Literature DB >> 35136667

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

John S Iiames1, Ellen Cooter2, Andrew N Pilant1, Yang Shao3.   

Abstract

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.

Entities:  

Keywords:  EPIC; MODIS; evaluation; in situ; leaf area index; satellite; simulation

Year:  2020        PMID: 35136667      PMCID: PMC8819677          DOI: 10.3390/rs12172764

Source DB:  PubMed          Journal:  Remote Sens (Basel)        ISSN: 2072-4292            Impact factor:   4.848


  4 in total

1.  Efficient atmospheric cleansing of oxidized organic trace gases by vegetation.

Authors:  T Karl; P Harley; L Emmons; B Thornton; A Guenther; C Basu; A Turnipseed; K Jardine
Journal:  Science       Date:  2010-10-21       Impact factor: 47.728

2.  Inconsistencies of interannual variability and trends in long-term satellite leaf area index products.

Authors:  Chongya Jiang; Youngryel Ryu; Hongliang Fang; Ranga Myneni; Martin Claverie; Zaichun Zhu
Journal:  Glob Chang Biol       Date:  2017-07-06       Impact factor: 10.863

3.  The role of the atmosphere in the provision of ecosystem services.

Authors:  Ellen J Cooter; Anne Rea; Randy Bruins; Donna Schwede; Robin Dennis
Journal:  Sci Total Environ       Date:  2012-08-24       Impact factor: 7.963

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

Authors:  John S Iiames; Ellen Cooter; Donna Schwede; Jimmy Williams
Journal:  Forests       Date:  2018       Impact factor: 2.633

  4 in total

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