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PLOTTINGFROMABOVE
ENHANCINGAGRICULTURALMAPPINGINASIAANDTHEPACIFIC
AnthonyBurgard;AnnaChristineDurante;PamelaLapitan;
MahinthanJosephMariasingham;ArturoY.Pacificador,Jr.;andMashalRiaz
JUNE2024
ASIANDEVELOPMENTBANK
PLOTTINGFROMABOVE
ENHANCINGAGRICULTURALMAPPINGINASIAANDTHEPACIFIC
AnthonyBurgard;AnnaChristineDurante;PamelaLapitan;
MahinthanJosephMariasingham;ArturoY.Pacificador,Jr.;andMashalRiaz
JUNE2024
ASIANDEVELOPMENTBANK
CreativeCommonsAttribution3.0IGOlicense(CCBY3.0IGO)
©2024AsianDevelopmentBank
6ADBAvenue,MandaluyongCity,1550MetroManila,Philippines
Tel+63286324444;Fax+63286362444
Somerightsreserved.Publishedin2024.
ISBN978-92-9270-774-3(print);978-92-9270-775-0(PDF);978-92-9270-776-7(ebook)PublicationStockNo.TCS240326-2
DOI:
/10.22617/TCS240326-2
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Notes:
Inthispublication,“$”referstoUnitedStatesdollars.ADBrecognizes“RepublicofArmenia”asArmenia.
Photos:AllphotosbytheAsianDevelopmentBankunlessotherwiseindicated.
Featuredonthecover,startingfromthetopleftandmovingclockwise,areimagescapturingfieldworkconductedinArmenia,theCookIslands(includingthethirdphoto),andtheLaoPeople'sDemocraticRepublic.ThefifthphotoisfromaremotesensingtrainingsessioninVietNam.
CONTENTS
TablesandFiguresv
TablesandFiguresiv
Forewordv
Introduction1
Methodology5
AnalysisofReportedandMeasuredArea16
ImplicationsforPolicyandRecommendations25
Conclusion26
Appendixes
12022CookIslandsPostEnumerationSurveyDesign27
2
DetailsofAreaSamplingFramefor2022PostEnumerationSurveyoftheCookIslands
34
3
2022CookIslandsPostEnumerationSurveyQuestionnaire
39
4
ProtocolsforGPSParcelAreaMeasurement
45
5
ProceduresforEditingGPSDataCollectedforAreaMeasurement
49
References
51
iii
TABLESANDFIGURES
Tables
Tables
1NumberofAgriculturalHouseholdsbyLevelofAgriculturalActivityfrom2011and2021Censuses9
ofPopulationandDwellingCookIslands
2ComparisonBetweenthe2011CensusofAgricultureand2022ADBPostEnumerationSurvey10
NumberofAgriculturalHouseholdsbyLevelofAgriculturalActivityBasedonCensusof
AgricultureDefinitions
3EstimatedTotalAreainSquareMetersandAcresofAgriculturalHoldings16
4ComparisonofEstimatedTotalAreaofHoldingsbyReportedandGPS-AssistedMeasurements17
A1.1DescriptiveStatisticsofSelectedEnumerationAreaCharacteristics(Rarotonga,CookIslands2021,32
78EnumerationAreas)
A1.2CorrelationMatrixBetweenDesign-TestVariables(A1,A2)andStratificationVariables(A3,A4)32
A1.3MeanandCoefficientofVariationValuesofDesign-TestVariablesbyStrata.33
A1.4CalculatedSampleSize(NumberofEnumerationAreas)atDifferentLevelsofTargetedPrecision34
Figures
1LandUseandLandCoverClassificationsofRarotonga7
2AgriculturalIntensityonRarotongaIsland,CookIslands7
3DefinitionsforLevelofAgriculturalActivityin2011CensusofAgricultureandthe2022Post9
EnumerationSurvey,CookIslands
4EffectsofGPSErroronAreaMeasurement11
5CookIslands—ParcelAreasCapturedbyHandheldGPS,GarmineTrex32x12
7CookIslands—ParcelAreasCapturedbyDigitizationonSatelliteImageMethod13
