Terrestrial primary production is a fundamental ecological process and a crucial component in understanding the flow of energy through trophic levels. The global MODIS gross primary production (GPP) and net primary production (NPP) products (MOD17) are widely used for monitoring GPP and NPP at coarse resolutions across broad spatial extents. The coarse input datasets and global biome-level parameters, however, are well-known limitations to the applicability of the MOD17 product at finer scales. We addressed these limitations and created two improved products for the conterminous United States (CONUS) that capture the spatiotemporal variability in terrestrial production. The MOD17 algorithm was utilized with medium resolution land cover classifications and improved meteorological data specific to CONUS in order to produce: (a) Landsat derived 16-day GPP and annual NPP at 30 m resolution from 1986 to 2016 (GPPL 30 and NPPL 30, respectively); and (b) MODIS derived 8-day GPP and annual NPP at 250 m resolution from 2001 to 2016 (GPPM 250 and NPPM 250 respectively). Biome-specific input parameters were optimized based on eddy covariance flux tower-derived GPP data from the FLUXNET2015 database. We evaluated GPPL 30 and GPPM 250 products against the standard MODIS GPP product utilizing a select subset of representative flux tower sites, and found improvement across all land cover classes except croplands. We also found consistent interannual variability and trends across NPPL 30, NPPM 250, and the standard MODIS NPP product. We highlight the application potential of the production products, demonstrating their improved capacity for monitoring terrestrial production at higher levels of spatial detail across broad spatiotemporal scales.
- Google earth engine
- gross primary production
- net primary production
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Computers in Earth Sciences
- Nature and Landscape Conservation