Investigating the potential of GIMMS and MODIS NDVI data sets for estimating gross primary productivity in Harvard Forest

2013 ◽  
Author(s):  
Xiaolei Yu ◽  
Zhaocong Wu ◽  
Xulin Guo
Keyword(s):  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Data Sets ◽  
Modis Ndvi ◽  
Harvard Forest

scholarly journals A geostatistical synthesis study of factors affecting gross primary productivity in various ecosystems of North America

2010 ◽  
Vol 7 (1) ◽  
pp. 1445-1487 ◽  
Author(s):  
V. Yadav ◽  
K. L. Mueller ◽  
D. Dragoni ◽  
A. M. Michalak
Keyword(s):  
Time Scales ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Factors Affecting ◽  
Regression Methods ◽  
Scrub Oak ◽  
Harvard Forest ◽  
Forest Sites ◽  
Competing Models ◽  
Kennedy Space

Abstract. A coupled Bayesian model selection and geostatistical regression modeling approach is adopted for empirical analysis of gross primary productivity (GPP) at six AmeriFlux sites, including the Kennedy Space Center Scrub Oak, Vaira Ranch, Tonzi Ranch, Blodgett Forest, Morgan Monroe State Forest, and Harvard Forest sites. The analysis is performed at a continuum of temporal scales ranging from daily to monthly, for a period of seven years. A total of 10 covariates representing environmental stimuli and indices of plant physiology are considered in explaining variations in GPP. Similar to other statistical methods, the proposed approach estimates regression coefficients and uncertainties associated with the covariates in a selected regression model. However, unlike traditional regression methods, the presented approach also estimates the uncertainty associated with the selection of a single "best" model of GPP. In addition, the approach provides an enhanced understanding of how the importance of specific covariates changes with temporal resolutions. An examination of trends in the importance of specific covariates reveals scaling thresholds above or below which covariates become significant in explaining GPP. Results indicate that most sites (especially those with a stronger seasonal cycle) exhibit at least one prominent scaling threshold between daily to 20-day temporal scale. This demonstrates that environmental variables that explain GPP at synoptic scales are different from those that capture its seasonality. At shorter time scales, radiation, temperature, and vapor pressure deficit exert most significant influence on GPP at most examined sites. However, at coarser time scales, the importance of these covariates in explaining GPP declines. Overall, unique best models are identified at most sites at the daily scale, whereas multiple competing models are identified at larger time scales. In addition, the selected models are able to explain a larger fraction of the observed variability for sites exhibiting strong seasonality.

scholarly journals Gross primary productivity of Brazilian Savanna (Cerrado) estimated by different remote sensing-based models

2021 ◽  
Vol 307 ◽  
pp. 108456
Author(s):  
Marcelo Sacardi Biudes ◽  
George Louis Vourlitis ◽  
Maísa Caldas Souza Velasque ◽  
Nadja Gomes Machado ◽  
Victor Hugo de Morais Danelichen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Brazilian Savanna

Divergent impacts of atmospheric water demand on gross primary productivity in three typical ecosystems in China

2021 ◽  
Vol 307 ◽  
pp. 108527
Author(s):  
Ning Chen ◽  
Changchun Song ◽  
Xiaofeng Xu ◽  
Xianwei Wang ◽  
Nan Cong ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Water Demand ◽  
Gross Primary Productivity ◽  
Atmospheric Water

scholarly journals Extreme events driving year-to-year differences in gross primary productivity across the US

2020 ◽  
Author(s):  
Alexander Turner ◽  
Philipp Köhler ◽  
Troy Magney ◽  
Christian Frankenberg ◽  
Inez Fung ◽  
...  
Keyword(s):  
Extreme Events ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
The Us

Identifying the dominant climate-driven uncertainties in modeling gross primary productivity

2021 ◽  
pp. 149518
Author(s):  
Yimian Ma ◽  
Xu Yue ◽  
Hao Zhou ◽  
Cheng Gong ◽  
Yadong Lei ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Gross Primary Productivity

scholarly journals Assessing the consistency between AVHRR and MODIS NDVI datasets for estimating terrestrial net primary productivity over India

2016 ◽  
Vol 125 (6) ◽  
pp. 1189-1204 ◽  
Author(s):  
R K Nayak ◽  
N Mishra ◽  
V K Dadhwal ◽  
N R Patel ◽  
M Salim ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Modis Ndvi
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