Comparison of MODIS gross primary production estimates for forests across the U.S.A. with those generated by a simple process model, 3-PGS. Nightingale, J. M., Coops, N. C., Waring, R. H., & Hargrove, W. W. Remote Sensing of Environment, 109(4):500–509, August, 2007. ![Comparison of MODIS gross primary production estimates for forests across the U.S.A. with those generated by a simple process model, 3-PGS [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Since 2000, NASA's Moderate Resolution Imaging Spectro-radiometer (MODIS) has provided 1×1 km estimates of 8-day gross primary production (GPP). The MODIS algorithm computes GPP as a simple function of absorbed photosynthetically active radiation and a regionally assigned light-use conversion efficiency (LUE) that is reduced if temperature or atmospheric vapor pressure deficits are suboptimal. We compared MODIS-derived GPP estimates for forested areas across the United States of America (U.S.A.) with those generated by the 3-PGS (Physiological Principles Predicting Growth using Satellite data) model, the latter of which considers spatial variation in available soil water storage capacity (ASWC) and nitrogen content. We expected seasonal and annual MODIS GPP values to be in close agreement with those derived from the 3-PGS model in regions with adequate precipitation, soil water storage, and moderately fertile soils. 3-PGS was initially run with STATSGO-derived soils information provided by the Oak Ridge National Laboratory. The analysis was expanded to include sensitivity analyses with ASWC set at 50, 100, 300, and 400 mm to identify areas within nine major ecoregions where drought might prove to be a major limitation on GPP. The majority of forests across the U.S.A. were relatively insensitive to large variations in ASW storage. In areas where ASWC was assumed \textless200 mm and average annual rainfall was \textless100 mm yr−1, GPP was predicted to be reduced by \textgreater60%. There was generally good agreement (within 20%) between MODIS and 3-PGS estimates of forest GPP across the U.S.A. GPP predicted by the MODIS model was generally higher in ecoregions with substantial drought and with relatively low soil fertility. The latter, which influences LUE, was more than twice as important as soil drought.
@article{nightingale_comparison_2007,
title = {Comparison of {MODIS} gross primary production estimates for forests across the {U}.{S}.{A}. with those generated by a simple process model, 3-{PGS}},
volume = {109},
issn = {0034-4257},
url = {https://www.sciencedirect.com/science/article/pii/S003442570700079X},
doi = {10.1016/j.rse.2007.02.004},
abstract = {Since 2000, NASA's Moderate Resolution Imaging Spectro-radiometer (MODIS) has provided 1×1 km estimates of 8-day gross primary production (GPP). The MODIS algorithm computes GPP as a simple function of absorbed photosynthetically active radiation and a regionally assigned light-use conversion efficiency (LUE) that is reduced if temperature or atmospheric vapor pressure deficits are suboptimal. We compared MODIS-derived GPP estimates for forested areas across the United States of America (U.S.A.) with those generated by the 3-PGS (Physiological Principles Predicting Growth using Satellite data) model, the latter of which considers spatial variation in available soil water storage capacity (ASWC) and nitrogen content. We expected seasonal and annual MODIS GPP values to be in close agreement with those derived from the 3-PGS model in regions with adequate precipitation, soil water storage, and moderately fertile soils. 3-PGS was initially run with STATSGO-derived soils information provided by the Oak Ridge National Laboratory. The analysis was expanded to include sensitivity analyses with ASWC set at 50, 100, 300, and 400 mm to identify areas within nine major ecoregions where drought might prove to be a major limitation on GPP. The majority of forests across the U.S.A. were relatively insensitive to large variations in ASW storage. In areas where ASWC was assumed {\textless}200 mm and average annual rainfall was {\textless}100 mm yr−1, GPP was predicted to be reduced by {\textgreater}60\%. There was generally good agreement (within 20\%) between MODIS and 3-PGS estimates of forest GPP across the U.S.A. GPP predicted by the MODIS model was generally higher in ecoregions with substantial drought and with relatively low soil fertility. The latter, which influences LUE, was more than twice as important as soil drought.},
language = {en},
number = {4},
urldate = {2023-06-29},
journal = {Remote Sensing of Environment},
author = {Nightingale, J. M. and Coops, N. C. and Waring, R. H. and Hargrove, W. W.},
month = aug,
year = {2007},
keywords = {Terrestrial Ecoregions (CEC 1997)},
pages = {500--509},
}
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The MODIS algorithm computes GPP as a simple function of absorbed photosynthetically active radiation and a regionally assigned light-use conversion efficiency (LUE) that is reduced if temperature or atmospheric vapor pressure deficits are suboptimal. We compared MODIS-derived GPP estimates for forested areas across the United States of America (U.S.A.) with those generated by the 3-PGS (Physiological Principles Predicting Growth using Satellite data) model, the latter of which considers spatial variation in available soil water storage capacity (ASWC) and nitrogen content. We expected seasonal and annual MODIS GPP values to be in close agreement with those derived from the 3-PGS model in regions with adequate precipitation, soil water storage, and moderately fertile soils. 3-PGS was initially run with STATSGO-derived soils information provided by the Oak Ridge National Laboratory. 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