WorldWideScience

Sample records for aboveground biomass estimation

  1. Timber volume and aboveground live tree biomass estimations for landscape analyses in the Pacific Northwest

    Science.gov (United States)

    Xiaoping Zhou; Miles A. Hemstrom

    2010-01-01

    Timber availability, aboveground tree biomass, and changes in aboveground carbon pools are important consequences of landscape management. There are several models available for calculating tree volume and aboveground tree biomass pools. This paper documents species-specific regional equations for tree volume and aboveground live tree biomass estimation that might be...

  2. Evaluating lidar point densities for effective estimation of aboveground biomass

    Science.gov (United States)

    Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason M.; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.

    2016-01-01

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

  3. Root biomass in cereals, catch crops and weeds can be reliably estimated without considering aboveground biomass

    DEFF Research Database (Denmark)

    Hu, Teng; Sørensen, Peter; Wahlström, Ellen Margrethe

    2018-01-01

    Reliable information on belowground plant biomass is essential to estimate belowground carbon inputs to soils. Estimations of belowground plant biomass are often based on a fixed allometric relationship of plant biomass between aboveground and belowground parts. However, environmental and managem......Reliable information on belowground plant biomass is essential to estimate belowground carbon inputs to soils. Estimations of belowground plant biomass are often based on a fixed allometric relationship of plant biomass between aboveground and belowground parts. However, environmental...... and management factors may affect this allometric relationship making such estimates uncertain and biased. Therefore, we aimed to explore how root biomass for typical cereal crops, catch crops and weeds could most reliably be estimated. Published and unpublished data on aboveground and root biomass (corrected...... to 0–25 cm depth) of cereal crops (wheat and barley), catch crops and weeds were collected from studies in Denmark. Leave one out cross validation was used to determine the model that could best estimate root biomass. Root biomass varied with year, farming system (organic versus conventional...

  4. ALLOMETRIC EQUATIONS FOR ESTIMATING ABOVEGROUND BIOMASS IN PAPUA TROPICAL FOREST

    Directory of Open Access Journals (Sweden)

    Sandhi Imam Maulana

    2014-10-01

    Full Text Available Allometric equations can be used to estimate biomass and carbon stock of  the forest. However, so far the allometric equations for commercial species in Papua tropical forests have not been appropriately developed. In this research, allometric equations are presented based on the genera of  commercial species. Few equations have been developed for the commercial species of  Intsia, Pometia, Palaquium and Vatica genera and an equation of  a mix of  these genera. The number of  trees sampled in this research was 49, with diameters (1.30 m above-ground or above buttresses ranging from 5 to 40 cm. Destructive sampling was used to collect the samples where Diameter at Breast Height (DBH and Wood Density (WD were used as predictors for dry weight of  Total Above-Ground Biomass (TAGB. Model comparison and selection were based on the values of  F-statistics, R-sq, R-sq (adj, and average deviation. Based on these statistical indicators, the most suitable model for Intsia, Pometia, Palaquium and Vatica genera respectively are Log(TAGB = -0.76 + 2.51Log(DBH, Log(TAGB = -0.84 + 2.57Log(DBH, Log(TAGB = -1.52 + 2.96Log(DBH, and Log(TAGB = -0.09 + 2.08Log(DBH. Additional explanatory variables such as Commercial Bole Height (CBH do not really increase the indicators’ goodness of  fit for the equation. An alternative model to incorporate wood density should  be considered for estimating the above-ground biomass for mixed genera. Comparing the presented mixed-genera equation; Log(TAGB = 0.205 + 2.08Log(DBH + 1.75Log(WD, R-sq: 97.0%, R-sq (adj: 96.9%, F statistics 750.67, average deviation: 3.5%; to previously published datashows that this local species specific equation differs substantially from previously published equations and this site-specific equation is  considered to give a better estimation of  biomass.

  5. Methods for estimating aboveground biomass and its components for Douglas-fir and lodgepole pine trees

    Science.gov (United States)

    K.P. Poudel; H. Temesgen

    2016-01-01

    Estimating aboveground biomass and its components requires sound statistical formulation and evaluation. Using data collected from 55 destructively sampled trees in different parts of Oregon, we evaluated the performance of three groups of methods to estimate total aboveground biomass and (or) its components based on the bias and root mean squared error (RMSE) that...

  6. Estimating aboveground tree biomass on forest land in the Pacific Northwest: a comparison of approaches

    Science.gov (United States)

    Xiaoping Zhou; Miles A. Hemstrom

    2009-01-01

    Live tree biomass estimates are essential for carbon accounting, bioenergy feasibility studies, and other analyses. Several models are currently used for estimating tree biomass. Each of these incorporates different calculation methods that may significantly impact the estimates of total aboveground tree biomass, merchantable biomass, and carbon pools. Consequently,...

  7. Developing a generalized allometric equation for aboveground biomass estimation

    Science.gov (United States)

    Xu, Q.; Balamuta, J. J.; Greenberg, J. A.; Li, B.; Man, A.; Xu, Z.

    2015-12-01

    A key potential uncertainty in estimating carbon stocks across multiple scales stems from the use of empirically calibrated allometric equations, which estimate aboveground biomass (AGB) from plant characteristics such as diameter at breast height (DBH) and/or height (H). The equations themselves contain significant and, at times, poorly characterized errors. Species-specific equations may be missing. Plant responses to their local biophysical environment may lead to spatially varying allometric relationships. The structural predictor may be difficult or impossible to measure accurately, particularly when derived from remote sensing data. All of these issues may lead to significant and spatially varying uncertainties in the estimation of AGB that are unexplored in the literature. We sought to quantify the errors in predicting AGB at the tree and plot level for vegetation plots in California. To accomplish this, we derived a generalized allometric equation (GAE) which we used to model the AGB on a full set of tree information such as DBH, H, taxonomy, and biophysical environment. The GAE was derived using published allometric equations in the GlobAllomeTree database. The equations were sparse in details about the error since authors provide the coefficient of determination (R2) and the sample size. A more realistic simulation of tree AGB should also contain the noise that was not captured by the allometric equation. We derived an empirically corrected variance estimate for the amount of noise to represent the errors in the real biomass. Also, we accounted for the hierarchical relationship between different species by treating each taxonomic level as a covariate nested within a higher taxonomic level (e.g. species equations, the plant's taxonomy, and their biophysical environment.

  8. Estimates of forest canopy height and aboveground biomass using ICESat.

    Science.gov (United States)

    Michael A. Lefsky; David J. Harding; Michael Keller; Warren B. Cohen; Claudia C. Carabajal; Fernando Del Bom; Maria O. Hunter; Raimundo Jr. de Oliveira

    2005-01-01

    Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land...

  9. Estimating aboveground biomass of mariola (Parthenium incanum) from plant dimensions

    Science.gov (United States)

    Carlos Villalobos

    2007-01-01

    The distribution and abundance of plant biomass in space and time are important properties of rangeland ecosystem. Land managers and researchers require reliable shrub weight estimates to evaluate site productivity, food abundance, treatment effects, and stocking rates. Rapid, nondestructive methods are needed to estimate shrub biomass in semi-arid ecosystems. Shrub...

  10. Nondestructive estimates of above-ground biomass using terrestrial laser scanning

    NARCIS (Netherlands)

    Calders, K.; Newnham, G.; Burt, A.; Murphy, S.; Raumonen, P.; Herold, M.; Culvenor, D.; Avitabile, V.; Disney, M.; Armston, J.; Kaasalainen, M.

    2015-01-01

    Allometric equations are currently used to estimate above-ground biomass (AGB) based on the indirect relationship with tree parameters. Terrestrial laser scanning (TLS) can measure the canopy structure in 3D with high detail. In this study, we develop an approach to estimate AGB from TLS data, which

  11. Airborne laser scanner-assisted estimation of aboveground biomass change in a temperate oak-pine forest

    Science.gov (United States)

    Nicholas S. Skowronski; Kenneth L. Clark; Michael Gallagher; Richard A. Birdsey; John L. Hom

    2014-01-01

    We estimated aboveground tree biomass and change in aboveground tree biomass using repeated airborne laser scanner (ALS) acquisitions and temporally coincident ground observations of forest biomass, for a relatively undisturbed period (2004-2007; ∇07-04), a contrasting period of disturbance (2007-2009; ∇09-07...

  12. Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam

    NARCIS (Netherlands)

    Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P R

    2016-01-01

    Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for

  13. Allometric equations for aboveground and belowground biomass estimations in an evergreen forest in Vietnam

    NARCIS (Netherlands)

    Nam, Vu Thanh; Kuijk, Van Marijke; Anten, Niels P.R.

    2016-01-01

    Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations

  14. Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam.

    Directory of Open Access Journals (Sweden)

    Vu Thanh Nam

    Full Text Available Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB and root biomass (RB based on 300 (of 45 species and 40 (of 25 species sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH and tree height (H, wood density (WD was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.

  15. Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam.

    Science.gov (United States)

    Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P R

    2016-01-01

    Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.

  16. Estimation of Aboveground Biomass Using Manual Stereo Viewing of Digital Aerial Photographs in Tropical Seasonal Forest

    Directory of Open Access Journals (Sweden)

    Katsuto Shimizu

    2014-11-01

    Full Text Available The objectives of this study are to: (1 evaluate accuracy of tree height measurements of manual stereo viewing on a computer display using digital aerial photographs compared with airborne LiDAR height measurements; and (2 develop an empirical model to estimate stand-level aboveground biomass with variables derived from manual stereo viewing on the computer display in a Cambodian tropical seasonal forest. We evaluate observation error of tree height measured from the manual stereo viewing, based on field measurements. RMSEs of tree height measurement with manual stereo viewing and LiDAR were 1.96 m and 1.72 m, respectively. Then, stand-level aboveground biomass is regressed against tree height indices derived from the manual stereo viewing. We determined the best model to estimate aboveground biomass in terms of the Akaike’s information criterion. This was a model of mean tree height of the tallest five trees in each plot (R2 = 0.78; RMSE = 58.18 Mg/ha. In conclusion, manual stereo viewing on the computer display can measure tree height accurately and is useful to estimate aboveground stand biomass.

  17. Allometric Models for Estimating Tree Volume and Aboveground Biomass in Lowland Forests of Tanzania

    Directory of Open Access Journals (Sweden)

    Wilson Ancelm Mugasha

    2016-01-01

    Full Text Available Models to assist management of lowland forests in Tanzania are in most cases lacking. Using a sample of 60 trees which were destructively harvested from both dry and wet lowland forests of Dindili in Morogoro Region (30 trees and Rondo in Lindi Region (30 trees, respectively, this study developed site specific and general models for estimating total tree volume and aboveground biomass. Specifically the study developed (i height-diameter (ht-dbh models for trees found in the two sites, (ii total, merchantable, and branches volume models, and (iii total and sectional aboveground biomass models of trees found in the two study sites. The findings show that site specific ht-dbh model appears to be suitable in estimating tree height since the tree allometry was found to differ significantly between studied forests. The developed general volume models yielded unbiased mean prediction error and hence can adequately be applied to estimate tree volume in dry and wet lowland forests in Tanzania. General aboveground biomass model appears to yield biased estimates; hence, it is not suitable when accurate results are required. In this case, site specific biomass allometric models are recommended. Biomass allometric models which include basic wood density are highly recommended for improved estimates accuracy when such information is available.

  18. Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.

    Science.gov (United States)

    Riegel, Joseph B; Bernhardt, Emily; Swenson, Jennifer

    2013-01-01

    Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R(2) values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R(2) of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas.

  19. Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.

    Directory of Open Access Journals (Sweden)

    Joseph B Riegel

    Full Text Available Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R(2 values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively. Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R(2 of 0.37. These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas.

  20. Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Katharine C. Kelsey

    2014-07-01

    Full Text Available Maps of forest biomass are important tools for managing natural resources and reporting terrestrial carbon stocks. Using the San Juan National Forest in Southwest Colorado as a case study, we evaluate regional biomass maps created using physical variables, spectral vegetation indices, and image textural analysis on Landsat TM imagery. We investigate eight gray level co-occurrence matrix based texture measures (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation on four window sizes (3 × 3, 5 × 5, 7 × 7, 9 × 9 at four offsets ([1,0], [1,1], [0,1], [1,−1] on four Landsat TM bands (2, 3, 4, and 5. The map with the highest prediction quality was created using three texture metrics calculated from Landsat Band 2 on a 3 × 3 window and an offset of [0,1]: entropy, mean and correlation; and one physical variable: slope. The correlation of predicted versus observed biomass values for our texture-based biomass map is r = 0.86, the Root Mean Square Error is 45.6 Mg∙ha−1, and the Coefficient of Variation of the Root Mean Square Error is 0.31. We find that models including image texture variables are more strongly correlated with biomass than models using only physical and spectral variables. Additionally, we suggest that the use of texture appears to better capture the magnitude and direction of biomass change following disturbance compared to spectral approaches. The biomass mapping methods we present here are widely applicable throughout the US, as they are based on publically available datasets and utilize relatively simple analytical routines.

  1. Improved allometric models to estimate the aboveground biomass of tropical trees.

    Science.gov (United States)

    Chave, Jérôme; Réjou-Méchain, Maxime; Búrquez, Alberto; Chidumayo, Emmanuel; Colgan, Matthew S; Delitti, Welington B C; Duque, Alvaro; Eid, Tron; Fearnside, Philip M; Goodman, Rosa C; Henry, Matieu; Martínez-Yrízar, Angelina; Mugasha, Wilson A; Muller-Landau, Helene C; Mencuccini, Maurizio; Nelson, Bruce W; Ngomanda, Alfred; Nogueira, Euler M; Ortiz-Malavassi, Edgar; Pélissier, Raphaël; Ploton, Pierre; Ryan, Casey M; Saldarriaga, Juan G; Vieilledent, Ghislain

    2014-10-01

    Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development. © 2014 John Wiley & Sons Ltd.

  2. Allometric models for estimating the aboveground biomass of the mangrove Rhizophora mangle

    Directory of Open Access Journals (Sweden)

    Heide Vanessa Souza Santos

    Full Text Available Abstract The development of species-specific allometric models is critical to the improvement of aboveground biomass estimates, as well as to the estimation of carbon stock and sequestration in mangrove forests. This study developed allometric equations for estimating aboveground biomass of Rhizophora mangle in the mangroves of the estuary of the São Francisco River, in northeastern Brazil. Using a sample of 74 trees, simple linear regression analysis was used to test the dependence of biomass (total and per plant part on size, considering both transformed (ln and not-transformed data. Best equations were considered as those with the lowest standard error of estimation (SEE and highest adjusted coefficient of determination (R2a. The ln-transformed equations showed better results, with R2a near 0.99 in most cases. The equations for reproductive parts presented low R2a values, probably attributed to the seasonal nature of this compartment. "Basal Area2 × Height" showed to be the best predictor, present in most of the best-fitted equations. The models presented here can be considered reliable predictors of the aboveground biomass of R. mangle in the NE-Brazilian mangroves as well as in any site were this widely distributed species present similar architecture to the trees used in the present study.

  3. DEVELOPMENT OF LOCAL ALLOMETRIC EQUATION TO ESTIMATE TOTAL ABOVEGROUND BIOMASS IN PAPUA TROPICAL FOREST

    Directory of Open Access Journals (Sweden)

    Sandhi Imam Maulana

    2016-10-01

    Full Text Available Recently, pantropical allometric equations  have been commonly used across the globe to  estimate the aboveground biomass of the forests, including in Indonesia. However, in relation to regional differences in diameter, height and wood density, the lack of data measured, particularly from eastern part of Indonesia, may raise the question on  accuracy of pantropical allometric in such area. Hence, this paper examines  the differences of local allometric equations of Papua Island with equations developed by Chave and his research groups.. Measurements of biomass in this study were conducted directly based on weighing and destructive samplings. Results show that the most appropriate local equation to estimate total aboveground biomass in Papua tropical forest is Log(TAGB = -0.267 + 2.23 Log(DBH +0.649 Log(WD (CF=1.013; VIF=1.6; R2= 95%; R2-adj= 95.1%; RMSE= 0.149; P<0.001. This equation is also a better option in comparison to those of previously published pantropical equations with only 6.47% average deviation and 5.37 points of relative bias. This finding implies that the locally developed equation should be a better option to produce more accurate site specific total aboveground biomass estimation.

  4. Estimating aboveground biomass for broadleaf woody plants and young conifers in Sierra Nevada, California forests.

    Science.gov (United States)

    McGinnis, Thomas W.; Shook, Christine D.; Keeley, Jon E.

    2010-01-01

    Quantification of biomass is fundamental to a wide range of research and natural resource management goals. An accurate estimation of plant biomass is essential to predict potential fire behavior, calculate carbon sequestration for global climate change research, assess critical wildlife habitat, and so forth. Reliable allometric equations from simple field measurements are necessary for efficient evaluation of plant biomass. However, allometric equations are not available for many common woody plant taxa in the Sierra Nevada. In this report, we present more than 200 regression equations for the Sierra Nevada western slope that relate crown diameter, plant height, crown volume, stem diameter, and both crown diameter and height to the dry weight of foliage, branches, and entire aboveground biomass. Destructive sampling methods resulted in regression equations that accurately predict biomass from one or two simple, nondestructive field measurements. The tables presented here will allow researchers and natural resource managers to easily choose the best equations to fit their biomass assessment needs.

  5. A comparison of above-ground dry-biomass estimators for trees in the Northeastern United States

    Science.gov (United States)

    James A. Westfall

    2012-01-01

    In the northeastern United States, both component and total aboveground tree dry-biomass estimates are available from several sources. In this study, comparisons were made among four methods to promote understanding of the similarities and differences in live-tree biomass estimators. The methods use various equations developed from biomass data collected in the United...

  6. Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass

    Science.gov (United States)

    Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.

    2017-07-01

    Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

  7. A simple non-destructive method for estimating aboveground biomass of emergent aquatic macrophytes

    Directory of Open Access Journals (Sweden)

    Laís Samira Correia Nunes

    Full Text Available Abstract: Aim Non-destructive methods for estimating aquatic macrophytes biomass may be employed by using indirect measurements, especially in experimental studies, thus enabling the conservation of plant samples. It is possible to estimate macrophyte biomass by developing mathematical equations that relate the plants’ dry mass to their morphological variables. The aim of this study was to evaluate the relationship between different morphological variables and biomass in order to determine which variable is easier to be obtained for the emergent aquatic macrophytes Crinum americanum and Spartina alterniflora. Methods We obtained the aboveground area and height of individuals of both species, with different sizes and distinct developmental stages. The samples were collected in the Itanhaém River Estuary (SP, Brazil. The plants were dried in a laboratory oven and weighed so as to obtain their dry mass. Simple linear regression analyses were applied to the morphological variables and the individual dry mass to obtain equations. Results For the both species, the relationship between area and biomass, and the relationship between individual height and biomass presented significant coefficients of determination (p < 0.0001. For the elaboration of models involving the individual height, we used only one morphological measure for each individual, whereas for models involving the individual area it was necessary to obtain more than one hundred morphological measurements per individual. Conclusions The morphological variables chosen are good attributes for estimating the aboveground biomass of C. americanum and S. alterniflora. Considering the models’ adjustment and the consumed time to obtain the measurements, we conclude that the individual height measurement is better for biomass estimation for both species.

  8. Development and validation of aboveground biomass estimations for four Salix clones in central New York

    Energy Technology Data Exchange (ETDEWEB)

    Arevalo, Carmela B.M.; Volk, Timothy A.; Bevilacqua, Eddie; Abrahamson, Lawrence [Faculty of Forest and Natural Resources Management, State University of New York, College of Environmental Science and Forestry, 1 Forestry Drive, Syracuse, NY 13210 (United States)

    2007-01-15

    Commercial and research scale plantings of short-rotation woody crops require reliable and efficient estimations of biomass yield before time of harvest. Biomass equations currently exist but the accuracy and efficiency of estimation procedures at the level of specificity needs to be quantified for clones being used in North America. Diameter-based allometric equations for aboveground biomass for four clones of willow (Salix discolor, Salix alba, Salix dasyclados, and Salix sachalinensis), between two sites (Canastota and Tully, NY), and across four years (1998-2001), were developed using ordinary least-squares regression (OLSR) on log-transformed variables, weighted least squares regression (WLSR) on log-transformed variables, and nonlinear regression (NLR) methods and validated using independent data sets. Biomass estimations derived from clone, age, and site (Specific) using OLSR equations had highest R{sup 2} and lowest percent bias (<2.3%) allowing for accurate estimations of standing biomass. Values for specific equations using WLSR were similar, but bias was higher for NLR (0.7-12.5%). However, the amount of time and effort required to develop specific equations, is large and in many situations prohibitive. Biomass estimates derived from clone and age, regardless of site (Intermediate), resulted in small increases in prediction error and a small increase in percent bias using OLSR (<0.4%) and WLSR (<1.7%). The increase in percent bias was larger (1.1-5.7%) for NLR equations. Intermediate models correspond to the loss of only a small amount of accuracy while gaining more efficiency in estimating standing biomass. Estimates of biomass derived from clone alone (general) equations, considering neither age nor site, had the weakest prediction abilities that may lead to large errors for biomass estimations using OLSR (7.0-9.5%), WLSR (1.1-21.7%) or NLR (31.9-143.4%). (author)

  9. Estimation of Forest Canopy Height and Aboveground Biomass from Spaceborne LiDAR and Landsat Imageries in Maryland

    Directory of Open Access Journals (Sweden)

    Mengjia Wang

    2018-02-01

    Full Text Available Mapping the regional distribution of forest canopy height and aboveground biomass is worthwhile and necessary for estimating the carbon stocks on Earth and assessing the terrestrial carbon flux. In this study, we produced maps of forest canopy height and the aboveground biomass at a 30 m spatial resolution in Maryland by combining Geoscience Laser Altimeter System (GLAS data and Landsat spectral imageries. The processes for calculating the forest biomass included the following: (i processing the GLAS waveform and calculating spatially discrete forest canopy heights; (ii developing canopy height models from Landsat imagery and extrapolating them to spatially contiguous canopy heights in Maryland; and, (iii estimating forest aboveground biomass according to the relationship between canopy height and biomass. In our study, we explore the ability to use the GLAS waveform to calculate canopy height without ground-measured forest metrics (R2 = 0.669, RMSE = 4.82 m, MRE = 15.4%. The machine learning models performed better than the principal component model when mapping the regional forest canopy height and aboveground biomass. The total forest aboveground biomass in Maryland reached approximately 160 Tg. When compared with the existing Biomass_CMS map, our biomass estimates presented a similar distribution where higher values were in the Western Shore Uplands region and Folded Application Mountain section, while lower values were located in the Delmarva Peninsula and Allegheny Mountain regions.

  10. Allometric Models Based on Bayesian Frameworks Give Better Estimates of Aboveground Biomass in the Miombo Woodlands

    Directory of Open Access Journals (Sweden)

    Shem Kuyah

    2016-02-01

    Full Text Available The miombo woodland is the most extensive dry forest in the world, with the potential to store substantial amounts of biomass carbon. Efforts to obtain accurate estimates of carbon stocks in the miombo woodlands are limited by a general lack of biomass estimation models (BEMs. This study aimed to evaluate the accuracy of most commonly employed allometric models for estimating aboveground biomass (AGB in miombo woodlands, and to develop new models that enable more accurate estimation of biomass in the miombo woodlands. A generalizable mixed-species allometric model was developed from 88 trees belonging to 33 species ranging in diameter at breast height (DBH from 5 to 105 cm using Bayesian estimation. A power law model with DBH alone performed better than both a polynomial model with DBH and the square of DBH, and models including height and crown area as additional variables along with DBH. The accuracy of estimates from published models varied across different sites and trees of different diameter classes, and was lower than estimates from our model. The model developed in this study can be used to establish conservative carbon stocks required to determine avoided emissions in performance-based payment schemes, for example in afforestation and reforestation activities.

  11. Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales

    Science.gov (United States)

    Li, Aihua; Dhakal, Shital; Glenn, Nancy F.; Spaete, Luke P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan

    2017-01-01

    Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R2 of 0.76 and RMSE of 125 g/m2 for shrub biomass and a pseudo R2 of 0.74 and RMSE of 141 g/m2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77–79% of the variance, with RMSE ranging from 120 to 129 g/m2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure

  12. Spatial distribution of forest aboveground biomass estimated from remote sensing and forest inventory data in New England, USA

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey

    2008-01-01

    We combined satellite (Landsat 7 and Moderate Resolution Imaging Spectrometer) and U.S. Department of Agriculture forest inventory and analysis (FIA) data to estimate forest aboveground biomass (AGB) across New England, USA. This is practical for large-scale carbon studies and may reduce uncertainty of AGB estimates. We estimate that total regional forest AGB was 1,867...

  13. Methods and equations for estimating aboveground volume, biomass, and carbon for trees in the U.S. forest inventory, 2010

    Science.gov (United States)

    Christopher W. Woodall; Linda S. Heath; Grant M. Domke; Michael C. Nichols

    2011-01-01

    The U.S. Forest Service, Forest Inventory and Analysis (FIA) program uses numerous models and associated coefficients to estimate aboveground volume, biomass, and carbon for live and standing dead trees for most tree species in forests of the United States. The tree attribute models are coupled with FIA's national inventory of sampled trees to produce estimates of...

  14. Estimating Stand Volume and Above-Ground Biomass of Urban Forests Using LiDAR

    Directory of Open Access Journals (Sweden)

    Vincenzo Giannico

    2016-04-01

    Full Text Available Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relationship between in situ measurements of stand characteristics and data from airborne laser scanning (LiDAR. In this study we assessed forest stand volume and above-ground biomass (AGB in a broadleaved urban forest, using a combination of LiDAR-derived metrics, which takes the form of a forest allometric model. We tested various methods for extracting proxies of basal area (BA and mean stand height (H from the LiDAR point-cloud distribution and evaluated the performance of different models in estimating forest stand volume and AGB. The best predictors for both models were the scale parameters of the Weibull distribution of all returns (except the first (proxy of BA and the 95th percentile of the distribution of all first returns (proxy of H. The R2 were 0.81 (p < 0.01 for the stand volume model and 0.77 (p < 0.01 for the AGB model with a RMSE of 23.66 m3·ha−1 (23.3% and 19.59 Mg·ha−1 (23.9%, respectively. We found that a combination of two LiDAR-derived variables (i.e., proxy of BA and proxy of H, which take the form of a forest allometric model, can be used to estimate stand volume and above-ground biomass in broadleaved urban forest areas. Our results can be compared to other studies conducted using LiDAR in broadleaved forests with similar methods.

  15. Remote Sensing-based estimates of herbaceous aboveground biomass on the Mongolian Plateau

    Science.gov (United States)

    John, R.; Chen, J.; Kim, Y.; Ouyang, Z.; Park, H.; Shao, C.

    2015-12-01

    Grasslands comprise most of the land area on the Mongolian Plateau, which includes Mongolia (MG), and the province of Inner Mongolia (IM). Substantial land cover/use change in the recent past, driven by a combination of post-liberalization, socio-economic changes as well as extreme climatic events has resulted in degradation of grasslands in structure and function, for e.g., their carbon sequestration ability. Hence there is a need for precise estimation of above-ground biomass (AGB). In this study, we collected surface reflectance spectra from field radiometry and quadrats and line transects, which include percentage of ground cover, vegetation height, above ground biomass, and species richness, during the growing season, between the periods, 2006-2011 in IM and 2011-2015 in MG. The field sampling was stratified by the dominant vegetation types on the plateau, including the meadow steppe, typical steppe, and the desert steppe. These sampling data were used as training and validation data for developing and testing predictive models for total herbaceous vegetation, and AGB, using Landsat and MODIS-surface reflectance bands and derived vegetation indices optimized for low cover conditions. Our results show that the independent ground sampling data were significantly correlated with remotely sensed estimates. In addition to providing measures of carbon sequestration to the community, these predictive models offer decision makers and rangeland managers the ability to accurately monitor grassland dynamics, control livestock stocking rates in these remote and extensive grasslands.

  16. Estimation of crown biomass of Pinus pinaster stands and shrubland above-ground biomass using forest inventory data, remotely sensed imagery and spatial prediction models

    Science.gov (United States)

    H. Viana; J. Aranha; D. Lopes; Warren B. Cohen

    2012-01-01

    Spatially crown biomass of Pinus pinaster stands and shrubland above-ground biomass (AGB) estimation was carried-out in a region located in Centre-North Portugal, by means of different approaches including forest inventory data, remotely sensed imagery and spatial prediction models. Two cover types (pine stands and shrubland) were inventoried and...

  17. Grass allometry and estimation of above-ground biomass in tropical alpine tussock grasslands

    NARCIS (Netherlands)

    Oliveras Menor, I.; Eynden, van der M.; Malhi, Y.; Cahuana, N.; Menor, C.; Zamora, F.; Haugaasen, T.

    2014-01-01

    The puna/páramo grasslands span across the highest altitudes of the tropical Andes, and their ecosystem dynamics are still poorly understood. In this study we examined the above-ground biomass and developed species specific and multispecies power-law allometric equations for four tussock grass

  18. Aboveground biomass estimation with airborne hyperspectral and LiDAR data in Tesinske Beskydy Mountains

    Czech Academy of Sciences Publication Activity Database

    Brovkina, Olga; Zemek, František; Fabiánek, Tomáš

    2015-01-01

    Roč. 8, č. 1 (2015), s. 35-46 ISSN 1803-2451 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk OC09001 Institutional support: RVO:67179843 Keywords : forest aboveground biomass * hyperspectral data * airborne LiDAR * Beskydy Mountains Subject RIV: EH - Ecology, Behaviour

  19. Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey

    2008-01-01

    We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

  20. Aboveground biomass estimation of mangrove species using ALOS-2 PALSAR imagery in Hai Phong City, Vietnam

    Science.gov (United States)

    Pham, Tien Dat; Yoshino, Kunihiko

    2017-04-01

    This study examined the potential of using the HH and HV backscatter from the Advanced Land Observing Satellite 2 (ALOS-2) with enhanced phased array L-band synthetic aperture radar (PALSAR) in high sensitive mode to estimate the above-ground biomass (AGB) of the two mangrove species of Hai Phong city, Vietnam. A positive correlation was observed between the mean backscattering coefficients of the dominant mangrove species at dual polarizations HH and HV and various biophysical parameters. In contrast, low correlations were observed between those coefficients and the tree densities for the two mangrove species. The AGB of the mangrove species were estimated at between 2.8 and 161.5 Mg ha-1 with an average of about 39 Mg ha-1 for Sonneratia caseolaris and between 27.6 and 209.2 Mg ha-1 with an average of ˜100 Mg ha-1 for Kandelia obovata. The main indicators used for the selection of the best potential models in estimating the AGB of different species were R2 and the root-mean-square error (RMSE). The results showed a satisfactory correlation between model estimation and field-based measurements with R2=0.51, RMSE=35.5 Mg ha-1 for S. caseolaris and R2=0.64, RMSE=41.3 Mg ha-1 for K. obovata. This research has illustrated the potential use of ALOS-2 PALSAR data in estimating the AGB of mangrove species in the tropics.

  1. Improved allometric equations for tree aboveground biomass estimation in tropical dipterocarp forests of Kalimantan, Indonesia

    Directory of Open Access Journals (Sweden)

    Solichin Manuri

    2016-12-01

    Full Text Available Background Currently, the common and feasible way to estimate the most accurate forest biomass requires ground measurements and allometric models. Previous studies have been conducted on allometric equations development for estimating tree aboveground biomass (AGB of tropical dipterocarp forests (TDFs in Kalimantan (Indonesian Borneo. However, before the use of existing equations, a validation for the selection of the best allometric equation is required to assess the model bias and precision. This study aims at evaluating the validity of local and pantropical equations; developing new allometric equations for estimating tree AGB in TDFs of Kalimantan; and validating the new equations using independent datasets. Methods We used 108 tree samples from destructive sampling to develop the allometric equations, with maximum tree diameter of 175 cm and another 109 samples from previous studies for validating our equations. We performed ordinary least squares linear regression to explore the relationship between the AGB and the predictor variables in the natural logarithmic form. Results This study found that most of the existing local equations tended to be biased and imprecise, with mean relative error and mean absolute relative error more than 0.1 and 0.3, respectively. We developed new allometric equations for tree AGB estimation in the TDFs of Kalimantan. Through a validation using an independent dataset, we found that our equations were reliable in estimating tree AGB in TDF. The pantropical equation, which includes tree diameter, wood density and total height as predictor variables performed only slightly worse than our new models. Conclusions Our equations improve the precision and reduce the bias of AGB estimates of TDFs. Local models developed from small samples tend to systematically bias. A validation of existing AGB models is essential before the use of the models.

  2. Aboveground tree biomass statistics for Maine: 1982

    Science.gov (United States)

    Eric H. Wharton; Thomas S. Frieswyk; Anne M. Malley

    1985-01-01

    Traditional measures of volume inadequately describe the total aboveground wood resource. The 1980-82 inventory of Maine included estimates of aboveground tree biomass on timberland. There are nearly 1,504.4 million green tons of wood and bark in all trees above the ground level, or 88.2 green tons per acre of timberland. Most of the biomass is in growing stock, but 49...

