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Related Experiment Videos

Spatial scaling between leaf area index maps of different resolutions.

Z Jin1, Q Tian, J M Chen

  • 1International Institute for Earth System Science, Nanjing University, Nanjing 210093, China. zhenyu.jin@geog.utah.edu

Journal of Environmental Management
|November 25, 2006
PubMed
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Ignoring surface heterogeneity in coarse resolution Leaf Area Index (LAI) maps causes bias. New algorithms using sub-pixel land cover data correct these biases, significantly improving LAI product accuracy.

Area of Science:

  • Earth Observation
  • Geographic Information Systems (GIS)
  • Ecological Modeling

Background:

  • Leaf Area Index (LAI) is crucial for ecological and biophysical processes.
  • Spatial scaling of LAI from coarse to fine resolutions presents significant challenges.
  • Existing coarse-resolution LAI products may contain biases due to ignored surface heterogeneity.

Purpose of the Study:

  • To develop and validate algorithms for spatial scaling of LAI using sub-pixel information.
  • To investigate the biases introduced by lumped versus distributed LAI calculations.
  • To correct coarse-resolution LAI products using sub-pixel land cover data.

Main Methods:

  • Comparison of LAI derived from distributed (Landsat ETM+) and lumped (resampled coarse data) calculations.

Related Experiment Videos

  • Development of algorithms to remove biases in lumped LAI maps using sub-pixel land cover-type information.
  • Application of developed algorithms to correct a coarse-resolution LAI product.

    • Main Results:

    • Lumped LAI calculations showed considerable bias compared to distributed calculations.
    • Ignoring within-pixel heterogeneity leads to biased global and regional LAI maps.
    • The developed algorithms significantly improved the accuracy of a coarse-resolution LAI product.

    Conclusions:

    • Sub-pixel land cover information is essential for accurate LAI spatial scaling.
    • Algorithms developed can effectively correct biases in coarse-resolution LAI products.
    • Improved LAI products have implications for ecological and climate modeling.