A Global 9-yr Biophysical Land Surface Dataset from NOAA AVHRR Data

Los, S.O.; Collatz, G. J.; Sellers, P. J.; Malmström, Carolyn M.; Pollack, N.; DeFries, Ruth; Bounoua, Lahouari; Parris, M. T.; Tucker, Compton J.; Dazlich, D. A.

doi:10.1175/1525-7541(2000)001<0183:agybls>2.0.co;2

Cited by 280 publications

(221 citation statements)

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“…[5] In the present study, the Fourier-adjusted, sensor and solar zenith angle corrected, interpolated and reconstructed (FASIR) Normalized Difference Vegetation Index (NDVI) version 4.1 data are used [Los et al, 2000[Los et al, , 2005. The NDVI is calculated as (r 2 À r 1 )/(r 2 + r 1 ), where r 1 is the visible (red) reflectance measured by AVHRR channel 1 and r 2 is the near-infrared reflectance measured by AVHRR channel 2.…”

Section: Datamentioning

confidence: 99%

“…The FASIR NDVI version 4.1 data are derived from the Pathfinder AVHRR Land (PAL) data for 1982[James and Kalluri, 1994. Additional corrections were applied to adjust the 8 km PAL data for residual sensor degradation effects and sensor calibration differences [Los, 1998], bidirectional reflectance distribution function (BRDF) effects [Los et al, 2005], effects of volcanic aerosols [Los et al, 2000], short-term (≤2 months) cloud effects and atmospheric effects, and missing data. The corrected 8 km data were averaged to 0.5 ∘ Â 0.5 ∘ resolution.…”

Section: Datamentioning

confidence: 99%

“…The three largest sources of uncertainty remaining in the FASIR NDVI data are related to (1) residual BRDF effects; estimated at 0.03 NDVI (root-mean-square error; RMSE) for dense vegetation (NDVI > 0.4). The RMSE is 0.02 NDVI when only the interannual variation is considered [Los et al, 2005]; (2) residual effects of volcanic aerosols after the El Chichon (1982-1983) and Mount Pinatubo (1991 eruptions (RMSE = 0.05 NDVI); and (3) missing data for September-December 1994 for which period a climatological average was used (RMSE = 0.05 NDVI); [Los et al, 2000]. For sparse vegetation (NDVI < 0.2), the error estimates are 2-10 times smaller.…”

Section: Datamentioning

confidence: 99%

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Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO₂ fertilization effect in global vegetation

Los

2013

Global Biogeochemical Cycles

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[1] Recent studies report an increase in vegetation greenness in mid-to-high northern latitudes. This increase is observed in leaf-out data in Europe and North America since the 1950s and in satellite data since the 1980s. Increased vegetation greenness is potentially a factor contributing to a land CO 2 sink. Various causes for increased vegetation greenness are suggested, but their relative importance is uncertain. In the present study, the effect of climate and CO 2 fertilization on increased vegetation greenness and the land CO 2 sink are investigated. The study is organized as follows: (1) (2) Residuals between RVI and NDVI are analyzed for associations with variations in downwelling solar radiation, nitrogen deposition, satellite-related artifacts, and CO 2 fertilization. CO 2 fertilization was the only factor that improved RVI modeling. (3) The effect of climate variations and CO 2 fertilization on the land CO 2 sink, as manifested in the RVI, is explored with the Carnegie Ames Stanford Assimilation (CASA) model. Climate (temperature and precipitation) and CO 2 fertilization each explain approximately 40% of the observed global trend in NDVI for 1982-2006 . For 1901-2006, estimated trends in NDVI related to CO 2 fertilization are four to five times larger than climate-related trends. CASA simulations indicate that the CO 2 fertilization effect on vegetation greenness contributes about 0.7 Pg C per year to the recent land CO 2 sink. This is a conservative estimate and is likely larger. This effect of CO 2 fertilization would be a large component of the land carbon sink. In the supporting information the RVI is used as a common standard to fuse MODIS and advanced very high resolution radiometer (AVHRR) NDVI data. This fusion compares well with SeaWiFS data.

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Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

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Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO₂ fertilization effect in global vegetation

Los

2013

Global Biogeochemical Cycles

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102

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“…The resolution of the DEM at 30 m×30 m was transformed into 5 m×5 m overlaid by remote sensing data through the data conversion tool of ArcGIS9.3 after projection conversion. According to the grading index of soil erosion intensity in the Luoyugou watershed (Zhang, 2012) Recently, vegetation coverage has been widely obtained from the remote sensing images through the correlation analysis of vegetation coverage and the spectral index (Los et al, 2000;Sellers et al, 1994) or using a regression model (Asrar et al, 1992;Graetz et al, 1988;North, 2002). Nonetheless, these methods are generally difficult to be implemented, require longtime observations, and have many limitations such as operation difficulty, longtime observation and low efficiency.…”