6DigitizinganAgriculturalParcelBoundaryinSurveySolutions13
8DigitizinganAgriculturalParcelBoundarybyWalkingAroundtheParcelinSurveySolutions14
9GPSMeasurementErrorsinIrregularShapes14
10DigitizationofAgriculturalParcelonSatelliteImagebySelectionofParcelCorners15
11CookIslands—Farmer-ReportedandDigitizedAreasVersusGPSAreaMeasurement18
12QuantileRegressionCoefficientsComparingFarmer-ReportedandGPSAreaMeasurement19
13DifferencesinthePerceptionofScaleasCapturedbyWalking(Green)andDigitization(Red)Methods20
14ArmeniaFarmer-ReportedandDigitizedAreaVersusGPSAreaMeasurement21
15GPSParcelAreasCapturedinPakPokVillage,VangVieng,VientianeProvince,LaoPeople’s22
DemocraticRepublic
iv
TablesandFigures
16LaoPeople’sDemocraticRepublicFarmer-ReportedandDigitizedAreaVersusGPSAreaMeasurement23
A1SampleEnumerationAreasSelectedforthePostEnumerationSurvey35
A4.1SampleSketchofParcel48
A4.2CheckingSatelliteAccuracyontheGarmineTrex32x49
A3.3MarkingaWaypointontheGarmineTrex32x49
A4.4MarkingaWaypointontheGarmineTrex32x50
A4.5SavingtheParcelArea50
A4.6WorkflowofGPSAreaMeasurementProtocol51
v
FOREWORD
ThisreportPlottingfromAbove:EnhancingAgriculturalMappinginAsiaandthePacificprovidesacomprehensiveoverviewoftheapplicationofamethodologyforagriculturalareameasurementandinsightsgainedfromits
implementationinthesethreecountries.
TheAsianDevelopmentBank(ADB)haslaunchedatechnicalassistanceprojecttostrengthenthecapabilities
ofnationalstatisticsofficesandotherministries,equippingthemwiththenecessaryskillstomeettheSustainableDevelopmentGoals’increasingdatademands.Apioneeringaspectofthisprojectistheuseofgeospatial
technologies,whichhavebeenemployedtocreatemethodologicaltoolsforagriculturalareameasurement.
Thesetoolsaredesignedtoevaluatethediscrepanciesinagriculturalareaestimatesbetweentraditionalfarmer-reportedmethodsandmoremodernapproachesusingGlobalPositioningSystem(GPS)devicesforobjective
measurements.
Agriculturallandisacrucialassetforfarmers,servingasthefoundationoftheireconomiclivelihood.Itfacilitatesvariousactivitiessuchascropcultivation,animalhusbandry,fisheries,andforestry.Historically,obtainingaccurateandunbiasedmeasurementsofagriculturallandshasbeenachallengingaspectofagriculturalstatistics.However,byidentifyingandaddressingbiasesinthesemeasurements,policymakerscangainamorepreciseunderstanding
ofagriculturalproductivity.Theadventofgeospatialtechnologieshasmadethistaskmoreaccessibleand
economical,revolutionizingthewayagriculturalareasaremeasured.Thistechnologicalshifthasmadeobjectiveareameasurementnotonlymorefeasiblebutalsomorecost-effective.
Thisreportfeaturesanin-depthanalysisofanareaframeapproachimplementedintheCookIslands.Theapproachusesnon-overlappingandrelativelyfixedgeographicalunitsfromwhichasamplemaybedrawn,insteadofthe
moretime-consumingtraditionallistframecomprisingagriculturalholdingscompiledduringanagriculturalcensus.
Geospatialdatacanbeintegratedwithasampleofpolygonsdrawnfromanareaframe,whichcanbefurtherstratifiedbyvariouscharacteristicssuchastopography.
