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Enhanced Global Land Cover Classification and Dynamics Analysis

This collection presents refined methodologies for classifying and analyzing global land cover types and dynamics. Includes improved thematic and spatial resolutions, updated databases, and ongoing validations for accuracy.

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Enhanced Global Land Cover Classification and Dynamics Analysis

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  1. Collection 5 Refinements and RevisionsMOD12Q1: Global Land Cover TypeMOD12Q2: Land Cover Dynamics Mark Friedl Dept of Geography and Environment Boston University friedl@bu.edu www-modis.bu.edu/landcover

  2. MOD12Q1 OverviewGlobal Land Cover Type • Thematic classification of land cover • Five Classification Schemes • IGBP, UMD, LAI/FPAR, PFT, Biome-BGC • Internally consistent! • Second most likely IGBP class • Classification confidence • C4: Global, 1-km, annual (2001-2004)

  3. MOD12Q2 OverviewLand Cover Dynamics • Global database • Twice per year • 12-month time periods • Includes 7 metrics • Onset of EVI increase, • Onset of EVI maximum, • Onset of EVI decrease, • Onset of EVI mimimum, • Min, max, & sum of growing season EVI • Collection 4 • Produced for 2001-2004 • Available on the LP DAAC Timing Annual Metrics

  4. Extract Exemplars From STEP Database MOD12Q1: Summary of Key Changes Estimate Classification (Ensemble Decision Trees) • Revision of land cover training site database • Smaller, high quality sites (~1500) • More recent scenes (post-2000) • Input features • 8-day, 500-m NBAR data • aggregated to 32-day • EVI, LST (MOD11) • Annual Metrics • Updated “priors” layers • Based on MOD12 C4 • New global agriculture from inventory data Apply Classification to Global Data Fuse Results With Ancillary Data (post-processing) Maps

  5. Preliminary C5 Results

  6. Preliminary C5 Results

  7. Preliminary C5 Results

  8. Preliminary C5 Results

  9. MOD12Q2: Summary of Key Changes • Temporal resolution • Using 8-day EVI • Spatial Resolution • 500-mNBAR inputs • Improved screening for snow • Using NBAR snow-flag in combination with LST (MOD11) • Identification and correction of several minor bugs in code.

  10. Summary • Key Results from Changes • Improved spatial resolution (MOD12Q1, Q2) • Improved temporal resolution (MOD12Q2) • Fewer missing values (MOD12Q1, Q2) • Most importantly • Improved thematic quality for MOD12Q1 • Improved accuracy & precision for MOD12Q2 • Ongoing and Future Activities (C6) • Focus on problematic classes; FAO LCCS • Stabilization across years • Smoothing and interpolation (clouds) for MOD12Q2 • Validation for C5 versions of both products • Creation of 1-km and CMG for C5

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