Section: Input Datamentioning

confidence: 99%

Optimization of Land Use Pattern Reduces Surface Runoff and Sediment Loss in a Hilly-Gully Watershed at the Loess Plateau, China

et al. 2016

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Aim of study: The aim is to find a way increasing gain yield and lessen area of farmland, and then increasing vegetation cover, improving environment and alleviating soil erosion.Area of study: The Hilly-Gully region at the loess plateau of China. Material and methods:In this study, an adjusted and optimized land use pattern was developed in Luoyugou watershed in the Yellow River valley based on the gradient distribution of land use types, and its effect on water and sediment transport was simulated using the SWAT model and GIS, with remote sensing images, land use maps and hydrologic data.Main results: The results indicate: average simulated runoff and sediment for the period 1986-2000 under conditions of the three land use pattern (2011, 2008 and optimized land use) reduced by 0.002-0.013 m 3 /s (2.7-17.6%) and 0.66 million tons, respectively. The runoff and sediment data obtained were compared with observed data from 2008, which showed that runoff and sediment production would be reduced by 467625 m 3 and 22754 tons, respectively.Research highlights: The adjustment of the land use pattern in comprehensive consideration of vegetation and geography have a positive effect on water and sediment transport which will be important for decision making and water resources management, and provides a reference for future environmental management and ecological construction in the loess plateau Hilly-Gully region.

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“…There were 64 environmental parameters in total for each sub-region, describing the dimensions, composition and mass transfer coefficients in all environmental compartments. The meteorological and land cover data were collected from remote sensing and satellite datasets (Huffman et al, 2007;Los et al, 2000). Data for the flux matrix were collected and balanced for the air, fresh water and coastal water (Carton and Giese, 2008;Draxler and Rolph, 2013;MWR, 2006MWR, -2011Saha et al, 2010).…”

Section: Parameterizationmentioning

confidence: 99%

Exploring the fate, transport and risk of Perfluorooctane Sulfonate (PFOS) in a coastal region of China using a multimedia model

Liu

Lü

Xie

et al. 2015

Environment International

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Perfluorooctane Sulfonate (PFOS) and related substances have been widely applied in both industrial processes and domestic products in China. Exploring the environmental fate and transport of PFOS using modeling methods provides an important link between emission and multimedia diffusion which forms a vital part in the human health risk assessment and chemical management for these substances. In this study, the gridded fugacity based BETR model was modified to make it more suitable to model transfer processes of PFOS in a coastal region, including changes to PFOS partition coefficients to reflect the influence of water salinity on its sorption behavior. The fate and transport of PFOS in the Bohai coastal region of China were simulated under steady state with the modified version of the model. Spatially distributed emissions of PFOS and related substances in 2010 were estimated and used in these simulations. Four different emission scenarios were investigated, in which a range of half-lives for PFOS related substances were considered. Concentrations of PFOS in air, vegetation, soil, fresh water, fresh water sediment and coastal water were derived from the model under the steady-state assumption. The median modeled PFOS concentrations in fresh water, fresh water sediment and soil were 7.20 ng/L, 0.39 ng/g and 0.21 ng/g, respectively, under Emission Scenario 2 (which assumed all PFOS related substances immediately degrade to PFOS) for the whole region, while the maximum concentrations were 47.10 ng/L, 4.98 ng/g and 2.49 ng/g, respectively. Measured concentration data for PFOS in the Bohai coastal region around the year of 2010 were collected from the literature. The reliability of the model results was evaluated by comparing the range of modeled concentrations with the measured data, which generally matched well for the main compartments. Fate and transfer fluxes were derived from the model based on the calculated inventory within the compartments, transfer fluxes between compartments and advection fluxes between sub-regions. It showed that soil and costal water were likely to be the most important sinks of PFOS in the Bohai costal region, in which more than 90% of PFOS was stored. Flows of fresh water were the driving force for spatial transport of PFOS in this region. Influences of the seasonal change of fresh water fluxes on the model results were also analyzed. When only seasonal changes of the fresh water flow rates were considered, concentrations of PFOS in winter and spring were predicted to be higher than that under annual average conditions, while the concentrations in summer and autumn were lower. For PFOS fluxes entering the sea, opposite conclusions were drawn compared to the concentrations. Environmental risks from the presence of PFOS in fresh water were assessed for this region through comparison with available water quality criteria values. The predicted concentrations of PFOS in the Bohai coastal region provided by the model were lower than the water quality criteria published by the United States ...

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A Global 9-yr Biophysical Land Surface Dataset from NOAA AVHRR Data

Cited by 280 publications

References 58 publications

Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO₂ fertilization effect in global vegetation

Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO₂ fertilization effect in global vegetation

Optimization of Land Use Pattern Reduces Surface Runoff and Sediment Loss in a Hilly-Gully Watershed at the Loess Plateau, China

Exploring the fate, transport and risk of Perfluorooctane Sulfonate (PFOS) in a coastal region of China using a multimedia model

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A Global 9-yr Biophysical Land Surface Dataset from NOAA AVHRR Data

Cited by 280 publications

References 58 publications

Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO2 fertilization effect in global vegetation

Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO2 fertilization effect in global vegetation

Optimization of Land Use Pattern Reduces Surface Runoff and Sediment Loss in a Hilly-Gully Watershed at the Loess Plateau, China

Exploring the fate, transport and risk of Perfluorooctane Sulfonate (PFOS) in a coastal region of China using a multimedia model

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Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO₂ fertilization effect in global vegetation

Analysis of trends in fused AVHRR and MODIS NDVI data for 1982–2006: Indication for a CO₂ fertilization effect in global vegetation