  3. Estimating terrestrial aboveground biomass estimation using lidar remote sensing: a meta-analysis

    Science.gov (United States)

    Zolkos, S. G.; Goetz, S. J.; Dubayah, R.

    2012-12-01

    Estimating biomass of terrestrial vegetation is a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD). The accuracy of biomass estimates is important in the context carbon markets emerging under REDD, since areas with more accurate estimates command higher prices, but also for characterizing uncertainty in estimates of carbon cycling and the global carbon budget. There is particular interest in mapping biomass so that carbon stocks and stock changes can be monitored consistently across a range of scales - from relatively small projects (tens of hectares) to national or continental scales - but also so that other benefits of forest conservation can be factored into decision making (e.g. biodiversity and habitat corridors). We conducted an analysis of reported biomass accuracy estimates from more than 60 refereed articles using different remote sensing platforms (aircraft and satellite) and sensor types (optical, radar, lidar), with a particular focus on lidar since those papers reported the greatest efficacy (lowest errors) when used in the a synergistic manner with other coincident multi-sensor measurements. We show systematic differences in accuracy between different types of lidar systems flown on different platforms but, perhaps more importantly, differences between forest types (biomes) and plot sizes used for field calibration and assessment. We discuss these findings in relation to monitoring, reporting and verification under REDD, and also in the context of more systematic assessment of factors that influence accuracy and error estimation.

  4. Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data

    Science.gov (United States)

    Narine, L.; Popescu, S. C.; Neuenschwander, A. L.

    2017-12-01

    The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.

  5. Estimating aboveground biomass in Avicennia marina plantation in Indian Sundarbans using high-resolution satellite data

    Science.gov (United States)

    Manna, Sudip; Nandy, Subrata; Chanda, Abhra; Akhand, Anirban; Hazra, Sugata; Dadhwal, Vinay Kumar

    2014-01-01

    Mangroves are active carbon sequesters playing a crucial role in coastal ecosystems. In the present study, aboveground biomass (AGB) was estimated in a 5-year-old Avicennia marina plantation (approximate area ≈190 ha) of Indian Sundarbans using high-resolution satellite data in order to assess its carbon sequestration potential. The reflectance values of each band of LISS IV satellite data and the vegetation indices, viz., normalized difference vegetation index (NDVI), optimized soil adjusted vegetation index (OSAVI), and transformed difference vegetation index (TDVI), derived from the satellite data, were correlated with the AGB. OSAVI showed the strongest positive linear relationship with the AGB and hence carbon content of the stand. OSAVI was found to predict the AGB to a great extent (r=0.72) as it is known to nullify the background soil reflectance effect added to vegetation reflectance. The total AGB of the entire plantation was estimated to be 236 metric tons having a carbon stock of 54.9 metric tons, sequestered within a time span of 5 years. Integration of this technique for monitoring and management of young mangrove plantations will give time and cost effective results.

  6. Development of Allometric Equations for Estimating Above-Ground Liana Biomass in Tropical Primary and Secondary Forests, Malaysia

    Directory of Open Access Journals (Sweden)

    Patrick Addo-Fordjour

    2013-01-01

    Full Text Available The study developed allometric equations for estimating liana stem and total above-ground biomass in primary and secondary forests in the Penang National Park, Penang, Malaysia. Using biomass-diameter-length data of 60 liana individuals representing 15 species, allometric equations were developed for liana stem biomass and total above-ground biomass (TAGB. Three types of allometric equations were developed: models fitted to untransformed, weighted, and log-transformed (log10 data. There was a significant linear relationship between biomass and the predictors (diameter, length, and/or their combinations. The same set of models was developed for primary and secondary forests due to absence of differences in regression line slopes of the forests (ANCOVA: . The coefficients of determination values of the models were high (stem: 0.861 to 0.990; TAGB: 0.900 to 0.992. Generally, log-transformed models showed better fit (Furnival's index, FI 0.5. A comparison of the best TAGB model in this study (based on FI with previously published equations indicated that most of the equations significantly ( overestimated TAGB of lianas. However, a previous equation from Southeast Asia estimated TAGB similar to that of the current equation (. Therefore, regional or intracontinental equations should be preferred to intercontinental equations when estimating liana biomass.

  7. CMS: Aboveground Biomass for Mangrove Forest, Zambezi River Delta, Mozambique

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset provides several estimates of aboveground biomass from various regressions and allometries for mangrove forest in the Zambezi River Delta, Mozambique....

  8. Mixed-species allometric equations and estimation of aboveground biomass and carbon stocks in restoring degraded landscape in northern Ethiopia

    Science.gov (United States)

    Mokria, Mulugeta; Mekuria, Wolde; Gebrekirstos, Aster; Aynekulu, Ermias; Belay, Beyene; Gashaw, Tadesse; Bräuning, Achim

    2018-02-01

    Accurate biomass estimation is critical to quantify the changes in biomass and carbon stocks following the restoration of degraded landscapes. However, there is lack of site-specific allometric equations for the estimation of aboveground biomass (AGB), which consequently limits our understanding of the contributions of restoration efforts in mitigating climate change. This study was conducted in northwestern Ethiopia to develop a multi-species allometric equation and investigate the spatial and temporal variation of C-stocks following the restoration of degraded landscapes. We harvested and weighed 84 trees from eleven dominant species from six grazing exclosures and adjacent communal grazing land. We observed that AGB correlates significantly with diameter at stump height D 30 (R 2 = 0.78 P Ethiopia over space and time. The estimated C-stocks can be used as a reference against which future changes in C-stocks can be compared.

  9. [Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

    Science.gov (United States)

    Liu, Feng; Tan, Chang; Lei, Pi-Feng

    2014-11-01

    Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.

  10. Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar

    Directory of Open Access Journals (Sweden)

    Cédric Véga

    2015-08-01

    Full Text Available Light Detection and Ranging (Lidar is a state of the art technology to assess forest aboveground biomass (AGB. To date, methods developed to relate Lidar metrics with forest parameters were built upon the vertical component of the data. In multi-layered tropical forests, signal penetration might be restricted, limiting the efficiency of these methods. A potential way for improving AGB models in such forests would be to combine traditional approaches by descriptors of the horizontal canopy structure. We assessed the capability and complementarity of three recently proposed methods for assessing AGB at the plot level using point distributional approach (DM, canopy volume profile approach (CVP, 2D canopy grain approach (FOTO, and further evaluated the potential of a topographical complexity index (TCI to explain part of the variability of AGB with slope. This research has been conducted in a mountainous wet evergreen tropical forest of Western Ghats in India. AGB biomass models were developed using a best subset regression approach, and model performance was assessed through cross-validation. Results demonstrated that the variability in AGB could be efficiently captured when variables describing both the vertical (DM or CVP and horizontal (FOTO structure were combined. Integrating FOTO metrics with those of either DM or CVP decreased the root mean squared error of the models by 4.42% and 6.01%, respectively. These results are of high interest for AGB mapping in the tropics and could significantly contribute to the REDD+ program. Model quality could be further enhanced by improving the robustness of field-based biomass models and influence of topography on area-based Lidar descriptors of the forest structure.

  11. Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests

    NARCIS (Netherlands)

    Basuki, T.M.; Laake, van P.E.; Skidmore, A.K.; Hussin, Y.A.

    2009-01-01

    Allometric equations can be used to estimate the biomass and carbon stock of forests. However, so far the equations for Dipterocarp forests have not been developed in sufficient detail. In this research, allometric equations are presented based on the genera of commercial species and mixed species.

  12. Allometric equations for estimating aboveground biomass for common shrubs in northeastern California

    Science.gov (United States)

    Steve Huff; Martin Ritchie; H. Temesgen

    2017-01-01

    Selected allometric equations and fitting strategies were evaluated for their predictive abilities for estimating above ground biomass for seven species of shrubs common to northeastern California. Size classes for woody biomass were categorized as 1-h fuels (0.1–0.6 cm), 10-h fuels (0.6–2.5 cm), 100-h fuels (2.5–7.6 cm), and 1000-h fuels (greater than 7.7 cm in...

  13. Lidar Estimation of Aboveground Biomass in a Tropical Coastal Forest of Gabon

    Science.gov (United States)

    Meyer, V.; Saatchi, S. S.; Poulsen, J.; Clark, C.; Lewis, S.; White, L.

    2012-12-01

    Estimation of tropical forest carbon stocks is a critical yet challenging problem from both ground surveys and remote sensing measurements. However, with its increasing importance in global climate mitigation and carbon cycle assessment, there is a need to develop new techniques to measure forest carbon stocks at landscape scales. Progresses have been made in terms of above ground biomass (AGB) monitoring techniques using ground measurements, with the development of tree allometry techniques. Besides, studies have shown that new remote sensing technologies such as Lidar can give accurate information on tree height and forest structure at a landscape level and can be very useful to estimate AGB. This study examines the ability of small footprint Lidar to estimate above ground biomass in Mondah forest, Gabon. Mondah forest is a coastal tropical forest that is partially flooded and includes areas of mangrove. Its mean annual temperature is 18.8C and mean annual precipitation is 2631mm/yr. Its proximity to the capital of Gabon, Libreville, makes it particularly subject to environmental pressure. The analysis is based on small footprint Lidar waveform information and relative height (RH) metrics that correspond to the percentiles of energy of the signal (25%, 50%, 75% and 100%). AGB estimation is calibrated with ground measurements. Ground-estimated AGB is calculated using allometric equations based on tree diameter, wood density and tree height. Lidar-derived AGB is calculated using a linear regression model between the four Lidar RH metrics and ground-estimated AGB and using available models developed in other tropical regions that use one height metric, average wood density, and tree stocking number. We present uncertainty of different approaches and discuss the universality of lidar biomass estimation models in tropical forests.

  14. Improving Estimates of Aboveground Biomass as Trajectory Indicators in Tidal Wetlands using NAIP Imagery

    Science.gov (United States)

    Ballanti, L.; Byrd, K. B.; Nguyen, D.; Windham-Myers, L.

    2016-12-01

    In an effort to improve carbon accounting in tidal marshes, a key "blue carbon" ecosystem, we developed a method for integrating high resolution imagery into biomass estimates and trajectory indicators of land cover change. Currently, NOAA's Coastal Change Analysis Program (C-CAP) provides tidal marsh cover classes nationally based on 30m Landsat imagery. In order to improve wetland biomass estimates derived from C-CAP land cover and Landsat reflectance data, we developed a methodology to better define biomass extents using 1m National Agriculture Imagery Program (NAIP) imagery. For each of six sentinel estuary sites around the U.S., we performed an object-based segmentation on NAIP imagery. Three classes, `green vegetation', `non- vegetation', and `water' were identified using four NAIP bands (red, green, blue and near infrared), the normalized difference vegetation index (NDVI), and normalized difference water index (NDWI), in a rule-based classification. We performed an accuracy assessment at each site with results ranging from 79% to 92% overall accuracy. Using a fishnet grid of Landsat pixel extents, combined with our 1m classification, we calculated the proportion of green vegetation, non-vegetation, and water per 30m pixel. The proportion of green vegetation was used to scale biomass measurements to improve carbon stock estimates. In addition, we explored the use of multi-temporal NAIP-based fractional cover estimates as trajectory indicators for active marsh loss and restoration as defined by the C-CAP land cover transitions. With NAIP imagery collected ever two years, these methods provide a feasible approach for U.S. blue carbon accounting over time.

  15. The Interpolation Method for Estimating the Above-Ground Biomass Using Terrestrial-Based Inventory

    Directory of Open Access Journals (Sweden)

    I Nengah Surati Jaya

    2014-09-01

    Full Text Available This paper examined several methods for interpolating biomass on logged-over dry land forest using terrestrial-based forest inventory in Labanan, East Kalimantan and Lamandau, Kota Wringing Barat, Central Kalimantan.  The plot-distances examined was 1,000−1,050 m for Labanan and 1,000−899m for Lawanda.  The main objective of this study was to obtain the best interpolation method having the most accurate prediction on spatial distribution of forest biomass for dry land forest. Two main interpolation methods were examined: (1 deterministic approach using the IDW method and (2 geo-statistics approach  using Kriging with spherical, circular, linear, exponential, and Gaussian models.   The study results at both sites consistently showed that the IDW method was better than the Kriging method for estimating the spatial distribution of biomass.  The validation results using chi-square test showed that the IDW interpolation provided accurate biomass estimation.   Using the percentage of mean deviation value (MD(%, it was also recognized that the IDWs with power parameter (p of 2 provided relatively low value , i.e., only 15% for Labanan, East Kalimantan Province and 17% for Lamandau, Kota Wringing Barat Central Kalimantan Province. In general, IDW interpolation method provided better results than the Kriging, where the Kriging method provided MD(% of about 27% and 21% for Lamandau and Labanan sites, respectively.Keywords:  deterministic, geostatistics, IDW, Kriging, above-groung biomass

  16. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

    Directory of Open Access Journals (Sweden)

    Dengsheng Lu

    2012-01-01

    Full Text Available Landsat Thematic mapper (TM image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis. Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems. LiDAR can overcome TM’s shortcoming providing better biomass estimation performance but has not been extensively applied in practice due to data availability constraints. The uncertainty analysis indicates that various sources affect the performance of forest biomass/carbon estimation. With that said, the clear dominate sources of uncertainty are the variation of input sample plot data and data saturation problem related to optical sensors. A possible solution to increasing the confidence in forest biomass estimates is to integrate the strengths of multisensor data.

  17. CMS: Aboveground Biomass from Penobscot Experimental Forest, Maine, 2012

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes estimates of aboveground biomass (AGB) in 2012 from the Penobscot Experimental Forest (PEF) in Bradley, Maine. The AGB was modeled using LiDAR...

  18. Evaluation of Radiometric and Atmospheric Correction Algorithms for Aboveground Forest Biomass Estimation Using Landsat 5 TM Data

    Directory of Open Access Journals (Sweden)

    Pablito M. López-Serrano

    2016-04-01

    Full Text Available Solar radiation is affected by absorption and emission phenomena during its downward trajectory from the Sun to the Earth’s surface and during the upward trajectory detected by satellite sensors. This leads to distortion of the ground radiometric properties (reflectance recorded by satellite images, used in this study to estimate aboveground forest biomass (AGB. Atmospherically-corrected remote sensing data can be used to estimate AGB on a global scale and with moderate effort. The objective of this study was to evaluate four atmospheric correction algorithms (for surface reflectance, ATCOR2 (Atmospheric Correction for Flat Terrain, COST (Cosine of the Sun Zenith Angle, FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes and 6S (Second Simulation of Satellite Signal in the Solar, and one radiometric correction algorithm (for reflectance at the sensor ToA (Apparent Reflectance at the Top of Atmosphere to estimate AGB in temperate forest in the northeast of the state of Durango, Mexico. The AGB was estimated from Landsat 5 TM imagery and ancillary information from a digital elevation model (DEM using the non-parametric multivariate adaptive regression splines (MARS technique. Field reference data for the model training were collected by systematic sampling of 99 permanent forest growth and soil research sites (SPIFyS established during the winter of 2011. The following predictor variables were identified in the MARS model: Band 7, Band 5, slope (β, Wetness Index (WI, NDVI and MSAVI2. After cross-validation, 6S was found to be the optimal model for estimating AGB (R2 = 0.71 and RMSE = 33.5 Mg·ha−1; 37.61% of the average stand biomass. We conclude that atmospheric and radiometric correction of satellite images can be used along with non-parametric techniques to estimate AGB with acceptable accuracy.

  19. Comparison of forest aboveground biomass estimates from passive and active remote sensing sensors over Kayar Khola watershed, Chitwan district, Nepal

    Science.gov (United States)

    Qazi, Waqas A.; Baig, Shahbaz; Gilani, Hammad; Waqar, Mirza Muhammad; Dhakal, Ashwin; Ammar, Ahmad

    2017-04-01

    We use passive optical high-resolution GeoEye-1 imagery and active synthetic aperture radar (SAR) Advanced Land Observing Satellite (ALOS-1) phased array type L-band synthetic aperture radar (PALSAR) L-band horizontal-horizontal-polarization imagery to estimate forest aboveground biomass (AGB) of the tropical mountainous forest test site in Kayar Khola watershed, Chitwan district, Nepal. Object-based tools were used to delineate tree crowns from the orthorectified pan-sharpened GeoEye-1 optical imagery. AGB modeling with crown projection area extracted from the optical imagery shows a good linear relationship with R2=0.76. The terrain-corrected, radiometrically calibrated, and speckle-filtered ALOS-1 PALSAR backscatter image was utilized for AGB modeling; the nonlinear modeling of AGB with the SAR backscatter (dB) shows R2=0.52. The validation R2 values for AGB estimates from GeoEye-1 and ALOS-1 PALSAR are 0.83 and 0.44, respectively. The direct comparison of AGB estimates from both sensors is made possible by the utilization of the same set of ground survey points for both training and validation of the statistical models for both datasets. The final AGB output maps from both sensors show that the spatial patterns of AGB are in reasonable agreement at lower elevation, while SAR seems to underestimate AGB values as compared with optical-based estimates in the higher elevation zones.

  20. [Tree above-ground biomass allometries for carbon stocks estimation in the Caribbean mangroves in Colombia].

    Science.gov (United States)

    Yepes, Adriana; Zapata, Mauricio; Bolivar, Jhoanata; Monsalve, Alejandra; Espinosa, Sandra Milena; Sierra-Correa, Paula Cristina; Sierra, Andrés

    2016-06-01

    The distribution of carbon in “Blue Carbon” ecosystems such as mangroves is little known, when compared with the highly known terrestrial forests, despite its particular and recognized high productivity and carbon storage capacity. The objective of this study was to analyze the above ground biomass (AGB) of the species Rhizophora mangle and Avicennia germinans from the Marine Protected Area of Distrito de Manejo Integrado (DMI), Cispatá-Tinajones-La Balsa, Caribbean Colombian coast. With official authorization, we harvested and studied 30 individuals of each species, and built allometric models in order to estimate AGB. Our AGB results indicated that the studied mangrove forests of the DMI Colombian Caribbean was of 129.69 ± 20.24 Mg/ha, equivalent to 64.85 ± 10.12 MgC/ha. The DMI has an area of 8 570.9 ha in mangrove forests, and we estimated that the total carbon potential stored was about 555 795.93 Mg C. The equations generated in this study can be considered as an alternative for the assessment of carbon stocks in AGB of mangrove forests in Colombia; as other available AGB allometric models do not discriminate mangrove forests, despite being particular ecosystems. They can be used for analysis at a more detailed scale and are considered useful to determine the carbon storage potential of mangrove forests, as a country alternative to support forest conservation and emission reduction strategies. In general, the potential of carbon storage from Colombian Caribbean mangrove forests is important and could promote the country leadership of the “blue carbon” stored.

  1. Estimation of the aboveground biomass in the trans-boundary River ...

    African Journals Online (AJOL)

    Michael Horsfall

    boundary River Sio Sub-catchment in Uganda. 1*BARASA, B; MAJALIWA, M G J; ..... Annual Reviews. DOI:0360-0572/96/0815-. 0129$08.00. National Biomass Study (2003), Technical Report. Forest Department, Kampala Uganda. ISBN:.

  2. Sensitivity of Above-Ground Biomass Estimates to Height-Diameter Modelling in Mixed-Species West African Woodlands.

    Directory of Open Access Journals (Sweden)

    Rubén Valbuena

    Full Text Available It has been suggested that above-ground biomass (AGB inventories should include tree height (H, in addition to diameter (D. As H is a difficult variable to measure, H-D models are commonly used to predict H. We tested a number of approaches for H-D modelling, including additive terms which increased the complexity of the model, and observed how differences in tree-level predictions of H propagated to plot-level AGB estimations. We were especially interested in detecting whether the choice of method can lead to bias. The compared approaches listed in the order of increasing complexity were: (B0 AGB estimations from D-only; (B1 involving also H obtained from a fixed-effects H-D model; (B2 involving also species; (B3 including also between-plot variability as random effects; and (B4 involving multilevel nested random effects for grouping plots in clusters. In light of the results, the modelling approach affected the AGB estimation significantly in some cases, although differences were negligible for some of the alternatives. The most important differences were found between including H or not in the AGB estimation. We observed that AGB predictions without H information were very sensitive to the environmental stress parameter (E, which can induce a critical bias. Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term. We presented a two-step methodology, which succeeded in identifying the species for which the general H-D relation was relevant to modify. Based on the results, our final choice was the single-level mixed-effects model (B3, which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance.

  3. Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta

    Science.gov (United States)

    Fatoyinbo, Temilola; Feliciano, Emanuelle A.; Lagomasino, David; Kuk Lee, Seung; Trettin, Carl

    2018-02-01

    Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as an effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+ (reducing emissions from deforestation and forest degradation), in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne Lidar (ALS) data has often been proposed as the most accurate way for larger scale assessments but the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and Lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types, the end result being a simplified approach for accurately estimating mangrove AGB at large scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall AGB stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R 2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing Lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg ha-1 up to 252 Mg ha-1. We suggest the best model

  4. Estimating Above-Ground Biomass in Sub-Tropical Buffer Zone Community Forests, Nepal, Using Sentinel 2 Data

    Directory of Open Access Journals (Sweden)

    Santa Pandit

    2018-04-01

    Full Text Available Accurate assessment of above-ground biomass (AGB is important for the sustainable management of forests, especially buffer zone (areas within the protected area, where restrictions are placed upon resource use and special measure are undertaken to intensify the conservation value of protected area areas with a high dependence on forest products. This study presents a new AGB estimation method and demonstrates the potential of medium-resolution Sentinel-2 Multi-Spectral Instrument (MSI data application as an alternative to hyperspectral data in inaccessible regions. Sentinel-2 performance was evaluated for a buffer zone community forest in Parsa National Park, Nepal, using field-based AGB as a dependent variable, as well as spectral band values and spectral-derived vegetation indices as independent variables in the Random Forest (RF algorithm. The 10-fold cross-validation was used to evaluate model effectiveness. The effect of the input variable number on AGB prediction was also investigated. The model using all extracted spectral information plus all derived spectral vegetation indices provided better AGB estimates (R2 = 0.81 and RMSE = 25.57 t ha−1. Incorporating the optimal subset of key variables did not improve model variance but reduced the error slightly. This result is explained by the technically-advanced nature of Sentinel-2, which includes fine spatial resolution (10, 20 m and strategically-positioned bands (red-edge, conducted in flat topography with an advanced machine learning algorithm. However, assessing its transferability to other forest types with varying altitude would enable future performance and interpretability assessments of Sentinel-2.

  5. Estimation of Forest Aboveground Biomass in Changbai Mountain Region Using ICESat/GLAS and Landsat/TM Data

    Directory of Open Access Journals (Sweden)

    Hong Chi

    2017-07-01

    Full Text Available Mapping the magnitude and spatial distribution of forest aboveground biomass (AGB, in Mg·ha−1 is crucial to improve our understanding of the terrestrial carbon cycle. Landsat/TM (Thematic Mapper and ICESat/GLAS (Ice, Cloud, and land Elevation Satellite, Geoscience Laser Altimeter System data were integrated to estimate the AGB in the Changbai Mountain area. Firstly, four forest types were delineated according to TM data classification. Secondly, different models for prediction of the AGB at the GLAS footprint level were developed from GLAS waveform metrics and the AGB was derived from field observations using multiple stepwise regression. Lastly, GLAS-derived AGB, in combination with vegetation indices, leaf area index (LAI, canopy closure, and digital elevation model (DEM, were used to drive a data fusion model based on the random forest approach for extrapolating the GLAS footprint AGB to a continuous AGB map. The classification result showed that the Changbai Mountain region was characterized as forest-rich in altitudinal vegetation zones. The contribution of remote sensing variables in modeling the AGB was evaluated. Vegetation index metrics account for large amount of contribution in AGB ranges <150 Mg·ha−1, while canopy closure has the largest contribution in AGB ranges ≥150 Mg·ha−1. Our study revealed that spatial information from two sensors and DEM could be combined to estimate the AGB with an R2 of 0.72 and an RMSE of 25.24 Mg·ha−1 in validation at stand level (size varied from ~0.3 ha to ~3 ha.

  6. A Comparison of Regression Techniques for Estimation of Above-Ground Winter Wheat Biomass Using Near-Surface Spectroscopy

    Directory of Open Access Journals (Sweden)

    Jibo Yue

    2018-01-01

    Full Text Available Above-ground biomass (AGB provides a vital link between solar energy consumption and yield, so its correct estimation is crucial to accurately monitor crop growth and predict yield. In this work, we estimate AGB by using 54 vegetation indexes (e.g., Normalized Difference Vegetation Index, Soil-Adjusted Vegetation Index and eight statistical regression techniques: artificial neural network (ANN, multivariable linear regression (MLR, decision-tree regression (DT, boosted binary regression tree (BBRT, partial least squares regression (PLSR, random forest regression (RF, support vector machine regression (SVM, and principal component regression (PCR, which are used to analyze hyperspectral data acquired by using a field spectrophotometer. The vegetation indexes (VIs determined from the spectra were first used to train regression techniques for modeling and validation to select the best VI input, and then summed with white Gaussian noise to study how remote sensing errors affect the regression techniques. Next, the VIs were divided into groups of different sizes by using various sampling methods for modeling and validation to test the stability of the techniques. Finally, the AGB was estimated by using a leave-one-out cross validation with these powerful techniques. The results of the study demonstrate that, of the eight techniques investigated, PLSR and MLR perform best in terms of stability and are most suitable when high-accuracy and stable estimates are required from relatively few samples. In addition, RF is extremely robust against noise and is best suited to deal with repeated observations involving remote-sensing data (i.e., data affected by atmosphere, clouds, observation times, and/or sensor noise. Finally, the leave-one-out cross-validation method indicates that PLSR provides the highest accuracy (R2 = 0.89, RMSE = 1.20 t/ha, MAE = 0.90 t/ha, NRMSE = 0.07, CV (RMSE = 0.18; thus, PLSR is best suited for works requiring high

  7. Estimation of coniferous forest aboveground biomass with aggregated airborne small-footprint LiDAR full-waveforms.

    Science.gov (United States)

    Qin, Haiming; Wang, Cheng; Xi, Xiaohuan; Tian, Jianlin; Zhou, Guoqing

    2017-08-07

    Forest aboveground biomass (AGB) is critical for assessing forest productivity and evaluating carbon sequestration rates. Discrete-return LiDAR has been widely used to estimate forest AGB, however, fewer studies have estimated the coniferous forest AGB using airborne small-footprint full-waveform LiDAR data. The objective of this study was to extract a suite of newly proposed metrics from airborne small-footprint full-waveform LiDAR data and to evaluate the ability of these metrics in estimating coniferous forest AGB. To achieve this goal, each waveform was first preprocessed, including de-noising, smoothing, and normalization. Next, all the waveforms within each plot were aggregated into a large pseudo waveform and the return energy profile was generated. Then, the foliage profile was retrieved from the return energy profile based on the Geometric Optical and Radiative Transfer (GORT) model. Finally, a series of new return energy profile metrics and foliage profile metrics were extracted to estimate forest AGB. Simple linear regression was conducted to assess the correlation between each LiDAR metric and forest AGB. Stepwise multiple regression analysis was then carried out to select important prediction metrics and establish the optimal forest AGB estimation model. Results indicated that both return energy profile and foliage profile based height-related metrics were strongly correlated to forest AGB. The energy weighted canopy height (H Eweight ) (R = 0.88) and foliage area weighted height (H Fweight ) (R = 0.89) all had the highest correlation coefficients with forest AGB in return energy profile metrics and foliage profile metrics respectively. Energy height percentiles and foliage height percentiles also had the ability to explain AGB variation. The energy-related metrics, foliage area-related metrics, and bounding volume-related metrics derived from the return energy profile and foliage profile were not all sensitive to forest AGB. This study also concluded

  8. Some metals in aboveground biomass of Scots pine in Lithuania

    DEFF Research Database (Denmark)

    Varnagiryte-Kabašinskiene, Iveta; Armolaitis, Kestutis; Stupak, Inge

    2014-01-01

    The stocks of iron (Fe), manganese (Mn), zinc (Zn) and aluminium (Al) in different compartments of the aboveground tree biomass were estimated in Scots pine (Pinus sylvestris L.) stands in Lithuania. Simulated removals of metals due to the forest biomass extraction in a model Scots pine stands...... during a 100-year-long rotation period were compared with metals pools in sandy soil and the fluxes through atmospheric deposition. Applying whole tree harvesting, total removal comprised about 20kgha-1 of each Al and Mn, and 5 times lower amount of each Zn and Fe. The metals were mainly removed...... with stemwood and living branches. However, metal export with aboveground biomass represented relatively small proportion of metals in mineral sandy soil. The annual inputs of Fe and Zn with atmospheric deposition were over 10 times higher than the mean annual removals with total aboveground biomass...

  9. Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR.

    Science.gov (United States)

    Garcia, Mariano; Saatchi, Sassan; Ferraz, Antonio; Silva, Carlos Alberto; Ustin, Susan; Koltunov, Alexander; Balzter, Heiko

    2017-12-01

    Accurate estimation of aboveground forest biomass (AGB) and its dynamics is of paramount importance in understanding the role of forest in the carbon cycle and the effective implementation of climate change mitigation policies. LiDAR is currently the most accurate technology for AGB estimation. LiDAR metrics can be derived from the 3D point cloud (echo-based) or from the canopy height model (CHM). Different sensors and survey configurations can affect the metrics derived from the LiDAR data. We evaluate the ability of the metrics derived from the echo-based and CHM data models to estimate AGB in three different biomes, as well as the impact of point density on the metrics derived from them. Our results show that differences among metrics derived at different point densities were significantly different from zero, with a larger impact on CHM-based than echo-based metrics, particularly when the point density was reduced to 1 point m -2 . Both data models-echo-based and CHM-performed similarly well in estimating AGB at the three study sites. For the temperate forest in the Sierra Nevada Mountains, California, USA, R 2 ranged from 0.79 to 0.8 and RMSE (relRMSE) from 69.69 (35.59%) to 70.71 (36.12%) Mg ha -1 for the echo-based model and from 0.76 to 0.78 and 73.84 (37.72%) to 128.20 (65.49%) Mg ha -1 for the CHM-based model. For the moist tropical forest on Barro Colorado Island, Panama, the models gave R 2 ranging between 0.70 and 0.71 and RMSE between 30.08 (12.36%) and 30.32 (12.46) Mg ha -1 [between 0.69-0.70 and 30.42 (12.50%) and 61.30 (25.19%) Mg ha -1 ] for the echo-based [CHM-based] models. Finally, for the Atlantic forest in the Sierra do Mar, Brazil, R 2 was between 0.58-0.69 and RMSE between 37.73 (8.67%) and 39.77 (9.14%) Mg ha -1 for the echo-based model, whereas for the CHM R 2 was between 0.37-0.45 and RMSE between 45.43 (10.44%) and 67.23 (15.45%) Mg ha -1 . Metrics derived from the CHM show a higher dependence on point density than metrics

  10. A comparison of two above-ground biomass estimation techniques integrating satellite-based remotely sensed data and ground data for tropical and semiarid forests in Puerto Rico

    Science.gov (United States)

    Iiames, J. S.; Riegel, J.; Lunetta, R.

    2013-12-01

    Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA) program. The U.S. Environmental Protection Agency (EPA) estimated above-ground forest biomass implementing methodology first posited by the Woods Hole Research Center developed for conterminous United States (National Biomass and Carbon Dataset [NBCD2000]). For EPA's effort, spatial predictor layers for above-ground biomass estimation included derived products from the U.S. Geologic Survey (USGS) National Land Cover Dataset 2001 (NLCD) (landcover and canopy density), the USGS Gap Analysis Program (forest type classification), the USGS National Elevation Dataset, and the NASA Shuttle Radar Topography Mission (tree heights). In contrast, the U.S. Forest Service (USFS) biomass product integrated FIA ground-based data with a suite of geospatial predictor variables including: (1) the Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; (2) NLCD land cover proportions; (3) topographic variables; (4) monthly and annual climate parameters; and (5) other ancillary variables. Correlations between both data sets were made at variable watershed scales to test level of agreement. Notice: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S EPA funded and conducted the research described in this paper. Although this work was reviewed by the EPA and has been approved for publication, it may not necessarily reflect official Agency policy. Mention of any trade names or commercial products does not constitute endorsement or recommendation for use.

  11. Estimating aboveground tree biomass for beetle-killed lodgepole pine in the Rocky Mountains of northern Colorado

    Science.gov (United States)

    Woodam Chung; Paul Evangelista; Nathaniel Anderson; Anthony Vorster; Hee Han; Krishna Poudel; Robert Sturtevant

    2017-01-01

    The recent mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic has affected millions of hectares of conifer forests in the Rocky Mountains. Land managers are interested in using biomass from beetle-killed trees for bioenergy and biobased products, but they lack adequate information to accurately estimate biomass in stands with heavy mortality. We...

