inaddition,rubber-tyredharvestingmachinesaregenerallyrestrictedtoslopes<19°where-astrackedmachinescanoperateonslopesupto27°,withsomespecialisedtrackedmachinesabletooper-ateonsteeperslopes(e.g.theValmetSnake(StampferandSteinmüller2001)).Previousharvesterproductivitystudieshaveusu-

allyextrapolatedstand-levelslopeinformationfromalimitednumberofpointsmanuallymeasuredwith

1. Introduction – UvodTheproductivityandefficiencyofamechanised

harvestingsystemisaffectedbyanumberoffactorsincludingforeststandcharacteristics(standdensity,undergrowth),treecharacteristics(treesizeorpiecesize,treeform,crownsize),terrainvariables(slope,rocks, woody debris, ground roughness, groundstrength,streamsanddrainagefeatures,roads,etc.),operators’experience,skill&worktechniqueandma-chinerylimitationsordesign(Brunbergetal.1989,Lageson1997,Nurminenetal.2006,Visseretal.2009).Knowledgeoftheimpactofthesefactorsonthepro-ductivityandefficiencyofforestharvestingmachinescanassistinpredictingtheirperformanceunderdif-ferentconditionsinacost-effectivewayandleadtomoreproductiveharvestingoperations.Treesize(volumeorweight)hasbeendetermined

bymanystudiestobethemostinfluentialfactoraf-

M. Alam et al. Self-Levelling Feller-Buncher Productivity Based on Lidar-Derived Slope (273–281)

274 Croat. j. for. eng. 34(2013)2

clinometersacrossthestudysiteorusedDTMs(DigitalTerrainModels)derivedfromcontours(e.g.AcunaandKellogg2009,OliveiraJúniorE.D.de.etal.2009).Li-DARisawell-recognisedtechnologyfortheproductionofhighqualityDTMs(Ackermann1999,WehrandLohr1999),whichcanbeusedtovisualiseandcalculateslope(GilesandFranklin1998)andasaninputintoharvestplanning(Reutebuchetal.2005).LiDARslopemapshavebeenshowntobeveryaccurateandofhighreso-lution comparedwithDTMsderived from contourmaps(VazeandTeng2007).UseofLiDARtogenerateaccurate,broadareaDTMsmakesitpossibletopredicttheimpactofslopeonforestharvestingmachinepro-ductivityacrossanentireforestestateusingmodelsrelatingproductivitytoslope.Self-levellingfeller-bunchershaverecentlybeen

introducedinpartsofAustraliaandNewZealandforharvestingoperationsinsteepterrain(Acunaetal.2011).Self-levellingfeller-bunchershaveadvantagesoverconventionalfeller-buncherssuchasreducingtheriskoftilting,increasedliftingcapacityandincreasedoperatorcomfortduringdownhilloperations(Mac-Donald1999,Acunaetal.2011).TheobjectiveofthestudywastouseLiDAR-derivedslopefromreadilyavailablelowcostLiDARdatatodeveloparelation-shipbetweenslopeandtheproductivityofaself-lev-ellingfeller-buncher,andthentousethisrelationshiptopredicttheproductivityofthefeller-buncherforotherareas,whereslopehadbeenestimatedusingsimilarLiDARdata.

2. Material and methods Materijal i metode

2.1 Study site – Mjesto istraživanjaThestudywaslocatednearPortArthur,Tasmania,

Australia(Latitude/Longitude:43°10’10”S/147°47’20”E).Thestandwas24-year-oldradiatapineplanta-tionof1057treesha-1withnoundergrowth.Thestudysitewasanareaofapproximately1hectarewithinaplantationbeingclearfelledforpulpwoodproduction.Treespacingwas2.5m×4mandlightlybranchytreesweregoodinformsandquality.Thesitehadneverbeenthinned.Theforestfloorconsistedofmoist,softandclayloamysoils.Thereweresomedoleriterocksthat accounted for theground roughness.Groundslopewasbetween7–27°withanaverageof21°.Onehundredandtwotreesofnormalgrowthand

formscoveringtherangeofheightsatthestudysitewereselectedandtheirheightsweremeasuredwithaVertexhypsometerandImpulse200lasertothenear-est0.1m.Thediameteratbreastheight(DBH,cm)of

