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Community level data collection and data management

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They may be complimentary non-durable goods such as fruits, ... Link measurements to satellite imagery and other data. Data analysis is a continuous process ... – PowerPoint PPT presentation

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Title: Community level data collection and data management


1
Community level data collectionand data
management
  • Patrick Van Laake
  • ITC

2
Community Forest Management
  • The management of local forest resources by
    organized community groups has proven to be very
    successful
  • Ownership
  • Long-term commitment
  • Social / Culturalpressure to protectthe forest

3
Secondary uses of the forest
  • Many communities rely on the forest for
    sustenance or livelihood
  • Such uses may be combined with REDD
  • They may be complimentary non-durable goods
    such as fruits, herbs, leaves
  • They can increase the productivity of the
    forest higher total income from the forest
  • Together they can be a viable alternative for
    deforestation or forest degradation

4
Carbon assessment by communities
  • With very little trainingand support,
    communitiescan accurately assessbasic
    parameters of theforest
  • Tree count
  • Species identification
  • DBH measurement
  • Cost of assessment isbetween 1 4 perhectare
    per year
  • Potential for collectinglarge volumes of data

5
Supplementary data
  • The data that the communities collect is
    relatively basic
  • Supplementary services and data collection by a
    professional party can increase accuracy
  • Stratification of the forest, determination of
    number and location of sampling plots
  • Wood density, free branch height, total tree
    height
  • Development of allometric equations
  • Large-scale data collection opens up
    opportunities for statistical analysis and
    filtering of data

6
Data collection procedures
  • Communities do not need much training to collect
    data
  • Plot and data management requires support
  • Support can be provided by NGOs that serve
    multiple communities
  • Equipment to support datacollection is ever
    moreaccessible and affordableGPS, PDA, smart
    phone
  • NGOs can help shareknowledge and
    equipmentbetween communities

7
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8
Allometric equations
  • Allometric equations give the relationship
    between above-ground biomass and some property of
    the tree
  • ln(AGBtree) c1 c2 ln(DBH)
  • Allometric equations have been developed for a
    few commercially interesting tree species, as
    well as for tropical forests
  • Better results are obtained with locally derived
    allometric equations, specific to forest type,
    ecological zone and management
  • Deriving allometric equations is costly, but may
    have large benefits for generating carbon credits
  • Allometric equations can be based on the type and
    quality of the data collected by local
    communities
  • Including properties beyond DBH may give a better
    prediction of biomass, but data collection will
    be more difficult

9
Data to be collected
  • For allometric equations, the typical data are
  • Diameter at breast height
  • Tree count
  • Additional data may be required but more
    difficult to collect
  • Maybe such data is only needed occasionally
  • Data should be collected in sampling plots to
    which the local community already has access
  • Provide labour in return for benefits money,
    use of forest resources
  • This depends very much on tenancy rights,
    economic opportunity, etc
  • Data can be collected on a regular basis
  • It is preferable to do so more often than
    strictly required
  • Create awareness, maintain involvement and
    experience
  • Extra data can be used for quality control
  • Other data should be collected as well
  • Use of the forest resources by the local
    population
  • Substitution of non-renewable resources by forest
    products
  • Ownership, use rights, cultural and social
    importance

10
Managing data
  • The volume of data that will be collected on a
    national scale is likely to be enormous
  • The responsible agency needs to set up enterprise
    class infrastructure to manage the data
  • Specially trained and dedicated staff will be
    necessary to operate the data management system
  • Unless the data management system is properly
    designed, analysis, quality assurance and
    reporting will be very difficult or impossible
  • UNFCCC will likely have stringent reporting
    guidelines and validation may require reviewing
    of raw data

11
Multi-user single data
Database
12
Data delivery
  • Data will come from everywhere
  • Paper records
  • Process in a field office and send through
    internet
  • Field data computers
  • Upload through internet from field office
  • Smart phones
  • Direct upload in standard format
  • Standard forest inventory
  • This will be non-standard data that has to be
    dealt with in a special way
  • The data management system will have to allow for
    all these different mechanisms to supply data

13
Data management for REDD
Emission reduction claim
Data management, analysis, quality assurance,
reporting
Forest inventory data
PFD
14
Data analysis
  • The data that is being delivered from the field
    needs to be processed in order to be useful
  • E.g. using allometric equations
  • This requires a very professional design of the
    data management system
  • Link measurements to time and place
  • Link measurements to community
  • Link measurements to ecological unit
  • Link measurements to satellite imagery and other
    data
  • Data analysis is a continuous process
  • Process data as it is received
  • Do not accumulate data until a report to the
    UNFCCC is due!

15
Data quality assurance
  • Data has to be checked for consistency over time
    and spatially
  • Remove measurement or reporting errors
  • Check if there are consistent errors from a
    location
  • Is the stratification wrong?
  • Does the community receive support or training?
  • Data are grouped in large homogeneous units for
    reporting
  • Multiple measurements give indication of
    variability and accuracy of the measurement
  • If the accuracy is too low
  • Refine the stratification
  • Add more measurements
  • Improve quality of measurements
  • Data quality assurance requires specially trained
    staff
  • Forest ecologists stratification, evaluation of
    measurements
  • Statisticians error analysis, sampling scheme
    design, QA indicators

16
Access to data
  • Even if all the data is uploaded to a national
    database, access should be given to third parties
    to support their efforts
  • Provincial Forest Departments
  • Planning
  • Evaluation of performance
  • Distribution of benefits
  • District Forest Department
  • Planning of activities
  • Support for communities
  • Communities
  • Overview of performance
  • Insight in benefits
  • Society at large
  • Overview of achievements
  • Access can be provided through a web site or with
    brochures, newsletters, etc

17
CCF and RS
  • The data that are collected by local communities
    are collated at higher levels in the national
    hierarchy and ultimately used to compute national
    emission reductions
  • Validation at the international level may very
    well require remote sensing
  • Objective methods exist
  • Uniformly applicable
  • Repeatable
  • Potentially lower transaction costs
  • National governments also want independent
    validation mechanism

18
QuickBird image of oil palm area in West New
Britain province, PNG
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