Skip to Main Content
Due to a lapse in federal funding, this USDA website will not be actively updated. Once funding has been reestablished, online operations will continue.
Modeling gross primary production of an evergreen needleleaf forest using MODIS and climate dataAuthor(s): Xiangming Xiao; Qingyuan Zhang; David Hollinger; John Aber; Berrien, III Moore
Source: Ecological Applications 15(3):954-969
Publication Series: Scientific Journal (JRNL)
Station: Northeastern Research Station
PDF: View PDF (1.86 MB)
DescriptionForest canopies are composed of photosynthetically active vegetation (PAV, chloroplasts) and nonphotosynthetic vegetation (NPV, e.g., cell wall, vein, branch). The fraction of photosynthetically active radiation (PAR) absorbed by the canopy (FAPAR) should be partitioned into FAPARPAV and FAPARNPV. Gross primary production (GPP) of forests is affected by FAPARPAV. In this study we developed and validated a satellite-based vegetation photosynthesis model (VPM; GPP = εg X FAPAPPAV X PAR) that incorporates improved vegetation indices derived from the moderate resolution imaging spectroradimeter (MODIS) sensor. Site-specific data from the CO2 flux tower site (evergreen needleleaf forest) at Howland, Maine, USA, were used. The enhanced vegetation index (EVI) better correlated with the seasonal dynamics of GPP than did the normalized difference vegetation index (NDVI). Simulations of the VPM model were conducted, using both daily and eight-day composites of MODIS images (500-m spatial resolution) and climate data (air temperature and PAR), respectively. Predicted GPP values in 2001 agree reasonably well with estimated GPP from the CO2 flux tower site. There were no significant differences in VPM-predicted GPP (from eight-day MODIS composites) among one pixel (~500-m resolution), 3 X 3 pixel block (~ 1.5-km resolution), and 5 X 5 pixel block (~ 2.5-km resolution). The differences between VPM-predicted and observed GPP were smaller for simulations using eight-day MODIS composites than for simulations using daily MODIS images. The results of this study have shown the potential of MODIS data (both daily and eight-day composites) and the VPM model for quantifying seasonal and interannual variations of GPP of evergreen needleleaf forests.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, email@example.com if you notice any errors which make this publication unusable.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationXiao, Xiangming; Zhang, Qingyuan; Hollinger, David; Aber, John; Moore, Berrien, III. 2005. Modeling gross primary production of an evergreen needleleaf forest using MODIS and climate data. Ecological Applications 15(3):954-969
KeywordsCO2 flux, Howland forest (Maine, USA), vegetation photosynthesis model
- Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation.
- Satellite-based modeling of gross primary production in an evergreen needleleaf forest
- Evaluation of MODIS NPP and GPP products across multiple biomes.
XML: View XML