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Validation of the GLC2000 products

This article discusses the validation strategy and quantitative accuracy assessment of GLC2000 products, including a systematic review by experts, comparison with reference data, and collaboration with local partners. It also explores the confidence-building method through a descriptive protocol, use of ancillary data, and archiving the evaluation in a database. The article further delves into the qualitative validation grid and design-based validation for statistical accuracy assessment. Key issues and considerations for validation are also addressed.

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Validation of the GLC2000 products

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  1. Validation of the GLC2000 products Philippe Mayaux

  2. GLC 2000 validation strategy Confidence-building method • Systematic review of the regionalproducts by experts and comparison with reference data Design-based method • Quantitative accuracy assessment of the global product using a stratified random sampling of high-resolution sites (in agreement with the CEOS-IGOS recommendations)

  3. Objectives of the quality control • to avoid macroscopic errors before the quantitative accuracy assessment • Wrong labels & limits • Inter- and intra-continental inconsistencies • Location of the errors (thematic or geographical) • toimprove the global acceptanceof GLC2000 products • collaboration with local partners

  4. Confidence-building method • Systematic descriptive protocol to document the verification per cell(proposed size = 2 by 2 degrees at the equator ~ 50,000 km2) • Use of ancillary data (maps, Landsat & SPOT images, aerial photographs…), expert opinion and intrinsic properties of the dataset (temporal profiles, colour composites…) • Archive the evaluation in a database

  5. The qualitative validation grid

  6. Qualitative check fields • Name of the expert • Type of reference material: high-resolution image, quick-look, thematic map, aerial photograph, field photograph • Spatial pattern: from homogenous to heterogeneous (4 levels) • Overall quality of the GLC product, very good, good, acceptable, unacceptable • LC classes well-identified and LC classes poorly identified • Nature of problem: label, limit, missing class, other

  7. Status of the quality control • Regions covered: Eurasia, Asia, Scandinavia, Africa, Canada

  8. Derived analysis

  9. An example in Russia

  10. An exemple in Asia

  11. Design-based validation • Objective: To provide a statistical assessment of the accuracy by class and an overall accuracy of the global map. • Constraints: • budget (data, interpretation) • time • spatial complexity • seasonality

  12. Key issues for the validation • Sampling issues (scheme, frame, size) • Reference material(nature, interpretation) • Accuracy statements (contigency matrix, fuzzy logic, double regression) • Single pixels or pixel blocks? • Upscaling of legends (mosaic classes) • Spatial pattern (linear, massive, diffuse) • Rare classes important for several users • Universal dataset • Detailed discussion during the CEOS workshop “Validation of Global Land-Cover Products”, 27-28 March

  13. Land-cover class area

  14. Regions of interest

  15. Land cover area per region

  16. Random sampling equally distributed per region

  17. Stratified sampling per class

  18. Stratified sampling per class

  19. Stratified sampling per class

  20. Interpretation of reference material • Reference material: high spatial resolution interpretations • CNES & NASA / USGS / UNEP-GRID • Existing sources of images • Interpretation by local experts • Very-well focused (better 1 or 2 good experts than a pool of less qualified experts) • Contracts with GVM Unit when necessary (realised on-site) • Visual interpretation • Efficiency • Accuracy • LCCS-based interpretation of the high-resolution images

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