Assessing the accuracy of the MODIS LAI 1-km product in southeastern United States loblolly pine plantations: Accounting for measurement variance from ground to satellite

Leaf area index (LAI), defined here as one-half of the total leaf area per unit ground surface area (Chen, 1996), has been estimated at a global scale from spectral data processed from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard two NASA EOS-AM spacecraft, Terra (launched in 1999) and Aqua (launched in 2002). The MOD15A2 LAI product is a 1 km global data product composited over an 8-day period and is derived from a three-dimensional radiative transfer model driven by an atmosphere corrected surface reflectance product (MOD09), a land cover product (MOD12) and ancillary information on surface characteristics. The United States Environmental Protection Agency (US EPA) initiated validation research (2002) in the evergreen needle leaf biome, as defined in the MOD12 classification, in a regional study located in the southeastern United States. The validation effort was prompted by the potential use of MODIS LAI inputs into atmospheric deposition and biogenic emission models developed within the US EPA Office of Research and Development. The MODIS LAI validation process involves the creation of a high spatial resolution LAI surface map, which when scaled to the MOD15A2 resolution (1 km) allowed for comparison and analysis with the 1 km MODIS LAI product. Creation of this LAI surface map involved: (1) the collection of in situ LAI measurements via indirect optical measurements, (2) the correlation of land cover specific LAI estimates with spectral values retrieved from high resolution imagery (20 m--30 m), and (3) the aggregation of these 30 m cells to 1 km spatial resolution, matching the resolution of the MODIS product and enabling a comparison of the two LAI values (Morisette et al. 2006). This research assessed the uncertainty associated with the creation of the high-resolution LAI reference map, specifically addressing uncertainty in the indirect in situ optical measurements of LAI and the uncertainty in the land cover classification process. Also addressed was the influence of vegetative understory on satellite-derived vegetation indices from the IKONOS sensor

Dynamics of canopy development of Cunninghamia lanceolata mid-age plantation in relation to foliar nitrogen and soil quality influenced by stand density

It has been generally accepted that different silvicultural practices affect the forest canopy morphology and structure. During forest establishment, many natural sites were converted to coniferous plantations in southern China. Retention of the canopy during stand conversion may be desirable to promote ecological function and meet conservation objectives. We tested the impact of planting density, foliar nitrogen and soil chemical properties on the canopy development of Chinese fir (Cunninghamia lanceolata) mid-age monoculture stands. Low density (1450 trees hm−2 with planting spacing of 2.36 × 2.36 m), intermediate-density (2460 trees hm−2 with planting spacing of 1.83 × 1.83 m) and high density (3950 trees hm−2 with planting spacing of 1.44 × 1.44 m) stands were selected in Xinkou forest plantations in Sanming City, China. Canopy characteristics such as leaf area index (LAI), mean tilt angle of the leaf (MTA) and average canopy openness index (DIFN) were measured. Measurements were taken using LAI-2200 PCA. The results illustrated that stand density was the primal factor responsible in canopy structuring while soil chemical properties seem to play a secondary role for canopy dynamics. LAI increased from 3.974 m2 m-2 to 5.072 m2 m-2 and MTA increases from 34.8° to 48.7° as the stand density increased while the DIFN decreased from 0.1542 to 0.0902 with the increasing stand density but it was no significantly different in intermediate and high-density stands. Additionally, LAI and MTA were positively correlated to foliar nitrogen while the DIFN was negatively correlated. In general, soil available nitrogen, available phosphorus and soil pH were not significant to canopy parameters. The results presented provide guiding principles about the canopy dynamics distribution in varying stand densities from LICOR measurements in mid-age Chinese fir monoculture. Furthermore, this provides a base to study canopy dynamics at mature stage forests because of more senescence activities.This research was financially supported by the National Natural Science Foundation of China (31870614 and 30970451), the Forestry Peak Discipline Project of Fujian Agriculture and Forestry University, China (71201800716) and Postdoctoral research funding of Central South University of Forestry and Technology (70702-45200003)

Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI Products

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

A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA

Vegetative leaf area is a critical input to models that simulate human and ecosystem exposure to atmospheric pollutants. Leaf area index (LAI) can be measured in the field or numerically simulated, but all contain some inherent uncertainty that is passed to the exposure assessments that use them. LAI estimates for minimally managed or natural forest stands can be particularly difficult to develop as a result of interspecies competition, age and spatial distribution. Satellite-based LAI estimates hold promise for retrospective analyses, but we must continue to rely on numerical models for alternative management analysis. Our objective for this study is to calculate and validate LAI estimates generated from the USDA Environmental Policy Impact Climate (EPIC) model (a widely used, field-scale, biogeochemical model) on four forest complexes spanning three physiographic provinces in Virginia and North Carolina. Measurements of forest composition (species and number), LAI, tree diameter, basal area, and canopy height were recorded at each site during the 2002 field season. Calibrated EPIC results show stand-level temporally resolved LAI estimates with R2 values ranging from 0.69 to 0.96, and stand maximum height estimates within 20% of observation. This relatively high level of performance is attributable to EPIC’s approach to the characterization of forest stand biogeochemical budgets, stand history, interspecies competition and species-specific response to local weather conditions. We close by illustrating the extension of this site-level approach to scales that could support regional air quality model simulations

Comparison of EPIC-Simulated and MODIS-Derived Leaf Area Index (LAI) across Multiple Spatial Scales

Modeled leaf area index (LAI) in conjunction with satellite-derived LAI data streams may be used to support various regional and local scale air quality models for retrospective and future meteorological assessments. The Environmental Policy Integrated Climate (EPIC) model holds promise for providing LAI within a dynamic range for input into climate and air quality models, improving on current LAI distribution assumptions typical within atmospheric modeling. To assess the potential use of EPIC LAI, we first evaluated the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product collections 5 and 6 (i.e., Mc5, Mc6) with in situ LAI estimates upscaled at four 1.0 km resolution research sites distributed over the Albemarle-Pamlico Basin in North Carolina and Virginia, USA. We then compared the EPIC modeled 12.0 km resolution LAI to aggregated MODIS LAI (Mc5, Mc6) over a 3 × 3 grid (or 36 km × 36 km) centered over the same four research sites. Upscaled in situ LAI comparison with MODIS LAI showed improvement with the newer collection where the Mc5 overestimate of +2.22 LAI was reduced to +0.97 LAI with the Mc6. On three of the four sites, the EPIC/MODIS LAI comparison at 12.0 km resolution grid showed similar weighted mean LAI differences (LAI 1.29–1.34), with both Mc5 and Mc6 exceeding EPIC LAI across most dates. For all four research sites, both MODIS collections showed a positive bias when compared to EPIC LAI, with Mc6 (LAI = 0.40) aligning closer to EPIC than the Mc5 (LAI = 0.61) counterpart. Despite modest differences between both MODIS collections and EPIC LAI, the overestimation trend suggests the potential for EPIC to be used for future meteorological alternative management applications on a regional or national scale