Additionally,thereportdelvesintotheuseofgeospatialtechnologiestoassessbiasesinagriculturallandreporting
inArmenia,theCookIslands,andtheLaoPeople'sDemocraticRepublic(PDR).Thestudyemployedarangeof
geospatialtechniquesforanunbiasedmeasurementofagriculturalland.Oneofthekeystrengthsofthisstudyisitsexplorationofthefeasibilityandapplicabilityoftheapproachacrossthreecountriesindifferentregionswithdistinctcharacteristics,agroclimaticconditions,andsocio-politicalcontexts.
TheADBprojectteamwouldliketotakethisopportunitytothanktheimplementingagenciesfromtheStatisticalCommitteeoftheRepublicofArmenia,theCookIslandsMinistryofAgriculture,andtheLaoPDRMinistryof
AgricultureandForestryfortheirinvaluablecontributionsandofferingcriticalinsightsintothediverseagriculturalpracticesacrossAsiaandthePacific.TheteamisgratefultoMr.GagikAnanyan,DeputyofthePresidentofthe
StatisticalCommitteeoftheRepublicofArmenia;Mrs.TemaramaAnguna-Kamana,SecretaryofAgriculture,CookIslandsMinistryofAgriculture;andMs.KhamvayNanthavong,DirectoroftheCenterforAgriculturalStatisticsof
vi
Foreword
theLaoPDRMinistryofAgricultureandForestryforspearheadingtheimplementationoftheprojectinthepilot
areas.SinceregratitudeisofferedtoArsenAvagyan,WilliamWigmore,TearoaIorangi,PunaKamoe,Angeylie
Ngaoire,andSengphachanKhounthikoummane,forprovidingtechnicalandlogisticalsupportintheconductofallprojectactivities.Further,theteamwouldliketoexpressappreciationtofieldandtechnicalstafffortheirdedicationtocollecting,processing,andanalyzingthedatafromwhichthisstudywouldnotbepossible.
ThereporthasbeenproducedbytheStatisticsandDataInnovationUnitwithintheEconomicResearchand
DevelopmentImpactDepartmentatADB,undertheoveralldirectionofElaineS.Tan.TheprojectandreportteamswereledbyMahinthanJosephMariasingham,withvaluableresearchandtechnicalsupportfromAnthonyBurgard,AnnaChristineDurante,PamelaLapitan,ArturoY.PacificadorJr.,andMashalRiaz.MelanieKellehercopyeditedthefinalmanuscript,EdithCreustypesetthereport,andClaudetteRodrigopreparedthecoverdesign.
Itishopedthatthisstudyaidsintheevolutionofmethodologiesformeasuringagriculturalareas.Thismethodologicaladvancementholdsthepotentialtoenhanceaccessibilityandaccuracyinagriculturaldatacollection.Itisanticipatedthatthisreportwillhaveapositiveinfluenceonthefutureofagriculturalstatistics.
AlbertFrancisPark
ChiefEconomistandDirectorGeneral
EconomicResearchandDevelopmentImpactDepartmentAsianDevelopmentBank
vii
INTRODUCTION
ATechnologicalShiftinAgriculturalStatistics
Thegrowingaccessibilityofgeospatialtechnologiesisreshapinghowagriculturalstatisticsaregathered,processed,anddisseminated.Advancedtechnologieslikeremotesensingusingsatelliteimagery,GlobalPositioningSystem
(GPS),andunmannedaerialvehicles(UAVs)offerthepotentialformoreefficientmethodstomonitorchangesinagriculturewithgreaterprecisionandfrequency.
Oncecost-prohibitiveforlarge-scalestatisticaldatacollection,geospatialtechnologiesarebecomingincreasinglycommonplace,efficient,andaccessibleinofficialstatistics.Consumer-gradeequipmentisnowmorecapable
andlessexpensive.Ascomputer-assistedinterviewingdatacollectionmethodsonceusheredinthedigitizationofstatisticaldatacollections,thesamemoderntechnologiesintabletcomputersprovideameanstosimplify
geospatialdatacollection.Itisnowmorecommonplaceforagriculturaldataproducerstoregularlycollect,forexample,thepointlocationofagriculturalhouseholdsandboundaryareasofagricultureandcroplands.