  12. Characterizing uncertainties of the national-scale forest gross aboveground biomass (AGB) loss estimate: a case study of the Democratic Republic of the Congo

    Science.gov (United States)

    Tyukavina, A.; Stehman, S.; Potapov, P.; Turubanova, S.; Baccini, A.; Goetz, S. J.; Laporte, N. T.; Houghton, R. A.; Hansen, M.

    2013-12-01

    Modern remote sensing techniques enable the mapping and monitoring of aboveground biomass (AGB) carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where a national forest inventory (NFI) has yet to be established due to a lack of infrastructure and political instability. We demonstrate a method for producing national-scale gross AGB loss estimates and quantifying uncertainty of the estimates using remotely sensed-derived forest cover loss and biomass carbon density data. Forest cover type and loss were characterized using published Landsat-based data sets and related to LIDAR-derived biomass data from the Geoscience Laser Altimeter System (GLAS). We produced two gross AGB loss estimates for the DRC for the last decade (2000-2010): a conservative estimate accounting for classification errors in the 60-m resolution FACET forest cover change product, and a maximal estimate that also took into consideration omitted change at the 30m spatial resolution. Omitted disturbances were largely related to smallholder agriculture, the detection of which is scale-dependent. The use of LIDAR data as a substitute for NFI data to estimate AGB loss based on Landsat-derived activity data was demonstrated. Comparisons of our forest cover loss and AGB estimates with published studies raise the issue of scale in forest cover change mapping and its impact on carbon stock change estimation using remotely sensed data.

  13. Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

    Science.gov (United States)

    Nelson, Ross; Margolis, Hank; Montesano, Paul; Sun, Guoqing; Cook, Bruce; Corp, Larry; Andersen, Hans-Erik; DeJong, Ben; Pellat, Fernando Paz; Fickel, Thaddeus; hide

    2016-01-01

    Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95 +/- 0.45 Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17 +/- 0.06 Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87 +/- 0.49 Gt) overestimated the national ground-based estimate by 7.5%. The comparable log-linear model result (63.29 +/-1.36 Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log-linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119

  14. Evaluating Generic Pantropical Allometric Models for the Estimation of Above-Ground Biomass in the Teak Plantations of Southern Western Ghats, India

    Directory of Open Access Journals (Sweden)

    S. Sandeep

    2015-09-01

    Full Text Available The use of suitable tree biomass allometric equations is crucial for making precise and non- destructive estimation of carbon storage and biomass energy values. The aim of this research was to evaluate the accuracy of the most commonly used pantropical allometric models and site-specific models to estimate the above-ground biomass (AGB in different aged teak plantations of Southern Western Ghats of India. For this purpose, the AGB data measured for 70 trees with diameter >10 cm from different aged teak plantations in Kerala part of Southern Western Ghats following destructive procedure was used. The results show that site specific models based on a single predictor variable diameter at breast height (dbh, though simple, may grossly increase the uncertainty across sites. Hence, a generic model encompassing dbh, height and wood specific gravity with sufficient calibration taking into account different forest types is advised for the tropical forest systems. The study also suggests that the commonly used pantropical models should be evaluated for different ecosystems prior to their application at national or regional scales.

  15. Estimating Forest Aboveground Biomass by Combining ALOS PALSAR and WorldView-2 Data: A Case Study at Purple Mountain National Park, Nanjing, China

    Directory of Open Access Journals (Sweden)

    Songqiu Deng

    2014-08-01

    Full Text Available Enhanced methods are required for mapping the forest aboveground biomass (AGB over a large area in Chinese forests. This study attempted to develop an improved approach to retrieving biomass by combining PALSAR (Phased Array type L-band Synthetic Aperture Radar and WorldView-2 data. A total of 33 variables with potential correlations with forest biomass were extracted from the above data. However, these parameters had poor fits to the observed biomass. Accordingly, the synergies of several variables were explored to identify improved relationships with the AGB. Using principal component analysis and multivariate linear regression (MLR, the accuracies of the biomass estimates obtained using PALSAR and WorldView-2 data were improved to approximately 65% to 71%. In addition, using the additional dataset developed from the fusion of FBD (fine beam dual-polarization and WorldView-2 data improved the performance to 79% with an RMSE (root mean square error of 35.13 Mg/ha when using the MLR method. Moreover, a further improvement (R2 = 0.89, relative RMSE = 17.08% was obtained by combining all the variables mentioned above. For the purpose of comparison with MLR, a neural network approach was also used to estimate the biomass. However, this approach did not produce significant improvements in the AGB estimates. Consequently, the final MLR model was recommended to map the AGB of the study area. Finally, analyses of estimated error in distinguishing forest types and vertical structures suggested that the RMSE decreases gradually from broad-leaved to coniferous to mixed forest. In terms of different vertical structures (VS, VS3 has a high error because the forest lacks undergrowth trees, while VS4 forest, which has approximately the same amounts of stems in each of the three DBH (diameter at breast height classes (DBH > 20, 10 ≤ DBH ≤ 20, and DBH < 10 cm, has the lowest RMSE. This study demonstrates that the combination of PALSAR and WorldView-2 data

  16. Age-related and stand-wise estimates of carbon stocks and sequestration in the aboveground coarse wood biomass of wetland forests in the northern Pantanal, Brazil

    Science.gov (United States)

    Schöngart, J.; Arieira, J.; Felfili Fortes, C.; Cezarine de Arruda, E.; Nunes da Cunha, C.

    2011-11-01

    In this study we use allometric models combined with tree ring analysis to estimate carbon stocks and sequestration in the aboveground coarse wood biomass (AGWB) of wetland forests in the Pantanal, located in central South America. In four 1-ha plots in stands characterized by the pioneer tree species Vochysia divergens Pohl (Vochysiaceae) forest inventories (trees ≥10 cm diameter at breast height, D) have been performed and converted to estimates of AGWB by two allometric models using three independent parameters (D, tree height H and wood density ρ). We perform a propagation of measurement errors to estimate uncertainties in the estimates of AGWB. Carbon stocks of AGWB vary from 7.8 ± 1.5 to 97.2 ± 14.4 Mg C ha-1 between the four stands. From models relating tree ages determined by dendrochronological techniques to C-stocks in AGWB we derived estimates for C-sequestration which differs from 0.50 ± 0.03 to 3.34 ± 0.31 Mg C ha-1 yr-1. Maps based on geostatistic techniques indicate the heterogeneous spatial distribution of tree ages and C-stocks of the four studied stands. This distribution is the result of forest dynamics due to the colonizing and retreating of V. divergens and other species associated with pluriannual wet and dry episodes in the Pantanal, respectively. Such information is essential for the management of the cultural landscape of the Pantanal wetlands.

  17. Estimation of Aboveground Biomass in Alpine Forests: A Semi-Empirical Approach Considering Canopy Transparency Derived from Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Martin Rutzinger

    2010-12-01

    Full Text Available In this study, a semi-empirical model that was originally developed for stem volume estimation is used for aboveground biomass (AGB estimation of a spruce dominated alpine forest. The reference AGB of the available sample plots is calculated from forest inventory data by means of biomass expansion factors. Furthermore, the semi-empirical model is extended by three different canopy transparency parameters derived from airborne LiDAR data. These parameters have not been considered for stem volume estimation until now and are introduced in order to investigate the behavior of the model concerning AGB estimation. The developed additional input parameters are based on the assumption that transparency of vegetation can be measured by determining the penetration of the laser beams through the canopy. These parameters are calculated for every single point within the 3D point cloud in order to consider the varying properties of the vegetation in an appropriate way. Exploratory Data Analysis (EDA is performed to evaluate the influence of the additional LiDAR derived canopy transparency parameters for AGB estimation. The study is carried out in a 560 km2 alpine area in Austria, where reference forest inventory data and LiDAR data are available. The investigations show that the introduction of the canopy transparency parameters does not change the results significantly according to R2 (R2 = 0.70 to R2 = 0.71 in comparison to the results derived from, the semi-empirical model, which was originally developed for stem volume estimation.

  18. Estimating Mangrove Canopy Height and Above-Ground Biomass in the Everglades National Park with Airborne LiDAR and TanDEM-X Data

    Directory of Open Access Journals (Sweden)

    Emanuelle A. Feliciano

    2017-07-01

    Full Text Available Mangrove forests are important natural ecosystems due to their ability to capture and store large amounts of carbon. Forest structural parameters, such as canopy height and above-ground biomass (AGB, provide a good measure for monitoring temporal changes in carbon content. The protected coastal mangrove forest of the Everglades National Park (ENP provides an ideal location for studying these processes, as harmful human activities are minimal. We estimated mangrove canopy height and AGB in the ENP using Airborne LiDAR/Laser (ALS and TanDEM-X (TDX datasets acquired between 2011 and 2013. Analysis of both datasets revealed that mangrove canopy height can reach up to ~25 m and AGB can reach up to ~250 Mg•ha−1. In general, mangroves ranging from 9 m to 12 m in stature dominate the forest canopy. The comparison of ALS and TDX canopy height observations yielded an R2 = 0.85 and Root Mean Square Error (RMSE = 1.96 m. Compared to a previous study based on data acquired during 2000–2004, our analysis shows an increase in mangrove stature and AGB, suggesting that ENP mangrove forests are continuing to accumulate biomass. Our results suggest that ENP mangrove forests have managed to recover from natural disturbances, such as Hurricane Wilma.

  19. Siberian Boreal Forest Aboveground Biomass and Fire Scar Maps, Russia, 1969-2007

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides 30-meter resolution mapped estimates of Cajander larch (Larix cajanderi) aboveground biomass (AGB), circa 2007, and a map of burn perimeters...

  20. ABoVE: Gridded 30-m Aboveground Biomass, Shrub Dominance, North Slope, AK, 2007-2016

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset includes 30-m gridded estimates of total plant aboveground biomass (AGB), the shrub AGB, and the shrub dominance (shrub/plant AGB) for non-water...

  1. Aboveground Tree Biomass for Pinus ponderosa in Northeastern California

    Directory of Open Access Journals (Sweden)

    Todd A. Hamilton

    2013-03-01

    Full Text Available Forest managers need accurate biomass equations to plan thinning for fuel reduction or energy production. Estimates of carbon sequestration also rely upon such equations. The current allometric equations for ponderosa pine (Pinus ponderosa commonly employed for California forests were developed elsewhere, and are often applied without consideration potential for spatial or temporal variability. Individual-tree aboveground biomass allometric equations are presented from an analysis of 79 felled trees from four separate management units at Blacks Mountain Experimental Forest: one unthinned and three separate thinned units. A simultaneous set of allometric equations for foliage, branch and bole biomass were developed as well as branch-level equations for wood and foliage. Foliage biomass relationships varied substantially between units while branch and bole biomass estimates were more stable across a range of stand conditions. Trees of a given breast height diameter and crown ratio in thinned stands had more foliage biomass, but slightly less branch biomass than those in an unthinned stand. The observed variability in biomass relationships within Blacks Mountain Experimental Forest suggests that users should consider how well the data used to develop a selected model relate to the conditions in any given application.

  2. Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

    Science.gov (United States)

    Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

    2018-04-01

    Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0

  3. Estimating aboveground forest biomass carbon and fire consumption in the U.S. Utah High Plateaus using data from the Forest Inventory and Analysis program, Landsat, and LANDFIRE

    Science.gov (United States)

    Chen, Xuexia; Liu, Shuguang; Zhu, Zhiliang; Vogelmann, James E.; Li, Zhengpeng; Ohlen, Donald O.

    2011-01-01

    The concentrations of CO2 and other greenhouse gases in the atmosphere have been increasing and greatly affecting global climate and socio-economic systems. Actively growing forests are generally considered to be a major carbon sink, but forest wildfires lead to large releases of biomass carbon into the atmosphere. Aboveground forest biomass carbon (AFBC), an important ecological indicator, and fire-induced carbon emissions at regional scales are highly relevant to forest sustainable management and climate change. It is challenging to accurately estimate the spatial distribution of AFBC across large areas because of the spatial heterogeneity of forest cover types and canopy structure. In this study, Forest Inventory and Analysis (FIA) data, Landsat, and Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) data were integrated in a regression tree model for estimating AFBC at a 30-m resolution in the Utah High Plateaus. AFBC were calculated from 225 FIA field plots and used as the dependent variable in the model. Of these plots, 10% were held out for model evaluation with stratified random sampling, and the other 90% were used as training data to develop the regression tree model. Independent variable layers included Landsat imagery and the derived spectral indicators, digital elevation model (DEM) data and derivatives, biophysical gradient data, existing vegetation cover type and vegetation structure. The cross-validation correlation coefficient (r value) was 0.81 for the training model. Independent validation using withheld plot data was similar with r value of 0.82. This validated regression tree model was applied to map AFBC in the Utah High Plateaus and then combined with burn severity information to estimate loss of AFBC in the Longston fire of Zion National Park in 2001. The final dataset represented 24 forest cover types for a 4 million ha forested area. We estimated a total of 353 Tg AFBC with an average of 87 MgC/ha in the Utah High

  4. Modeling aboveground biomass of Tamarix ramosissima in the Arkansas River Basin of Southeastern Colorado, USA

    Science.gov (United States)

    Evangelista, P.; Kumar, S.; Stohlgren, T.J.; Crall, A.W.; Newman, G.J.

    2007-01-01

    Predictive models of aboveground biomass of nonnative Tamarix ramosissima of various sizes were developed using destructive sampling techniques on 50 individuals and four 100-m2 plots. Each sample was measured for average height (m) of stems and canopy area (m2) prior to cutting, drying, and weighing. Five competing regression models (P < 0.05) were developed to estimate aboveground biomass of T. ramosissima using average height and/or canopy area measurements and were evaluated using Akaike's Information Criterion corrected for small sample size (AICc). Our best model (AICc = -148.69, ??AICc = 0) successfully predicted T. ramosissima aboveground biomass (R2 = 0.97) and used average height and canopy area as predictors. Our 2nd-best model, using the same predictors, was also successful in predicting aboveground biomass (R2 = 0.97, AICc = -131.71, ??AICc = 16.98). A 3rd model demonstrated high correlation between only aboveground biomass and canopy area (R2 = 0.95), while 2 additional models found high correlations between aboveground biomass and average height measurements only (R2 = 0.90 and 0.70, respectively). These models illustrate how simple field measurements, such as height and canopy area, can be used in allometric relationships to accurately predict aboveground biomass of T. ramosissima. Although a correction factor may be necessary for predictions at larger scales, the models presented will prove useful for many research and management initiatives.

  5. Applying inventory methods to estimate aboveground biomass from satellite light detection and ranging (LiDAR) forest height data

    Science.gov (United States)

    Sean P. Healey; Paul L. Patterson; Sassan Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman; Gretchen G. Moisen

    2012-01-01

    Light Detection and Ranging (LiDAR) returns from the spaceborne Geoscience Laser Altimeter (GLAS) sensor may offer an alternative to solely field-based forest biomass sampling. Such an approach would rely upon model-based inference, which can account for the uncertainty associated with using modeled, instead of field-collected, measurements. Model-based methods have...

  6. Age-related and stand-wise estimates of carbon stocks and sequestration in the aboveground coarse wood biomass of wetland forests in the northern Pantanal, Brazil

    Directory of Open Access Journals (Sweden)

    J. Schöngart

    2011-11-01

    Full Text Available In this study we use allometric models combined with tree ring analysis to estimate carbon stocks and sequestration in the aboveground coarse wood biomass (AGWB of wetland forests in the Pantanal, located in central South America. In four 1-ha plots in stands characterized by the pioneer tree species Vochysia divergens Pohl (Vochysiaceae forest inventories (trees ≥10 cm diameter at breast height, D have been performed and converted to estimates of AGWB by two allometric models using three independent parameters (D, tree height H and wood density ρ. We perform a propagation of measurement errors to estimate uncertainties in the estimates of AGWB. Carbon stocks of AGWB vary from 7.8 ± 1.5 to 97.2 ± 14.4 Mg C ha−1 between the four stands. From models relating tree ages determined by dendrochronological techniques to C-stocks in AGWB we derived estimates for C-sequestration which differs from 0.50 ± 0.03 to 3.34 ± 0.31 Mg C ha−1 yr−1. Maps based on geostatistic techniques indicate the heterogeneous spatial distribution of tree ages and C-stocks of the four studied stands. This distribution is the result of forest dynamics due to the colonizing and retreating of V. divergens and other species associated with pluriannual wet and dry episodes in the Pantanal, respectively. Such information is essential for the management of the cultural landscape of the Pantanal wetlands.

  7. Influence of tree size, taxonomy, and edaphic conditions on heart rot in mixed-dipterocarp Bornean rainforests: implications for aboveground biomass estimates

    Science.gov (United States)

    Heineman, K. D.; Russo, S. E.; Baillie, I. C.; Mamit, J. D.; Chai, P. P.-K.; Chai, L.; Hindley, E. W.; Lau, B.-T.; Tan, S.; Ashton, P. S.

    2015-05-01

    Fungal decay of heartwood creates hollows and areas of reduced wood density within the stems of living trees known as heart rot. Although heart rot is acknowledged as a source of error in forest aboveground biomass estimates, there are few datasets available to evaluate the environmental controls over heart rot infection and severity in tropical forests. Using legacy and recent data from drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of heart rot, and used generalized linear mixed effect models to characterize the association of heart rot with tree size, wood density, taxonomy, and edaphic conditions. Heart rot was detected in 55% of felled stems > 30 cm DBH, while the detection frequency was lower for stems of the same size evaluated by non-destructive drilling (45%) and coring (23%) methods. Heart rot severity, defined as the percent stem volume lost in infected stems, ranged widely from 0.1-82.8%. Tree taxonomy explained the greatest proportion of variance in heart rot frequency and severity among the fixed and random effects evaluated in our models. Heart rot frequency, but not severity, increased sharply with tree diameter, ranging from 56% infection across all datasets in stems > 50 cm DBH to 11% in trees 10-30 cm DBH. The frequency and severity of heart rot increased significantly in soils with low pH and cation concentrations in topsoil, and heart rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the percent of stem biomass lost to heart rot varied significantly with soil properties, and we estimate that 7% of the forest biomass is in some stage of heart rot decay. This study demonstrates not only that heart rot is a significant source of error in forest carbon estimates, but also that it strongly covaries with soil resources, underscoring the need to account for edaphic variation in

  8. Assessing the influence of return density on estimation of lidar-based aboveground biomass in tropical peat swamp forests of Kalimantan, Indonesia

    Science.gov (United States)

    Manuri, Solichin; Andersen, Hans-Erik; McGaughey, Robert J.; Brack, Cris

    2017-04-01

    The airborne lidar system (ALS) provides a means to efficiently monitor the status of remote tropical forests and continues to be the subject of intense evaluation. However, the cost of ALS acquisition can vary significantly depending on the acquisition parameters, particularly the return density (i.e., spatial resolution) of the lidar point cloud. This study assessed the effect of lidar return density on the accuracy of lidar metrics and regression models for estimating aboveground biomass (AGB) and basal area (BA) in tropical peat swamp forests (PSF) in Kalimantan, Indonesia. A large dataset of ALS covering an area of 123,000 ha was used in this study. This study found that cumulative return proportion (CRP) variables represent a better accumulation of AGB over tree heights than height-related variables. The CRP variables in power models explained 80.9% and 90.9% of the BA and AGB variations, respectively. Further, it was found that low-density (and low-cost) lidar should be considered as a feasible option for assessing AGB and BA in vast areas of flat, lowland PSF. The performance of the models generated using reduced return densities as low as 1/9 returns per m2 also yielded strong agreement with the original high-density data. The use model-based statistical inferences enabled relatively precise estimates of the mean AGB at the landscape scale to be obtained with a fairly low-density of 1/4 returns per m2, with less than 10% standard error (SE). Further, even when very low-density lidar data was used (i.e., 1/49 returns per m2) the bias of the mean AGB estimates were still less than 10% with a SE of approximately 15%. This study also investigated the influence of different DTM resolutions for normalizing the elevation during the generation of forest-related lidar metrics using various return densities point cloud. We found that the high-resolution digital terrain model (DTM) had little effect on the accuracy of lidar metrics calculation in PSF. The accuracy of

  9. Evaluation of stem rot in 339 Bornean tree species: implications of size, taxonomy, and soil-related variation for aboveground biomass estimates

    Science.gov (United States)

    Heineman, K. D.; Russo, S. E.; Baillie, I. C.; Mamit, J. D.; Chai, P. P.-K.; Chai, L.; Hindley, E. W.; Lau, B.-T.; Tan, S.; Ashton, P. S.

    2015-10-01

    Fungal decay of heart wood creates hollows and areas of reduced wood density within the stems of living trees known as stem rot. Although stem rot is acknowledged as a source of error in forest aboveground biomass (AGB) estimates, there are few data sets available to evaluate the controls over stem rot infection and severity in tropical forests. Using legacy and recent data from 3180 drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of stem rot in a total of 339 tree species, and related variation in stem rot with tree size, wood density, taxonomy, and species' soil association, as well as edaphic conditions. Predicted stem rot frequency for a 50 cm tree was 53 % of felled, 39 % of drilled, and 28 % of cored stems, demonstrating differences among methods in rot detection ability. The percent stem volume infected by rot, or stem rot severity, ranged widely among trees with stem rot infection (0.1-82.8 %) and averaged 9 % across all trees felled. Tree taxonomy explained the greatest proportion of variance in both stem rot frequency and severity among the predictors evaluated in our models. Stem rot frequency, but not severity, increased sharply with tree diameter, ranging from 13 % in trees 10-30 cm DBH to 54 % in stems ≥ 50 cm DBH across all data sets. The frequency of stem rot increased significantly in soils with low pH and cation concentrations in topsoil, and stem rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the maximum percent of stem biomass lost to stem rot varied significantly with soil properties, and we estimate that stem rot reduces total forest AGB estimates by up to 7 % relative to what would be predicted assuming all stems are composed strictly of intact wood. This study demonstrates not only that stem rot is likely to be a significant source of error in forest AGB estimation

  10. Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

    Science.gov (United States)

    Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

    2017-12-01

    The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement

  11. Estimating the Above-Ground Biomass in Miombo Savanna Woodlands (Mozambique, East Africa Using L-Band Synthetic Aperture Radar Data

    Directory of Open Access Journals (Sweden)

    Maria J. Vasconcelos

    2013-03-01

    Full Text Available The quantification of forest above-ground biomass (AGB is important for such broader applications as decision making, forest management, carbon (C stock change assessment and scientific applications, such as C cycle modeling. However, there is a great uncertainty related to the estimation of forest AGB, especially in the tropics. The main goal of this study was to test a combination of field data and Advanced Land Observing Satellite (ALOS Phased Array L-band Synthetic Aperture Radar (PALSAR backscatter intensity data to reduce the uncertainty in the estimation of forest AGB in the Miombo savanna woodlands of Mozambique (East Africa. A machine learning algorithm, based on bagging stochastic gradient boosting (BagSGB, was used to model forest AGB as a function of ALOS PALSAR Fine Beam Dual (FBD backscatter intensity metrics. The application of this method resulted in a coefficient of correlation (R between observed and predicted (10-fold cross-validation forest AGB values of 0.95 and a root mean square error of 5.03 Mg·ha−1. However, as a consequence of using bootstrap samples in combination with a cross validation procedure, some bias may have been introduced, and the reported cross validation statistics could be overoptimistic. Therefore and as a consequence of the BagSGB model, a measure of prediction variability (coefficient of variation on a pixel-by-pixel basis was also produced, with values ranging from 10 to 119% (mean = 25% across the study area. It provides additional and complementary information regarding the spatial distribution of the error resulting from the application of the fitted model to new observations.

  12. Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico.

    Science.gov (United States)

    Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, Christiane

    2018-02-21

    Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R 2 , Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated

  13. The relationship between species richness and aboveground biomass in a primary Pinus kesiya forest of Yunnan, southwestern China.

    Science.gov (United States)

    Li, Shuaifeng; Lang, Xuedong; Liu, Wande; Ou, Guanglong; Xu, Hui; Su, Jianrong

    2018-01-01

    The relationship between biodiversity and biomass is an essential element of the natural ecosystem functioning. Our research aims at assessing the effects of species richness on the aboveground biomass and the ecological driver of this relationship in a primary Pinus kesiya forest. We sampled 112 plots of the primary P. kesiya forests in Yunnan Province. The general linear model and the structural equation model were used to estimate relative effects of multivariate factors among aboveground biomass, species richness and the other explanatory variables, including climate moisture index, soil nutrient regime and stand age. We found a positive linear regression relationship between the species richness and aboveground biomass using ordinary least squares regressions. The species richness and soil nutrient regime had no direct significant effect on aboveground biomass. However, the climate moisture index and stand age had direct effects on aboveground biomass. The climate moisture index could be a better link to mediate the relationship between species richness and aboveground biomass. The species richness affected aboveground biomass which was mediated by the climate moisture index. Stand age had direct and indirect effects on aboveground biomass through the climate moisture index. Our results revealed that climate moisture index had a positive feedback in the relationship between species richness and aboveground biomass, which played an important role in a link between biodiversity maintenance and ecosystem functioning. Meanwhile, climate moisture index not only affected positively on aboveground biomass, but also indirectly through species richness. The information would be helpful in understanding the biodiversity-aboveground biomass relationship of a primary P. kesiya forest and for forest management.

  14. Estimating aboveground live understory vegetation carbon in the United States

    Science.gov (United States)

    Johnson, Kristofer D.; Domke, Grant M.; Russell, Matthew B.; Walters, Brian; Hom, John; Peduzzi, Alicia; Birdsey, Richard; Dolan, Katelyn; Huang, Wenli

    2017-12-01

    Despite the key role that understory vegetation plays in ecosystems and the terrestrial carbon cycle, it is often overlooked and has few quantitative measurements, especially at national scales. To understand the contribution of understory carbon to the United States (US) carbon budget, we developed an approach that relies on field measurements of understory vegetation cover and height on US Department of Agriculture Forest Service, Forest Inventory and Analysis (FIA) subplots. Allometric models were developed to estimate aboveground understory carbon. A spatial model based on stand characteristics and remotely sensed data was also applied to estimate understory carbon on all FIA plots. We found that most understory carbon was comprised of woody shrub species (64%), followed by nonwoody forbs and graminoid species (35%) and seedlings (1%). The largest estimates were found in temperate or warm humid locations such as the Pacific Northwest and southeastern US, thus following the same broad trend as aboveground tree biomass. The average understory aboveground carbon density was estimated to be 0.977 Mg ha-1, for a total estimate of 272 Tg carbon across all managed forest land in the US (approximately 2% of the total aboveground live tree carbon pool). This estimate is more than twice as low as previous FIA modeled estimates that did not rely on understory measurements, suggesting that this pool may currently be overestimated in US National Greenhouse Gas reporting.

  15. Above-ground biomass of mangrove species. I. Analysis of models

    Science.gov (United States)

    Soares, Mário Luiz Gomes; Schaeffer-Novelli, Yara

    2005-10-01

    This study analyzes the above-ground biomass of Rhizophora mangle and Laguncularia racemosa located in the mangroves of Bertioga (SP) and Guaratiba (RJ), Southeast Brazil. Its purpose is to determine the best regression model to estimate the total above-ground biomass and compartment (leaves, reproductive parts, twigs, branches, trunk and prop roots) biomass, indirectly. To do this, we used structural measurements such as height, diameter at breast-height (DBH), and crown area. A combination of regression types with several compositions of independent variables generated 2.272 models that were later tested. Subsequent analysis of the models indicated that the biomass of reproductive parts, branches, and prop roots yielded great variability, probably because of environmental factors and seasonality (in the case of reproductive parts). It also indicated the superiority of multiple regression to estimate above-ground biomass as it allows researchers to consider several aspects that affect above-ground biomass, specially the influence of environmental factors. This fact has been attested to the models that estimated the biomass of crown compartments.

  16. Standing crop and aboveground biomass partitioning of a dwarf mangrove forest in Taylor River Slough, Florida

    Science.gov (United States)

    Coronado-Molina, C.; Day, J.W.; Reyes, E.; Perez, B.C.

    2004-01-01

    The structure and standing crop biomass of a dwarf mangrove forest, located in the salinity transition zone ofTaylor River Slough in the Everglades National Park, were studied. Although the four mangrove species reported for Florida occurred at the study site, dwarf Rhizophora mangle trees dominated the forest. The structural characteristics of the mangrove forest were relatively simple: tree height varied from 0.9 to 1.2 meters, and tree density ranged from 7062 to 23 778 stems haa??1. An allometric relationship was developed to estimate leaf, branch, prop root, and total aboveground biomass of dwarf Rhizophora mangle trees. Total aboveground biomass and their components were best estimated as a power function of the crown area times number of prop roots as an independent variable (Y = B ?? Xa??0.5083). The allometric equation for each tree component was highly significant (pRhizophora mangle contributed 85% of total standing crop biomass. Conocarpus erectus, Laguncularia racemosa, and Avicennia germinans contributed the remaining biomass. Average aboveground biomass allocation was 69% for prop roots, 25% for stem and branches, and 6% for leaves. This aboveground biomass partitioning pattern, which gives a major role to prop roots that have the potential to produce an extensive root system, may be an important biological strategy in response to low phosphorus availability and relatively reduced soils that characterize mangrove forests in South Florida.

  17. Aboveground Biomass and Litterfall Dynamics in Secondary Forest ...

    African Journals Online (AJOL)

    The differences in aboveground biomass, litterfall patterns and the seasonality of litterfall in three secondary forest fields aged 1, 5 and 10 years of age regenerating from degraded abandoned rubber plantation and a mature forest were studied in southern Nigeria. This is with a view to understanding the possibility of ...

  18. Family Differences in Aboveground Biomass Allocation in Loblolly Pine

    Science.gov (United States)

    Scott D. Roberts

    2002-01-01

    The proportion of tree growth allocated to stemwood is an important economic component of growth efficiency. Differences in growth efficiency between species, or between families within species, may therefore be related to how growth is proportionally allocated between the stem and other aboveground biomass components. This study examines genetically related...

  19. Aboveground Biomass Equations for Small Trees of Brutian Pine in Turkey to Facilitate Harvesting and Management

    Directory of Open Access Journals (Sweden)

    Mehmet Eker

    2017-12-01

    Full Text Available Brutian pine (Pinus brutia Ten. is the most widespread conifer species in the Eastern Mediterranean. Aboveground biomass equations for small diameter brutian pine trees are needed for accurate fuel inventory and to assess carbon sequestration potential. In this study, we developed tree biomass models based on 143 brutian pine saplings measured in 11 research plots. Aboveground biomass (AGB was modeled with a nonlinear mixed effects model which accounted for the variability among plots. The predicted total AGB was then distributed into foliage, branch and stem components. The Beta, Dirichlet, and multinomial logistic regressions were unbiased in their estimates of biomass component proportions. The Dirichlet regression has the advantage of an additive property and does not require non-standard data.

  20. Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests

    Directory of Open Access Journals (Sweden)

    P. Köhler

    2010-08-01

    Full Text Available The canopy height h of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or LIDAR. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground life biomass (AGB (and thus carbon content of vegetation and leaf area index (LAI and identify how correlation and uncertainty vary for two different spatial scales. The process-based forest growth model FORMIND2.0 was applied to simulate (a undisturbed forest growth and (b a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia in South-East Asia. In both undisturbed and disturbed forests AGB can be expressed as a power-law function of canopy height h (AGB = a · hb with an r2 ~ 60% if data are analysed in a spatial resolution of 20 m × 20 m (0.04 ha, also called plot size. The correlation coefficient of the regression is becoming significant better in the disturbed forest sites (r2 = 91% if data are analysed hectare wide. There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2 ~ 60% between AGB and the area fraction of gaps in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a

  1. Aboveground biomass estimation using SAR-optical (Lidar, RapidEye) and field inventory datasets in Skukuza, Kruger National Park in South Africa

    Science.gov (United States)

    Onyango Odipo, Victor; Hüttich, Christian; Luck, Wolfgang; Schmullius, Christiane

    2015-04-01

    African savanna covers approximately two-thirds of sub-saharan Africa, playing important roles as a carbon pool, habitat for mankind and wildlife, source of livelihood, an important tropical climate modifier, among other ecological roles. Sub-saharan Africa alone accounts for 25% of the tropical aboveground carbon stock (193 Gt C). Global and national level AGB estimates rely on extrapolations with regression models from few field inventories, leading in some cases, up to 100% uncertainty. Remote sensing has proven to provide reliable vegetation structural mapping, given the high spatial and temporal resolution allowing datasets to be availed in areas where ground based inventories are infeasible due to time and financial constraints. The availability of freely accessible optical remotely-sensed datasets has made this feat attainable. However, the heterogeneity of tropical savannas (co-existence of trees and grasses), coupled with erratic rainfall events and atmospheric clouds and aerosol in the tropics has made it difficult to extract biophysical properties of the savannas by solely using optical datasets. This has necessitated an assessment of synergies between active and passive remotely sensed datasets to benefit from the complementarities. In this study we assess the extent to which multi-level sub-centimeter Unmanned Aerial Vehicle (UAV) Lidar, high resolution RapidEye and microwave (ALOS PALSAR L-band and Sentinel-1 C-band) remotely sensed datasets can be used together with tree census datasets to estimate AGB within the complex southern Africa savanna ecosystem. A random forest (RF) regression model is produced which relates the Lidar canopy-height metrics (CHM) with both synthetic aperture radar (SAR) and high resolution RapidEye datasets. As a validation, we compare our results with both national and global level ABG estimates.

