scholarly journals Evaluation of the Sensitivity of SMOS L-VOD to Forest Above-Ground Biomass at Global Scale

2020 ◽  
Vol 12 (9) ◽  
pp. 1450
Author(s):  
Arnaud Mialon ◽  
Nemesio J. Rodríguez-Fernández ◽  
Maurizio Santoro ◽  
Sassan Saatchi ◽  
Stéphane Mermoz ◽  
...  
Keyword(s):  
Large Scale ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Northern Latitudes ◽  
Ocean Salinity ◽  
Good Proxy ◽  
Using Data ◽  
The Tropics

The present study evaluates the L band Vegetation Optical Depth (L-VOD) derived from the Soil Moisture and Ocean Salinity (SMOS) satellite to monitor Above Ground Biomass (AGB) at a global scale. Although SMOS L-VOD has been shown to be a good proxy for AGB in Africa and Tropics, little is known about this relationship at large scale. In this study, we further examine this relationship at a global scale using the latest AGB maps from Saatchi et al. and GlobBiomass computed using data acquired during the SMOS period. We show that at a global scale the L-VOD from SMOS is well-correlated with the AGB estimates from Saatchi et al. and GlobBiomass with the Pearson’s correlation coefficients (R) of 0.91 and 0.94 respectively. Although AGB estimates in Africa and the Tropics are well-captured by SMOS L-VOD (R > 0.9), the relationship is less straightforward for the dense forests over the northern latitudes (R = 0.32 and 0.69 with Saatchi et al. and GlobBiomass respectively). This paper gives strong evidence in support of the sensitivity of SMOS L-VOD to AGB estimates at a globale scale, providing an interesting alternative and complement to exisiting sensors for monitoring biomass evolution. These findings can further facilitate research on biomass now that SMOS is providing more than 10 years of data.

scholarly journals Evaluation of modeled global carbon dynamics: analysis based on global carbon flux and above-ground biomass data

2016 ◽  
Author(s):  
Bao-Lin Xue ◽  
Qinghua Guo ◽  
Tianyu Hu ◽  
Yongcai Wang ◽  
Shengli Tao ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Carbon Flux ◽  
Large Scale ◽  
Gross Primary Production ◽  
Carbon Dynamics ◽  
Global Scale ◽  
Above Ground Biomass ◽  
Carbon Cycles ◽  
Ground Biomass ◽  
Global Carbon

Abstract. Dynamic global vegetation models are useful tools for the simulation of carbon dynamics on regional and global scales. However, even the most validated models are usually hampered by the poor availability of global biomass data in the model validation, especially on regional/global scales. Here, taking the integrated biosphere simulator model (IBIS) as an example, we evaluated the modeled carbon dynamics, including gross primary production (GPP) and potential above-ground biomass (AGB), on the global scale. The IBIS model was constrained by both in situ GPP and plot-level AGB data collected from the literature. Independent validation showed that IBIS could reproduce GPP and evapotranspiration with acceptable accuracy at site and global levels. On the global scale, the IBIS-simulated total AGB was similar to those obtained in other studies. However, discrepancies were observed between the model-derived and observed spatial patterns of AGB for Amazonian forests. The differences among the AGB spatial patterns were mainly caused by the single-parameter set of the model used. This study showed that different meteorological inputs can also introduce substantial differences in AGB on the global scale. Further analysis showed that this difference is small compared with parameter-induced differences. The conclusions of our research highlight the necessity of considering the heterogeneity of key model physiological parameters in modeling global AGB. The research also shows that to simulate large-scale carbon dynamics, both carbon flux and AGB data are necessary to constrain the model. The main conclusions of our research will help to improve model simulations of global carbon cycles.

scholarly journals Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0138456 ◽  
Author(s):  
Stéphane Guitet ◽  
Bruno Hérault ◽  
Quentin Molto ◽  
Olivier Brunaux ◽  
Pierre Couteron
Keyword(s):  
Spatial Structure ◽  
Large Scale ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Forest Inventories ◽  
Carbon Mapping

scholarly journals Dry Above Ground Biomass for a Soybean Crop Using an Empirical Model in Greece

Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 201
Author(s):  
Christos Vamvakoulas ◽  
Stavros Alexandris ◽  
Ioannis Argyrokastritis
Keyword(s):  
Empirical Model ◽  
Above Ground Biomass ◽  
Crop Evapotranspiration ◽  
Area Index ◽  
Soybean Crop ◽  
Ground Biomass ◽  
Cultivation Period ◽  
Proposed Model ◽  
Glycine Max L ◽  
Using Data