Similarly,thecostofremotesensingsatelliteimageryhasdecreased,largelyduetoinitiativesbyorganizationsliketheEuropeanSpaceAgency(ESA),theJapanAerospaceExplorationAgency,andtheNationalAeronauticsandSpaceAdministration,whichhavemadehigh-resolutionsatelliteimagerymorereadilyavailableasafreeglobal
publicgood.
GreateraccessibilityofUAVsandultra-high-resolutionimageryhaveempowered,forexample,thePacificislandcountries—whichhavetraditionallybeensusceptibletoclimatechange—toregularlymapandmonitorland
changeswithgreaterdetailandtimeliness.Theseadvancementspavethewayforthebroaderadoptionandutilizationofgeospatialtechnologies,significantlyenhancingagriculturalstatistics.
OneoftheobjectivesoftheAsianDevelopmentBank(ADB)technicalassistanceprojectistointegrategeospatialtechnologiesintotraditionalsurveydesignandbuildthecapacityofdataproducersintheregiononitspotential
usecaseapplications.Despitetheincreasingrelevanceofsuchtechnology,nationalstatisticalofficesandofficialproducersofagriculturalstatisticsoftenfacechallengesinitsutilization.Thisincludeshiringstaffskilledin
workingwiththesedatatypesandupgradinginformationtechnologyinfrastructuretomanagethelargerdatasets.Whilemanyorganizationshaveestablishedgeographicinformationsystem(GIS)unitswithintheiroffices,their
applicationisprimarilylimitedtocreatinganddistributingmaps.Therehasbeenlimitedprogressbycomparisoninintegratinggeospatialtechniquesintosurveydesignanddatacollectionprocesses.
Oneinnovation,however,usesgeospatialtechniquesforsurveydesignandimprovesuponthetraditional
samplinglistframe.Constructionofthetraditionallistframe—acomprehensivelistofagriculturalholdingsina
country—isacostlyundertakingoftencompletedonceevery5to10yearsduringagriculturecensusesand—ifwellmaintained—updatedthroughasystemofintercensalagriculturalsurveys.Thelistframeisapainpointformany
1
PlottingfromAbove
officialdataproducersasitisnotoriouslydifficultandexpensivetobuild,update,andmaintain.Whilecountries
intheregionhavetrendedtopursueafarmer-registry-basedapproachtotheconstructionoftheseframes,they
arecurrentlylimitedbylowfarmervolunteerratesandmaylackkeyauxiliarydatatoserveasaneffectivesamplinglistframe.Acomplementaryapproachhasbeenforofficialstatisticsproducerstoadoptamixed-frameapproachincorporatingtheuseofanareaframe.Anareaframeconsistsofnon-overlappingandrelativelyfixedgeographicalunitsfromwhichasamplemaybetaken.
Alimitationofareaframesisthattheyarenotalwaysoptimizedforstatisticalpurposesandareconstructedwith
broaderusecases,suchasthedemarcationofadministrativeboundaries.Thisoftenresultsininsufficientauxiliaryinformationtoenhancesurveysampleefficiency.Withthegrowingaccessibilityofgeospatialdata,opportunities
existtointegratediversegeospatialdatasources,includinglanduseorlandcovermaps,topographicalmaps,and
thelocationsofnaturalandhuman-madefeatures.Usinglocationasareferencepoint,thesedatacanbeintegratedtoenhancesamplingmethods.Thisintegrationallowsformoreefficientor“smart”samplingapproaches—suchas
stratifyingbydifferingagriculturalcharacteristics—therebyimprovingtheaccuracyandefficiencyofdatacollectionprocesses.Thisstratificationcould,forexample,bebasedonthedensityoftheestimatedagriculturalareaor
distinctagroecologicalzones,thusimprovingtheprecisionofthesurveysample.