  2. Effect of stand structure on models for volume and aboveground biomass assessment (Castelfusano pinewood, Roma

    Directory of Open Access Journals (Sweden)

    2009-03-01

    Full Text Available The main purpose of this research was to analyse the effects of stand structure on biomass allocation and on the accurancy of estimation models for volume and aboveground biomass of Italian stone pine (Pinus pinea L.. Although the species is widely distributed on Mediterranean coasts, few studies on forest biomass estimation have focused on pinewoods. The research was carried out in the Castelfusano’s pinewood (Rome and concerned the two most common structural types: (a 50 years-old pinewood originated by broadcast seeding; and (b 62 years-old pinewood originated by partial seeding alternating worked strips to firm strips. Some 83 sample trees were selected for stem volume estimation and a subset of 32 trees used to quantify the total epigeous biomass, the wooden biomass compartment, including stem and big branches (diameter > 3 cm and the photosynthetic biomass, including thin branches (diameter < 3 cm and needles. Collected data were used to elaborate allometric relations for stem volume, total biomass and specific relations for both compartments, based on one (d2 or two (d2h indipendent variables, for both structural types. Furthermore, pinewood specific biomass expansion factors (BEF - indexes used to estimate carbon stocks starting from stem biomass data - were obtained. The achieved estimation models were subjected to both parallelism and coincidence tests, showing significant effects of stand structure on the accurancy of the allometric relations. The effects of stand structure and reliability of tree height curves on the accurancy of estimation models for volume and aboveground biomass and on biomass allocation in different compartments are analysed and discussed.

  3. Loss of aboveground forest biomass and landscape biomass variability in Missouri, US

    Science.gov (United States)

    Brice B. Hanberry; Hong S. He; Stephen R. Shifley

    2016-01-01

    Disturbance regimes and forests have changed over time in the eastern United States. We examined effects of historical disturbance (circa 1813 to 1850) compared to current disturbance (circa 2004 to 2008) on aboveground, live tree biomass (for trees with diameters ≥13 cm) and landscape variation of biomass in forests of the Ozarks and Plains landscapes in Missouri, USA...

  4. Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar.

    Science.gov (United States)

    Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin

    2017-01-19

    Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass ( R ² = 0.340, root-mean-square error (RMSE) = 81.89 g·m -2 , and relative error of 14.1%). The improvement of multiple regressions to the R ² and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns.

  5. Carbon sequestration rate and aboveground biomass carbon potential of three young species in lower Gangetic plain.

    Science.gov (United States)

    Jana, Bipal K; Biswas, Soumyajit; Majumder, Mrinmoy; Roy, Pankaj K; Mazumdar, Asis

    2011-07-01

    Carbon is sequestered by the plant photosynthesis and stored as biomass in different parts of the tree. Carbon sequestration rate has been measured for young species (6 years age) of Shorea robusta at Chadra forest in Paschim Medinipur district, Albizzia lebbek in Indian Botanic Garden in Howrah district and Artocarpus integrifolia at Banobitan within Kolkata in the lower Gangetic plain of West Bengal in India by Automated Vaisala Made Instrument GMP343 and aboveground biomass carbon has been analyzed by CHN analyzer. The specific objective of this paper is to measure carbon sequestration rate and aboveground biomass carbon potential of three young species of Shorea robusta, Albizzia lebbek and Artocarpus integrifolia. The carbon sequestration rate (mean) from the ambient air during winter season as obtained by Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 11.13 g/h, 14.86 g/h and 4.22g/h, respectively. The annual carbon sequestration rate from ambient air were estimated at 8.97 t C ha(-1) by Shorea robusta, 11.97 t C ha(-1) by Albizzia lebbek and 3.33 t C ha(-1) by Artocarpus integrifolia. The percentage of carbon content (except root) in the aboveground biomass of Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 47.45, 47.12 and 43.33, respectively. The total aboveground biomass carbon stock per hectare as estimated for Shorea robusta, Albizzia lebbek and Artocarpus integrifolia were 5.22 t C ha(-1) , 6.26 t C ha(-1) and 7.28 t C ha(-1), respectively in these forest stands.

  6. LEAF AREA INDEX DERIVED FROM HEMISPHERICAL PHOTOGRAPH AND ITS CORRELATION WITH ABOVEGROUND FOREST BIOMASS

    Directory of Open Access Journals (Sweden)

    Tyas Mutiara Basuki

    2015-04-01

    Full Text Available Leaf area index (LAI is one of the key physical factors in the energy exchange between terrestrial ecosystem and atmosphere. It determines the photosynthesis process to produce biomass and plays an important role in performing forest stand reflectance. Therefore building relationship between LAI and biomass from field measurements can be used to develop allometric equations for biomass estimation. This paper studies the relationship between diameter at breast height (DBH and leaves biomass, DBH and crown biomass (sum up of leaves, twigs and branches as well as between LAI and leaves biomass; LAI and crown biomass; LAI and Total Above-ground Biomass (TAGB in East Kalimantan Province. Destructive sampling was conducted to develop allometric equations. The DBH measurements from 52 sample plots were used as training data for model development (35 plots and for validation (17 plots. A hemispherical photograph was used to record LAI. The result shows that strong corelation (r exists between natural logarithmic (ln DBH and crown biomass ranging from 0.88 to 0.98. The correlation (r between LAI and biomass of leaves; leaves + twigs + branches; TAGB were 0.742, 0.768 and 0.772, respectively. Improvement of (r between LAI and biomass can be conducted by proper time of LAI measurement, when the sky is uniformly overcast.

  7. Mapping Aboveground Biomass in the Amazon Basin: Exploring Sensors, Scales, and Strategies for Optimal Data Linkage

    Science.gov (United States)

    Walker, W. S.; Baccini, A.

    2013-05-01

    encompassing the state of Acre Brazil. Through a comprehensive comparison involving nearly 50 separate analyses, we assess accuracy in aboveground biomass estimates with respect to varying (a) satellite data inputs, (b) image spatial scales, (c) and field/image data linkage strategies. Our results confirm the utility of both ALOS/PALSAR and Landsat data for the provision of accurate estimates of aboveground biomass, with accuracy increasing markedly with increasing spectral resolution, decreasing spatial resolution, and as the spatial mismatches between field and image data sources are minimized.

  8. [Spatial distribution of Tamarix ramosissima aboveground biomass and water consumption in the lower reaches of Heihe River, Northwest China].

    Science.gov (United States)

    Peng, Shou-Zhang; Zhao, Chuan-Yan; Peng, Huan-Hua; Zheng, Xiang-Lin; Xu, Zhong-Lin

    2010-08-01

    Based on the field observation on the Tamarix ramosissima populations in the lower reaches of Heihe River, the relationship models between the aboveground biomass of T. ramosissima and its morphological features (basal diameter, height, and canopy perimeter) were built. In the mean time, the land use/cover of the study area was classified by the decision tree classification with high resolution image (QuickBird), the distribution of T. ramosissima was extracted from classification map, and the morphological feature (canopy perimeter) of T. ramosissima was calculated with ArcGIS 9.2. On the bases of these, the spatial distribution of T. ramosissima aboveground biomass in the study area was estimated. Finally, the spatial distribution of the water consumption of T. ramosissima in the study area was calculated by the transpiration coefficient (300) and the aboveground biomass. The results showed that the aboveground biomass of T. ramosissima was 69644.7 t, and the biomass per unit area was 0.78 kg x m(-2). Spatially, the habitats along the banks of Heihe River were suitable for T. ramosissima, and thus, this tree species had a high biomass. The total amount of water consumption of T. ramosissima in the study area was 2.1 x 10(7) m3, and the annual mean water consumption of T. ramosissima ranged from 30 mm to 386 mm.

  9. Tropical Soil Carbon Stocks do not Reflect Aboveground Forest Biomass Across Geological and Rainfall Gradients

    Science.gov (United States)

    Cusack, D. F.; Markesteijn, L.; Turner, B. L.

    2016-12-01

    Soil organic carbon (C) dynamics present a large source of uncertainty in global C cycle models, and inhibit our ability to predict effects of climate change. Tropical wet and seasonal forests exert a disproportionate influence on the global C cycle relative to their land area because they are the most C-rich ecosystems on Earth, containing 25-40% of global terrestrial C stocks. While significant advances have been made to map aboveground C stocks in tropical forests, determining soil C stocks using remote sensing technology is still not possible for closed-canopy forests. It is unclear to what extent aboveground C stocks can be used to predict soil C stocks across tropical forests. Here we present 1-m-deep soil organic C stocks for 42 tropical forest sites across rainfall and geological gradients in Panama. We show that soil C stocks do not correspond to aboveground plant biomass or to litterfall productivity in these humid tropical forests. Rather, soil C stocks were strongly and positively predicted by fine root biomass, soil clay content, and rainfall (R2 = 0.47, p chemical characteristics form an important basis for improving model estimates of soil C stocks and predictions of climate change effects on tropical C storage.

  10. Evaluation of total aboveground biomass and total merchantable biomass in Missouri

    Science.gov (United States)

    Michael E. Goerndt; David R. Larsen; Charles D. Keating

    2014-01-01

    In recent years, the state of Missouri has been converting to biomass weight rather than volume as the standard measurement of wood for buying and selling sawtimber. Therefore, there is a need to identify accurate and precise methods of estimating whole tree biomass and merchantable biomass of harvested trees as well as total standing biomass of live timber for...

  11. Comparative analysis of spectral unmixing and neural networks for estimating small diameter tree above-ground biomass in the State of Mississippi

    Science.gov (United States)

    Moham P. Tiruveedhula; Joseph Fan; Ravi R. Sadasivuni; Surya S. Durbha; David L. Evans

    2010-01-01

    The accumulation of small diameter trees (SDTs) is becoming a nationwide concern. Forest management practices such as fire suppression and selective cutting of high grade timber have contributed to an overabundance of SDTs in many areas. Alternative value-added utilization of SDTs (for composite wood products and biofuels) has prompted the need to estimate their...

  12. Aboveground tree biomass for Pinus ponderosa in northeastern California

    Science.gov (United States)

    Martin W. Ritchie; Jianwei Zhang; Todd A. Hamilton

    2013-01-01

    Forest managers need accurate biomass equations to plan thinning for fuel reduction or energy production. Estimates of carbon sequestration also rely upon such equations. The current allometric equations for ponderosa pine (Pinus ponderosa) commonly employed for California forests were developed elsewhere, and are often applied without consideration potential for...

  13. National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China

    Directory of Open Access Journals (Sweden)

    Hong Chi

    2015-05-01

    Full Text Available Forest aboveground biomass (AGB was mapped throughout China using large footprint LiDAR waveform data from the Geoscience Laser Altimeter System (GLAS onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat, Moderate Resolution Imaging Spectro-radiometer (MODIS imagery and forest inventory data. The entire land of China was divided into seven zones according to the geographic characteristics of the forests. The forest AGB prediction models were separately developed for different forest types in each of the seven forest zones at GLAS footprint level from GLAS waveform parameters and biomass derived from height and diameter at breast height (DBH field observation. Some waveform parameters used in the prediction models were able to reduce the effects of slope on biomass estimation. The models of GLAS-based biomass estimates were developed by using GLAS footprints with slopes less than 20° and slopes ≥ 20°, respectively. Then, all GLAS footprint biomass and MODIS data were used to establish Random Forest regression models for extrapolating footprint AGB to a nationwide scale. The total amount of estimated AGB in Chinese forests around 2006 was about 12,622 Mt vs. 12,617 Mt derived from the seventh national forest resource inventory data. Nearly half of all provinces showed a relative error (% of less than 20%, and 80% of total provinces had relative errors less than 50%.

  14. LBA-ECO LC-15 Amazon Basin Aboveground Live Biomass Distribution Map: 1990-2000

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides a single raster image containing the spatial distribution of aboveground live forest biomass of the Amazon basin. This product was derived...

  15. Retrieval of Mangrove Aboveground Biomass at the Individual Species Level with WorldView-2 Images

    Directory of Open Access Journals (Sweden)

    Yuanhui Zhu

    2015-09-01

    Full Text Available Previous research studies have demonstrated that the relationship between remote sensing-derived parameters and aboveground biomass (AGB could vary across different species types. However, there are few studies that calibrate reliable statistical models for mangrove AGB. This study quantifies the differences of accuracy in AGB estimation between the results obtained with and without the consideration of species types using Worldview-2 images and field surveys. A Back Propagation Artificial Neural Network (BP ANN based model is developed for the accurate estimation of uneven-aged and dense mangrove forest biomass. The contributions of the input variables are further quantified using a “Weights” method based on BP ANN model. Two types of mangrove species, Sonneratia apetala (S. apetala and Kandelia candel (K. candel, are examined in this study. Results show that the species type information is the most important variable for AGB estimation, and the red edge band and the associated vegetation indices from WorldView-2 images are more sensitive to mangrove AGB than other bands and vegetation indices. The RMSE of biomass estimation at the incorporation of species as a dummy variable is 19.17% lower than that of the mixed species level. The results demonstrate that species type information obtained from the WorldView-2 images can significantly improve of the accuracy of the biomass estimation.

  16. Evaluation of sampling strategies to estimate crown biomass

    Science.gov (United States)

    Krishna P Poudel; Hailemariam Temesgen; Andrew N Gray

    2015-01-01

    Depending on tree and site characteristics crown biomass accounts for a significant portion of the total aboveground biomass in the tree. Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire...

  17. A regression-adjusted approach can estimate competing biomass

    Science.gov (United States)

    James H. Miller

    1983-01-01

    A method is presented for estimating above-ground herbaceous and woody biomass on competition research plots. On a set of destructively-sampled plots, an ocular estimate of biomass by vegetative component is first made, after which vegetation is clipped, dried, and weighed. Linear regressions are then calculated for each component between estimated and actual weights...

  18. Tree height integrated into pantropical forest biomass estimates

    NARCIS (Netherlands)

    Feldpausch, T.R.; Lloyd, J.; Lewis, S.L.; Brienen, R.J.W.; Gloor, M.; Montegudo Mendoza, A.; Arets, E.J.M.M.

    2012-01-01

    Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer

  19. Landscape Patterns of Wood Density and Aboveground Biomass Along a Tropical Elevation Gradient in Costa Rica

    Science.gov (United States)

    Robinson, C. M.

    2015-12-01

    This research sought to understand how tree wood density and taxonomic diversity relate to topography and three-dimensional vegetation structure in the tropical montane forest of Braulio Carrillo National Park in Costa Rica. The study utilized forest inventory and botanical data from twenty 1-ha plots ranging from 55 m to 2800 m above sea level and remote sensing data from an airborne lidar sensor (NASA's Land, Vegetation, and Ice Sensor [LVIS]) to quantify variations in forest structure. There is growing evidence that ecosystem structure may help to control the functional variations across landscapes. This study relates patterns of tree functional wood density and alpha diversity to three-dimensional structure using remote sensing observations of forest structure. We were able to test the effect of the gradient on wood density measured from collected tree cores and on the subsequent aboveground biomass estimations. We sought to determine if there was a significant pattern of wood density across the altitudinal gradient, which has implications for conservation of both ecosystem services and biodiversity. We also wanted to determine how many random individuals could be sampled to accurately estimate aboveground biomass in a one-hectare plot. Our results indicate that there is a strong relationship between LVIS-derived forest 3D-structure and alpha diversity, likely controlled by variations in abiotic factors and topography along the elevation. Using spatial analysis with the aid of remote sensing data, we found patterns along the environmental gradients defining species composition and forest structure. Wood density values were found to vary significantly from database values for the same species. This variation in tree growth has repercussions on overall forest structure, and subsequent carbon estimates extrapolated from field measurements. Because these wood density values are directly tied to biomass estimates, it is possible that carbon storage has been

  20. Allometric models and aboveground biomass stocks of a West African Sudan Savannah watershed in Benin.

    Science.gov (United States)

    Chabi, Adéyèmi; Lautenbach, Sven; Orekan, Vincent Oladokoun Agnila; Kyei-Baffour, Nicholas

    2016-12-01

    The estimation of forest biomass changes due to land-use change is of significant importance for estimates of the global carbon budget. The accuracy of biomass density maps depends on the availability of reliable allometric models used in combination with data derived from satellites images and forest inventory data. To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on allometric equations and the spatial distribution of aboveground biomass stocks in each land use/land cover (LULC) class is needed for the different ecological zones. Such information has been sparse for the West African Sudan Savannah zone. This paper provides new data and results for this important zone. The analysis combines satellite images and locally derived allometric models based on non-destructive measurements to estimate aboveground biomass stocks at the watershed level in the Sudan Savannah zone in Benin. We compared three types of empirically fitted allometric models of varying model complexity with respect to the number of input parameters that are easy to measure at the ground: model type I based only on the diameter at breast height (DBH), type II which used DBH and tree height and model type III which used DBH, tree height and wood density as predictors. While for most LULC classes model III outperformed the other models even the simple model I showed a good performance. The estimated mean dry biomass density values and attached standard error for the different LULC class were 3.28 ± 0.31 (for cropland and fallow), 3.62 ± 0.36 (for Savanna grassland), 4.86 ± 1.03 (for Settlements), 14.05 ± 0.72 (for Shrub savanna), 45.29 ± 2.51 (for Savanna Woodland), 46.06 ± 14.40 (for Agroforestry), 94.58 ± 4.98 (for riparian forest and woodland), 162 ± 64.88 (for Tectona grandis plantations), 179.62 ± 57.61 (for Azadirachta indica plantations), 25.17 ± 7.46 (for Gmelina arborea plantations

  1. Allometric models and aboveground biomass stocks of a West African Sudan Savannah watershed in Benin

    Directory of Open Access Journals (Sweden)

    Adéyèmi Chabi

    2016-08-01

    Full Text Available Abstract Background The estimation of forest biomass changes due to land-use change is of significant importance for estimates of the global carbon budget. The accuracy of biomass density maps depends on the availability of reliable allometric models used in combination with data derived from satellites images and forest inventory data. To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on allometric equations and the spatial distribution of aboveground biomass stocks in each land use/land cover (LULC class is needed for the different ecological zones. Such information has been sparse for the West African Sudan Savannah zone. This paper provides new data and results for this important zone. The analysis combines satellite images and locally derived allometric models based on non-destructive measurements to estimate aboveground biomass stocks at the watershed level in the Sudan Savannah zone in Benin. Results We compared three types of empirically fitted allometric models of varying model complexity with respect to the number of input parameters that are easy to measure at the ground: model type I based only on the diameter at breast height (DBH, type II which used DBH and tree height and model type III which used DBH, tree height and wood density as predictors. While for most LULC classes model III outperformed the other models even the simple model I showed a good performance. The estimated mean dry biomass density values and attached standard error for the different LULC class were 3.28 ± 0.31 (for cropland and fallow, 3.62 ± 0.36 (for Savanna grassland, 4.86 ± 1.03 (for Settlements, 14.05 ± 0.72 (for Shrub savanna, 45.29 ± 2.51 (for Savanna Woodland, 46.06 ± 14.40 (for Agroforestry, 94.58 ± 4.98 (for riparian forest and woodland, 162 ± 64.88 (for Tectona grandis plantations, 179.62 ± 57.61 (for Azadirachta indica plantations, 25.17

  2. Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar

    Science.gov (United States)

    Chen, Qi

    2015-08-01

    Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.

  3. Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran

    Directory of Open Access Journals (Sweden)

    Sasan Vafaei

    2018-01-01

    Full Text Available The main objective of this research is to investigate the potential combination of Sentinel-2A and ALOS-2 PALSAR-2 (Advanced Land Observing Satellite -2 Phased Array type L-band Synthetic Aperture Radar-2 imagery for improving the accuracy of the Aboveground Biomass (AGB measurement. According to the current literature, this kind of investigation has rarely been conducted. The Hyrcanian forest area (Iran is selected as the case study. For this purpose, a total of 149 sample plots for the study area were documented through fieldwork. Using the imagery, three datasets were generated including the Sentinel-2A dataset, the ALOS-2 PALSAR-2 dataset, and the combination of the Sentinel-2A dataset and the ALOS-2 PALSAR-2 dataset (Sentinel-ALOS. Because the accuracy of the AGB estimation is dependent on the method used, in this research, four machine learning techniques were selected and compared, namely Random Forests (RF, Support Vector Regression (SVR, Multi-Layer Perceptron Neural Networks (MPL Neural Nets, and Gaussian Processes (GP. The performance of these AGB models was assessed using the coefficient of determination (R2, the root-mean-square error (RMSE, and the mean absolute error (MAE. The results showed that the AGB models derived from the combination of the Sentinel-2A and the ALOS-2 PALSAR-2 data had the highest accuracy, followed by models using the Sentinel-2A dataset and the ALOS-2 PALSAR-2 dataset. Among the four machine learning models, the SVR model (R2 = 0.73, RMSE = 38.68, and MAE = 32.28 had the highest prediction accuracy, followed by the GP model (R2 = 0.69, RMSE = 40.11, and MAE = 33.69, the RF model (R2 = 0.62, RMSE = 43.13, and MAE = 35.83, and the MPL Neural Nets model (R2 = 0.44, RMSE = 64.33, and MAE = 53.74. Overall, the Sentinel-2A imagery provides a reasonable result while the ALOS-2 PALSAR-2 imagery provides a poor result of the forest AGB estimation. The combination of the Sentinel-2A imagery and the ALOS-2 PALSAR-2

  4. Dynamics, aboveground biomass and composition on permanent plots, Tambopata National Reserve. Madre de Dios, Peru

    Directory of Open Access Journals (Sweden)

    Nadir C. Pallqui

    2014-12-01

    Full Text Available In this study we evaluated the floristic composition and changes in stored biomass and dynamics over time in 9 permanent plots monitored by RAINFOR (Amazon Forest Inventory Network and located in the lowland Amazon rainforest of the Tambopata National Reserve. Data were acquired in the field using the standardized methodology of RAINFOR. The biomass was estimated using the equation for tropical moist forests of Chave et al. (2005. Biomass dynamics were analyzed, in three separated periods from 2003 to 2011. 64 families, 219 genera and 531 species were recorded. The tree floristic composition is very similar in all plots except for one swamp plot, although but it is also evident that two slightly different forest communities exist in the rest of landscape, apparently related to the age of the ancient river terraces in the area. Mortality and recruitment of individuals averaged 2.12 ± 0.52% and 1.92 ± 0.49%, respectively. The turnover rate is 2.02% per year. Aboveground biomass stored in these forests averages 296.2 ± 33.9 t ha-1. The biomass dynamics show a total net gain of 1.96, 1.69 and –1.23 t ha-1 for period respectively. Prior to the drought of 2010 a change in biomass was found 1.88 t ha-1 yr-1 and post drought was -0.18 t ha-1 yr-1 on average, though the difference is not significant. Demographic analysis suggests a dynamic equilibrium in the plots. The negative balance of biomass observed for the period 2008 – 2011 may be due to the drought of 2010, in which half of the monitored plots experienced negative net biomass change due to mortality of individuals selectively affecting the floristic composition.

  5. Aboveground biomass subdivisions in woody species of the savanna ecosystem project study area, Nylsvley

    CSIR Research Space (South Africa)

    Rutherford, MC

    1979-01-01

    Full Text Available Aboveground peak season biomass is given for 11 woody species in each of five belt transects under study. Mean aerial biomass for all species was 16 273 kg ha, made up of 14 937 kg ha wood, 236 kg ha current season's twigs and 1 100 kg ha leaves...

  6. Modeling loblolly pine aboveground live biomass in a mature pine-hardwood stand: a cautionary tale

    Science.gov (United States)

    D. C. Bragg

    2011-01-01

    Carbon sequestration in forests is a growing area of interest for researchers and land managers. Calculating the quantity of carbon stored in forest biomass seems to be a straightforward task, but it is highly dependent on the function(s) used to construct the stand. For instance, there are a number of possible equations to predict aboveground live biomass for loblolly...

  7. Demographic Drivers of Aboveground Biomass Dynamics During Secondary Succession in Neotropical Dry and Wet Forests

    NARCIS (Netherlands)

    Rozendaal, Danaë M.A.; Chazdon, Robin L.; Arreola-Villa, Felipe; Balvanera, Patricia; Bentos, Tony V.; Dupuy, Juan M.; Hernández-Stefanoni, J.L.; Jakovac, Catarina C.; Lebrija-Trejos, Edwin E.; Lohbeck, Madelon; Martínez-Ramos, Miguel; Massoca, Paulo E.S.; Meave, Jorge A.; Mesquita, Rita C.G.; Mora, Francisco; Pérez-García, Eduardo A.; Romero-Pérez, I.E.; Saenz-Pedroza, Irving; Breugel, van Michiel; Williamson, G.B.; Bongers, Frans

    2017-01-01

    The magnitude of the carbon sink in second-growth forests is expected to vary with successional biomass dynamics resulting from tree growth, recruitment, and mortality, and with the effects of climate on these dynamics. We compare aboveground biomass dynamics of dry and wet Neotropical forests,

  8. Mapping Aboveground Biomass using Texture Indices from Aerial Photos in a Temperate Forest of Northeastern China

    Directory of Open Access Journals (Sweden)

    Shili Meng

    2016-03-01

    Full Text Available Optical remote sensing data have been considered to display signal saturation phenomena in regions of high aboveground biomass (AGB and multi-storied forest canopies. However, some recent studies using texture indices derived from optical remote sensing data via the Fourier-based textural ordination (FOTO approach have provided promising results without saturation problems for some tropical forests, which tend to underestimate AGB predictions. This study was applied to the temperate mixed forest of the Liangshui National Nature Reserve in Northeastern China and demonstrated the capability of FOTO texture indices to obtain a higher prediction quality of forest AGB. Based on high spatial resolution aerial photos (1.0 m spatial resolution acquired in September 2009, the relationship between FOTO texture indices and field-derived biomass measurements was calibrated using a support vector regression (SVR algorithm. Ten-fold cross-validation was used to construct a robust prediction model, which avoided the over-fitting problem. By further comparison the performance of the model estimates for greater coverage, the predicted results were compared with a reference biomass map derived from LiDAR metrics. This study showed that the FOTO indices accounted for 88.3% of the variance in ground-based AGB; the root mean square error (RMSE was 34.35 t/ha, and RMSE normalized by the mean value of the estimates was 22.31%. This novel texture-based method has great potential for forest AGB estimation in other temperate regions.

  9. Sensitivity of Multi-Source SAR Backscatter to Changes in Forest Aboveground Biomass

    Directory of Open Access Journals (Sweden)

    Wenli Huang

    2015-07-01

    Full Text Available Accurate estimates of forest aboveground biomass (AGB after anthropogenic disturbance could reduce uncertainties in the carbon budget of terrestrial ecosystems and provide critical information to policy makers. Yet, the loss of carbon due to forest disturbance and the gain from post-disturbance recovery have not been sufficiently assessed. In this study, a sensitivity analysis was first conducted to investigate: (1 the influence of incidence angle and soil moisture on Synthetic Aperture Radar (SAR backscatter; (2 the feasibility of cross-image normalization between multi-temporal and multi-sensor SAR data; and (3 the possibility of applying normalized backscatter data to detect forest biomass changes. An empirical model was used to reduce incidence angle effects, followed by cross-image normalization procedure to lessen soil moisture effect. Changes in forest biomass at medium spatial resolution (100 m were mapped using both spaceborne and airborne SAR data. Results indicate that (1 the effect of incidence angle on SAR backscatter could be reduced to less than 1 dB by the correction model for airborne SAR data; (2 over 50% of the changes in SAR backscatter due to soil moisture could be eliminated by the cross-image normalization procedure; and (3 forest biomass changes greater than 100 Mg·ha−1 or above 50% of 150 Mg·ha−1 are detectable using cross-normalized SAR data.

  10. Aboveground biomass production of a semi-arid southern African ...

    African Journals Online (AJOL)

    The model predicts the annual aboveground net primary production (ANPP) from regression equations of canopy cover by annual production fraction for plant functional classes. We tested the output of the model against another fully independent net primary production (NPP) model, namely the MODIS NPP product.

  11. Aboveground Biomass Variability Across Intact and Degraded Forests in the Brazilian Amazon

    Science.gov (United States)

    Longo, Marcos; Keller, Michael; Dos-Santos, Maiza N.; Leitold, Veronika; Pinage, Ekena R.; Baccini, Alessandro; Saatchi, Sassan; Nogueira, Euler M.; Batistella, Mateus; Morton, Douglas C.

    2016-01-01

    Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, re, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained70 of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 +/- 2.5 and 31.9 +/- 10.8 kg C m(exp -2). Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 +/- 0.7 kg C m(-2)(94%) of ACD. Forests that burned nearly15 years ago had between 4.1 +/- 0.5 and 6.8 +/- 0.3 kg C m(exp -2) (22-40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 +/- 0.3 and 4.4 +/- 0.4 kg C m(exp -2)(4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pan-tropical products consistently overestimated ACD in degraded forests, under-estimated ACD in intact forests, and showed little sensitivity to res and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation(REDD+).

  12. High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR

    Directory of Open Access Journals (Sweden)

    Jose A. Jimenez-Berni

    2018-02-01

    Full Text Available Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR, mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR (r2 of 0.99 and root mean square error of 0.017 m were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association (r2 = 0.92 and slope = 1.02 at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI and 3D profile index (3DPI. The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass (r2 = 0.93 and r2 = 0.92 for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new

  13. High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.

    Science.gov (United States)

    Jimenez-Berni, Jose A; Deery, David M; Rozas-Larraondo, Pablo; Condon, Anthony Tony G; Rebetzke, Greg J; James, Richard A; Bovill, William D; Furbank, Robert T; Sirault, Xavier R R

    2018-01-01

    Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR ( r 2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association ( r 2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass ( r 2 = 0.93 and r 2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new

  14. Long-term effects of fuel treatments on aboveground biomass accumulation in ponderosa pine forests of the northern Rocky Mountains

    Science.gov (United States)

    Kate A. Clyatt; Christopher R. Keyes; Sharon M. Hood

    2017-01-01

    Fuel treatments in ponderosa pine forests of the northern Rocky Mountains are commonly used to modify fire behavior, but it is unclear how different fuel treatments impact the subsequent production and distribution of aboveground biomass, especially in the long term. This research evaluated aboveground biomass responses 23 years after treatment in two silvicultural...

  15. Structure, Aboveground Biomass, and Soil Characterization of Avicennia marina in Eastern Mangrove Lagoon National Park, Abu Dhabi

    Science.gov (United States)

    Alsumaiti, Tareefa Saad Sultan

    Mangrove forests are national treasures of the United Arab Emirates (UAE) and other arid countries with limited forested areas. Mangroves form a crucial part of the coastal ecosystem and provide numerous benefits to society, economy, and especially the environment. Mangrove trees, specifically Avicennia marina, are studied in their native habitat in order to characterize their population structure, aboveground biomass, and soil properties. This study focused on Eastern Mangrove Lagoon National Park in Abu Dhabi, which was the first mangrove protected area to be designated in UAE. In situ measurements were collected to estimate Avicennia marina status, mortality rate (%), height (m), crown spread (m), stem number, diameter at breast height (cm), basal area (m), and aboveground biomass (t ha-1 ). Small-footprint aerial light detection and ranging (LIDAR) data acquired by UAE were processed to characterize mangrove canopy height and aboveground biomass density. This included extraction of LIDAR-derived height percentile statistics, segmentation of the forest into structurally homogenous units, and development of regression relationships between in situ reference and remote sensing data using a machine learning approach. An in situ soil survey was conducted to examine the soils' physical and chemical properties, fertility status, and organic matter. The data of soil survey were used to create soil maps to evaluate key characteristics of soils, and their influence on Avicennia marina in Eastern Mangrove Lagoon National Park. The results of this study provide new insights into Avicennia marina canopy population, structure, aboveground biomass, and soil properties in Abu Dhabi, as data in such arid environments is lacking. This valuable information can help in managing and preserving this unique ecosystem.

  16. Decomposition of aboveground biomass of a herbaceous wetland stand

    OpenAIRE

    KLIMOVIČOVÁ, Lucie

    2010-01-01

    The master?s thesis is part of the project GA ČR č. P504/11/1151- Role of plants in the greenhouse gas budget of a sedge fen. This thesis deals with the decomposition of aboveground vegetation in a herbaceous wetland. The decomposition rate was established on the flooded part of the Wet Meadows near Třeboň. The rate of the decomposition processes was evaluated using the litter-bag method. Mesh bags filled with dry plant matter were located in the vicinity of the automatic meteorological stati...