A new empirical equation for the estimation of daily dry above ground biomass (D-AGB) for a hybrid of soybean (Glycine max L.) is proposed. This equation requires data for three crop dependent parameters; leaf area index, plant height, and cumulative crop evapotranspiration. Bilinear surface regression analysis was used in order to estimate the factors entering in the empirical model. For the calibration of the proposed model, data yielded from a well-watered soybean crop for the year 2015, in the experimental field (0.1 ha) of the agricultural University of Athens, were used as a reference. Verification of the validity of the model was obtained by using data from a 2014 cultivation period for well-watered soybean cultivation (100% of crop evapotranspiration water treatment), as well as data from three irrigation treatments (75%, 50%, 25% of crop evapotranspiration) for two cultivation periods (2014–2015). The proposed method for the estimation of D-AGB may be proven as a useful tool for estimations without using destructive sampling.

scholarly journals Is profitability a good proxy for efficiency? Evidence from the subsector of tour operators

2017 ◽  
Vol 17 (4) ◽  
pp. 425-440
Author(s):  
Veronika Hedija ◽  
Roman Fiala ◽  
Martina Kuncová
Keyword(s):  
Economic Efficiency ◽  
Correlation Coefficients ◽  
Efficiency Score ◽  
Data Envelopment ◽  
The Czech Republic ◽  
Dea Models ◽  
Good Proxy ◽  
Using Data ◽  
Almost All ◽  
Profitability Ratios

Abstract The goal of the paper is to evaluate the economic efficiency of tour operators in the Czech Republic in the period 2007-2014 using data envelopment analysis (DEA) models and prove the link between economic efficiency and profitability and to find out if profitability is a good proxy for economic efficiency. Data was exported from the database Albertina CZ Gold Edition. We calculated the efficiency score using CCR (Charnes, Cooper and Rhodes) and BCC (Banker, Charnes and Cooper) models based on 3 inputs and 1 output. In the years 2007 to 2010, the efficiency score of almost all the companies was higher than 0.5; however, in years since 2011, we revealed significant differences in the efficiency of individual firms and only about 40 percent of tour operators achieved an efficiency score higher than 0.5. Using Pearson and Spearman correlation coefficients, our findings show that, in the case of the Czech tour operator market, profitability ratios do not correspond with firm efficiency. Profitability ratios are not a good proxy for economic efficiency and should not be used as the only firm criterion of performance.

scholarly journals Development of allometric relationships for estimate above ground biomass of trees in the tropical abandoned land

2019 ◽  
Vol 20 (12) ◽  
Author(s):  
Karyati Karyati ◽  
Kusno Yuli Widiati ◽  
Karmini Karmini ◽  
Rachmad Mulyadi
Keyword(s):  
Correlation Coefficients ◽  
Tree Height ◽  
Allometric Equation ◽  
Allometric Relationships ◽  
Above Ground Biomass ◽  
Study Objective ◽  
Land Type ◽  
Ground Biomass ◽  
Abandoned Land ◽  
Abandoned Lands

Abstract. Karyati, Widiati KY, Karmini, Mulyadi R. 2019. Development of allometric relationships for estimate above ground biomass of trees in the tropical abandoned lands. Biodiversitas 20: 3508-3516. The abandoned lands have important role in the ecological function as well as carbon sequestration. The allometric equations to estimate above ground biomass in abandoned land are still limited available. This study objective was to develop allometric relationships between tree size variables (diameter at breast height (DBH) and tree height) and leaf, branch, trunk, and total above ground biomass (TAGB) in abandoned land in East Kalimantan, Indonesia. The correlation coefficients between stem DBH and tree height to leaf and branch indicating a relatively weak relationship. The moderately strong relationships were showed by DBH and tree height to trunk and TAGB. The specific allometric equation of above ground biomass for different land use and land type is needed to estimate the accurate TAGB in the site.

Estimation of above-ground biomass of trees and shrubs in a Eucalyptus populnea F. Muell. woodland by regression of mass on trunk diameter and plant height

1979 ◽  
Vol 27 (2) ◽  
pp. 135 ◽  
Author(s):  
G Harrington
Keyword(s):  
Standard Error ◽  
Correlation Coefficients ◽  
Common Species ◽  
Regression Equations ◽  
Above Ground Biomass ◽  
Trunk Diameter ◽  
Ground Biomass ◽  
Acacia Aneura ◽  
Trees And Shrubs ◽  
Eucalyptus Populnea