Table 1 Means and value ranges for pre-harvest tree measurementsTablica 1. Raspon i prosječne vrijednosti izmjere stabala prije sječe

Mean

Arit. sredina

Range

Raspon

Height – Visina, m 26.1 10–37

DBH – Prsni promjer, m 0.29 0.10–0.46

Basal area – Temeljnica, m2 0.07 0.01–0.16

Volume – Obujam, m3 0.61 0.06–1.84

alltreesonthestudysitewasmeasuredwithadiam-etertapetothenearest1cm.Aheight-diametermod-elderivedfromthemeasuredtreeheightswasusedtoestimateheightsoftheremainingtrees.Eachtreehadauniquenumberpaintedonthestemtoallowittobeidentifiedduringthetimeandmotionstudy.AvolumefunctionsuppliedbyNorskeSkog,Australiawasusedto estimate each tree merchantable volume (m3).Meansandvaluerangesforpre-harvesttreemeasure-mentsarepresentedinTable1.

2.2 Airborne LiDAR system – Sustav LiDARLiDARdatacoveringthestudysitewassupplied

byForestryTasmania,withthespecificationspresent-edinTable2.ThisLiDARdatawasavailableasithadbeencollectedforthepurposeofresourceandlandmanagementusedbyForestryTasmaniathatman-agesnativeandplantationforestsintheregion.LiDARdata supplied in .LAS formatwere classified intogroundandnon-groundpoints.LiDARdataaccuracywasverifiedbythedataprovider.ADTMwasconstructedwithacellsizeof2mus-

inggroundLiDARpointsandslopewasderivedfromtheDTMusingArcGIS10.Theterrainslopeclassifica-tion used by the Forestry Commission UK (1996)(Level=0–6º,Gentle=6–11º,Moderate=11–18º,Steep=18–27º,Verysteep=>27º)wasadoptedinthestudybecause:(i)theclassesarebasedaroundoperationalconsiderations,(ii)therewasnowidelyacceptedter-rainclassificationsysteminuseinAustralia,(iii)thisclassificationisverysimilartothatusedbytheForestPracticessysteminTasmania(ForestPracticesBoard2000)ofHilly=12–19º,Steep=20–26º,VerySteep=27ºandaboveand(iv)itisaninternationallyrecognisedclassification.

2.3 Time and motion study – Studij rada i vremenaAnoperatorwith twelveyears experience (two

yearswithcurrentmachine)carriedouttheharvesting

Self-Levelling Feller-Buncher Productivity Based on Lidar-Derived Slope (273–281) M. Alam et al.

Croat. j. for. eng. 34(2013)2 275

Table 2 LiDAR parameters and scanning system settingsTablica 2. Parametri LiDAR-a i postavke sustava snimanja

LiDAR attribute – Obilježja LiDAR-a Values – Vrijednosti

Date of flight – Datum leta 25/05/2011

System – Sustav ALTM (Airborne Laser Terrain Mapping) Gemini

Beam divergence – Odstupanje pulsa 0.20 milliradian

Footprint diameter – Prostorna rezolucija 20 cm

Laser mode – Mod lasera Single pulse

Pulse return density (range) – Gustoća povratka pulsa (raspon) >3 m-2 (1st , 2nd, 3rd and last) (2.3–3.2)

Horizontal accuracy – Horizontalna točnost 0.15 m

Vertical accuracy – Vertikalna točnost 0.15 m

Pulse rate frequency – Frekvencija pulsa 70 kHz

Table 3 Description of time elementsTablica 3. Opis radnih sastavnica

Time elements – Radne sastavnice

Moving time: Begins when the feller-buncher or the boom starts to move to a tree and ends when machine head is clamped on the tree

Premještanje: Započinje kada feler bančer ili dizalica započinje s pomicanjem i završava kada sječna glava zahvati stablo

Felling time: Starts when the feller-buncher head clamps on to the tree stem and ends when the tree touches the ground

Sječa: Započinje kada sječna glava zahvati stablo te završava kada posječeno stablo dodirne tlo