InseveralAsiancountries,nationalstatisticalofficesandagriculturallineministriesaretransitioningtoprecisionagricultureusingdigitalrecordsandgeospatialinformationtomapagriculturalareas.Thisincludesdigitizing
agriculturalparcelstoenhanceproductionstatisticsestimationasseeninthelastagriculturecensusofthe
People’sRepublicofChina,theSmartFarmInitiativeintheRepublicofKorea,andtheagriculturaladministrativerecordsysteminSriLanka.Additionally,theseplatformsofferthepotentialforasystemofgroundtruthvalidationpointsrequiredforothertechnicalestimationsuchasremotesensing-basedcropestimation.
ThispaperwillexploreacasestudyforimplementinganareaframeapproachintheCookIslandsusingalandcovermapdevelopedwiththeassistanceofESAasanauxiliarydatasource.Thelandcovermap—createdfromhigh-
resolutionsatelliteimageryofRarotongaIslandin2021—enabledtheclassificationofareaswithahighprobabilityofagriculturalproduction.Thisclassificationwasinstrumentalindeterminingthesampleallocationforapost
enumerationsurveyconductedafterthe2021AgricultureCensus.
Thepaperwillfurtherinvestigateusinggeospatialtechnologiestoevaluatebiasesinreportingagriculturalland
inArmenia,theCookIslands,andtheLaoPeople’sDemocraticRepublic(LaoPDR).Thestudyapplieddiverse
geospatialmethodsforanobjectivemeasurementofagriculturalland,includingspecializedhandheldGPSdevicesandtablet-basedsoftwarefordigitizingtheboundariesofagriculturalparcelsonhigh-resolutionsatelliteimagery.
AgriculturalLandisaKeyFactorinEconomicProduction
Agriculturallandisakeyproductiveassetforfarmers,formingthebaseoftheireconomiclivelihood.Itisakeyfactorofproduction,enablingthegrowingofcrops,raisinganimals,fisheries,andforestryactivities.Thesizeofagricultural
landisacriticalstatisticfromapolicyperspectiveasithelpspolicymakersbetterunderstandhowfarmingis
structuredinacountry.Accuratemeasurementsofagriculturalareaareimportantforevaluatinghowproductivefarmsare,planningforagriculturalgrowth,andmakingeffectiveagriculturalpolicies.
Fromamacroeconomicperspective,agriculturallandareafeedsintothecriticalcalculationofpotentialeconomicoutput.Inmanycases,cropproductionstatisticsarederivedbasedonreportedagriculturalareamultipliedbyanaverageyieldestimateforthelocality.Anybiasesinlandareaestimatesreportedbythefarmerwillsignificantly
compoundtheestimatefortotalagriculturaloutput.
2
Introduction
Biasesinestimatingagriculturalareasmayalsonegativelyimpactresourceallocationstogovernmentsupport
programs.Foodsecurityisaprimaryconcernformanygovernments,especiallythoseinclimate-vulnerableareassuchasthePacificislandcountries.Anoverestimationorunderestimationofagriculturallandarea—andtherebyproduction—canaffecttheabilityofacountrytomeetitscaloricandnutrientneedssustainably.Andwherefoodsecurityisachallenge,improvedstatisticsontheagriculturalareahelpgovernmentsimproveplanstoimportkeyagriculturalcommoditiestomeettheserequirements.Thesedatamaythenbeusedtosupportcropandinput
subsidies,cropinsuranceschemes,andadditionaltechnicalsupportthroughagriculturalextensionservices.
Finally,agriculturesignificantlyimpactstheenvironment,contributingtogreenhousegasemissionsand
encroachmentonnaturalforests,leadingtobiodiversityloss.Improvedestimatesofagriculturallanduseareessentialforurbanandrurallanduseplanningandmanagingtheseimpactsinthelongterm.