An estimate of the above-ground biomass of leaf and wood in the shrubs and trees of Eucalyptus populnea woodland near Cobar, N.S.W., was made, by regression of leaf and wood weight on height or trunk diameter of the most common species. A new double regression technique was used for E. populnea to avoid destructively sampling whole trees. The mass of branches was regressed on primary branch diameter and these equations were used to estimate the total mass of crowns of trees. The estimated crown mass was then regressed on trunk diameters. Regression equations for estimation of mass of wood and leaf are provided for Geijera parvifora, Cassia nemophila, Dodonaea viscosa, Eremophila mitchellii, E. sturtii, E. bowmanii, Myoporum deserti and young Acacia aneura. The error of the estimates varied between 3 and 18% for different species. Log transformation of the data usually improved the correlation coefficients obtained but sometimes increased the standard error of the estimate. Estimates based on canopy measurements were rarely more accurate than those from height or trunk diameter. The overall estimate of biomass was 3.4 t of leaf and 51.4 t of wood per ha with a standard error of < 15%.

scholarly journals Large-Scale Tropospheric Transport in the Chemistry Climate Model Initiative (CCMI) Simulations

2017 ◽  
Author(s):  
Clara Orbe ◽  
Huang Yang ◽  
Darryn W. Waugh ◽  
Guang Zeng ◽  
Olaf Morgenstern ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Atmospheric Transport ◽  
Global Scale ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Free Running ◽  
The Mean ◽  
The Tropics ◽  
Interhemispheric Transport

Abstract. Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among models participating in the IGAC SPARC Chemistry-Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 years and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations and, in particular, to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and, in some cases, larger than) the differences among free-running simulations, due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

scholarly journals High-Throughput Measurements of Stem Characteristics to Estimate Ear Density and Above-Ground Biomass

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Xiuliang Jin ◽  
Simon Madec ◽  
Dan Dutartre ◽  
Benoit de Solan ◽  
Alexis Comar ◽  
...  
Keyword(s):  
Cross Section ◽  
Spatial Resolution ◽  
Average Diameter ◽  
Stem Density ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Good Proxy ◽  
Nitrogen Treatments ◽  
Deep Learning Model ◽  
Better Than

Total above-ground biomass at harvest and ear density are two important traits that characterize wheat genotypes. Two experiments were carried out in two different sites where several genotypes were grown under contrasted irrigation and nitrogen treatments. A high spatial resolution RGB camera was used to capture the residual stems standing straight after the cutting by the combine machine during harvest. It provided a ground spatial resolution better than 0.2 mm. A Faster Regional Convolutional Neural Network (Faster-RCNN) deep-learning model was first trained to identify the stems cross section. Results showed that the identification provided precision and recall close to 95%. Further, the balance between precision and recall allowed getting accurate estimates of the stem density with a relative RMSE close to 7% and robustness across the two experimental sites. The estimated stem density was also compared with the ear density measured in the field with traditional methods. A very high correlation was found with almost no bias, indicating that the stem density could be a good proxy of the ear density. The heritability/repeatability evaluated over 16 genotypes in one of the two experiments was slightly higher (80%) than that of the ear density (78%). The diameter of each stem was computed from the profile of gray values in the extracts of the stem cross section. Results show that the stem diameters follow a gamma distribution over each microplot with an average diameter close to 2.0 mm. Finally, the biovolume computed as the product of the average stem diameter, the stem density, and plant height is closely related to the above-ground biomass at harvest with a relative RMSE of 6%. Possible limitations of the findings and future applications are finally discussed.

scholarly journals Academic vs. Biological Age in Research on Academic Careers: A Large-scale Study with Implications for Scientifically Developing Systems

2021 ◽  
Author(s):  
Marek Kwiek ◽  
Wojciech Roszka
Keyword(s):  
Large Scale ◽  
Academic Career ◽  
Age Groups ◽  
Correlation Coefficients ◽  
Academic Careers ◽  
Biological Age ◽  
Contingency Analysis ◽  
Global Science ◽  
Engineering Mathematics ◽  
Good Proxy

Biological age is an important sociodemographic factor in studies on academic careers (research productivity, scholarly impact, and collaboration patterns). It is assumed that the academic age, or the time elapsed from the first publication, is a good proxy for biological age. In this study, we analyze the limitations of the proxy in academic career studies, using as an example the entire population of Polish academic scientists visible in the last decade in global science and holding at least a PhD (N = 20,569). The proxy works well for science, technology, engineering, mathematics, and medicine (STEMM) disciplines; however, for non-STEMM disciplines (particularly for humanities and social sciences), it has a dramatically worse performance. This negative conclusion is particularly important for systems that have only become recently visible in global academic journals. The micro-level data suggest a delayed participation of social scientists and humanists in global science networks, with practical implications for predicting biological age from academic age. We calculate correlation coefficients, present contingency analysis of academic career stages with academic positions and age groups, and create a linear multivariate regression model. Our research suggests that in scientifically developing countries, academic age as a proxy for biological age must be used more cautiously than in advanced countries: ideally, it must be used only for STEMM disciplines.

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