Stacking time: Starts when the feller-buncher grabs a log and ends when it drops the log onto the pile

Uhrpavanje: Započinje kada feler bančer zahvati deblo i završava u trenutku kada ga ispusti na složaj

Cycle time: Starts when the feller-buncher commences moving to a tree and ends when the feller-buncher completes felling the tree

Vrijeme turnusa: Započinje premještanjem feler bančera ka stablu i završava kad feler bančer posječe stablo

Delay: Any interruption to the harvesting operation spending extra time. The cause of the delay (e.g. operational, personal, mechanical, or study induced) is recorded

Prekidi: Svako prekidanje pridobivanja drva koje izaziva dodatni utrošak vremena. Uzroci su prekida (npr. povremeni radovi, osobni, kvarovi ili izazvani istraživanjem) zabilježeni

operationwithaself-levellingtrackedfeller-buncher,Valmet475EXLfittedwithaQuadcohotsawaccumu-latinghead. Itwasmanufactured in2004andhadworked for 7751hours. TheValmet 475EXL isde-signed tooperateonunevengroundandonsteepslopes.Theharvestingoperationwas recordedusinga

digitalvideocamerainmainlyfineandsunnycondi-tionsonthe4thApril2011.Severalbriefepisodesofdrizzlyrainoccurred,butdidnotdisrupttheharvest-ingoperationandfilming.Theoperatorwasobservedtofelltreesina4row

swathdirectlyuphill(movingatrightanglestothe

contours)oronside-hill(movingparalleltothecon-tours)ongentle&moderateterrainanddownhillonsteepterrain.Infact,terrainconditionslargelydic-tatedtreeharvestingpatterninsteepandmoderatesteepslopeareas.Treeswere laidout in theprevi-ouslyharvestedareaatrightanglestothedirectionofharvestermovementforsubsequentprocessingintologs.Thelengthofeachswathwasapproximately100m.Onetothreetreeswerefelledateachstop.ToavoidissuesassociatedwithGPS(GlobalPosi-

tioningSystem)accuracyandperformanceundertreecover,followingtheharvestingoperationGPSloca-tionsof100stumpsalongtheborderofthestudysite


276 Croat. j. for. eng. 34(2013)2

wererecordedwithastandardGPSmeasuringdevice.CoordinatesofstumplocationswereusedtolocatetheharvestareaontheLiDAR-derivedDTM.TimerProProfessionalsoftware(www.acsco.com)

wasusedtoextracteachtimeelementfromthevideorecording(Table3).Timeelementsunrelatedtotreesizeandslopeincludingstacking,brushing,clearingandanydelayswereexcludedfromtheanalysisbe-causeoftheirrandomoccurrences.Inorder todevelop feller-buncherproductivity

modelsforeachslopeclass,thefollowingstepswerecarriedout:

Þ Stumplocationsontheboundaryandtreespac-ingmeasurementsintheplantationareawereusedtointerpolatethelocationsofremainingtreesusingArcGIS10.

Þ Onehundredandtwenty-sixtreesinthemoder-ateslopeareaand124treesinthesteepslopeareaofthestudysitewereselectedformodeldevelopmentusingpreviouslyderivedLiDARslope. Treeswith normal growth and forms

wereselectedfrombothslopeareasandselec-tionwaslimitedtotreesthatcouldclearlybeidentifiedasbeingintheallocatedslopeclass.Therewasinsufficientareaofgentleslopeatthestudysiteforproductivitymodelling.

Þ Forestimatedlocationofeachtreeinthestudyarea,bothtreevolumeandslopeclasswereal-located.

Þ Timeconsumptionsofeachtreeforslopeclasseswereestimatedfromthetimeandmotionstudy.

Þ Acorrelationbetweentreevolumesandtimeconsumptionsforeachslopeclasswasestab-lished,whichinturnwasusedtoformulateaproductivitymodel.

Þ Priortomodeldevelopment,meantreesizesforeachslopeclasswerecomparedusingat-test (p<0.05).

