Evaluation of MODIS NPP and GPP products across multiple biomes

Turner, David P.; Ritts, William D.; Cohen, Warren B.; Gower, Stith T.; Running, S. W.; Zhao, Maosheng; Costa, Marcos Heil; Kirschbaum, Alan; Ham, Jay M.; Saleska, S. R.; Ahl, Douglas E.

doi:10.1016/j.rse.2006.02.017

Cited by 580 publications

(414 citation statements)

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“…Bandaruet al (2013) found that modeled NPP in Illinois and Iowa were 2.4 and 1.1 times greater than the MODIS GPP/NPP product for corn and soybean, respectively. However, model evaluation did not identify significant biases in other biomes (Sjöström et al, 2013;Turner et al, 2006), which implies that the differences between field and satellite LUE estimates are the most pronounced in croplands (Garbulsky et al, 2010).…”

Section: Introductionmentioning

confidence: 88%

“…Most validation efforts for MODIS GPP have been made using eddy covariance data from flux tower measurements, and some studies suggest increasing the ε * GPP values in models to estimate cropland GPP (Chen et al, 2011;Zhang et al, 2008). On the other hand, some large-scale modeling studies identified overestimations of crop productivity in comparison with statistical inventory data when applying field-derived ε * GPP values (Lobell et al, 2002;Ruimy et al, 1994;Turner et al, 2006). However, two recent studies that incorporate fine-resolution land use maps and coarse-resolution MODIS data recommend applying field-estimated LUE values for large-scale cropland modeling (Bandaru et al, 2013;Xin et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States

Xin

Broich

Suyker

et al. 2015

Agricultural and Forest Meteorology

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Section: Introductionmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States

Xin

Broich

Suyker

et al. 2015

Agricultural and Forest Meteorology

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“…8). It should be kept in mind that MODIS-GPP had a calculated 18 % uncertainty due to climate forcing (Zhao et al, 2006). Besides, a low bias of MODIS-GPP for grasslands has been reported in a tallgrass prairie in the United States (Turner et al, 2006) and in an alpine meadow on the Tibetan Plateau (Zhang et al, 2008) when compared to the GPP from flux-tower measurements.…”

Section: Causes Of Regional Grass-biomass Production Deficitsmentioning

confidence: 99%

“…It should be kept in mind that MODIS-GPP had a calculated 18 % uncertainty due to climate forcing (Zhao et al, 2006). Besides, a low bias of MODIS-GPP for grasslands has been reported in a tallgrass prairie in the United States (Turner et al, 2006) and in an alpine meadow on the Tibetan Plateau (Zhang et al, 2008) when compared to the GPP from flux-tower measurements. The underestimate of MODIS-GPP is mostly related to the low value of the maximum light-use efficiency parameters used in the MODIS-GPP algorithm (Turner et al, 2006;Zhang et al, 2008).…”

Section: Causes Of Regional Grass-biomass Production Deficitsmentioning

confidence: 99%

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

et al. 2016

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Abstract. Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grassbiomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5 • by 0.5 • . The grassbiomass demand is derived from a livestock dataset for 2000, extended to cover the period 1901-2012. The grassbiomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, rising CO 2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6

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“…EVI has been widely used to monitor and measure vegetation growth status [29,30], primary productivity [31][32][33][34][35][36][37], evapotranspiration [38], and plant phenology changes [39].…”

Section: Introductionmentioning

confidence: 99%

The Greenness of Major Shrublands in China Increased from 2001 to 2013

et al. 2016

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Abstract:Shrubs have been reported to expand into grassland and polar regions in the world, which causes complex changes in ecosystem carbon, nutrients, and resilience. Given the projected global drying trend, shrubs with their superior drought resistance and tolerance may play more important roles in global ecosystem function. Shrubland exists in all of the climate zones in China, from subtropical to temperate and high cold regions, and they occupy more than 20% of the land area. In this paper, we analyzed the spatiotemporal trend of MODIS (Moderate Resolution Imaging Spectroradiometer) EVI (Enhanced Vegetation Index) for six shrubland types in China from 2001 to 2013 and its relationship to intra-and inter-annual regional climate dynamics. Existing literature reported that the vegetation index did not change significantly in China during 2000-2012. However, we found that the shrubland EVI in China increased significantly at a rate of 1.01ˆ10´3 EVI¨a´1 from 2001 to 2013. Two major shrubland types (subtropical evergreen and temperate deciduous) and two desert types (high-cold desert and temperate desert) increased significantly, whereas subalpine evergreen shrubland decreased at a rate of´0.64ˆ10´3 EVI¨a´1. We also detected a significantly lengthened growing season of temperate deciduous shrubland. The growing season length contributed significantly to the annual averaged EVI for temperate deciduous, subalpine deciduous and subtropical evergreen shrublands. Furthermore, the precipitation variation contributed more to the annual averaged EVI than the temperature. The year-round decrease in rainfall and the increase in temperature led to a significant reduction in the subalpine evergreen shrubland EVI. The enhancement of countrywide shrubland EVI may promote its contribution to the regional ecosystem function and its potential to invade grasslands.

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Evaluation of MODIS NPP and GPP products across multiple biomes

Cited by 580 publications

References 50 publications

Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States

Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

The Greenness of Major Shrublands in China Increased from 2001 to 2013

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