You are here:
Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI Products
Citation:
Iiames, J., R. Congalton, T. Lewis, AND D. Pilant. Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI Products. Remote Sensing. MDPI, Basel, Switzerland, 7(0):1397-1421, (2015).
Impact/Purpose:
Leaf area index (LAI), defined here as one-half of the total leaf area per unit ground surface area [1], has been estimated at a global scale from spectral data processed from a number of moderate resolution sensors. Validation efforts for these moderate resolution LAI products (i.e., >1 km) have a similar structural design where field observed LAI measurements are upscaled — the process of associating field measurements with spectral reflectance values from high-resolution imagery (i.e., 20-30 m). This high-resolution ‘LAI reference map’ (LAI-RM) is then aggregated to the target LAI product resolution [2]. Atmospheric modelers at the United States Environmental Protection Agency (US EPA) have considered integrating temporally and spatially explicit space-based LAI inputs into atmospheric deposition and biogenic emission models. Understanding the uncertainty within this validation process is necessary to assess whether a non-spatially explicit static LAI value should be used rather than LAI values extracted from a satellite-derived LAI product. This research assessed the uncertainty in key factors associated with the creation of a high-resolution LAI reference map (in situ ‘upscaling’), specifically addressing uncertainty in the indirect in situ optical measurements of loblolly pine (Pinus taeda) LAI and the uncertainty in the land cover (LC) classification process.
Description:
The validation process for a moderate resolution leaf area index (LAI) product (i.e., MODIS) involves the creation of a high spatial resolution LAI reference map (Lai-RM), which when scaled to the moderate LAI resolution (i.e., >1 km) allows for comparison and analysis with this LAI product. This research addresses two major sources of uncertainty in the creation of the LAI-RM: (1) the uncertainty associated with the indirect in situ optical measurements of southeastern United States needle-leaf LAI and (2) the uncertainty in the process of classifying land cover (LC). Uncertainty within the loblolly pine (Pinus taeda) in situ data collection was highest for the assessment of the plant area index (PAI), Le (27.2%), and the woody-to-total ratio, α, (30.6%). The needle-to-shoot ratio, λE, and the element clumping index, ΩE, contributed 14.9% and 9.3%, respectively, to the uncertainty in the calculation of LAI. Combining LC differences (3.4%) with the uncertainty within the loblolly pine component resulted in doubling the LAI-RM variability (σ = 0.50 to σ = 0.97) at the 1 km2 validation site located in Appomattox, Virginia, USA.