2.4 Data analysis – Obrada podatakaProductivitymodelsforthefeller-buncherwere

developedbasedonthecycletimesforthetreesse-

Fig. 1 LiDAR-derived slope class (Field tree distribution and Field measured tree rows refer to approximate locations)Slika 1. Razredi nagiba terena izvedeni iz LiDAR-ovih snimaka (terenske izmjere redova i pojedinih stabala odnose se na približne položaje)


Croat. j. for. eng. 34(2013)2 277

lectedineachslopeareatodeterminewhetherslopesignificantlyaffectedfeller-buncherproductivity.

Productivity(m3PMH0–1)wasestimatedusing

thefollowingformula: Productivity=(volume/cycletime)*60

Where, Volume–treevolume(m3)estimatedfromfield measurements Cycletime(min)–refertoTable3. PMH0–ProductiveMachineHoursexcluding delaytimeRegressionmodelsweredevelopedforeachslope

classandtestedtodeterminethebest-fitmodelsusingtheirmeanBias,MeanAbsoluteDeviation(MAD),RMSE(RootMeanSquareError),R2 and the distribu-tionoftheresiduals.Thebest-fitmodelsforeachslopeclasswerecomparedusinganF-test (p<0.05)(Motul-skyandChristopoulos2003).Therelationshipbetweentreevolumeandmoving

&fellingtimesforeachslopeclasswastestedusinglinearregressiontodeterminewhethertreevolumewasapotentialcovariateinaone-wayAnalysisofCovari-ance(ANCOVA).Ifitwasfoundnottobe,aone-wayAnalysisofVariance(ANOVA)wouldbeperformed.AgenerallinearmodelwasusedtoanalysetheANCOVAand/orANOVAmodels (Minitab 16,MinitabLtd.).MeanfellingandmovingtimesforeachslopeclasswerecomparedbyaposthocanalysisofthemeansusingTukey’stestinordertoidentifytheimpactofeachtimeelementonfeller-buncherproductivity.Inordertotestwhethertheproductivitymodels

developedinthestudywereabletoaccuratelypredicttheproductivityof the feller-buncherwhen fellingtreeselsewhereonthestudysite,thirty-fivetreesnotusedinthemodeldevelopmentprocesswererandom-lyselectedfromeachslopeclass.Topographicvari-abilityandsloperangesofmodeltestingareaswere

chosenandverifiedtobesimilartothoseofmodeldevelopment areas. The productivity of the feller-buncherforeachofthesetreeswascalculatedusingcycletimeandtreevolumeandwasestimatedusingthe productivitymodels developed for each slopeclass.Foreachslopeclass,thecalculatedandestimat-edproductivityvalueswerecomparedusingapairedt-test.Linearregression[Y=a+b(X)]analysiswasperformedtopredictproductivityofthefeller-bunch-erforeachslopeclass,whereX istheindependentvariable,fieldmeasuredproductivity;Yisthedepen-dentvariable,predictedproductivityanda&baretheregressioncoefficients.StatisticalsoftwareExcel2007wasusedtoperformanalyses.

3. Results – RezultatiFieldmeasuredstumplocations(coordinates)were

usedtolocatetheharvestareaontheLiDAR-derivedDTM.TheLiDAR-derivedsloperangeforthestudysitewas7–27°withameanslopeof19°,whichwasfoundtobecomparabletofieldmeasurementsofthestudysite.Theslopeofthestudysitewasclassifiedintothreeclasses:gentleslope(7–11°),moderateslope(11–18°)andsteepslope(18–27°)(ForestryCommis-sionUK1996)(Fig.1).Severalsmallareas(maximum8m×6m)ofover27°slopewereaddedtothesteepslopeclassastheyweretoosmalltoaffecttheproduc-tivityofthefeller-buncher.Meantreevolumesinthemoderateandsteepslope

areaswerenotsignificantlydifferent(Table4).Astherewereveryfewinstancesofstackingtime

duringthestudy,itwasexcludedfromcycletime.Twotreeswerecutandaccumulatedinheadintwoocca-sionsandtheywerealsoexcludedfromtheanalysiswhile developing themodel to be consistentwithoveralltreeselectiontechnique.Inthesteepslopear-eas,anumberoftreeshadfallenonothertreesduringharvestoperationandtheoperatorwasobservedto

Table 4 Summary tree volume (m3) statistics for each slope classTablica 4. Statistički prikaz obujma stabala za svaki razred nagiba terena