RecallBiasesinEstimatingAgriculturalLand
Thecommonmethodforestimatingagriculturallandincensusandsurveysinvolvessubjectiverecallbyfarmers,
askingthemtoreporttheextentoftheiroperatedland.Thisapproachpresentsseveralchallenges.Itassumes
farmers’understandingofthetermoperationalagriculturalland,aconceptthatcanintroducenon-samplingbiasesifunclear.Theseissuesarecompoundedbydifferencesinagriculturalpracticesthroughouttheregion,wherein
somecountries,itmaybecommontosharecommunalareasforagriculturalproductionandliveandworkinareaswherelandtenureisnotclearlydefined.
Thismethodassumesfarmershaveaccurateknowledgeofthesizeoftheirland.Thisknowledgeistypicallybasedoninformationfromformallandtitlesordeeds,providingofficialdocumentationofprecisemeasurementsofthe
land.Withoutthesedocuments,farmers’estimatesmaybelargelyspeculative.InArmenia,forexample,astrong
landcadastralsystemexistsinwhichlandareaislinkedwithpropertytaxandgovernmentplanningsystems.Insuchcases,farmerknowledgeoftheirareaisbasedonhowupdatedthesesystemsareandtheextentofpublicaccesstothesedocuments.
Thereisalsotheissueofreportedareameasurementunits.Familiaritywithstandardunitsofareameasurementisnotalwayscommonamongfarmers.Forinstance,intheCookIslands,afarmermightdescribetheirlandintermsofarugbyfieldsizeorreferencenaturallandmarkslikealargetree.IntheLaoPDR,localunitssuchas“lai”and“ngam”arecommon,complicatingaccuratereportinginstandardizedunitslikeacresorhectares.Farmersmayusedifferentareaunitsfordifferentlandfeaturesincertaininstances.Forexample,totalareamightbereportedinacres,while
individualplotsaredescribedinsquaremeters(m2).Differencesinareaunitsreportedmayburdenthefieldstaffwhenperformingqualityassurancechecks.
Thelackoffamiliaritywithstandardizedunitsofmeasurementaddstotheresponseburdenforfarmers,leading
themtoeitherinaccuratelyconverttheunitsorgivespeculativeanswers.Toaddressthis,agriculturalsurveys
increasinglypermitrespondentstospecifytheunitsusedforeacharea-relatedquestion.However,inconsistencies
inreportedareasremainacommonissue.Theserequirecarefulvalidationandadjustmentduringthedataprocessingtoensureaccuracyandconsistency.
Finally,thephysicalcharacteristicsofthelandcanhinderaccurateareaestimation.InmanyAsianandPacific
countries—especiallysmallholdermixedcroppingsystems—agriculturalparcelsoftenhaveirregularshapes.
Theymaybesituatedinsteepmountainousterrain,affectingfarmers’perceptionoftheirsize.Thiscomplexitycanleadtoinaccuraciesinreportedlandarea,significantlyimpactingthequalityofagriculturalstatistics.
3
PlottingfromAbove
IntroducingObjectiveMeasurementstoAssessAgriculturalLand
Acknowledgingthesubjectivebiasesassociatedwithfarmerrecalldata,oneapproachtomitigatethisisbyintroducing
objectiveareameasurement.Traditionally,objectiveareameasurementinvolveslandsurveyingtodelineateagriculturalparcelsusingthetape-and-compassapproach(FAO,1982).Thismethodentailsmeasuringeachsideoftheparcel
withatapemeasureandusingacompasstodeterminetheanglesbetweensides.However,thistechniqueistime-consumingandresource-intensive.Italsodemandshighlyskilledworkerstoperformprecisemeasurementsandcalculatetheareausingcomplextrigonometricfunctions.Whendonecorrectly,however,thetapeandcompass
methodisconsideredthe“goldstandard”foragriculturalareameasurement(Carlettoetal.,2016).
In2018,ADBconductedapilotstudytoexploreusingGPSandsatellitedataastechnologicalalternativesfor
objectivelymeasuringagriculturalparcels.Thestudyfindingsindicatedthatthesemethodsalignedwellwiththe
“goldstandard”ofmeasurementand,onaverage,weremor
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