  17. Biomassas de partes aéreas em plantas da caatinga Aboveground biomass of caatinga plants

    Directory of Open Access Journals (Sweden)

    Grécia Cavalcanti Silva

    2008-06-01

    Full Text Available As biomassas de partes aéreas de nove espécies da caatinga foram determinadas e relacionadas com as medidas das plantas, cortando-se 30 plantas de cada espécie e separando-as em caule, galhos, ramos e folhas. As espécies foram divididas em dois grupos: seis espécies com plantas grandes e três com plantas menores. Cada grupo foi separado em classes de diâmetro do caule (DAP. As alturas totais (HT dobraram (3,8 a 8,5 m da classe de menor para a de maior diâmetro (Biomass of aboveground parts of nine caatinga species were determined and related to plant measurements. Thirty plants of each species were collected and separated into stems, branches, twigs and leaves. The species were divided in two groups: six species of large plants and three species of smaller plants. Each group was divided into classes of stem diameter (DBH. Plant height (H doubled (3.8 to 8.5 m from the smallest-diameter class to the largest diameter ( 5 cm diameter, 20% of branches from 1 to 5 cm, 5% of twigs < 1 cm and 5% of leaves. DBH was the single variable that best predicted biomass of parts, in both species groups, according to a power equation (B = a DBH b. H and CPA were also significantly related to biomass for some parts and group, but with R² lower than DBH. Combining DBH and H improved estimation but not enough to justify the extra field effort in determining H. Therefore, plant part biomass can be estimated from measurements of stem diameter, in a non-destructive process.

  18. Changes in vegetation structure and aboveground biomass in ...

    African Journals Online (AJOL)

    Biomass of both trees and shrubs was significantly higher (p < 0.001) in grazing enclosures than in other treatments, whereas herbaceous vegetation biomass was higher, but not significantly, in prescribed fire managed rangeland units. Importantly, fire-managed areas also contained the highest densities of some of the ...

  19. Estimating biomass of individual pine trees using airborne lidar

    Energy Technology Data Exchange (ETDEWEB)

    Popescu, Sorin C. [Spatial Sciences Laboratory, Department of Ecosystem Science and Management, Texas A and M University, 1500 Research Parkway, Suite B 223, College Station, TX 77845 (United States)

    2007-09-15

    Airborne lidar (Light Detection And Ranging) is a proven technology that can be used to accurately assess aboveground forest biomass and bio-energy feedstocks. The overall goal of this study was to develop a method for assessing aboveground biomass and component biomass for individual trees using airborne lidar data in forest settings typical for loblolly pine stands (Pinus taeda L.) in the southeastern United States. More specific objectives included: (1) assessing the accuracy of estimating diameter at breast height (dbh) for individual pine trees using lidar-derived individual tree measurements, such as tree height and crown diameter, and (2) investigating the use of lidar-derived individual tree measurements with linear and nonlinear regression to estimate per tree aboveground biomass. In addition, the study presents a method for estimating the biomass of individual tree components, such as foliage, coarse roots, stem bark, and stem wood, as derived quantities from the aboveground biomass prediction. A lidar software application, TreeVaW, was used to extract forest inventory parameters at individual tree level from a lidar-derived canopy height model. Lidar-measured parameters at individual tree level, such as height and crown diameter, were used with regression models to estimate dbh, aboveground tree biomass, and tree-component biomass. Field measurements were collected for 45 loblolly pine trees over 0.1- and 0.01-acre plots. Linear regression models were able to explain 93% of the variability associated with individual tree biomass, 90% for dbh, and 79-80% for components biomass. (author)

  20. A novel protocol for assessment of aboveground biomass in rangeland environments

    NARCIS (Netherlands)

    Mundava, C.; Schut, A.G.T.; Helmholtz, P.; Stovold, R.G.H.; Donald, G.; Lamb, D.W.

    2015-01-01

    Current methods to measure aboveground biomass (AGB) do not deliver adequate results in relation to the extent and spatial variability that characterise rangelands. An optimised protocol for the assessment ofAGBis presented that enables calibration and validation of remote-sensing imagery or plant

  1. Light Use Efficiency of Aboveground Biomass Production of Norway Spruce Stands

    Czech Academy of Sciences Publication Activity Database

    Bellan, Michal; Marková, I.; Zaika, A.; Krejza, Jan

    2017-01-01

    Roč. 65, č. 1 (2017), s. 9-16 ISSN 1211-8516 R&D Projects: GA TA ČR TA02010945 Institutional support: RVO:67179843 Keywords : absorbed photosynthetically active radiation * aboveground biomass increment * allometric relation Subject RIV: GC - Agronomy OBOR OECD: Agronomy, plant breeding and plant protection

  2. Long-term above-ground biomass production in a red oak-pecan agroforestry system

    Science.gov (United States)

    Agroforestry systems have widely been recognized for their potential to foster long-term carbon sequestration in woody perennials. This study aims to determine the above-ground biomass in a 16-year-old red oak (Quercus rubra) - pecan (Carya illinoinensis) silvopastoral planting (141 and 53 trees ha-...

  3. Environmental and biotic controls over aboveground biomass throughout a tropical rainforest

    Science.gov (United States)

    G.P. Asner; R.F. Hughes; T.A. Varga; D.E. Knapp; T. Kennedy-Bowdoin

    2009-01-01

    The environmental and biotic factors affecting spatial variation in canopy three-dimensional (3-D) structure and aboveground tree biomass (AGB) are poorly understood in tropical rain forests. We combined field measurements and airborne light detection and ranging (lidar) to quantify 3-D structure and AGB across a 5,016 ha rain forest reserve on the...

  4. Relationship between aboveground biomass and multiple measures of biodiversity in subtropical forest of Puerto Rico

    Science.gov (United States)

    Heather D. Vance-Chalcraft; Michael R. Willig; Stephen B. Cox; Ariel E. Lugo; Frederick N. Scatena

    2010-01-01

    Anthropogenic activities have accelerated the rate of global loss of biodiversity, making it more important than ever to understand the structure of biodiversity hotspots. One current focus is the relationship between species richness and aboveground biomass (AGB) in a variety of ecosystems. Nonetheless, species diversity, evenness, rarity, or dominance represent other...

  5. Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data

    Science.gov (United States)

    Qi Chen; Dengsheng Lu; Michael Keller; Maiza dos-Santos; Edson Bolfe; Yunyun Feng; Changwei Wang

    2015-01-01

    Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems...

  6. Predicting aboveground forest biomass with topographic variables in human-impacted tropical dry forest landscapes

    NARCIS (Netherlands)

    Salinas-Melgoza, Miguel A.; Skutsch, Margaret; Lovett, Jon C.

    2018-01-01

    Topographic variables such as slope and elevation partially explain spatial variations in aboveground biomass (AGB) within landscapes. Human activities that impact vegetation, such as cattle grazing and shifting cultivation, often follow topographic features and also play a key role in determining

  7. Allometric models for aboveground biomass of ten tree species in northeast China

    Directory of Open Access Journals (Sweden)

    Shuo Cai

    2013-07-01

    Full Text Available China contains 119 million hectares of natural forest, much of which is secondary forest. An accurate estimation of the biomass of these forests is imperative because many studies conducted in northeast China have only used primary forest and this may have resulted in biased estimates. This study analyzed secondary forest in the area using information from a forest inventory to develop allometric models of the aboveground biomass (AGB. The parameter values of the diameter at breast height (DBH, tree height (H, and crown length (CL were derived from a forest inventory of 2,733 trees in a 3.5 ha plot. The wood-specific gravity (WSG was determined for 109 trees belonging to ten species. A partial sampling method was also used to determine the biomass of branches (including stem, bark and foliage in 120 trees, which substantially easy the field works. The mean AGB was 110,729 kg ha–1. We developed four allometric models from the investigation and evaluated the utility of other 19 published ones for AGB in the ten tree species. Incorporation of full range of variables with WSG-DBH-H-CL, significantly improved the precision of the models. Some of models were chosen that best fitted each tree species with high precision (R2 = 0.939, SEE 0.167. At the latitude level, the estimated AGBof secondary forest was lower than that in mature primary forests, but higher than that in primary broadleaf forest and the average level in other types of forest likewise. 

  8. Carbon Sequestration Potential in Aboveground Biomass of Hybrid Eucalyptus Plantation Forest

    Directory of Open Access Journals (Sweden)

    Siti Latifah

    2013-04-01

    Full Text Available Forests are a significant part of the global carbon cycle. Forests sequester carbon by conducting photosynthesis, which is the process of converting light energy to chemical energy and storing it in the chemical bonds of sugar. Carbon sequestration through forestry has the potential to play a significant role in ameliorating global environmental problems such as atmospheric accumulation of GHG's and climate change.  The present investigation was carried out to determine carbon sequestration potential of hybrid Eucalyptus. This study was conducted primarily to develop a prediction model of carbon storage capacity for plantation forest of hybrid Eucalyptus in Aek Nauli, Simalungun District, North Sumatera. Models were tested and assessed for statistical validity and accuracy in predicting biomass and carbon, based on determination coefficient (R and correlation coefficient (r, aggregative deviation percentage (AgD, and the average deviation percentage (AvD. The best general model to estimate the biomass of hybrid Eucalyptus was Y = 1351,09x^0,876. e^(0,094.  Results showed that hybrid Eucalyptus had an average above-ground biomass in year 0 (the land without the eucalyptus trees up to year 3 as large as 1.36, 11.56, 43.18, and 63.84 t ha. The carbon content of hybrid Eucalyptus were 0.61, 5.2, 19.43 t^(-1, and 28,73  t^(-1 C ha while the carbon sequestration potential were 2.23, 19.08, 71.31, and 105.43 t^(-1 CO  ha^(-1 respectively.Keywords: biomass, carbon stock, model, hybrid Eucalyptus, plantation forest

  9. Final Harvest of Above-Ground Biomass and Allometric Analysis of the Aspen FACE Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Mark E. Kubiske

    2013-04-15

    The Aspen FACE experiment, located at the US Forest Service Harshaw Research Facility in Oneida County, Wisconsin, exposes the intact canopies of model trembling aspen forests to increased concentrations of atmospheric CO2 and O3. The first full year of treatments was 1998 and final year of elevated CO2 and O3 treatments is scheduled for 2009. This proposal is to conduct an intensive, analytical harvest of the above-ground parts of 24 trees from each of the 12, 30 m diameter treatment plots (total of 288 trees) during June, July & August 2009. This above-ground harvest will be carefully coordinated with the below-ground harvest proposed by D.F. Karnosky et al. (2008 proposal to DOE). We propose to dissect harvested trees according to annual height growth increment and organ (main stem, branch orders, and leaves) for calculation of above-ground biomass production and allometric comparisons among aspen clones, species, and treatments. Additionally, we will collect fine root samples for DNA fingerprinting to quantify biomass production of individual aspen clones. This work will produce a thorough characterization of above-ground tree and stand growth and allocation above ground, and, in conjunction with the below ground harvest, total tree and stand biomass production, allocation, and allometry.

  10. Improving North American forest biomass estimates from literature synthesis and meta-analysis of existing biomass equations

    Science.gov (United States)

    David C. Chojnacky; Jennifer C. Jenkins; Amanda K. Holland

    2009-01-01

    Thousands of published equations purport to estimate biomass of individual trees. These equations are often based on very small samples, however, and can provide widely different estimates for trees of the same species. We addressed this issue in a previous study by devising 10 new equations that estimated total aboveground biomass for all species in North America (...

  11. Topographic variation in aboveground biomass in a subtropical evergreen broad-leaved forest in China.

    Directory of Open Access Journals (Sweden)

    Dunmei Lin

    Full Text Available The subtropical forest biome occupies about 25% of China, with species diversity only next to tropical forests. Despite the recognized importance of subtropical forest in regional carbon storage and cycling, uncertainties remain regarding the carbon storage of subtropical forests, and few studies have quantified within-site variation of biomass, making it difficult to evaluate the role of these forests in the global and regional carbon cycles. Using data for a 24-ha census plot in east China, we quantify aboveground biomass, characterize its spatial variation among different habitats, and analyse species relative contribution to the total aboveground biomass of different habitats. The average aboveground biomass was 223.0 Mg ha(-1 (bootstrapped 95% confidence intervals [217.6, 228.5] and varied substantially among four topographically defined habitats, from 180.6 Mg ha(-1 (bootstrapped 95% CI [167.1, 195.0] in the upper ridge to 245.9 Mg ha(-1 (bootstrapped 95% CI [238.3, 253.8] in the lower ridge, with upper and lower valley intermediate. In consistent with our expectation, individual species contributed differently to the total aboveground biomass of different habitats, reflecting significant species habitat associations. Different species show differently in habitat preference in terms of biomass contribution. These patterns may be the consequences of ecological strategies difference among different species. Results from this study enhance our ability to evaluate the role of subtropical forests in the regional carbon cycle and provide valuable information to guide the protection and management of subtropical broad-leaved forest for carbon sequestration and carbon storage.

  12. Reducing Uncertainty in Mapping of Mangrove Aboveground Biomass Using Airborne Discrete Return Lidar Data

    Directory of Open Access Journals (Sweden)

    Francisca Rocha de Souza Pereira

    2018-04-01

    Full Text Available Remote sensing techniques offer useful tools for estimating forest biomass to large extent, thereby contributing to the monitoring of land use and landcover dynamics and the effectiveness of environmental policies. The main goal of this study was to investigate the potential use of discrete return light detection and ranging (lidar data to produce accurate aboveground biomass (AGB maps of mangrove forests. AGB was estimated in 34 small plots scatted over a 50 km2 mangrove forest in Rio de Janeiro, Brazil. Plot AGB was computed using either species-specific or non-species-specific allometric models. A total of 26 descriptive lidar metrics were extracted from the normalized height of the lidar point cloud data, and various model forms (random forest and partial least squares regression with backward selection of predictors (Auto-PLS were tested to predict the recorded AGB. The models developed using species-specific allometric models were distinctly more accurate (R2(calibration = 0.89, R2(validation = 0.80, root-mean-square error (RMSE, calibration = 11.20 t·ha−1, and RMSE(validation = 14.80 t·ha−1. The use of non-species-specific allometric models yielded large errors on a landscape scale (+14% or −18% bias depending on the allometry considered, indicating that using poor quality training data not only results in low precision but inaccuracy at all scales. It was concluded that under suitable sampling pattern and provided that accurate field data are used, discrete return lidar can accurately estimate and map the AGB in mangrove forests. Conversely this study underlines the potential bias affecting the estimates of AGB in other forested landscapes where only non-species-specific allometric equations are available.

  13. Predicting the above-ground biomass of calabrian pine ( Pinus ...

    African Journals Online (AJOL)

    Karaisalý Regional Forestry Management Area. Thirty three sample plots, each of 0.04 ha, were chosen in order to define the biomass equations of calabrian pine, the most common needle leave species in Turkey. A tree which is the most similar ...

  14. LEAF AREA DYNAMICS AND ABOVEGROUND BIOMASS OF SPECIFIC VEGETATION TYPES OF A SEMI-ARID GRASSLAND IN SOUTHERN ETHIOPIA

    Directory of Open Access Journals (Sweden)

    Bosco Kidake Kisambo

    2016-12-01

    Full Text Available Leaf Area Index (LAI dynamics and aboveground biomass of a semi-arid grassland region in Southern Ethiopia were determined over a long rain season. The vegetation was categorized into four distinct vegetation types namely Grassland (G, Tree-Grassland (TG, Bushed-Grassland (BG and Bush-Tree grassland (BT. LAI was measured using a Plant Canopy Analyzer (LAI2000. Biomass dynamics of litter and herbaceous components were determined through clipping while the above ground biomass of trees and shrubs were estimated using species-specific allometric equations from literature. LAI showed a seasonal increase over the season with the maximum recorded in the BG vegetation (2.52. Total aboveground biomass for the different vegetation types ranged from 0.61 ton C/ha in areas where trees were non-existent to 8.80 ± 3.81ton C/ha in the Tree-Grassland vegetation in the study site. A correlation of LAI and AGB yielded a positive relationship with an R2 value of 0.55. The results demonstrate the importance of tropical semi-arid grasslands as carbon sinks hence their potential in mitigation of climate change.

  15. Above-ground biomass production and allometric relations of Eucalyptus globulus Labill. coppice plantations along a chronosequence in the central highlands of Ethiopia

    Energy Technology Data Exchange (ETDEWEB)

    Zewdie, Mulugeta; Olsson, Mats; Verwijst, Theo [Swedish University of Agricultural Sciences, Department of Crop Production Ecology, P.O. Box 7043, 75007 Uppsala (Sweden)

    2009-03-15

    Eucalyptus plantations are extensively managed for wood production in the central highlands of Ethiopia. Nevertheless, little is known about their biomass (dry matter) production, partitioning and dynamics over time. Data from 10 different Eucalyptus globulus stands, with a plantation age ranging from 11 to 60 years and with a coppice-shoot age ranging from 1 to 9 years were collected and analyzed. Above-ground tree biomass of 7-10 sampled trees per stand was determined destructively. Dry weights of tree components (W{sub c}; leaves, twigs, branches, stembark, and stemwood) and total above-ground biomass (W{sub a}) were estimated as a function of diameter above stump (D), tree height (H) and a combination of these. The best fits were obtained, using combinations of D and H. When only one explanatory variable was used, D performed better than H. Total above-ground biomass was linearly related to coppice-shoot age. In contrast a negative relation was observed between the above-ground biomass production and total plantation age (number of cutting cycles). Total above-ground biomass increased from 11 t ha{sup -1} at a stand age of 1 year to 153 t ha{sup -1} at 9 years. The highest dry weight was allocated to stemwood and decreased in the following order: stemwood > leaves > stembark > twigs > branches. The equations developed in this study to estimate biomass components can be applied to other Eucalyptus plantations under the assumption that the populations being studied are similar with regard to density and tree size to those for which the relationships were developed. (author)

  16. Above-ground biomass production and allometric relations of Eucalyptus globulus Labill. coppice plantations along a chronosequence in the central highlands of Ethiopia

    International Nuclear Information System (INIS)

    Zewdie, Mulugeta; Olsson, Mats; Verwijst, Theo

    2009-01-01

    Eucalyptus plantations are extensively managed for wood production in the central highlands of Ethiopia. Nevertheless, little is known about their biomass (dry matter) production, partitioning and dynamics over time. Data from 10 different Eucalyptus globulus stands, with a plantation age ranging from 11 to 60 years and with a coppice-shoot age ranging from 1 to 9 years were collected and analyzed. Above-ground tree biomass of 7-10 sampled trees per stand was determined destructively. Dry weights of tree components (W c ; leaves, twigs, branches, stembark, and stemwood) and total above-ground biomass (W a ) were estimated as a function of diameter above stump (D), tree height (H) and a combination of these. The best fits were obtained, using combinations of D and H. When only one explanatory variable was used, D performed better than H. Total above-ground biomass was linearly related to coppice-shoot age. In contrast a negative relation was observed between the above-ground biomass production and total plantation age (number of cutting cycles). Total above-ground biomass increased from 11 t ha -1 at a stand age of 1 year to 153 t ha -1 at 9 years. The highest dry weight was allocated to stemwood and decreased in the following order: stemwood > leaves > stembark > twigs > branches. The equations developed in this study to estimate biomass components can be applied to other Eucalyptus plantations under the assumption that the populations being studied are similar with regard to density and tree size to those for which the relationships were developed

  17. Aboveground and belowground biomass allocation in native Prosopis caldenia Burkart secondaries woodlands in the semi-arid Argentinean pampas

    International Nuclear Information System (INIS)

    Risio, Lucia; Herrero, Celia; Bogino, Stella M.; Bravo, Felipe

    2014-01-01

    The woodlands in the south-west of the Argentinean pampas are dominated by Prosopis Caldenia Burkart (calden). The current deforestation rate of this woodlands is 0.82% per year. Different compensation initiatives have begun that recognize the role of forests as environmental service providers. The financial incentives they offer make it necessary to quantify the amount of carbon stored in the forest biomass. A model for estimating calden biomass was developed. Thirty-eight trees were selected, felled and divided into sections. An equation system was fitted using joint generalized regression to ensure the additivity property. A weighted regression was used to avoid heteroscedasticity. In these woodlands fire is the main disturbance and it can modify tree allometry, due this all models included the area of the base of the stem and tree height as independent variables since it indirectly collects this variability. Total biomass and the stem fraction had the highest R2 A dj. values (0.75), while branches with a diameter less than 7 cm had the lowest (0.58). Tree biomass was also analyzed by partitioning into the basic fractions of stem, crown, roots, and the root/shoot ratio. Biomass allocation was greatest in the crown fraction and the mean root/shoot ratio was 0.58. The carbon stock of the caldenales considering only calden tree biomass is 20.2 Mg ha −1 . While the overall carbon balance of the region is negative (deforestation and biomass burning, the remnant forested area has increased their calden density and in an indirect way his carbon sequestration capacity could also be increased. - Highlights: • A model for estimating aboveground and belowground Prosopis caldenia biomass was developed. • Biomass allocation into the tree and the root/shoot ratio were analyzed. • The equation systems presented had made it possible to more accurately estimate the biomass stored in calden woodlands

  18. Spaceborne SAR Data for Aboveground-Biomass Retrieval of Indian Tropical Forests

    Science.gov (United States)

    Khati, U.; Singh, G.; Musthafa, M.

    2017-12-01

    Forests are important and indispensable part of the terrestrial ecosystems, and have a direct impact on the global carbon cycle. Forest biophysical parameters such as forest stand height and forest above-ground biomass (AGB) are forest health indicators. Measuring the forest biomass using traditional ground survey techniques are man-power consuming and have very low spatial coverage. Satellite based remote sensing techniques provide synoptic view of the earth with continuous measurements over large, inaccessible forest regions. Satellite Synthetic Aperture Radar (SAR) data has been shown to be sensitive to these forest bio-physical parameters and have been extensively utilized over boreal and tropical forests. However, there are limited studies over Indian tropical forests due to lack of auxiliary airborne data and difficulties in manual in situ data collection. In this research work we utilize spaceborne data from TerraSAR-X/TanDEM-X and ALOS-2/PALSAR-2 and implement both Polarimetric SAR and PolInSAR techniques for retrieval of AGB of a managed tropical forest in India. The TerraSAR-X/TanDEM-X provide a single-baseline PolInSAR data robust to temporal decorrelation. This would be used to accurately estimate the forest stand height. The retrieved height would be an input parameter for modelling AGB using the L-band ALOS-2/PALSAR-2 data. The IWCM model is extensively utilized to estimate AGB from SAR observations. In this research we utilize the six component scattering power decomposition (6SD) parameters and modify the IWCM based technique for a better retrieval of forest AGB. PolInSAR data shows a high estimation accuracy with r2 of 0.8 and a RMSE of 2 m. With this accurate height provided as input to the modified model along with 6SD parameters shows promising results. The results are validated with extensive field based measurements, and are further analysed in detail.

  19. Aboveground Biomass Monitoring over Siberian Boreal Forest Using Radar Remote Sensing Data

    Science.gov (United States)

    Stelmaszczuk-Gorska, M. A.; Thiel, C. J.; Schmullius, C.

    2014-12-01

    Aboveground biomass (AGB) plays an essential role in ecosystem research, global cycles, and is of vital importance in climate studies. AGB accumulated in the forests is of special monitoring interest as it contains the most of biomass comparing with other land biomes. The largest of the land biomes is boreal forest, which has a substantial carbon accumulation capability; carbon stock estimated to be 272 +/-23 Pg C (32%) [1]. Russian's forests are of particular concern, due to the largest source of uncertainty in global carbon stock calculations [1], and old inventory data that have not been updated in the last 25 years [2]. In this research new empirical models for AGB estimation are proposed. Using radar L-band data for AGB retrieval and optical data for an update of in situ data the processing scheme was developed. The approach was trained and validated in the Asian part of the boreal forest, in southern Russian Central Siberia; two Siberian Federal Districts: Krasnoyarsk Kray and Irkutsk Oblast. Together the training and testing forest territories cover an area of approximately 3,500 km2. ALOS PALSAR L-band single (HH - horizontal transmitted and received) and dual (HH and HV - horizontal transmitted, horizontal and vertical received) polarizations in Single Look Complex format (SLC) were used to calculate backscattering coefficient in gamma nought and coherence. In total more than 150 images acquired between 2006 and 2011 were available. The data were obtained through the ALOS Kyoto and Carbon Initiative Project (K&C). The data were used to calibrate a randomForest algorithm. Additionally, a simple linear and multiple-regression approach was used. The uncertainty of the AGB estimation at pixel and stand level were calculated approximately as 35% by validation against an independent dataset. The previous studies employing ALOS PALSAR data over boreal forests reported uncertainty of 39.4% using randomForest approach [2] or 42.8% using semi-empirical approach [3].

  20. Grassland Aboveground Biomass in Inner Mongolia: Dynamics (2001-2016) and Driving force

    Science.gov (United States)

    Li, F.; Zeng, Y.; Chen, J.; Wu, B.

    2017-12-01

    Plant biomass is the most critical measure of carbon stored in an ecosystem, yet it remains imprecisely modeled for many terrestrial biomes. This lack of modeling capacity for biomass and its change through time and space has impeded scientists from making headway concerning issues in the geographic and social sciences. Satellite remote sensing techniques excel at detecting changes in the Earth's surface; however, accurate estimates of biomass for the heterogeneous biome landscapes based on remote sensing techniques are few and far between, which has led to many repetitive studies. Here, we argued that our ability to assess biomass in a heterogeneous landscape using satellite remote sensing techniques would be effectively enhanced through a stratification of landscapes, i.e homogenizing landscapes. Specifically, above-ground biomass (AGB) for an extended heterogeneous grassland biome over the entirety of Inner Mongolia during the past 16 years (2001-2016) was explored using remote sensing time series data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Massive and extensive in-situ measurement AGB data and pure vegetation index (PVI) models, developed from normal remote sensing vegetation indices such as the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI), were highlighted in the accomplishment of this study. Taking into full consideration the landscape heterogeneity for the grassland biome over Inner Mongolia, we achieved a series of AGB models with high R2 (>0.85) and low RMSE ( 20.85 g/m2). The total average amount of fresh AGB for the entirety of Inner Mongolia grasslands over the past 16 years was estimated as 87 Tg with an inter-annual standard deviation of 9 Tg. Overall, the grassland AGB for Inner Mongolia increased sporadically. We found that the dynamics of AGB in the grassland biome of Inner Mongolia were substantially dominated by variation in precipitation despite the accommodation of a huge

  1. Challenges for Validating Large Scale Maps of Aboveground Biomass of Humid Tropical Forests

    Science.gov (United States)

    Saatchi, S. S.; Xu, L.; Yu, Y.

    2017-12-01

    Post-2020 will witness a series of new observations from NASA and ESA spaceborne missions dedicated to measurements of aboveground forest structure and biomass (AGB). These measurements are designed to significantly reduce the uncertainty in terrestrial carbon cycle by providing globally consistent estimates of forest aboveground carbon stocks and dynamics from land use and climate related changes. The products of these missions are maps of AGB at spatial resolutions ranging from 1-ha to 100 ha derived from dense spatial sampling in the case of NASA's Global Ecosystem Dynamics Investigation (GEDI), or wall-to-wall coverage in the case of NASA and ISRO SAR (NISAR), and ESA's BIOMASS (launch in 2020-21) missions. Validation of these maps over tropical forests requires ground observations that allow assessments of spatial uncertainty at the pixel level and verification of systematic errors in regional spatial patterns and carbon estimates. Current ground plots are either based on adhoc sampling of forests at landscapes, or if from systematic sampling have large uncertainty associated with ground measurements, sample size, and allometric models. Satellite observations, on the other hand, provide either significantly larger sample size or the entire population, have consistent and systematic measurements of the forest structural attributes, and may inform variations of forest allometry across regions. Therefore, not only ground observations of AGB may not be suitable for validation of satellite products, but satellite products may be superior in measurement accuracy (in the case of forest structure), sampling, and consistency across regions. Here, we address challenges associated with the validation of satellite AGB products over tropical forests and provide examples of how ground and airborne data may be integrated to verify the satellite derived products at local scales. We also discuss the strong possibility that satellite observations of spatial patterns and

  2. Topographically mediated controls on aboveground biomass across a mediterranean-type landscape

    Science.gov (United States)

    Dahlin, K.; Asner, G. P.; Field, C. B.

    2009-12-01

    Aboveground biomass accumulation is a useful metric for evaluating habitat restoration and ecosystem services projects, in addition to being a robust measure of carbon sequestration. However, at the landscape scale non-anthropogenic controls on biomass accumulation are poorly understood. In this study we combined field measurements, high resolution data from the NASA JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the Carnegie Airborne Observatory (CAO) airborne light detection and ranging (lidar) system to create a comprehensive map of aboveground biomass across a patchy mediterranean-type landscape (Jasper Ridge Biological Preserve, Stanford, CA). Candidate explanatory variables (e.g. slope, elevation, incident solar radiation) were developed using a geologic map and a digital elevation model derived from the lidar data. Finally, candidate variables were tested, and a model was produced to predict aboveground biomass from environmental data. Though many of the explanatory variables have only indirect effects on plant growth, the model permits inferences to be made about the relative importance of light, water, temperature, and edaphic characteristics on carbon accumulation in mediterranean-type systems.

  3. Methods for biomass stock estimation in Mediterranean maquis systems

    OpenAIRE

    Sirca C; Caddeo A; Spano D; Bacciu V; Marras S

    2016-01-01

    As a result of Kyoto Protocol agreements, the scientific community increased its efforts to enhance the availability of biomass and organic carbon stock data in forest ecosystems. Nevertheless, a considerable data shortage has been recognized in estimating the stock of above-ground biomass (AGB) in Mediterranean maquis systems. This work aims at contributing in addressing such shortage by testing quick and non-disruptive methods to estimate the AGB stock in maquis species. Two methodologies w...

  4. Impacts of Tree Height-Dbh Allometry on Lidar-Based Tree Aboveground Biomass Modeling

    Science.gov (United States)

    Fang, R.

    2016-06-01

    Lidar has been widely used in tree aboveground biomass (AGB) estimation at plot or stand levels. Lidar-based AGB models are usually constructed with the ground AGB reference as the response variable and lidar canopy indices as predictor variables. Tree diameter at breast height (dbh) is the major variable of most allometric models for estimating reference AGB. However, lidar measurements are mainly related to tree vertical structure. Therefore, tree height-dbh allometric model residuals are expected to have a large impact on lidar-based AGB model performance. This study attempts to investigate sensitivity of lidar-based AGB model to the decreasing strength of height-dbh relationship using a Monte Carlo simulation approach. Striking decrease in R2 and increase in relative RMSE were found in lidar-based AGB model, as the variance of height-dbh model residuals grew. I, therefore, concluded that individual tree height-dbh model residuals fundamentally introduce errors to lidar-AGB models.

  5. QUANTIFYING FOREST ABOVEGROUND CARBON POOLS AND FLUXES USING MULTI-TEMPORAL LIDAR A report on field monitoring, remote sensing MMV, GIS integration, and modeling results for forestry field validation test to quantify aboveground tree biomass and carbon

    Energy Technology Data Exchange (ETDEWEB)

    Lee Spangler; Lee A. Vierling; Eva K. Stand; Andrew T. Hudak; Jan U.H. Eitel; Sebastian Martinuzzi

    2012-04-01

    Sound policy recommendations relating to the role of forest management in mitigating atmospheric carbon dioxide (CO{sub 2}) depend upon establishing accurate methodologies for quantifying forest carbon pools for large tracts of land that can be dynamically updated over time. Light Detection and Ranging (LiDAR) remote sensing is a promising technology for achieving accurate estimates of aboveground biomass and thereby carbon pools; however, not much is known about the accuracy of estimating biomass change and carbon flux from repeat LiDAR acquisitions containing different data sampling characteristics. In this study, discrete return airborne LiDAR data was collected in 2003 and 2009 across {approx}20,000 hectares (ha) of an actively managed, mixed conifer forest landscape in northern Idaho, USA. Forest inventory plots, established via a random stratified sampling design, were established and sampled in 2003 and 2009. The Random Forest machine learning algorithm was used to establish statistical relationships between inventory data and forest structural metrics derived from the LiDAR acquisitions. Aboveground biomass maps were created for the study area based on statistical relationships developed at the plot level. Over this 6-year period, we found that the mean increase in biomass due to forest growth across the non-harvested portions of the study area was 4.8 metric ton/hectare (Mg/ha). In these non-harvested areas, we found a significant difference in biomass increase among forest successional stages, with a higher biomass increase in mature and old forest compared to stand initiation and young forest. Approximately 20% of the landscape had been disturbed by harvest activities during the six-year time period, representing a biomass loss of >70 Mg/ha in these areas. During the study period, these harvest activities outweighed growth at the landscape scale, resulting in an overall loss in aboveground carbon at this site. The 30-fold increase in sampling density

  6. High-Resolution Mapping of Aboveground Biomass for Forest Carbon Monitoring - A Case Study in Three Mid-Atlantic States, USA

    Science.gov (United States)

    Huang, W.; Dolan, K. A.; Johnson, K. D.; ONeil-Dunne, J.; Dubayah, R.; Hurtt, G. C.