Moderate slope (11–18°)

Umjereni nagib (11–18°)

Steep slope (18–27°)

Strmi nagib (18–27°)

Mean volume – Srednji obujam, m3 0.55 0.51

SD – Standardna devijacija, m3 0.26 0.26

Volume range – Raspon obujma, m3 0.05–1.12 0.13–1.20

Count – Veličina uzorka 126 124


278 Croat. j. for. eng. 34(2013)2

Table 5 Model coefficients and goodness of fit statistics for the feller-buncher productivity model for each slope classTablica 5. Koeficijenti modela i dobrota statističke prikladnosti modela proizvodnosti feler bančera za svaki razred nagiba

Model coefficients – Koef. modela Goodness of fit statistics – Dobrota statističke prikladnosti

b0 b1 MBE MAD RMSE R2

Moderate slope – Umjereni nagib (11–18°) 12.3 3.8 2.5 24.0 34.7 0.60

Steep slope – Strmi nagib (18–27°) 10.8 3.5 2.0 17.7 25.8 0.61

Table 6 Feller-buncher mean felling and moving times, standard deviations (SD), min. and max. values for slope classes at the study siteTablica 6. Deskriptivna statistika vremena sječe i premještanja za razrede nagiba istraživane sječine

Felling time, sec – Vrijeme sječe, s Moving time, sec – Vrijeme premještanja, s

Mea

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Aritm

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Stan

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Stan

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Mini

mum

Najm

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vrije

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Max

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Najve

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ijedn

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Mea

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Aritm

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a

Stan

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Moderate slope – Umjereni nagib (11–18°) 9.7 5.4 4.9 56.4 11.6 7.7 3.5 44.6

Steep slope – Strmi nagib (18–27°) 14.3 8.4 5.9 56.8 12.4 6.6 4.7 45.8

dragthemoutintheprocessingareas.Themodelformthatbestfittedthedatawasanaturallogarithmtrans-formationofprocessedvolumeandthesquarerootofproductivity:

(Productivity)1/2 = β0 + β1 * ln (Processed volume)

Asthemodelsweredevelopedbasedonthesquarerootof thedependentvariable, thegoodnessoffitmeasuresfortheproductivitymodelswerecalculatedfromback-transformedmodeloutputs(ScottandWild1991).ModelcoefficientsandfitstatisticsareshowninTable5.Productivityofthefeller-buncherwasstronglycor-

relatedwithtreevolumeinbothslopeareas(Fig.2).Productivitywasgreater(97m3PMH0

-1)forthemod-erateslopeclass(11–18°)thanthat(73m3PMH0

-1)forthesteepslopeclass(18–27°)atthepooledmeantreevolumeof0.53m3.Thedifferencebetweentheproduc-tivitymodelswasstatisticallysignificant(p<0.05).Feller-bunchermovingandfellingtimesweresep-

aratelyfoundtobepoorlyrelatedtotreevolumeandthusaone-wayANOVAwasperformed.ThedataforthefellingandmovingtimeswerefoundtosatisfytheANOVAassumptions.Mean felling times for eachslopeclassweresignificantlydifferent,whereastherewasnosignificantdifferencebetweenmeanmovingtimesforeachslopeclass(Table6).

Fig. 2 Productivity of the feller-buncher against tree volume for moderate slope (11–18°) and steep slope (18–27°)Slika 2. Ovisnost proizvodnosti feler bančera o obujmu stabla za umjereni (11–18°) i strmi (18–27°) nagib

Themeanfeller-buncherproductivity,predictedusingtheslopeclassproductivitymodelsfortreesnotusedinthemodeldevelopment,wasnotsignificantly


Croat. j. for. eng. 34(2013)2 279

differentfromthemeanfeller-buncherproductivitycalculatedfromcycletimesandtreevolumesforthesametrees(p<0.05).Measuredproductivitywasfoundtobestronglycorrelatedwithpredictedproductivityforeachslope(Fig.3).

