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Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions

Publication ,  Journal Article
Gebremichael, M; Barros, AP
Published in: Remote Sensing of Environment
January 30, 2006

Near real-time vegetation indices derived from MODIS (MODerate resolution Imaging Spectroradiometer) observations (http://modis.gsfc.nasa.gov) provide a first opportunity to monitor ecohydrological systems globally at a spatial resolution consistent with biophysical processes at the field scale. Here, we present work toward the quantitative estimation of the uncertainty associated with MODIS Gross Primary Productivity (GPP), an end-product that depends on several MODIS derived vegetation indices. GPP products, available at 8-day and 1-km resolutions, were evaluated in two representative tropical ecosystems: a mixed forest site in the humid tropics (the Marsyandi river basin in the Nepalese Himalayas), and an open shrubland site in a semi-arid region (the Sonora river basin in northern Mexico). The MODIS-GPP products were compared against simulations made with a process-based biochemical-hydrology model driven by flux tower meteorological observations. Whereas the temporal march of vegetation indices and GPP products is consistent between the model and the algorithm, our study indicates that that there is a positive bias in the case of the mixed forest biome in the Marsyandi basin, and a negative bias in the case of open shrublands in the Sonora basin. We examined the error contribution from the DAO meteorological data used in the standard MODIS GPP products. The bias between the GPP estimates using DAO and tower meteorology is - 2.77 gC/m 2/day (i.e., - 77% of the mean of the tower-based GPP) in the Marsyandi, and 0.33 gC/m2/day (i.e., 18% of the mean of the tower-based GPP) in Sonora. Analysis of the temporal evolution of the discrepancies between the model and the MODIS algorithm points to the need for examining the light use efficiency parameterization, especially with regard to the representation of nonlinear functional dependencies on vapor pressure deficit (VPD), photosynthetically available radiation (PAR), and seasonal evolution of the productive capacity of vegetation as influenced by water stress. © 2005 Elsevier Inc. All rights reserved.

Duke Scholars

Published In

Remote Sensing of Environment

DOI

ISSN

0034-4257

Publication Date

January 30, 2006

Volume

100

Issue

2

Start / End Page

150 / 166

Related Subject Headings

  • Geological & Geomatics Engineering
  • 37 Earth sciences
  • 0909 Geomatic Engineering
  • 0406 Physical Geography and Environmental Geoscience
 

Citation

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Gebremichael, M., & Barros, A. P. (2006). Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions. Remote Sensing of Environment, 100(2), 150–166. https://doi.org/10.1016/j.rse.2005.10.009
Gebremichael, M., and A. P. Barros. “Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions.” Remote Sensing of Environment 100, no. 2 (January 30, 2006): 150–66. https://doi.org/10.1016/j.rse.2005.10.009.
Gebremichael M, Barros AP. Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions. Remote Sensing of Environment. 2006 Jan 30;100(2):150–66.
Gebremichael, M., and A. P. Barros. “Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions.” Remote Sensing of Environment, vol. 100, no. 2, Jan. 2006, pp. 150–66. Scopus, doi:10.1016/j.rse.2005.10.009.
Gebremichael M, Barros AP. Evaluation of MODIS Gross Primary Productivity (GPP) in tropical monsoon regions. Remote Sensing of Environment. 2006 Jan 30;100(2):150–166.
Journal cover image

Published In

Remote Sensing of Environment

DOI

ISSN

0034-4257

Publication Date

January 30, 2006

Volume

100

Issue

2

Start / End Page

150 / 166

Related Subject Headings

  • Geological & Geomatics Engineering
  • 37 Earth sciences
  • 0909 Geomatic Engineering
  • 0406 Physical Geography and Environmental Geoscience