    2016-12-01

    Accurate mapping of forest aboveground biomass is critical for reducing uncertainties in carbon monitoring and accounting systems. As part of NASA's Carbon Monitoring System program, we have developed a robust, replicable and scalable framework that quantifies forest structure and aboveground biomass over large areas at high resolution. Discrete return LiDAR data were collected over 150,000 square km area in three Mid-Atlantic States (Maryland, Delaware and Pennsylvania). A set of 30-m LiDAR metrics derived from LiDAR point clouds were extracted as co-variables for mapping forest aboveground biomass density. Machine learning Random Forest models for four Eco-Regions (i.e., Eastern Broadleaf, Northeastern Mixed, Outer Coastal Plain, and Central Appalachian) were calibrated by linking LiDAR metrics to estimates of biomass from FIA plot measurements that most closely matched the year of LiDAR acquisition. Independent field plot measurements over four eco-regions were used for validation, and spatial errors were estimated at the pixel level using Quantile Random Forests. Additionally, we conducted detailed map comparisons to national products at pixel-, county-, and state-level. Results show that the proposed framework can produce accurate estimates of biomass at fine spatial resolution. High-resolution LiDAR-derived biomass maps such as these, provide a valuable bottom-up reference to improve the analysis and interpretation of large-scale mapping efforts, and future development of a national carbon monitoring system.

  7. [Aboveground biomass of Tamarix on piedmont plain of Tianshan Mountains south slope].

    Science.gov (United States)

    Zhao, Zhenyong; Wang, Ranghui; Zhang, Huizhi; Wang, Lei

    2006-09-01

    Based on the geo-morphological and hydro-geological characteristics, the piedmont plain of Tianshan Mountains south slope was classified into 4 geo-morphological belts, i.e., flood erosion belt, groundwater spill belt, delta belt, and the joining belt of piedmont plain and Tarim floodplain. A field investigation on the Tamarix shrub in this region showed that there was a significant difference in its aboveground biomass among the four belts, ranged from 1428.53 kg x hm(-2) at groundwater spill belt to 111.18 kg x hm(-2) at the joining belt of piedmont plain and Tarim floodplain. The main reason for such a big difference might be the different density of Tamarix shrub on different belts. Both the Tamarix aboveground biomass and the topsoil's salinity were decreased with increasing groundwater level. Groundwater level was the main factor limiting Tamarix growth, while soil salinity was not.

  8. Carbon stock in forest aboveground biomass –comparison based on Landsat data

    Czech Academy of Sciences Publication Activity Database

    Pechanec, V.; Stržínek, F.; Purkyt, Jan; Štěrbová, Lenka; Cudlín, Pavel

    2017-01-01

    Roč. 63, 2-3 (2017), s. 126-132 ISSN 2454-0358 R&D Projects: GA MŠk(CZ) LO1415 Grant - others:EHP,MF ČR(CZ) EHP-CZ02-OV-1-014-2014 Program:CZ02 Institutional support: RVO:67179843 Keywords : aboveground biomass * carbon stock * remote sensing data * vegetation indices * Czech Republic Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7)

  9. Above-ground biomass and structure of 260 African tropical forests

    Science.gov (United States)

    Lewis, Simon L.; Sonké, Bonaventure; Sunderland, Terry; Begne, Serge K.; Lopez-Gonzalez, Gabriela; van der Heijden, Geertje M. F.; Phillips, Oliver L.; Affum-Baffoe, Kofi; Baker, Timothy R.; Banin, Lindsay; Bastin, Jean-François; Beeckman, Hans; Boeckx, Pascal; Bogaert, Jan; De Cannière, Charles; Chezeaux, Eric; Clark, Connie J.; Collins, Murray; Djagbletey, Gloria; Djuikouo, Marie Noël K.; Droissart, Vincent; Doucet, Jean-Louis; Ewango, Cornielle E. N.; Fauset, Sophie; Feldpausch, Ted R.; Foli, Ernest G.; Gillet, Jean-François; Hamilton, Alan C.; Harris, David J.; Hart, Terese B.; de Haulleville, Thales; Hladik, Annette; Hufkens, Koen; Huygens, Dries; Jeanmart, Philippe; Jeffery, Kathryn J.; Kearsley, Elizabeth; Leal, Miguel E.; Lloyd, Jon; Lovett, Jon C.; Makana, Jean-Remy; Malhi, Yadvinder; Marshall, Andrew R.; Ojo, Lucas; Peh, Kelvin S.-H.; Pickavance, Georgia; Poulsen, John R.; Reitsma, Jan M.; Sheil, Douglas; Simo, Murielle; Steppe, Kathy; Taedoumg, Hermann E.; Talbot, Joey; Taplin, James R. D.; Taylor, David; Thomas, Sean C.; Toirambe, Benjamin; Verbeeck, Hans; Vleminckx, Jason; White, Lee J. T.; Willcock, Simon; Woell, Hannsjorg; Zemagho, Lise

    2013-01-01

    We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha−1 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha−1) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426 ± 11 stems ha−1 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C : N ratio (suggesting a positive soil phosphorus–AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes. PMID:23878327

  10. LiDAR-based Biomass Estimates, Boreal Forest Biome, Eurasia, 2005-2006

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides estimates of aboveground biomass (AGB) for defined land cover types within World Wildlife Fund (WWF) ecoregions across the boreal biome of...

  11. NACP LiDAR-based Biomass Estimates, Boreal Forest Biome, North America, 2005-2006

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides estimates of aboveground biomass (AGB) for defined land cover types within World Wildlife Fund (WWF) ecoregions across the boreal biome of...

  12. CMS: Estimated Deforested Area Biomass, Tropical America, Africa, and Asia, 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides estimates of pre-deforestation aboveground live woody biomass (AGLB) at 30-m resolution for deforested areas of tropical America, tropical...

  13. LBA-ECO LC-08 Ecosystem Demography Model Estimated C, NPP, and Biomass For Amazonia

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides Ecosystem Demography Model (ED) estimates of potential above-ground net primary production (NPP) (kg C/m2/y), potential average live biomass...

  14. Functional dominance rather than taxonomic diversity and functional diversity mainly affects community aboveground biomass in the Inner Mongolia grassland.

    Science.gov (United States)

    Zhang, Qing; Buyantuev, Alexander; Li, Frank Yonghong; Jiang, Lin; Niu, Jianming; Ding, Yong; Kang, Sarula; Ma, Wenjing

    2017-03-01

    The relationship between biodiversity and productivity has been a hot topic in ecology. However, the relative importance of taxonomic diversity and functional characteristics (including functional dominance and functional diversity) in maintaining community productivity and the underlying mechanisms (including selection and complementarity effects) of the relationship between diversity and community productivity have been widely controversial. In this study, 194 sites were surveyed in five grassland types along a precipitation gradient in the Inner Mongolia grassland of China. The relationships between taxonomic diversity (species richness and the Shannon-Weaver index), functional dominance (the community-weighted mean of four plant traits), functional diversity (Rao's quadratic entropy), and community aboveground biomass were analyzed. The results showed that (1) taxonomic diversity, functional dominance, functional diversity, and community aboveground biomass all increased from low to high precipitation grassland types; (2) there were significant positive linear relationships between taxonomic diversity, functional dominance, functional diversity, and community aboveground biomass; (3) the effect of functional characteristics on community aboveground biomass is greater than that of taxonomic diversity; and (4) community aboveground biomass depends on the community-weighted mean plant height, which explained 57.1% of the variation in the community aboveground biomass. Our results suggested that functional dominance rather than taxonomic diversity and functional diversity mainly determines community productivity and that the selection effect plays a dominant role in maintaining the relationship between biodiversity and community productivity in the Inner Mongolia grassland.

  15. Landscape-level effects on aboveground biomass of tropical forests: A conceptual framework.

    Science.gov (United States)

    Melito, Melina; Metzger, Jean Paul; de Oliveira, Alexandre A

    2018-02-01

    Despite the general recognition that fragmentation can reduce forest biomass through edge effects, a systematic review of the literature does not reveal a clear role of edges in modulating biomass loss. Additionally, the edge effects appear to be constrained by matrix type, suggesting that landscape composition has an influence on biomass stocks. The lack of empirical evidence of pervasive edge-related biomass losses across tropical forests highlights the necessity for a general framework linking landscape structure with aboveground biomass. Here, we propose a conceptual model in which landscape composition and configuration mediate the magnitude of edge effects and seed-flux among forest patches, which ultimately has an influence on biomass. Our model hypothesizes that a rapid reduction of biomass can occur below a threshold of forest cover loss. Just below this threshold, we predict that changes in landscape configuration can strongly influence the patch's isolation, thus enhancing biomass loss. Moreover, we expect a synergism between landscape composition and patch attributes, where matrix type mediates the effects of edges on species decline, particularly for shade-tolerant species. To test our conceptual framework, we propose a sampling protocol where the effects of edges, forest amount, forest isolation, fragment size, and matrix type on biomass stocks can be assessed both collectively and individually. The proposed model unifies the combined effects of landscape and patch structure on biomass into a single framework, providing a new set of main drivers of biomass loss in human-modified landscapes. We argue that carbon trading agendas (e.g., REDD+) and carbon-conservation initiatives must go beyond the effects of forest loss and edges on biomass, considering the whole set of effects on biomass related to changes in landscape composition and configuration. © 2017 John Wiley & Sons Ltd.

  16. Changes in composition, structure and aboveground biomass over seventy-six years (1930-2006) in the Black Rock Forest, Hudson Highlands, southeastern New York state

    Energy Technology Data Exchange (ETDEWEB)

    Schuster, W.S.F. [Black Rock Forest Consortium, Cornwall, NY (United States); Griffin, K.L. [Colombia Univ., Palisades, NY (United States). Lamont-Doherty Earth Observatory; Roth, H. [Barnard College, New York, NY (United States). Dept. of Environmental Science; Turnbull, M.H. [Canterbury Univ., Christchurch (New Zealand). School of Biological Sciences; Whitehead, D. [Landcare Research, Lincoln (New Zealand); Tissue, D.T. [Texas Tech Univ., Lubbock, TX (United States). Dept. of Biology

    2008-04-15

    This study measured changes in tree species composition and structures over a period of 76 years in the Black Rock Forest in southeastern New York. The study used data from periodic forest inventories and long-term plots as well as species-specific allometric equations to estimate aboveground forest biomass (AGB) and carbon content. Sixteen long-term plots were monitored at various forest elevations. Density, basal area, and aboveground biomass were calculated. Allometric regression equations were used to estimate live aboveground tree biomass. Results of the review showed that paper birch, black spruce, and American elm species were extirpated from the forest between the early 1930s and the year 2000. Species that invaded the forest included white poplar, red mulberry, eastern cottonwood, and slippery elm. Red oak and chestnut oaks dominated the forest canopy. The forest understory changed over the period from mixed oak to red maple and black birch. Red oak canopy trees stored carbon at twice the rate of similar-sized canopy trees in the forest. A significant loss of live tree biomass was attributed to canopy tree mortality since 1999. It was concluded that insect outbreaks and droughts are important constraints on long-term biomass growth. 87 refs., 2 tabs., 5 figs.

  17. Long-term patterns in tropical reforestation: plant community composition and aboveground biomass accumulation.

    Science.gov (United States)

    Marín-Spiotta, E; Ostertag, R; Silver, W L

    2007-04-01

    Primary tropical forests are renowned for their high biodiversity and carbon storage, and considerable research has documented both species and carbon losses with deforestation and agricultural land uses. Economic drivers are now leading to the abandonment of agricultural lands, and the area in secondary forests is increasing. We know little about how long it takes for these ecosystems to achieve the structural and compositional characteristics of primary forests. In this study, we examine changes in plant species composition and aboveground biomass during eight decades of tropical secondary succession in Puerto Rico, and compare these patterns with primary forests. Using a well-replicated chronosequence approach, we sampled primary forests and secondary forests established 10, 20, 30, 60, and 80 years ago on abandoned pastures. Tree species composition in all secondary forests was different from that of primary forests and could be divided into early (10-, 20-, and 30-year) vs. late (60- and 80-year) successional phases. The highest rates of aboveground biomass accumulation occurred in the first 20 years, with rates of C sequestration peaking at 6.7 +/- 0.5 Mg C x ha(-1) x yr(-1). Reforestation of pastures resulted in an accumulation of 125 Mg C/ha in aboveground standing live biomass over 80 years. The 80 year-old secondary forests had greater biomass than the primary forests, due to the replacement of woody species by palms in the primary forests. Our results show that these new ecosystems have different species composition, but similar species richness, and significant potential for carbon sequestration, compared to remnant primary forests.

  18. Plant diversity and functional groups affect Si and Ca pools in aboveground biomass of grassland systems.

    Science.gov (United States)

    Schaller, Jörg; Roscher, Christiane; Hillebrand, Helmut; Weigelt, Alexandra; Oelmann, Yvonne; Wilcke, Wolfgang; Ebeling, Anne; Weisser, Wolfgang W

    2016-09-01

    Plant diversity is an important driver of nitrogen and phosphorus stocks in aboveground plant biomass of grassland ecosystems, but plant diversity effects on other elements also important for plant growth are less understood. We tested whether plant species richness, functional group richness or the presence/absence of particular plant functional groups influences the Si and Ca concentrations (mmol g(-1)) and stocks (mmol m(-2)) in aboveground plant biomass in a large grassland biodiversity experiment (Jena Experiment). In the experiment including 60 temperate grassland species, plant diversity was manipulated as sown species richness (1, 2, 4, 8, 16) and richness and identity of plant functional groups (1-4; grasses, small herbs, tall herbs, legumes). We found positive species richness effects on Si as well as Ca stocks that were attributable to increased biomass production. The presence of particular functional groups was the most important factor explaining variation in aboveground Si and Ca stocks (mmol m(-2)). Grass presence increased the Si stocks by 140 % and legume presence increased the Ca stock by 230 %. Both the presence of specific plant functional groups and species diversity altered Si and Ca stocks, whereas Si and Ca concentration were affected mostly by the presence of specific plant functional groups. However, we found a negative effect of species diversity on Si and Ca accumulation, by calculating the deviation between mixtures and mixture biomass proportions, but in monoculture concentrations. These changes may in turn affect ecosystem processes such as plant litter decomposition and nutrient cycling in grasslands.

  19. Assessment of forest management influences on total live aboveground tree biomass in William B Bankhead National Forest, Alabama

    Science.gov (United States)

    Callie Schweitzer; Dawn Lemke; Wubishet Tadesse; Yong Wang

    2015-01-01

    Forests contain a large amount of carbon (C) stored as tree biomass (above and below ground), detritus, and soil organic material. The aboveground tree biomass is the most rapid change component in this forest C pool. Thus, management of forest resources can influence the net C exchange with the atmosphere by changing the amount of C stored, particularly in landscapes...

  20. Aboveground Biomass Modeling from Field and LiDAR Data in Brazilian Amazon Tropical Rain Forest

    Science.gov (United States)

    Silva, C. A.; Hudak, A. T.; Vierling, L. A.; Keller, M. M.; Klauberg Silva, C. K.

    2015-12-01

    Tropical forests are an important component of global carbon stocks, but tropical forest responses to climate change are not sufficiently studied or understood. Among remote sensing technologies, airborne LiDAR (Light Detection and Ranging) may be best suited for quantifying tropical forest carbon stocks. Our objective was to estimate aboveground biomass (AGB) using airborne LiDAR and field plot data in Brazilian tropical rain forest. Forest attributes such as tree density, diameter at breast height, and heights were measured at a combination of square plots and linear transects (n=82) distributed across six different geographic zones in the Amazon. Using previously published allometric equations, tree AGB was computed and then summed to calculate total AGB at each sample plot. LiDAR-derived canopy structure metrics were also computed at each sample plot, and random forest regression modelling was applied to predict AGB from selected LiDAR metrics. The LiDAR-derived AGB model was assessed using the random forest explained variation, adjusted coefficient of determination (Adj. R²), root mean square error (RMSE, both absolute and relative) and BIAS (both absolute and relative). Our findings showed that the 99th percentile of height and height skewness were the best LiDAR metrics for AGB prediction. The AGB model using these two best predictors explained 59.59% of AGB variation, with an Adj. R² of 0.92, RMSE of 33.37 Mg/ha (20.28%), and bias of -0.69 (-0.42%). This study showed that LiDAR canopy structure metrics can be used to predict AGC stocks in Tropical Forest with acceptable precision and accuracy. Therefore, we conclude that there is good potential to monitor carbon sequestration in Brazilian Tropical Rain Forest using airborne LiDAR data, large field plots, and the random forest algorithm.

  1. Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines

    OpenAIRE

    Singh, Minerva; Friess, Daniel A.; Vilela, Bruno; Alban, Jose Don T. De; Monzon, Angelica Kristina V.; Veridiano, Rizza Karen A.; Tumaneng, Roven D.

    2017-01-01

    This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to iden...

  2. Annual Removal of Aboveground Plant Biomass Alters Soil Microbial Responses to Warming

    Directory of Open Access Journals (Sweden)

    Kai Xue

    2016-09-01

    Full Text Available Clipping (i.e., harvesting aboveground plant biomass is common in agriculture and for bioenergy production. However, microbial responses to clipping in the context of climate warming are poorly understood. We investigated the interactive effects of grassland warming and clipping on soil properties and plant and microbial communities, in particular, on microbial functional genes. Clipping alone did not change the plant biomass production, but warming and clipping combined increased the C4 peak biomass by 47% and belowground net primary production by 110%. Clipping alone and in combination with warming decreased the soil carbon input from litter by 81% and 75%, respectively. With less carbon input, the abundances of genes involved in degrading relatively recalcitrant carbon increased by 38% to 137% in response to either clipping or the combined treatment, which could weaken long-term soil carbon stability and trigger positive feedback with respect to warming. Clipping alone also increased the abundance of genes for nitrogen fixation, mineralization, and denitrification by 32% to 39%. Such potentially stimulated nitrogen fixation could help compensate for the 20% decline in soil ammonium levels caused by clipping alone and could contribute to unchanged plant biomass levels. Moreover, clipping tended to interact antagonistically with warming, especially with respect to effects on nitrogen cycling genes, demonstrating that single-factor studies cannot predict multifactorial changes. These results revealed that clipping alone or in combination with warming altered soil and plant properties as well as the abundance and structure of soil microbial functional genes. Aboveground biomass removal for biofuel production needs to be reconsidered, as the long-term soil carbon stability may be weakened.

  3. Human and natural controls of the variation in aboveground tree biomass in African dry tropical forests.

    Science.gov (United States)

    Pelletier, Johanne; Siampale, Abel; Legendre, Pierre; Jantz, Patrick; Laporte, Nadine T; Goetz, Scott J

    2017-07-01

    Understanding the anthropogenic and natural controls that affect the patterns, distribution, and dynamics of terrestrial carbon is crucial to meeting climate change mitigation objectives. We assessed the human and natural controls over aboveground tree biomass density in African dry tropical forests, using Zambia's first nationwide forest inventory. We identified predictors that best explain the variation in biomass density, contrasted anthropogenic and natural sites at different spatial scales, and compared sites with different stand structure characteristics and species composition. In addition, we evaluated the effects of different management and conservation practices on biomass density. Variation in biomass density was mostly determined by biotic processes, linked with both species richness and dominance (evenness), and to a lesser extent, by land use, environmental controls, and spatial structure. Biomass density was negatively associated with tree species evenness and positively associated with species richness for both natural and human-modified sites. Human influence variables (including distance to roads, distance to town, fire occurrence, and the population on site) did not explain substantial variation in biomass density in comparison to biodiversity variables. The relationship of human activities to biomass density in managed sites appears to be mediated by effects on species diversity and stand structure characteristics, with lower values in human-modified sites for all metrics tested. Small contrasts in carbon density between human-modified and natural forest sites signal the potential to maintain carbon in the landscape inside but also outside forestlands in this region. Biodiversity is positively related to biomass density in both human and natural sites, demonstrating potential synergies between biodiversity conservation and climate change mitigation. This is the first evidence of positive outcomes of protected areas and participatory forest

  4. Impact of deforestation and climate on the Amazon Basin's above-ground biomass during 1993-2012.

    Science.gov (United States)

    Exbrayat, Jean-François; Liu, Yi Y; Williams, Mathew

    2017-11-15

    Since the 1960s, large-scale deforestation in the Amazon Basin has contributed to rising global CO 2 concentrations and to climate change. Recent advances in satellite observations enable estimates of gross losses of above-ground biomass (AGB) stocks due to deforestation. However, because of simultaneous regrowth, the net contribution of deforestation emissions to rising atmospheric CO 2 concentrations is poorly quantified. Climate change may also reduce the potential for forest regeneration in previously disturbed regions. Here, we address these points of uncertainty with a machine-learning approach that combines satellite observations of AGB with climate data across the Amazon Basin to reconstruct annual maps of potential AGB during 1993-2012, the above-ground C storage potential of the undisturbed landscape. We derive a 2.2 Pg C loss of AGB over the study period, and, for the regions where these losses occur, we estimate a 0.7 Pg C reduction in potential AGB. Thus, climate change has led to a decline of ~1/3 in the capacity of these disturbed forests to recover and recapture the C lost in disturbances during 1993-2012. Our approach further shows that annual variations in land use change mask the natural relationship between the El Niño/Southern Oscillation and AGB stocks in disturbed regions.

  5. Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data

    Directory of Open Access Journals (Sweden)

    Tianyu Hu

    2016-07-01

    Full Text Available As a large carbon pool, global forest ecosystems are a critical component of the global carbon cycle. Accurate estimations of global forest aboveground biomass (AGB can improve the understanding of global carbon dynamics and help to quantify anthropogenic carbon emissions. Light detection and ranging (LiDAR techniques have been proven that can accurately capture both horizontal and vertical forest structures and increase the accuracy of forest AGB estimation. In this study, we mapped the global forest AGB density at a 1-km resolution through the integration of ground inventory data, optical imagery, Geoscience Laser Altimeter System/Ice, Cloud, and Land Elevation Satellite data, climate surfaces, and topographic data. Over 4000 ground inventory records were collected from published literatures to train the forest AGB estimation model and validate the resulting global forest AGB product. Our wall-to-wall global forest AGB map showed that the global forest AGB density was 210.09 Mg/ha on average, with a standard deviation of 109.31 Mg/ha. At the continental level, Africa (333.34 ± 63.80 Mg/ha and South America (301.68 ± 67.43 Mg/ha had higher AGB density. The AGB density in Asia, North America and Europe were 172.28 ± 94.75, 166.48 ± 84.97, and 132.97 ± 50.70 Mg/ha, respectively. The wall-to-wall forest AGB map was evaluated at plot level using independent plot measurements. The adjusted coefficient of determination (R2 and root-mean-square error (RMSE between our predicted results and the validation plots were 0.56 and 87.53 Mg/ha, respectively. At the ecological zone level, the R2 and RMSE between our map and Intergovernmental Panel on Climate Change suggested values were 0.56 and 101.21 Mg/ha, respectively. Moreover, a comprehensive comparison was also conducted between our forest AGB map and other published regional AGB products. Overall, our forest AGB map showed good agreements with these regional AGB products, but some of the regional

  6. Biomass Estimation of Dry Tropical Woody Species at Juvenile Stage

    Directory of Open Access Journals (Sweden)

    R. K. Chaturvedi

    2012-01-01

    Full Text Available Accurate characterization of biomass in different forest components is important to estimate their contribution to total carbon stock. Due to lack of allometric equations for biomass estimation of woody species at juvenile stage, the carbon stored in this forest component is ignored. We harvested 47 woody species at juvenile stage in a dry tropical forest and developed regression models for the estimation of above-ground biomass (AGB. The models including wood-specific gravity ( exhibited higher 2 than those without . The model consisting of , stem diameter (, and height ( not only exhibited the highest 2 value but also had the lowest standard error of estimate. We suggest that -based regression model is a viable option for nondestructive estimation of biomass of forest trees at juvenile stage.

  7. [Vegetation above-ground biomass and its affecting factors in water/wind erosion crisscross region on Loess Plateau].

    Science.gov (United States)

    Wang, Jian-guo; Fan, Jun; Wang, Quan-jiu; Wang, Li

    2011-03-01

    Field investigations were conducted in Liudaogou small watershed in late September 2009 to study the differences of vegetation above-ground biomass, soil moisture content, and soil nutrient contents under different land use patterns, aimed to approach the vegetation above-ground biomass level and related affecting factors in typical small watershed in water/wind erosion crisscross region on Loess Plateau. The above-ground dry biomass of the main vegetations in Liudaogou was 177-2207 g x m(-2), and that in corn field, millet field, abandoned farmland, artificial grassland, natural grassland, and shrub land was 2097-2207, 518-775, 248-578, 280-545, 177-396, and 372-680 g x m(-2), respectively. The mean soil moisture content in 0-100 layer was the highest (14.2%) in farmlands and the lowest (10.9%) in shrub land. The coefficient of variation of soil moisture content was the greatest (26. 7% ) in abandoned farmland, indicating the strong spatial heterogeneity of soil moisture in this kind of farmland. The mean soil water storage was in the order of farmland > artificial grassland > natural grassland > shrub land. Soil dry layer was observed in alfalfa and caragana lands. There was a significant positive correlation (r = 0.639, P water storage, and also, a very significant positive correlation between above-ground fresh biomass and vegetation height. The above-ground biomass of the higher vegetations could potentially better control the wind and water erosion in the water/wind erosion crisscross region. Vegetation above-ground biomass was highly correlated with soil moisture and nutrient contents, but had no significant correlations with elevation, slope gradient, slope aspect, and soil bulk density.

  8. Estimating Swedish biomass energy supply

    International Nuclear Information System (INIS)

    Johansson, J.; Lundqvist, U.

    1999-01-01

    Biomass is suggested to supply an increasing amount of energy in Sweden. There have been several studies estimating the potential supply of biomass energy, including that of the Swedish Energy Commission in 1995. The Energy Commission based its estimates of biomass supply on five other analyses which presented a wide variation in estimated future supply, in large part due to differing assumptions regarding important factors. In this paper, these studies are assessed, and the estimated potential biomass energy supplies are discusses regarding prices, technical progress and energy policy. The supply of logging residues depends on the demand for wood products and is limited by ecological, technological, and economic restrictions. The supply of stemwood from early thinning for energy and of straw from cereal and oil seed production is mainly dependent upon economic considerations. One major factor for the supply of willow and reed canary grass is the size of arable land projected to be not needed for food and fodder production. Future supply of biomass energy depends on energy prices and technical progress, both of which are driven by energy policy priorities. Biomass energy has to compete with other energy sources as well as with alternative uses of biomass such as forest products and food production. Technical progress may decrease the costs of biomass energy and thus increase the competitiveness. Economic instruments, including carbon taxes and subsidies, and allocation of research and development resources, are driven by energy policy goals and can change the competitiveness of biomass energy

  9. Tundra plant above-ground biomass and shrub dominance mapped across the North Slope of Alaska

    Science.gov (United States)

    Berner, Logan T.; Jantz, Patrick; Tape, Ken D.; Goetz, Scott J.

    2018-03-01

    Arctic tundra is becoming greener and shrubbier due to recent warming. This is impacting climate feedbacks and wildlife, yet the spatial distribution of plant biomass in tundra ecosystems is uncertain. In this study, we mapped plant and shrub above-ground biomass (AGB; kg m-2) and shrub dominance (%; shrub AGB/plant AGB) across the North Slope of Alaska by linking biomass harvests at 28 field sites with 30 m resolution Landsat satellite imagery. We first developed regression models (p accounting for ~43% of regional plant AGB. The new maps capture landscape variation in plant AGB visible in high resolution satellite and aerial imagery, notably shrubby riparian corridors. Modeled shrub AGB was strongly correlated with field measurements of shrub canopy height at 25 sites (rs  = 0.88) and with a regional map of shrub cover (rs  = 0.76). Modeled plant AGB and shrub dominance were higher in shrub tundra than graminoid tundra and increased between areas with the coldest and warmest summer air temperatures, underscoring the fact that future warming has the potential to greatly increase plant AGB and shrub dominance in this region. These new biomass maps provide a unique source of ecological information for a region undergoing rapid environmental change.

  10. Diversity and aboveground biomass of lianas in the tropical seasonal rain forests of Xishuangbanna, SW China.

    Science.gov (United States)

    Lü, Xiao-Tao; Tang, Jian-Wei; Feng, Zhi-Li; Li, Mai-He

    2009-01-01

    Lianas are important components of tropical forests and have significant impacts on the diversity, structure and dynamics of tropical forests. The present study documented the liana flora in a Chinese tropical region. Species richness, abundance, size-class distribution and spatial patterns of lianas were investigated in three 1-ha plots in tropical seasonal rain forests in Xishuangbanna, SW China. All lianas with > or = 2 cm diameter at breast height (dbh) were measured, tagged and identified. A total of 458 liana stems belonging to 95 species (ranging from 38 to 50 species/ha), 59 genera and 32 families were recorded in the three plots. The most well-represented families were Loganiaceae, Annonceae, Papilionaceae, Apocynaceae and Rhamnaceae. Papilionaceae (14 species recorded) was the most important family in the study forests. The population density, basal area and importance value index (IVI) varied greatly across the three plots. Strychnos cathayensis, Byttneria grandifolia and Bousigonia mekongensis were the dominant species in terms of IVI across the three plots. The mean aboveground biomass of lianas (3 396 kg/ha) accounted for 1.4% of the total community above-ground biomass. The abundance, diversity and biomass of lianas in Xishuangbanna tropical seasonal rain forests are lower than those in tropical moist and wet forests, but higher than those in tropical dry forests. This study provides new data on lianas from a geographical region that has been little-studied. Our findings emphasize that other factors beyond the amount and seasonality of precipitation should be included when considering the liana abundance patterns across scales.

  11. Spatial effects of aboveground biomass on soil ecological parameters and trace gas fluxes in a savannah ecosystem of Mount Kilimanjaro

    Science.gov (United States)

    Becker, Joscha; Gütlein, Adrian; Sierra Cornejo, Natalia; Kiese, Ralf; Hertel, Dietrich; Kuzyakov, Yakov

    2015-04-01

    The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation in this area consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. Canopy structure is known to affect microclimate, throughfall and evapotranspiration and thereby controls soil moisture conditions. Consequently, the canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine trends and changes of soil parameters and relate their spatial variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. Distances were calculated in relation to the crown radius. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass carbon C and N, soil respiration as well as root biomass and -density, soil temperature and soil water content. Each tree was characterized by crown spread, leaf area index and basal area. Preliminary results show that C and N stocks decreased about 50% with depth independently of distance to the tree. Soil water content under the tree crown increased with depth while it decreased under grass cover. Microbial

  12. Landscape and forest structural controls on wood density and aboveground biomass along a tropical elevation gradient in Costa Rica

    Science.gov (United States)

    Robinson, C. M.; Saatchi, S. S.; Clark, D. B.; Gillespie, T. W.; Andelman, S.

    2014-12-01

    This research seeks to understand how tree wood density and taxonomic diversity relate to topography and three-dimensional vegetation structure in the tropical montane forest of Braulio Carrillo National Park in Costa Rica. The study utilized forest inventory and botanical data from twenty 1-ha plots ranging from 55 m to 2800 m above sea level and remote sensing data from an airborne lidar sensor (NASA's Land, Vegetation, and Ice Sensor [LVIS]) to quantify variations in forest structure. There is growing evidence that ecosystem structure plays an important role in defining patterns of species diversity and help to control the phenotypic and functional variations across landscapes. Elevation gradients along mountains provide landscape-size scales through which variations in topography, climate, and edaphic conditions as drivers of biodiversity can be tested. In this study we report on the effectiveness of relating patterns of tree wood density and alpha diversity to three-dimensional structure of a tropical montane forest using remote sensing observations of forest structure. Wood density is an important parameter for aboveground biomass and carbon estimations. Tree cores were analyzed for wood density and compared to existing database values for the same species. In this manner we were able to test the effect of the gradient on wood density and on the subsequent aboveground biomass estimations. Understanding these patterns has implications for conservation of both ecosystem services and biodiversity. Our results indicate that there is a strong relationship between LVIS-derived forest 3D-structure and alpha diversity, likely controlled controlled by variations in abiotic factors and topography along the elevation. Using spatial analysis with the aid of remote sensing data, we found distinct patterns along the environmental gradients defining species composition and forest structure. Wood density values were found to vary significantly from database values for the

  13. The effect of topography on arctic-alpine aboveground biomass and NDVI patterns

    Science.gov (United States)

    Riihimäki, Henri; Heiskanen, Janne; Luoto, Miska

    2017-04-01

    Topography is a key factor affecting numerous environmental phenomena, including Arctic and alpine aboveground biomass (AGB) distribution. Digital Elevation Model (DEM) is a source of topographic information which can be linked to local growing conditions. Here, we investigated the effect of DEM derived variables, namely elevation, topographic position, radiation and wetness on AGB and Normalized Difference Vegetation Index (NDVI) in a Fennoscandian forest-alpine tundra ecotone. Boosted regression trees were used to derive non-parametric response curves and relative influences of the explanatory variables. Elevation and potential incoming solar radiation were the most important explanatory variables for both AGB and NDVI. In the NDVI models, the response curves were smooth compared with AGB models. This might be caused by large contribution of field and shrub layer to NDVI, especially at the treeline. Furthermore, radiation and elevation had a significant interaction, showing that the highest NDVI and biomass values are found from low-elevation, high-radiation sites, typically on the south-southwest facing valley slopes. Topographic wetness had minor influence on AGB and NDVI. Topographic position had generally weak effects on AGB and NDVI, although protected topographic position seemed to be more favorable below the treeline. The explanatory power of the topographic variables, particularly elevation and radiation demonstrates that DEM-derived land surface parameters can be used for exploring biomass distribution resulting from landform control on local growing conditions.