4. Discussion and Conclusion – Rasprava sa zaključcima

Theproductivityofthefeller-buncherinthecurrentstudywasfoundtodecreaseinthesteeperslopeclass,whichwasconsistentwith thefindingsofpreviousstudies(e.g.FPInnovations2008,OliveiraJúniorE.D.de.etal.2009).However,thereisconsiderablevariationamongstthepreviousstudiesinthedegreeofdecreaseinproductivitywithincreasingslope,whichimpliesfactorsotherthanslopeareinfluencingtheresults.Inthecurrentstudy,thedecreaseinproductivitybetweensteepslope(18–27°)andmoderateslope(11–18°)was24%whereasAcunaandKellogg(2009)foundnosig-

nificantdifferenceintheproductivityofafeller-bunch-eracrossasloperangefrom<10ºto20ºandFPInnova-tions(2008)showeda30%reductioninproductivitybetween6–11ºslopesand11–18ºslopesbasedonmod-elledresultsfromanumberoffeller-buncherstudies.Thegreatestdecrease in feller-buncherproductivitywasreportedbyOliveiraJúniorE.D.de.etal.(2009),who found an 80% decrease in productivity for atrackedfeller-buncherbetween0and27ºslopes.Thislargeproductivitydropwasexplainedbythedifferenceinsoiltype(e.g.»agri-loose«soil)anddifficultiesinhan-dlinglargertreesonsteepterrain.Otherpotentialfac-torsaccountingforthevariationbetweenthestudyre-sultsmayincludemachinecharacteristics,operatorskillandthenumberofstemsremovedperhectare,becausetravellingtimebetweentreesmayincreasedispropor-tionatelywithincreasingslope.Thesefactors,however,werenotinvestigatedinthisstudy.Toisolatethecauseoftheproductivitydifferences

between the slopeclasses in thecurrent study, thecycle timecomponents (movingandfelling times),werefurtheranalysed.Thestudyfoundfellingtimetobethemaindriverforthevariationinproductivity,whichwastheresultoftheoperatorspendingsignifi-cantlymoretimepertree(over4seconds)fellingtreesinthesteepslopearea(Table6).Terrainconditionslargelydictatedtheharvestingpatternandobserva-tions indicated it had a greater impact on steeperslopeswithinthesteepslopeclassification.Sinceop-eratingthemachineonanuphillslopeisslightlymorecomfortableandproductive(Howe2011),theoperatorwasobservedtofelltreesuphillbypredominantlyex-tendingtheboomandmovingthefeller-buncherinthemoderateslopeareasandlaythemoutforpro-cessingprimarilyusing theboom,whereas, in thesteepslopeareastheoperatordrovedownhilltofelleachtreeandthenbackuphilltodeposittheminsuit-ableareas,preferablythosewithmoderateslope,forprocessing.Inthesteepslopeareas,theoperatoralsospenttimedraggingoutanumberoftreesthathadfallenonothertrees.Thecombinationofthesefactorscontributedtohighertimeconsumptionwhenfellingtreesinthesteepslopeareas.Thestudydidnotinvestigatewhethersoilstrength

wasaninfluentialfactoraffectingthemachine’sstabil-ityandtractioninthesteepslopeareas,althoughthesoilinthesteepslopeareaswasobservedtobemuddycomparedwiththatinthegentleandmoderateslopeareas.StampferandSteinmüller(2001)demonstratedthatthelocomotionoftheharvesterwasdependentontheterrainslopeandthesoilbearingcapacity.There-fore,considerationofthesoilbearingcapacity,whileevaluatingslopeeffectsonharvesterproductivity,maybeanareaforfutureresearch.

Fig. 3 Predicted productivity as a function of measured productiv-ity for moderate slope (11–18°) and steep slope (18–27°) of the model testing areasSlika 3. Predviđena proizvodnost kao funkcija izmjerene proizvod-nosti za umjereni (11–18°) i strmi (18–27°) nagib istraživane sječine


