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USDA Forest Service Forest Inventory and Analysis

USDA Forest Service Forest Inventory and Analysis. An Assessment of Repeatability for Crown Measurements Taken on Conifer Tree Species James A. Westfall William A. Bechtold KaDonna C. Randolph. FIA QA/QC Data Collection. Hot Checks Cold Checks Blind Checks

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USDA Forest Service Forest Inventory and Analysis

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  1. USDA Forest ServiceForest Inventory and Analysis An Assessment of Repeatability for Crown Measurements Taken on Conifer Tree Species James A. Westfall William A. Bechtold KaDonna C. Randolph

  2. FIA QA/QC Data Collection • Hot Checks • Cold Checks • Blind Checks • Independent Plot Remeasurement • Randomly Chosen Plots • Experienced Personnel • Target 3%

  3. Conifer Data • FIA Tree Crown Indicator (Phase 3) • Uncompacted Crown Ratio (nearest 1%) • Light Exposure (6 categories) • Crown Position (4 categories) • Crown Vigor Class (saplings – 3 categories) • Crown Density (nearest 5%) • Dieback (nearest 5%) • Foliage Transparency (nearest 5%)

  4. Analysis • Data Matching (i.e., trees) • No one-to-one correspondence (independent remeasure) • Manually expensive (large # observations) • Automate most matches • 2-pass approach • Weighted distance = f(dbh, horz. distance, azimuth) • ‘Conservatism’ via a decision rule • MUST review unmatched trees and add legitimate matches into analysis data set

  5. Analysis • MQOs and Tolerances • Tolerance • A range of acceptable variation • Can be specific value or percentage • Example: ± 0.1 in. for dbh • Measurement Quality Objective (MQO) • The desired percentage of measurements that fall within the tolerance range • Example: 95% of the time

  6. Analysis • Computations • Obtain differences between field and QA crews for matched observations • Determine percentage of total observations where difference is within the tolerance range • Compare with MQO to see if standard is met • Optional: compute percentages across range of tolerance values

  7. Results *

  8. Results

  9. Results

  10. Uncompacted CR

  11. Vigor Class

  12. Crown Density

  13. Crown Dieback

  14. Foliage Transparency

  15. Conclusion • Crown Light Exposure, Crown Dieback, and Foliage Transparency measurements met the stated repeatability standard. • Uncompacted CR, Crown Position, Crown Vigor, and Crown Density measurements did not meet the repeatability standard.

  16. Conclusion • With few exceptions, levels of repeatability are similar across geographic regions. • The poorest repeatability statistics were generally associated with relatively rarer crown characteristics. • For some variables, improved training and/ or re-evaluation of the tolerance/MQO may be needed.

  17. Conclusion • Quality assurance data are important for: • Evaluating training effectiveness • Employee performance feedback • Evaluating measurement protocols • Identifying significant sources of error for computed attributes, model projections, etc.

  18. Conclusion • Further reading: • Westfall, J.A., ed. 2009. FIA national assessment of data quality for forest health indicators. USDA For. Serv. Gen. Tech. Rep. NRS-53. • Pollard, J.E., et al. 2006. FIA national data quality assessment report for 2000-2003. USDA For. Serv. Gen. Tech. Rep. RMRS-181.

  19. Questions ??

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