  14. Does biodiversity make a difference? Relationships between species richness, evolutionary diversity, and aboveground live tree biomass across US forests

    Science.gov (United States)

    Kevin M. Potter; Christopher W. Woodall

    2014-01-01

    Biodiversity conveys numerous functional benefits to forested ecosystems, including community stability and resilience. In the context of managing forests for climate change mitigation/adaptation, maximizing and/or maintaining aboveground biomass will require understanding the interactions between tree biodiversity, site productivity, and the stocking of live trees....

  15. Effect of nitrogen addition and drought on above-ground biomass of expanding tall grasses Calamagrostis epigejos and Arrhenatherum elatius

    Czech Academy of Sciences Publication Activity Database

    Fiala, Karel; Tůma, Ivan; Holub, Petr

    2011-01-01

    Roč. 66, č. 2 (2011), s. 275-281 ISSN 0006-3088 R&D Projects: GA ČR(CZ) GA526/06/0556 Institutional research plan: CEZ:AV0Z60050516 Keywords : nitrogen * drought * above-ground biomass Subject RIV: EF - Botanics Impact factor: 0.557, year: 2011

  16. Spatial relationships among species, above-ground biomass, N, and P in degraded grasslands in Ordus Plateau, northwestern China

    Science.gov (United States)

    X. Cheng; S. An; J. chen; B. Li; Y. Liu; S. Liu

    2007-01-01

    We chose five communities, representing a mild to severe gradient of grassland desertification in a semi-arid area of Ordos Plateau, northwestern China, to explore the spatial relationships among plant species, above-ground biomass (AGB), and plant nutrients (N and P). Community 1 (Cl) was dominated by Stipa bungeana; community 2 (C2) by a mix of S...

  17. NACP Aboveground Biomass and Carbon Baseline Data, V.2 (NBCD 2000), U.S.A., 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The NBCD 2000 (National Biomass and Carbon Dataset for the Year 2000) data set provides a high-resolution (30 m) map of year-2000 baseline estimates of...

  18. NACP Aboveground Biomass and Carbon Baseline Data (NBCD 2000), U.S.A., 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The NBCD 2000 (National Biomass and Carbon data set for the Year 2000) data set provides a high-resolution (30 m) map of year-2000 baseline estimates of...

  19. NACP Aboveground Biomass and Carbon Baseline Data, V.2 (NBCD 2000), U.S.A., 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — The NBCD 2000 (National Biomass and Carbon Dataset for the Year 2000) data set provides a high-resolution (30 m) map of year-2000 baseline estimates of basal...

  20. NPP Grassland: Consistent Worldwide Site Estimates, 1954-1990, R1

    Data.gov (United States)

    National Aeronautics and Space Administration — In many grasslands, aboveground net primary productivity (ANPP) is commonly estimated by measuring peak aboveground biomass. Estimates of belowground net primary...

  1. Aboveground Biomass and Dynamics of Forest Attributes using LiDAR Data and Vegetation Model

    Science.gov (United States)

    V V L, P. A.

    2015-12-01

    In recent years, biomass estimation for tropical forests has received much attention because of the fact that regional biomass is considered to be a critical input to climate change. Biomass almost determines the potential carbon emission that could be released to the atmosphere due to deforestation or conservation to non-forest land use. Thus, accurate biomass estimation is necessary for better understating of deforestation impacts on global warming and environmental degradation. In this context, forest stand height inclusion in biomass estimation plays a major role in reducing the uncertainty in the estimation of biomass. The improvement in the accuracy in biomass shall also help in meeting the MRV objectives of REDD+. Along with the precise estimate of biomass, it is also important to emphasize the role of vegetation models that will most likely become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. Remote sensing is an efficient way to estimate forest parameters in large area, especially at regional scale where field data is limited. LIDAR (Light Detection And Ranging) provides accurate information on the vertical structure of forests. We estimated average tree canopy heights and AGB from GLAS waveform parameters by using a multi-regression linear model in forested area of Madhya Pradesh (area-3,08,245 km2), India. The derived heights from ICESat-GLAS were correlated with field measured tree canopy heights for 60 plots. Results have shown a significant correlation of R2= 74% for top canopy heights and R2= 57% for stand biomass. The total biomass estimation 320.17 Mt and canopy heights are generated by using random forest algorithm. These canopy heights and biomass maps were used in vegetation models to predict the changes biophysical/physiological characteristics of forest according to the changing climate. In our study we have

  2. Tree height and tropical forest biomass estimation

    Science.gov (United States)

    M.O. Hunter; M. Keller; D. Vitoria; D.C. Morton

    2013-01-01

    Tropical forests account for approximately half of above-ground carbon stored in global vegetation. However, uncertainties in tropical forest carbon stocks remain high because it is costly and laborious to quantify standing carbon stocks. Carbon stocks of tropical forests are determined using allometric relations between tree stem diameter and height and biomass....

  3. Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii

    Directory of Open Access Journals (Sweden)

    Adel H. Youkhana

    2017-05-01

    Full Text Available Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB, biomass carbon (C stock non-destructively have not yet been developed for tropical perennial C4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R2 = 0.98, 0.96, and 0.97, respectively. The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations

  4. Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4Grasses in Hawaii.

    Science.gov (United States)

    Youkhana, Adel H; Ogoshi, Richard M; Kiniry, James R; Meki, Manyowa N; Nakahata, Mae H; Crow, Susan E

    2017-01-01

    Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C 4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, ( R 2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a

  5. Aboveground tree biomass in a recovering tropical sal (Shorea robusta Gaertn. f.) forest of Eastern Ghats, India

    Energy Technology Data Exchange (ETDEWEB)

    Behera, Soumit K.; Misra, Malaya K. [Ecology and Floristic Laboratory, Department of Botany, Berhampur University, Berhampur 760 007, Orissa (India)

    2006-06-15

    Aboveground biomass of individual tree species by component and total biomass per unit area for four different stages of a recovering tropical dry deciduous forest stands, dominated by sal (Shorea robusta Gaertn. f.) of the Eastern Ghats, India were investigated during 2001-2002. Different periods of recovering (2, 4, 6, and 10-year) forest stands (84{sup o}13'E, 20{sup o}29'N) were selected in the Kandhamal district of Orissa, India and sample trees of all species were harvested. Tree species diversity was 23, 23, 21 and 22 in 2, 4, 6, and 10-year recovering stands, respectively. Species-wise Ixora pavetta showed the highest biomass in 2 and 4-year stands while Shorea robusta in 6 and 10-year stands. Component-wise, in all species, bole-wood contribution ranged between 22.6% and 60.9%. Aboveground tree biomass, in all the stands, was dominated by Shorea robusta, which ranged between 12.68 and 231.91Mgha{sup -1}. Total aboveground tree biomass was 30.12, 49.21, 107.54 and 261.08Mgha{sup -1} in 2, 4, 6 and 10-year stands, respectively. (author)

  6. Lidar remote sensing of above-ground biomass in three biomes.

    Science.gov (United States)

    Michael A. Lefsky; Warren B. Cohen; David J. Harding; Geoffrey G. Parkers; Steven A. Acker; S. Thomas. Gower

    2002-01-01

    Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical...

  7. ABILITY OF LANDSAT-8 OLI DERIVED TEXTURE METRICS IN ESTIMATING ABOVEGROUND CARBON STOCKS OF COPPICE OAK FORESTS

    Directory of Open Access Journals (Sweden)

    A. Safari

    2016-06-01

    Full Text Available The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9, and four different offsets ([0,1], [1,1], [1,0], and [1,-1] to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance from four bands (blue, green, red, and infrared. Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived

  8. Ability of LANDSAT-8 Oli Derived Texture Metrics in Estimating Aboveground Carbon Stocks of Coppice Oak Forests

    Science.gov (United States)

    Safari, A.; Sohrabi, H.

    2016-06-01

    The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI) derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9), and four different offsets ([0,1], [1,1], [1,0], and [1,-1]) to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance) from four bands (blue, green, red, and infrared). Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived texture metrics

  9. Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.

    Science.gov (United States)

    Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto

    2017-09-08

    Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% ( n = 35, p BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.

  10. Estimates of grassland biomass and turnover time on the Tibetan Plateau

    Science.gov (United States)

    Xia, Jiangzhou; Ma, Minna; Liang, Tiangang; Wu, Chaoyang; Yang, Yuanhe; Zhang, Li; Zhang, Yangjian; Yuan, Wenping

    2018-01-01

    The grassland of the Tibetan Plateau forms a globally significant biome, which represents 6% of the world’s grasslands and 44% of China’s grasslands. However, large uncertainties remain concerning the vegetation carbon storage and turnover time in this biome. In this study, we quantified the pool size of both the aboveground and belowground biomass and turnover time of belowground biomass across the Tibetan Plateau by combining systematic measurements taken from a substantial number of surveys (i.e. 1689 sites for aboveground biomass, 174 sites for belowground biomass) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is effective tool for upscaling local biomass observations to the regional scale, and for producing continuous biomass estimates of the Tibetan Plateau. On average, the models estimated 46.57 Tg (1 Tg = 1012g) C of aboveground biomass and 363.71 Tg C of belowground biomass in the Tibetan grasslands covering an area of 1.32 × 106 km2. The turnover time of belowground biomass demonstrated large spatial heterogeneity, with a median turnover time of 4.25 years. Our results also demonstrated large differences in the biomass simulations among the major ecosystem models used for the Tibetan Plateau, largely because of inadequate model parameterization and validation. This study provides a spatially continuous measure of vegetation carbon storage and turnover time, and provides useful information for advancing ecosystem models and improving their performance.

  11. Tropical Africa: Land use, biomass, and carbon estimates for 1980

    Energy Technology Data Exchange (ETDEWEB)

    Brown, S. [Environmental Protection Agency, Corvallis, OR (United States). Western Ecology Division; Gaston, G. [Environmental Protection Agency, Corvallis, OR (United States). National Research Council; Daniels, R.C. [ed.] [Oak Ridge National Lab., TN (United States)

    1996-06-01

    This document describes the contents of a digital database containing maximum potential aboveground biomass, land use, and estimated biomass and carbon data for 1980 and describes a methodology that may be used to extend this data set to 1990 and beyond based on population and land cover data. The biomass data and carbon estimates are for woody vegetation in Tropical Africa. These data were collected to reduce the uncertainty associated with the possible magnitude of historical releases of carbon from land use change. Tropical Africa is defined here as encompassing 22.7 x 10{sup 6} km{sup 2} of the earth`s land surface and includes those countries that for the most part are located in Tropical Africa. Countries bordering the Mediterranean Sea and in southern Africa (i.e., Egypt, Libya, Tunisia, Algeria, Morocco, South Africa, Lesotho, Swaziland, and Western Sahara) have maximum potential biomass and land cover information but do not have biomass or carbon estimate. The database was developed using the GRID module in the ARC/INFO{sup TM} geographic information system. Source data were obtained from the Food and Agriculture Organization (FAO), the U.S. National Geophysical Data Center, and a limited number of biomass-carbon density case studies. These data were used to derive the maximum potential and actual (ca. 1980) aboveground biomass-carbon values at regional and country levels. The land-use data provided were derived from a vegetation map originally produced for the FAO by the International Institute of Vegetation Mapping, Toulouse, France.

  12. Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

    Science.gov (United States)

    Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

    2017-08-01

    The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest

  13. Relationships between functional diversity and aboveground biomass production in the Northern Tibetan alpine grasslands.

    Science.gov (United States)

    Zhu, Juntao; Jiang, Lin; Zhang, Yangjian

    2016-09-26

    Functional diversity, the extent of functional differences among species in a community, drives biodiversity-ecosystem function (BEF) relationships. Here, four species traits and aboveground biomass production (ABP) were considered. We used two community-wide measures of plant functional composition, (1) community weighted means of trait values (CWM) and (2) functional trait diversity based on Rao's quadratic diversity (FD Q ) to evaluate the effects of functional diversity on the ABP in the Northern Tibetan alpine grasslands. Both species and functional diversity were positively related to the ABP. Functional trait composition had a larger predictive power for the ABP than species diversity and FD Q , indicating a primary dependence of ecosystem property on the identity of dominant species in our study system. Multivariate functional diversity was ineffective in predicting ecosystem function due to the trade-offs among different traits or traits selection criterions. Our study contributes to a better understanding of the mechanisms driving the BEF relationships in stressed ecosystems, and especially emphasizes that abiotic and biotic factors affect the BEF relationships in alpine grasslands.

  14. Wildfires in bamboo-dominated Amazonian forest: impacts on above-ground biomass and biodiversity.

    Directory of Open Access Journals (Sweden)

    Jos Barlow

    Full Text Available Fire has become an increasingly important disturbance event in south-western Amazonia. We conducted the first assessment of the ecological impacts of these wildfires in 2008, sampling forest structure and biodiversity along twelve 500 m transects in the Chico Mendes Extractive Reserve, Acre, Brazil. Six transects were placed in unburned forests and six were in forests that burned during a series of forest fires that occurred from August to October 2005. Normalized Burn Ratio (NBR calculations, based on Landsat reflectance data, indicate that all transects were similar prior to the fires. We sampled understorey and canopy vegetation, birds using both mist nets and point counts, coprophagous dung beetles and the leaf-litter ant fauna. Fire had limited influence upon either faunal or floral species richness or community structure responses, and stems <10 cm DBH were the only group to show highly significant (p = 0.001 community turnover in burned forests. Mean aboveground live biomass was statistically indistinguishable in the unburned and burned plots, although there was a significant increase in the total abundance of dead stems in burned plots. Comparisons with previous studies suggest that wildfires had much less effect upon forest structure and biodiversity in these south-western Amazonian forests than in central and eastern Amazonia, where most fire research has been undertaken to date. We discuss potential reasons for the apparent greater resilience of our study plots to wildfire, examining the role of fire intensity, bamboo dominance, background rates of disturbance, landscape and soil conditions.

  15. Effects of model choice and forest structure on inventory-based estimations of Puerto Rican forest biomass

    Science.gov (United States)

    Thomas J. Brandeis; Maria Del Rocio; Suarez Rozo

    2005-01-01

    Total aboveground live tree biomass in Puerto Rican lower montane wet, subtropical wet, subtropical moist and subtropical dry forests was estimated using data from two forest inventories and published regression equations. Multiple potentially-applicable published biomass models existed for some forested life zones, and their estimates tended to diverge with increasing...

  16. Response of Plant Height, Species Richness and Aboveground Biomass to Flooding Gradient along Vegetation Zones in Floodplain Wetlands, Northeast China

    Science.gov (United States)

    Lou, Yanjing; Pan, Yanwen; Gao, Chuanyu; Jiang, Ming; Lu, Xianguo; Xu, Y. Jun

    2016-01-01

    Flooding regime changes resulting from natural and human activity have been projected to affect wetland plant community structures and functions. It is therefore important to conduct investigations across a range of flooding gradients to assess the impact of flooding depth on wetland vegetation. We conducted this study to identify the pattern of plant height, species richness and aboveground biomass variation along the flooding gradient in floodplain wetlands located in Northeast China. We found that the response of dominant species height to the flooding gradient depends on specific species, i.e., a quadratic response for Carex lasiocarpa, a negative correlation for Calamagrostis angustifolia, and no response for Carex appendiculata. Species richness showed an intermediate effect along the vegetation zone from marsh to wet meadow while aboveground biomass increased. When the communities were analysed separately, only the water table depth had significant impact on species richness for two Carex communities and no variable for C. angustifolia community, while height of dominant species influenced aboveground biomass. When the three above-mentioned communities were grouped together, variations in species richness were mainly determined by community type, water table depth and community mean height, while variations in aboveground biomass were driven by community type and the height of dominant species. These findings indicate that if habitat drying of these herbaceous wetlands in this region continues, then two Carex marshes would be replaced gradually by C. angustifolia wet meadow in the near future. This will lead to a reduction in biodiversity and an increase in productivity and carbon budget. Meanwhile, functional traits must be considered, and should be a focus of attention in future studies on the species diversity and ecosystem function in this region. PMID:27097325

  17. Response of Plant Height, Species Richness and Aboveground Biomass to Flooding Gradient along Vegetation Zones in Floodplain Wetlands, Northeast China.

    Directory of Open Access Journals (Sweden)

    Yanjing Lou

    Full Text Available Flooding regime changes resulting from natural and human activity have been projected to affect wetland plant community structures and functions. It is therefore important to conduct investigations across a range of flooding gradients to assess the impact of flooding depth on wetland vegetation. We conducted this study to identify the pattern of plant height, species richness and aboveground biomass variation along the flooding gradient in floodplain wetlands located in Northeast China. We found that the response of dominant species height to the flooding gradient depends on specific species, i.e., a quadratic response for Carex lasiocarpa, a negative correlation for Calamagrostis angustifolia, and no response for Carex appendiculata. Species richness showed an intermediate effect along the vegetation zone from marsh to wet meadow while aboveground biomass increased. When the communities were analysed separately, only the water table depth had significant impact on species richness for two Carex communities and no variable for C. angustifolia community, while height of dominant species influenced aboveground biomass. When the three above-mentioned communities were grouped together, variations in species richness were mainly determined by community type, water table depth and community mean height, while variations in aboveground biomass were driven by community type and the height of dominant species. These findings indicate that if habitat drying of these herbaceous wetlands in this region continues, then two Carex marshes would be replaced gradually by C. angustifolia wet meadow in the near future. This will lead to a reduction in biodiversity and an increase in productivity and carbon budget. Meanwhile, functional traits must be considered, and should be a focus of attention in future studies on the species diversity and ecosystem function in this region.

  18. Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth

    OpenAIRE

    Singh, Minerva; Evans, Damian; Friess, Daniel; Tan, Boun; Nin, Chan

    2015-01-01

    This study develops a modelling framework for utilizing very high-resolution (VHR) aerial imagery for monitoring stocks of above-ground biomass (AGB) in a tropical forest in Southeast Asia. Three different texture-based methods (grey level co-occurrence metric (GLCM), Gabor wavelets and Fourier-based textural ordination (FOTO)) were used in conjunction with two different machine learning (ML)-based regression techniques (support vector regression (SVR) and random forest (RF) regression). Thes...

  19. Evaluating land use and aboveground biomass dynamics in an oil palm–dominated landscape in Borneo using optical remote sensing

    OpenAIRE

    Singh, Minerva; Malhi, Yadvinder; Bhagwat, Shonil

    2014-01-01

    The focus of this study is to assess the efficacy of using optical remote sensing (RS) in evaluating disparities in forest composition and aboveground biomass (AGB). The research was carried out in the East Sabah region, Malaysia, which constitutes a disturbance gradient ranging from pristine old growth forests to forests that have experienced varying levels of disturbances. Additionally, a significant proportion of the area consists of oil palm plantations. In accordance with local laws, rip...

  20. Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR

    Directory of Open Access Journals (Sweden)

    J. Jubanski

    2013-06-01

    Full Text Available Quantification of tropical forest above-ground biomass (AGB over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+ projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia through correlating airborne light detection and ranging (LiDAR to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52. Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.

  1. Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR

    Science.gov (United States)

    Jubanski, J.; Ballhorn, U.; Kronseder, K.; Franke, J.; Siegert, F.

    2013-06-01

    Quantification of tropical forest above-ground biomass (AGB) over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+) projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia) through correlating airborne light detection and ranging (LiDAR) to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52). Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC) showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG) emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.

  2. Diversity and aboveground biomass of lianas in the tropical seasonal rain forests of Xishuangbanna, SW China

    Directory of Open Access Journals (Sweden)

    Xiao-Tao Lü

    2009-06-01

    Full Text Available Lianas are important components of tropical forests and have significant impacts on the diversity, structure and dynamics of tropical forests. The present study documented the liana flora in a Chinese tropical region. Species richness, abundance, size-class distribution and spatial patterns of lianas were investigated in three 1-ha plots in tropical seasonal rain forests in Xishuangbanna, SW China. All lianas with = 2 cm diameter at breast height (dbh were measured, tagged and identified. A total of 458 liana stems belonging to 95 species (ranging from 38 to 50 species/ha, 59 genera and 32 families were recorded in the three plots. The most well-represented families were Loganiaceae, Annonceae, Papilionaceae, Apocynaceae and Rhamnaceae. Papilionaceae (14 species recorded was the most important family in the study forests. The population density, basal area and importance value index (IVI varied greatly across the three plots. Strychnos cathayensis, Byttneria grandifolia and Bousigonia mekongensis were the dominant species in terms of IVI across the three plots. The mean aboveground biomass of lianas (3 396 kg/ha accounted for 1.4% of the total community aboveground biomass. The abundance, diversity and biomass of lianas in Xishuangbanna tropical seasonal rain forests are lower than those in tropical moist and wet forests, but higher than those in tropical dry forests. This study provides new data on lianas from a geographical region that has been little-studied. Our findings emphasize that other factors beyond the amount and seasonality of precipitation should be included when considering the liana abundance patterns across scales. Rev. Biol. Trop. 57 (1-2: 211-222. Epub 2009 June 30.Las lianas son componentes importantes de los bosques tropicales y tienen importantes impactos en la diversidad, la estructura y la dinámica de los bosques tropicales. El presente estudio documenta la flora de lianas en una región tropical estacional china. La

  3. Spatiotemporal dynamics of grassland aboveground biomass on the Qinghai-Tibet Plateau based on validated MODIS NDVI.

    Science.gov (United States)

    Liu, Shiliang; Cheng, Fangyan; Dong, Shikui; Zhao, Haidi; Hou, Xiaoyun; Wu, Xue

    2017-06-23

    Spatiotemporal dynamics of aboveground biomass (AGB) is a fundamental problem for grassland environmental management on the Qinghai-Tibet Plateau (QTP). Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data can feasibly be used to estimate AGB at large scales, and their precise validation is necessary to utilize them effectively. In our study, the clip-harvest method was used at 64 plots in QTP grasslands to obtain actual AGB values, and a handheld hyperspectral spectrometer was used to calculate field-measured NDVI to validate MODIS NDVI. Based on the models between NDVI and AGB, AGB dynamics trends during 2000-2012 were analyzed. The results showed that the AGB in QTP grasslands increased during the study period, with 70% of the grasslands undergoing increases mainly in the Qinghai Province. Also, the meadow showed a larger increasing trend than steppe. Future AGB dynamic trends were also investigated using a combined analysis of the slope values and the Hurst exponent. The results showed high sustainability of AGB dynamics trends after the study period. Predictions indicate 60% of the steppe and meadow grasslands would continue to increase in AGB, while 25% of the grasslands would remain in degradation, with most of them distributing in Tibet.

  4. Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth

    Directory of Open Access Journals (Sweden)

    Minerva Singh

    2015-04-01

    Full Text Available This study develops a modelling framework for utilizing very high-resolution (VHR aerial imagery for monitoring stocks of above-ground biomass (AGB in a tropical forest in Southeast Asia. Three different texture-based methods (grey level co-occurrence metric (GLCM, Gabor wavelets and Fourier-based textural ordination (FOTO were used in conjunction with two different machine learning (ML-based regression techniques (support vector regression (SVR and random forest (RF regression. These methods were implemented on both 50-cm resolution Digital Globe data extracted from Google Earth™ (GE and 8-cm commercially obtained VHR imagery. This study further examines the role of forest biophysical parameters, such as ground-measured canopy cover and vertical canopy height, in explaining AGB distribution. Three models were developed using: (i horizontal canopy variables (i.e., canopy cover and texture variables plus vertical canopy height; (ii horizontal variables only; and (iii texture variables only. AGB was variable across the site, ranging from 51.02 Mg/ha to 356.34 Mg/ha. GE-based AGB estimates were comparable to those derived from commercial aerial imagery. The findings demonstrate that novel use of this array of texture-based techniques with GE imagery can help promote the wider use of freely available imagery for low-cost, fine-resolution monitoring of forests parameters at the landscape scale.

  5. Tree height integrated into pantropical forest biomass estimates

    Directory of Open Access Journals (Sweden)

    T. R. Feldpausch

    2012-08-01

    Full Text Available Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H. We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions:

    1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass?

    2. To what extent does including H estimates derived in (1 reduce uncertainty in biomass estimates across all 327 plots?

    3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates?

    The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06, was half that when excluding H (mean 0.13. Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4 to 8.0 Mg ha−1 (−2.5 to 23.0. For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI, or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly

  6. A wood density and aboveground biomass variability assessment using pre-felling inventory data in Costa Rica.

    Science.gov (United States)

    Svob, Sienna; Arroyo-Mora, J Pablo; Kalacska, Margaret

    2014-12-01

    The high spatio-temporal variability of aboveground biomass (AGB) in tropical forests is a large source of uncertainty in forest carbon stock estimation. Due to their spatial distribution and sampling intensity, pre-felling inventories are a potential source of ground level data that could help reduce this uncertainty at larger spatial scales. Further, exploring the factors known to influence tropical forest biomass, such as wood density and large tree density, will improve our knowledge of biomass distribution across tropical regions. Here, we evaluate (1) the variability of wood density and (2) the variability of AGB across five ecosystems of Costa Rica. Using forest management (pre-felling) inventories we found that, of the regions studied, Huetar Norte had the highest mean wood density of trees with a diameter at breast height (DBH) greater than or equal to 30 cm, 0.623 ± 0.182 g cm -3 (mean ± standard deviation). Although the greatest wood density was observed in Huetar Norte, the highest mean estimated AGB (EAGB) of trees with a DBH greater than or equal to 30 cm was observed in Osa peninsula (173.47 ± 60.23 Mg ha -1 ). The density of large trees explained approximately 50% of EAGB variability across the five ecosystems studied. Comparing our study's EAGB to published estimates reveals that, in the regions of Costa Rica where AGB has been previously sampled, our forest management data produced similar values. This study presents the most spatially rich analysis of ground level AGB data in Costa Rica to date. Using forest management data, we found that EAGB within and among five Costa Rican ecosystems is highly variable. Combining commercial logging inventories with ecological plots will provide a more representative ground level dataset for the calibration of the models and remotely sensed data used to EAGB at regional and national scales. Additionally, because the non-protected areas of the tropics offer the greatest opportunity to reduce

  7. Importance of tree basic density in biomass estimation and associated uncertainties

    DEFF Research Database (Denmark)

    Njana, Marco Andrew; Meilby, Henrik; Eid, Tron

    2016-01-01

    Key message Aboveground and belowground tree basic densities varied between and within the three mangrove species. If appropriately determined and applied, basic density may be useful in estimation of tree biomass. Predictive accuracy of the common (i.e. multi-species) models including aboveground...... of sustainable forest management, conservation and enhancement of carbon stocks (REDD+) initiatives offer an opportunity for sustainable management of forests including mangroves. In carbon accounting for REDD+, it is required that carbon estimates prepared for monitoring reporting and verification schemes...... and examine uncertainties in estimation of tree biomass using indirect methods. Methods This study focused on three dominant mangrove species (Avicennia marina (Forssk.) Vierh, Sonneratia alba J. Smith and Rhizophora mucronata Lam.) in Tanzania. A total of 120 trees were destructively sampled for aboveground...

  8. Volume and aboveground biomass models for dry Miombo woodland in Tanzania

    DEFF Research Database (Denmark)

    Mwakalukwa, Ezekiel Edward; Meilby, Henrik; Treue, Thorsten

    2014-01-01

    Tools to accurately estimate tree volume and biomass are scarce for most forest types in East Africa, including Tanzania. Based on a sample of 142 trees and 57 shrubs from a 6,065 ha area of dry miombo woodland in Iringa rural district in Tanzania, regression models were developed for volume...... and biomass of three important species, Brachystegia spiciformis Benth. (n=40), Combretum molle G. Don (n=41), and Dalbergia arbutifolia Baker (n=37) separately, and for broader samples of trees (28 species, n=72), shrubs (16 species, n=31), and trees and shrubs combined (44 species, n=104). Applied...... of the predictions tended to increase from general to species-specific models. Except for a few volume and biomass models developed for shrubs, all models had R2 values of 96–99%. Thus, the models appear robust and should be applicable to forests with similar site conditions, species, and diameter ranges....

  9. [Aboveground biomass input of Myristicaceae tree species in the Amazonian Forest in Peru].

    Science.gov (United States)

    Ureta Adrianzén, Marisabel

    2015-03-01

    Amazonian forests are a vast storehouse of biodiversity and function as carbon sinks from biomass that accumulates in various tree species. In these forests, the taxa with the greatest contribution of biomass cannot be precisely defined, and the representative distribution of Myristicaceae in the Peruvian Amazon was the starting point for designing the present study, which aimed to quantify the biomass contribution of this family. For this, I analyzed the databases that corresponded to 38 sample units that were previously collected and that were provided by the TeamNetwork and RAINFOR organizations. The analysis consisted in the estimation of biomass using pre-established allometric equations, Kruskal-Wallis sample comparisons, interpolation-analysis maps, and nonparametric multidimensional scaling (NMDS). The results showed that Myristicaceae is the fourth most important biomass contributor with 376.97 Mg/ha (9.92 Mg/ha in average), mainly due to its abundance. Additionally, the family shows a noticeable habitat preference for certain soil conditions in the physiographic units, such is the case of Virola pavonis in "varillales", within "floodplain", or Iryanthera tessmannii and Virola loretensis in sewage flooded areas or "igapo" specifically, and the preference of Virola elongata and irola surinamensis for white water flooded areas or "varzea" edaphic conditions of the physiographic units taken in the study.

  10. Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines

    Science.gov (United States)

    Singh, Minerva; Friess, Daniel A.; Vilela, Bruno; Alban, Jose Don T. De; Monzon, Angelica Kristina V.; Veridiano, Rizza Karen A.; Tumaneng, Roven D.

    2017-01-01

    This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1) low AGB and low IUCN richness, and 2) low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species. PMID:29206228

  11. Spatial relationships between above-ground biomass and bird species biodiversity in Palawan, Philippines.

    Directory of Open Access Journals (Sweden)

    Minerva Singh

    Full Text Available This study maps distribution and spatial congruence between Above-Ground Biomass (AGB and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1. A support vector regression (SVR model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1 low AGB and low IUCN richness, and 2 low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species.

  12. Volume equations and biomass estimates for three species in ...

    African Journals Online (AJOL)

    Volume equations predict the volume of the stem of a tree from dendrometrical characteristics that are easy to measure, such as diameter and/or height. These equations can serve as a surrogate for biomass equations, by converting the stem volume to stem biomass, and then expanding it to the total aboveground biomass.

  13. Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

    Science.gov (United States)

    Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

    2017-09-01

    Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates

  14. Bridging scale gaps between regional maps of forest aboveground biomass and field sampling plots using TanDEM-X data

    Science.gov (United States)

    Ni, W.; Zhang, Z.; Sun, G.

    2017-12-01

    Several large-scale maps of forest AGB have been released [1] [2] [3]. However, these existing global or regional datasets were only approximations based on combining land cover type and representative values instead of measurements of actual forest aboveground biomass or forest heights [4]. Rodríguez-Veiga et al[5] reported obvious discrepancies of existing forest biomass stock maps with in-situ observations in Mexico. One of the biggest challenges to the credibility of these maps comes from the scale gaps between the size of field sampling plots used to develop(or validate) estimation models and the pixel size of these maps and the availability of field sampling plots with sufficient size for the verification of these products [6]. It is time-consuming and labor-intensive to collect sufficient number of field sampling data over the plot size of the same as resolutions of regional maps. The smaller field sampling plots cannot fully represent the spatial heterogeneity of forest stands as shown in Figure 1. Forest AGB is directly determined by forest heights, diameter at breast height (DBH) of each tree, forest density and tree species. What measured in the field sampling are the geometrical characteristics of forest stands including the DBH, tree heights and forest densities. The LiDAR data is considered as the best dataset for the estimation of forest AGB. The main reason is that LiDAR can directly capture geometrical features of forest stands by its range detection capabilities.The remotely sensed dataset, which is capable of direct measurements of forest spatial structures, may serve as a ladder to bridge the scale gaps between the pixel size of regional maps of forest AGB and field sampling plots. Several researches report that TanDEM-X data can be used to characterize the forest spatial structures [7, 8]. In this study, the forest AGB map of northeast China were produced using ALOS/PALSAR data taking TanDEM-X data as a bridges. The TanDEM-X InSAR data used in

  15. Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

    Science.gov (United States)

    Scott L. Powell; Warren B. Cohen; Sean P. Healey; Robert E. Kennedy; Gretchen G. Moisen; Kenneth B. Pierce; Janet L. Ohmann

    2010-01-01

    Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to...