280 Croat. j. for. eng. 34(2013)2

Themodelsdevelopedinthestudywereabletopredicttheproductivityofthefeller-buncherfellingtreesfromeachslopeclassonthestudysitewherethetopographicalfeaturesandsloperangesweresimilartomodeldevelopmentareas.Thissuggeststhatthemodelscanbeusedtopredicttheproductivityofthefeller-buncheroperatinginotherareasofradiatapineplantationwithtreevolumebetween0.06–1.84m3 and slopebetween11–27°.Themodelsmaynotbeappli-cablewhere topographicvariability is significantlydifferent(higherorlower)fromthemodeldevelop-mentareas,becausetheassignmentoftreesforeachslope class basedon themethodologyused in thestudymaynotrepresenttheexactlocations,whichexcludedtheuseoftreesontheboundaryoftheslopeclassesandwhereslopewasveryvariableanddiffer-entslopevariabilitywillpotentiallyinfluencetheop-eratorapproach.Inadditiontobeingabletoestimateterrain slope, LiDARhas been demonstrated by anumberofresearcherstobeabletoaccuratelypredicttreevolume(e.g.Hyyppaetal.2001,Perssonetal.2002).However, theLiDARpointdensity in thesestudieswasconsiderablygreaterthanthatforthecur-rentstudy,whichtargetedusingreadilyavailableLi-DARdataintheinterestofexploringamethodologythatwouldbecost-effectiveforpracticalapplication.

Acknowledgement – ZahvalaWeacknowledgethesupportofMrs.SandraHeth-

eringtonandherteamofNorskeSkog,Tasmania,Aus-traliaandRickMitchell(WesternAustraliaPlantationResources)fororganisingharvestoperationrequiredfordataacquisition.WealsoacknowledgethesupportofMr.DavidMannes(ForestryTasmania)forprovid-ingLiDARdata.

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Sažetak

Proizvodnost feler bančera sa žiroskopskom kabinom temeljena na nagibu terena izvedenom iz LiDAR-ovih snimaka

Cilj je istraživanja bio ocijeniti mogućnost uporabe LiDAR-ovih snimaka za određivanje nagiba terena na velikim površinama te ispitati djelovanje nagiba na proizvodnost feler bančera sa žiroskopskom kabinom.

Istraživanje je provedeno u čistoj sječi plantaže smolastoga bora (Pinus radiata) u Tasmaniji, u blizini Port Arthura (Australija). Plantaža je bila u dobi od 24 godine. Korišten je feler bančer sa žiroskopskom kabinom, oprem-ljen gusjenicama.

Visina i prsni promjer stabala mjereni su prije sječe. Upotrijebljene su LiDAR-ove snimke niskoga intenziteta (>3 točke po m2) iz 2011. godine kako bi se odredio nagib terena. Pri sječi i izradbi obavljen je i studij rada i vremena radi određivanja proizvodnosti vozila, a u ovisnosti o obujmu posječenih stabala i nagibu terena.

Rezultati istraživanja dokazuju primjenjivost LiDAR-ovih snimaka za raščlambu nagiba terena. Može se zaključiti da je za stablo prosječna drvnoga obujma od 0,53 m3 proizvodnost feler bančera sa žiroskopskom kabinom bila 97 m3/h (ne uključujući prekide rada) na terenu umjerena nagiba (11–18°) odnosno 73 m3/h (ne uključujući prekide rada) na strmijim terenima (18–27°). Razlika u proizvodnosti vozila zasniva se na različitim postupcima pri sječi i izradi koje je radnik morao obavljati ovisno o nagibu terena. Modeli proizvodnosti temelje se na stvarno posječenom i izrađenom drvnom obujmu.

Ključne riječi: Tasmanija, proizvodnost, feler bančer sa žiroskopskom kabinom, LiDAR, strojna sječa, nagib

Received(Primljeno):February8,2013Accepted(Prihvaćeno):June3,2013

Authors’address–Adresa autorâ:

MuhammadAlam*,PhD.Studente-mail:mmalam@student.unimelb.edu.auUniversityofMelbourne500YarraBoulevardRichmond,Australia3121MauricioAcuna,PhD.e-mail:[email protected](AFORA)UniversityoftheSunshineCoastHobart,Tasmania,7001,AustraliaProf.MarkBrown,PhD.e-mail:[email protected](AFORA)UniversityoftheSunshineCoastMaroochydoreDC,Queensland,4558Australia

*Correspondingauthor–Glavni autor

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Self-Levelling Feller-Buncher Productivity Based on Lidar