  16. Relationships between aboveground biomass and plant cover at two spatial scales and their determinants in northern Tibetan grasslands.

    Science.gov (United States)

    Jiang, Yanbin; Zhang, Yangjian; Wu, Yupeng; Hu, Ronggui; Zhu, Juntao; Tao, Jian; Zhang, Tao

    2017-10-01

    The relationships between cover and AGB for the dominant and widely distributed alpine grasslands on the northern Tibetan Plateau is still not fully examined. The objectives of this study are to answer the following question: (1) How does aboveground biomass (AGB) of alpine grassland relate to plant cover at different spatial scales? (2) What are the major biotic and abiotic factors influencing on AGB-cover relationship? A community survey (species, cover, height, and abundance) was conducted within 1 m × 1 m plots in 70 sites along a precipitation gradient of 50-600 m. Ordinary linear regression was employed to examine AGB-cover relationships of both community and species levels at regional scale of entire grassland and landscape scale of alpine meadow, alpine steppe, and desert steppe. Hierarchical partitioning was employed to estimate independent contributions of biotic and abiotic factors to AGB and cover at both scales. Partial correlation analyses were used to discriminate the effects of biotic and abiotic factors on AGB-cover relationships at two spatial scales. AGB and community cover both exponentially increased along the precipitation gradient. At community level, AGB was positively and linearly correlated with cover for all grasslands except for alpine meadow. AGB was also linearly correlated with cover of species level at both regional and landscape scales. Contributions of biotic and abiotic factors to the relationship between AGB and cover significantly depended on spatial scales. Cover of cushions, forbs, legumes and sedges, species richness, MAP, and soil bulk density were important factors that influenced the AGB-cover relationship at either regional or landscape scale. This study indicated generally positive and linear relationships between AGB and cover are at both regional and landscape scales. Spatial scale may affect ranges of cover and modify the contribution of cover to AGB. AGB-cover relationships were influenced mainly by species

  17. Volume and Aboveground Biomass Models for Dry Miombo Woodland in Tanzania

    Directory of Open Access Journals (Sweden)

    Ezekiel Edward Mwakalukwa

    2014-01-01

    Full Text Available Tools to accurately estimate tree volume and biomass are scarce for most forest types in East Africa, including Tanzania. Based on a sample of 142 trees and 57 shrubs from a 6,065 ha area of dry miombo woodland in Iringa rural district in Tanzania, regression models were developed for volume and biomass of three important species, Brachystegia spiciformis Benth. (n = 40, Combretum molle G. Don (n = 41, and Dalbergia arbutifolia Baker (n = 37 separately, and for broader samples of trees (28 species, n = 72, shrubs (16 species, n = 32, and trees and shrubs combined (44 species, n = 104. Applied independent variables were log-transformed diameter, height, and wood basic density, and in each case a range of different models were tested. The general tendency among the final models is that the fit improved when height and wood basic density were included. Also the precision and accuracy of the predictions tended to increase from general to species-specific models. Except for a few volume and biomass models developed for shrubs, all models had R2 values of 96–99%. Thus, the models appear robust and should be applicable to forests with similar site conditions, species, and diameter ranges.

  18. Evaluation of sampling strategies to estimate crown biomass

    Directory of Open Access Journals (Sweden)

    Krishna P Poudel

    2015-01-01

    Full Text Available Background Depending on tree and site characteristics crown biomass accounts for a significant portion of the total aboveground biomass in the tree. Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire modeling. However, crown biomass is difficult to predict because of the variability within and among species and sites. Thus the allometric equations used for predicting crown biomass should be based on data collected with precise and unbiased sampling strategies. In this study, we evaluate the performance different sampling strategies to estimate crown biomass and to evaluate the effect of sample size in estimating crown biomass. Methods Using data collected from 20 destructively sampled trees, we evaluated 11 different sampling strategies using six evaluation statistics: bias, relative bias, root mean square error (RMSE, relative RMSE, amount of biomass sampled, and relative biomass sampled. We also evaluated the performance of the selected sampling strategies when different numbers of branches (3, 6, 9, and 12 are selected from each tree. Tree specific log linear model with branch diameter and branch length as covariates was used to obtain individual branch biomass. Results Compared to all other methods stratified sampling with probability proportional to size estimation technique produced better results when three or six branches per tree were sampled. However, the systematic sampling with ratio estimation technique was the best when at least nine branches per tree were sampled. Under the stratified sampling strategy, selecting unequal number of branches per stratum produced approximately similar results to simple random sampling, but it further decreased RMSE when information on branch diameter is used in the design and estimation phases. Conclusions Use of

  19. Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon

    Science.gov (United States)

    Marcos Longo; Michael Keller; Maiza N. dos-Santos; Veronika Leitold; Ekena R. Pinagé; Alessandro Baccini; Sassan Saatchi; Euler M. Nogueira; Mateus Batistella; Douglas C. Morton

    2016-01-01

    Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, fire, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n = 359) and airborne lidar data (18,000 ha)...

  20. Regional contingencies in the relationship between aboveground biomass and litter in the world’s grasslands

    Science.gov (United States)

    L.R. O' Halloran; E.T. Borer; E.W. Seabloom; A.S. MacDougall; E.E. Cleland; R.L. McCulley; S. Hobbie; S. Harpole; N.M. DeCrappeo; C.-J. Chu; J.D. Bakker; K.F. Davies; G. Du; J. Firn; N. Hagenah; K.S. Hofmockel; J.M.H. Knops; W. Li; B.A. Melbourne; J.W. Morgan; J.L. Orrock; S.M. Prober; C.J. Stevens

    2013-01-01

    Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a...

  1. Estimating herbaceous biomass of grassland vegetation using the reference unit method

    Science.gov (United States)

    Eric D. Boyda; Jack L. Butler; Lan Xu

    2015-01-01

    Aboveground net primary production provides valuable information on wildlife habitat, fire fuel loads, and forage availability. Aboveground net primary production in herbaceous plant communities is typically measured by clipping aboveground biomass. However, the high costs associated with physically harvesting plant biomass may prevent collecting sufficient...

  2. [Aboveground biomass and nutrient distribution patterns of larch plantation in a montane region of eastern Liaoning Province, China].

    Science.gov (United States)

    Yan, Tao; Zhu, Jiao-Jun; Yang, Kai; Yu, Li-Zhong

    2014-10-01

    Larch is the main timber species of forest plantations in North China. Imbalance in nutrient cycling in soil emerged due to single species composition and mono system structure of plantation. Thus it is necessary to grasp its biomass and nutrients allocation for scientific management and nutrient cycling studies of larch plantation. We measured aboveground biomass (stem, branch, bark and leaf) and nutrient concentrations (C, N, P, K, Ca, Mg, Fe, Mn, Cu and Zn), and analyzed the patterns of accumulation and distribution of 19-year-old larch plantation with diameter at breast height of 12. 8 cm, tree height of 15. 3 m, and density of 2308 trees · hm(-2), in a montane region of eastern Liaoning Province, China. The results showed that aboveground biomass values were 70.26 kg and 162.16 t · hm(-2) for the individual tree of larch and the stand, respectively. There was a significant difference between biomass of the organs, and decreased in the order of stem > branch > bark > leaf. Nutrient accumulation was 749.94 g and 1730.86 kg · hm(-2) for the individual tree of larch and the stand, respectively. Nutrient accumulation of stem was significantly higher than that of branch, bark and leaf, whether it was macro-nutrient or micro-nutrient. Averagely, 749.94 g nutrient elements would be removed from the system when a 19-year-old larch tree was harvested. If only the stem part was removed from the system, the removal of nutrient elements could be reduced by 40.7%.

  3. The variable effects of soil nitrogen availability and insect herbivory on aboveground and belowground plant biomass in an old-field ecosystem

    DEFF Research Database (Denmark)

    Blue, Jarrod D.; Souza, Lara; Classen, Aimée T.

    2011-01-01

    Nutrient availability and herbivory can regulate primary production in ecosystems, but little is known about how, or whether, they may interact with one another. Here, we investigate how nitrogen availability and insect herbivory interact to alter aboveground and belowground plant community biomass...... in an old-field ecosystem. In 2004, we established 36 experimental plots in which we manipulated soil nitrogen (N) availability and insect abundance in a completely randomized plot design. In 2009, after 6 years of treatments, we measured aboveground biomass and assessed root production at peak growth...... not be limiting primary production in this ecosystem. Insects reduced the aboveground biomass of subdominant plant species and decreased coarse root production. We found no statistical interactions between N availability and insect herbivory for any response variable. Overall, the results of 6 years of nutrient...

  4. Assessment of Aboveground Woody Biomass Dynamics Using Terrestrial Laser Scanner and L-Band ALOS PALSAR Data in South African Savanna

    Directory of Open Access Journals (Sweden)

    Victor Onyango Odipo

    2016-11-01

    Full Text Available The use of optical remote sensing data for savanna vegetation structure mapping is hindered by sparse and heterogeneous distribution of vegetation canopy, leading to near-similar spectral signatures among lifeforms. An additional challenge to optical sensors is the high cloud cover and unpredictable weather conditions. Longwave microwave data, with its low sensitivity to clouds addresses some of these problems, but many space borne studies are still limited by low quality structural reference data. Terrestrial laser scanning (TLS derived canopy cover and height metrics can improve aboveground biomass (AGB prediction at both plot and landscape level. To date, few studies have explored the strength of TLS for vegetation structural mapping, and particularly few focusing on savannas. In this study, we evaluate the potential of high resolution TLS-derived canopy cover and height metrics to estimate plot-level aboveground biomass, and to extrapolate to a landscape-wide biomass estimation using multi-temporal L-band Synthetic Aperture Radar (SAR within a 9 km2 area savanna in Kruger National Park (KNP. We inventoried 42 field plots in the wet season and computed AGB for each plot using site-specific allometry. Canopy cover, canopy height, and their product were regressed with plot-level AGB over the TLS-footprint, while SAR backscatter was used to model dry season biomass for the years 2007, 2008, 2009, and 2010 for the study area. The results from model validation showed a significant linear relationship between TLS-derived predictors with field biomass, p < 0.05 and adjusted R2 ranging between 0.56 for SAR to 0.93 for the TLS-derived canopy cover and height. Log-transformed AGB yielded lower errors with TLS metrics compared with non-transformed AGB. An assessment of the backscatter based on root mean square error (RMSE showed better AGB prediction with cross-polarized (RMSE = 6.6 t/ha as opposed to co-polarized data (RMSE = 6.7 t/ha, attributed to

  5. Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics

    DEFF Research Database (Denmark)

    Slik, J.W.Ferry; Paoli, Gary; McGuire, Krista

    2013-01-01

    Aim Large trees (d.b.h. ≥ 70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore...

  6. Spatial and temporal variations in aboveground and belowground biomass of Spartina maritima (small cordgrass) in created and natural marshes

    Science.gov (United States)

    Castillo, Jesús M.; Leira-Doce, Pablo; Rubio-Casal, Alfredo E.; Figueroa, Enrique

    2008-07-01

    Spartina species are commonly used for salt marsh manipulative projects, where aboveground and belowground biomasses are functional traits that play important roles, showing high spatial and temporal variations. This work analyses variations in AGB and BGB of Spartina maritima and abiotic environmental parameters along a chronosequence of six marshes created from 1997 to 2003 with disparate sediment dynamics, and adjacent natural marshes and unvegetated tidal flats. S. maritima behaved as an autogenic engineer, as its colonization of bare sediments yielded abiotic environmental changes: specifically, bed level rise accompanied by higher oxygenation and salinity. These modifications of the environment were site-specific, depending mainly on sedimentary dynamics. At the same time, abiotic environmental changes determined biomass production rates of S. maritima that were higher in more-accreting marshes; however, AGB was kept constant from early in its development (2 years). The increase in BGB with elevation seemed to be related to the inhibition of subsurface tissue development in anoxic sediments. Biomass accumulation and production varied markedly, depending on the spatial scale, indicating the relevance of the plot size chosen for the analysis of biomass of cordgrasses. Our results show that managers of salt marshes should consider sedimentary dynamics carefully when setting realistic expectations for success criteria of created and restored wetlands.

  7. Estimates of US biomass energy consumption 1992

    Energy Technology Data Exchange (ETDEWEB)

    1994-05-06

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  8. Estimates of US biomass energy consumption 1992

    International Nuclear Information System (INIS)

    1994-01-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large

  9. Estimating Biomass of Barley Using Crop Surface Models (CSMs Derived from UAV-Based RGB Imaging

    Directory of Open Access Journals (Sweden)

    Juliane Bendig

    2014-10-01

    Full Text Available Crop monitoring is important in precision agriculture. Estimating above-ground biomass helps to monitor crop vitality and to predict yield. In this study, we estimated fresh and dry biomass on a summer barley test site with 18 cultivars and two nitrogen (N-treatments using the plant height (PH from crop surface models (CSMs. The super-high resolution, multi-temporal (1 cm/pixel CSMs were derived from red, green, blue (RGB images captured from a small unmanned aerial vehicle (UAV. Comparison with PH reference measurements yielded an R2 of 0.92. The test site with different cultivars and treatments was monitored during “Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie” (BBCH Stages 24–89. A high correlation was found between PH from CSMs and fresh biomass (R2 = 0.81 and dry biomass (R2 = 0.82. Five models for above-ground fresh and dry biomass estimation were tested by cross-validation. Modelling biomass between different N-treatments for fresh biomass produced the best results (R2 = 0.71. The main limitation was the influence of lodging cultivars in the later growth stages, producing irregular plant heights. The method has potential for future application by non-professionals, i.e., farmers.

  10. Efficacy of generic allometric equations for estimating biomass: a test in Japanese natural forests.

    Science.gov (United States)

    Ishihara, Masae I; Utsugi, Hajime; Tanouchi, Hiroyuki; Aiba, Masahiro; Kurokawa, Hiroko; Onoda, Yusuke; Nagano, Masahiro; Umehara, Toru; Ando, Makoto; Miyata, Rie; Hiura, Tsutom

    2015-07-01

    Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved

  11. Net aboveground biomass declines of four major forest types with forest ageing and climate change in western Canada's boreal forests.

    Science.gov (United States)

    Chen, Han Y H; Luo, Yong

    2015-10-01

    Biomass change of the world's forests is critical to the global carbon cycle. Despite storing nearly half of global forest carbon, the boreal biome of diverse forest types and ages is a poorly understood component of the carbon cycle. Using data from 871 permanent plots in the western boreal forest of Canada, we examined net annual aboveground biomass change (ΔAGB) of four major forest types between 1958 and 2011. We found that ΔAGB was higher for deciduous broadleaf (DEC) (1.44 Mg ha(-1)  year(-1) , 95% Bayesian confidence interval (CI), 1.22-1.68) and early-successional coniferous forests (ESC) (1.42, CI, 1.30-1.56) than mixed forests (MIX) (0.80, CI, 0.50-1.11) and late-successional coniferous (LSC) forests (0.62, CI, 0.39-0.88). ΔAGB declined with forest age as well as calendar year. After accounting for the effects of forest age, ΔAGB declined by 0.035, 0.021, 0.032 and 0.069 Mg ha(-1)  year(-1) per calendar year in DEC, ESC, MIX and LSC forests, respectively. The ΔAGB declines resulted from increased tree mortality and reduced growth in all forest types except DEC, in which a large biomass loss from mortality was accompanied with a small increase in growth. With every degree of annual temperature increase, ΔAGB decreased by 1.00, 0.20, 0.55 and 1.07 Mg ha(-1)  year(-1) in DEC, ESC, MIX and LSC forests, respectively. With every cm decrease of annual climatic moisture availability, ΔAGB decreased 0.030, 0.045 and 0.17 Mg ha(-1)  year(-1) in ESC, MIX and LSC forests, but changed little in DEC forests. Our results suggest that persistent warming and decreasing water availability have profound negative effects on forest biomass in the boreal forests of western Canada. Furthermore, our results indicate that forest responses to climate change are strongly dependent on forest composition with late-successional coniferous forests being most vulnerable to climate changes in terms of aboveground biomass. © 2015 John Wiley & Sons Ltd.

  12. Predicting small-diameter loblolly pine aboveground biomass in naturally regenerated stands

    Science.gov (United States)

    Kristin M. McElligott; Don C. Bragg; Jamie L. Schuler

    2015-01-01

    There is growing interest in managing southern pine forests for both carbon sequestration and bioenergy. For instance, thinning otherwise unmerchantable trees in naturally regenerated pine-dominated forests should generate biomass without conflicting with more traditional forest products. However, we lack the tools to accurately quantify the biomass in these...

  13. Luxury consumption of soil nutrients: a possible competitive strategy in above-ground and below-ground biomass allocation and root morphology for slow-growing arctic vegetation?

    NARCIS (Netherlands)

    Wijk, van M.T.; Williams, M.; Gough, L.; Hobbie, S.E.; Shaver, G.R.

    2003-01-01

    1 A field-experiment was used to determine how plant species might retain dominance in an arctic ecosystem receiving added nutrients. We both measured and modelled the above-ground and below-ground biomass allocation and root morphology of non-acidic tussock tundra near Toolik Lake, Alaska, after 4

  14. Stand restoration burning in oak-pine forests in the southern Applachians: effects on aboveground biomass and carbon and nitrogen cycling

    Science.gov (United States)

    Robert M. Hubbard; James M. Vose; Barton D. Clinton; Katherine J. Elliott; Jennifer D. Knoepp

    2004-01-01

    Understory prescribed burning is being suggested as a viable management tool for restoring degraded oak–pine forest communities in the southern Appalachians yet information is lacking on how this will affect ecosystem processes. Our objectives in this study were to evaluate the watershed scale effects of understory burning on total aboveground biomass, and the carbon...

  15. Evaluation of drought and UV radiation impacts on above-ground biomass of mountain grassland by spectral reflectance and thermal imaging techniques

    Czech Academy of Sciences Publication Activity Database

    Novotná, Kateřina; Klem, Karel; Holub, Petr; Rapantová, Barbora; Urban, Otmar

    2016-01-01

    Roč. 9, 1-2 (2016), s. 21-30 ISSN 1803-2451 R&D Projects: GA MŠk(CZ) LO1415 Institutional support: RVO:67179843 Keywords : above-ground biomass * drought stress * grassland * UV radiation * precipitation * spectral reflectance * thermal imaging Subject RIV: EH - Ecology, Behaviour

  16. Aboveground biomass, wood volume, nutrient stocks and leaf litter in novel forests compared to native forests and tree plantations in Puerto Rico

    Science.gov (United States)

    A.E. Lugo; O. Abelleira Martínez; J. Fonseca da Silva

    2012-01-01

    The article presents comparative data for aboveground biomass, wood volume, nutirent stocks (N, P, K) and leaf litter in different types of forests in Puerto Rico. The aim of the study is to assess how novel forests of Castilla elastica, Panama Rubber Tree, and Spathodea campanulata, African Tulip Tree, compare with tree plantations and native historical forests (both...

  17. National-scale estimation of gross forest aboveground carbon loss: a case study of the Democratic Republic of the Congo

    Science.gov (United States)

    Tyukavina, A.; Stehman, S. V.; Potapov, P. V.; Turubanova, S. A.; Baccini, A.; Goetz, S. J.; Laporte, N. T.; Houghton, R. A.; Hansen, M. C.

    2013-12-01

    Recent advances in remote sensing enable the mapping and monitoring of carbon stocks without relying on extensive in situ measurements. The Democratic Republic of the Congo (DRC) is among the countries where national forest inventories (NFI) are either non-existent or out of date. Here we demonstrate a method for estimating national-scale gross forest aboveground carbon (AGC) loss and associated uncertainties using remotely sensed-derived forest cover loss and biomass carbon density data. Lidar data were used as a surrogate for NFI plot measurements to estimate carbon stocks and AGC loss based on forest type and activity data derived using time-series multispectral imagery. Specifically, DRC forest type and loss from the FACET (Forêts d’Afrique Centrale Evaluées par Télédétection) product, created using Landsat data, were related to carbon data derived from the Geoscience Laser Altimeter System (GLAS). Validation data for FACET forest area loss were created at a 30-m spatial resolution and compared to the 60-m spatial resolution FACET map. We produced two gross AGC loss estimates for the DRC for the last decade (2000-2010): a map-scale estimate (53.3 ± 9.8 Tg C yr-1) accounting for whole-pixel classification errors in the 60-m resolution FACET forest cover change product, and a sub-grid estimate (72.1 ± 12.7 Tg C yr-1) that took into account 60-m cells that experienced partial forest loss. Our sub-grid forest cover and AGC loss estimates, which included smaller-scale forest disturbances, exceed published assessments. Results raise the issue of scale in forest cover change mapping and validation, and subsequent impacts on remotely sensed carbon stock change estimation, particularly for smallholder dominated systems such as the DRC.

  18. A tree biomass and carbon estimation system

    Science.gov (United States)

    Emily B. Schultz; Thomas G. Matney; Donald L. Grebner

    2013-01-01

    Appropriate forest management decisions for the developing woody biofuel and carbon credit markets require inventory and growth-and-yield systems reporting component tree dry weight biomass estimates. We have developed an integrated growth-and-yield and biomass/carbon calculator. The objective was to provide Mississippi’s State inventory system with bioenergy economic...

  19. Forest biomass estimated from MODIS and FIA data in the Lake States: MN, WI and MI, USA

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey

    2007-01-01

    This study linked the Moderate Resolution Imaging Spectrometer and USDA Forest Service, Forest Inventory and Analysis (FIA) data through empirical models established using high-resolution Landsat Enhanced Thematic Mapper Plus observations to estimate aboveground biomass (AGB) in three Lake States in the north-central USA. While means obtained from larger sample sizes...

  20. Effect of growth regulator Kelpak SL on the formation of aboveground biomass of Festulolium braunii (K. Richt. A. Camus

    Directory of Open Access Journals (Sweden)

    Jacek Sosnowski

    2013-07-01

    Full Text Available A study on the cultivation of Festulolium braunii cv. 'Felopa' was carried out using polyurethane rings with a diameter of 36 cm and a height of 40 cm, which were sunk into the ground to a depth of 30 cm and filled with soil material. In this experiment, Kelpak SL was used as a bioregulator. It consists of natural plant hormones such as auxins (11 mg in dm3 and cytokinins (0.03 mg in dm3. The experimental factors were as follows: A1-control; A2 – 20% solution of the growth regulator; A3 – 40% solution; and A4 – 60% solution. The preparation was applied to all three regrowths in the form of spray, at a rate of 3 cm3 ring-1, at the stem elongation stage. The full period of this experiment was in the years 2010–2011. During this time, detailed investigations were carried out on aboveground biomass yield (g DM ring-1, number of shoots (pcs ring-1, leaf blade length (cm, width of the leaf blade base (mm, leaf greenness index (SPAD. The study showed a significant effect of the growth regulator on the formation of Festulolium braunii biomass. However, its highest effectiveness was observed when the 60% solution was applied.

  1. Volume and aboveground biomass models for dry Miombo woodland in Tanzania

    DEFF Research Database (Denmark)

    Mwakalukwa, Ezekiel Edward; Meilby, Henrik; Treue, Thorsten

    2014-01-01

    and biomass of three important species, Brachystegia spiciformis Benth. (n=40), Combretum molle G. Don (n=41), and Dalbergia arbutifolia Baker (n=37) separately, and for broader samples of trees (28 species, n=72), shrubs (16 species, n=31), and trees and shrubs combined (44 species, n=104). Applied...

  2. Aboveground biomass equations for 7-year-old Acacia mangium Willd in Botucatu, Brazil

    Science.gov (United States)

    Ricardo A. A. Veiga; Maria A. M. Brasil; Carlos M. Carvalho

    2000-01-01

    The biomass of steins, leaves, and branches was determined for 152 sample trees of Acacia mangium Willd were in a 7-year-old experimental plantation in Botucatu, Sao Paulo State, Brazil. After felling, dimensional measurements were taken from each tree. Cross sections were collected in 125 sample trees at ground level (0 percent), 25 percent, 50...

  3. Aboveground herbivory shapes the biomass distribution and flux of soil invertebrates.

    Directory of Open Access Journals (Sweden)

    Christian Mulder

    Full Text Available BACKGROUND: Living soil invertebrates provide a universal currency for quality that integrates physical and chemical variables with biogeography as the invertebrates reflect their habitat and most ecological changes occurring therein. The specific goal was the identification of "reference" states for soil sustainability and ecosystem functioning in grazed vs. ungrazed sites. METHODOLOGY/PRINCIPAL FINDINGS: Bacterial cells were counted by fluorescent staining and combined direct microscopy and automatic image analysis; invertebrates (nematodes, mites, insects, oligochaetes were sampled and their body size measured individually to allow allometric scaling. Numerical allometry analyses food webs by a direct comparison of weight averages of components and thus might characterize the detrital soil food webs of our 135 sites regardless of taxonomy. Sharp differences in the frequency distributions are shown. Overall higher biomasses of invertebrates occur in grasslands, and all larger soil organisms differed remarkably. CONCLUSIONS/SIGNIFICANCE: Strong statistical evidence supports a hypothesis explaining from an allometric perspective how the faunal biomass distribution and the energetic flux are affected by livestock, nutrient availability and land use. Our aim is to propose faunal biomass flux and biomass distribution as quantitative descriptors of soil community composition and function, and to illustrate the application of these allometric indicators to soil systems.

  4. Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests

    Science.gov (United States)

    Vaglio Laurin, Gaia; Puletti, Nicola; Chen, Qi; Corona, Piermaria; Papale, Dario; Valentini, Riccardo

    2016-10-01

    Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests. This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables. We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment.

  5. Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania.

    Science.gov (United States)

    Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik

    2015-12-01

    Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.

  6. Tropical Africa: Land Use, Biomass, and Carbon Estimates for 1980 (NDP-055)

    Energy Technology Data Exchange (ETDEWEB)

    Brown, S.

    2002-04-16

    This document describes the contents of a digital database containing maximum potential aboveground biomass, land use, and estimated biomass and carbon data for 1980. The biomass data and carbon estimates are associated with woody vegetation in Tropical Africa. These data were collected to reduce the uncertainty associated with estimating historical releases of carbon from land use change. Tropical Africa is defined here as encompassing 22.7 x 10{sup 6} km{sup 2} of the earth's land surface and is comprised of countries that are located in tropical Africa (Angola, Botswana, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Congo, Benin, Equatorial Guinea, Ethiopia, Djibouti, Gabon, Gambia, Ghana, Guinea, Ivory Coast, Kenya, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger, Nigeria, Guinea-Bissau, Zimbabwe (Rhodesia), Rwanda, Senegal, Sierra Leone, Somalia, Sudan, Tanzania, Togo, Uganda, Burkina Faso (Upper Volta), Zaire, and Zambia). The database was developed using the GRID module in the ARC/INFO{trademark} geographic information system. Source data were obtained from the Food and Agriculture Organization (FAO), the U.S. National Geophysical Data Center, and a limited number of biomass-carbon density case studies. These data were used to derive the maximum potential and actual (ca. 1980) aboveground biomass values at regional and country levels. The land-use data provided were derived from a vegetation map originally produced for the FAO by the International Institute of Vegetation Mapping, Toulouse, France.

  7. The importance of crown dimensions to improve tropical tree biomass estimates.

    Science.gov (United States)

    Goodman, Rosa C; Phillips, Oliver L; Baker, Timothy R

    2014-06-01

    Tropical forests play a vital role in the global carbon cycle, but the amount of carbon they contain and its spatial distribution remain uncertain. Recent studies suggest that once tree height is accounted for in biomass calculations, in addition to diameter and wood density, carbon stock estimates are reduced in many areas. However, it is possible that larger crown sizes might offset the reduction in biomass estimates in some forests where tree heights are lower because even comparatively short trees develop large, well-lit crowns in or above the forest canopy. While current allometric models and theory focus on diameter, wood density, and height, the influence of crown size and structure has not been well studied. To test the extent to which accounting for crown parameters can improve biomass estimates, we harvested and weighed 51 trees (11-169 cm diameter) in southwestern Amazonia where no direct biomass measurements have been made. The trees in our study had nearly half of total aboveground biomass in the branches (44% +/- 2% [mean +/- SE]), demonstrating the importance of accounting for tree crowns. Consistent with our predictions, key pantropical equations that include height, but do not account for crown dimensions, underestimated the sum total biomass of all 51 trees by 11% to 14%, primarily due to substantial underestimates of many of the largest trees. In our models, including crown radius greatly improves performance and reduces error, especially for the largest trees. In addition, over the full data set, crown radius explained more variation in aboveground biomass (10.5%) than height (6.0%). Crown form is also important: Trees with a monopodial architectural type are estimated to have 21-44% less mass than trees with other growth patterns. Our analysis suggests that accounting for crown allometry would substantially improve the accuracy of tropical estimates of tree biomass and its distribution in primary and degraded forests.

  8. Allometric Equations for Estimating Compartment Biomass and Stem Volume in Mature Hybrid Poplars: General or Site-Specific?

    Directory of Open Access Journals (Sweden)

    Julien Fortier

    2017-08-01

    Full Text Available We evaluated the extent to which general or site-specific allometric equations, using diameter at breast height (DBH as a predictor, are more accurate for estimating stem volume, stem biomass, branch biomass, aboveground woody biomass, and coarse root biomass in 14 year-old plantations of Populus canadensis × Populus maximowiczii (clone DN × M-915508 located along an environmental gradient in southern Québec (eastern Canada. The effect of tree size and site on stem wood basic density, moisture content, and proportion of branch biomass was also evaluated. For stem volume, stem biomass, and aboveground biomass, site-specific and general models had comparable fit and accuracy, but lower Akaike’s Information Criterion (AICc values were observed for the general models. For the branch and coarse root biomass, higher fit and accuracy and lower AICc values were observed for the site-specific models. Allometric trajectory changes (plastic allometry across sites were mainly observed for coarse root biomass, branch biomass, and stem volume. On the low fertility site, allocation was increased to coarse roots and decreased to stem volume. Site-specific tradeoffs between tree architecture and stem wood density explained the relatively invariant allometry for the whole aboveground woody biomass across the plantation sites. On the high fertility sites, basic wood density was the lowest and declined as tree DBH increased. At all sites, stem wood moisture content and the proportion of branch biomass increased with DBH. Overall, this study showed that biomass allometry, tree architecture, and biomass quality are a function of both tree size and plantation environment in hybrid poplar. Allometric model selection (site-specific or general should depend on the objective pursued (evaluation of yield, nutrient budget, carbon stocks.

  9. Influence of water level fluctuation on the mortality and aboveground biomass of the aquatic macrophyte Eleocharis interstincta (VAHL roemer et schults

    Directory of Open Access Journals (Sweden)

    Santos Anderson Medeiros dos

    2004-01-01

    Full Text Available The goal of this study was to study the biometric alterations of Eleocharis interstincta in response to water level fluctuations in Cabiúnas Lagoon, located on the northern coast of the state of Rio de Janeiro, in the municipality of Macaé. Three quadrats of 0.0625 m² were harvested every two weeks from June/1997 to June/1998; samples were separated into stems, dead stems (detritus and rhizome; lenghted, dried and weighted. The water level fluctuated seasonally in the macrophyte stand with two periods of drawdown. The first period occurred naturally at the end of winter and beginning of spring, when rainfall in the area was normally lowest. The second period of drawdown was the result of an artificial breaching of the sandbar that isolate the lagoon from the sea. The breach was made in the summer, at the time of highest rainfall, when the water level in the lagoon reached the maximum value recorded during the study (1.35 m. There was a strongly positive correlation of the water level with stems mean height and aboveground biomass, indicating that water level played an important role in the determination of these parameters. There was a significant difference between stem height (ANOVA; p < 0.001 and biomass (ANOVA; p < 0.001 in each sampling period, ranging from 143.9 cm and 338.8 g dry wt.m-2, before the sandbar opening, to 16.3 cm and 20.2 g dry wt.m-2 respectively after the sandbar breaching. The drastic variation of the water level, leading mass mortality of the stems, together with the lowest mean biomass/stem (0.057 g dry wt.individual-1, recorded after the sandbar breaching, did not represent a strong disturbance for E. interstincta, since the resilience time estimated for this population was about 30 days.

  10. Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models.

    Science.gov (United States)

    Johnson, Michelle O; Galbraith, David; Gloor, Manuel; De Deurwaerder, Hannes; Guimberteau, Matthieu; Rammig, Anja; Thonicke, Kirsten; Verbeeck, Hans; von Randow, Celso; Monteagudo, Abel; Phillips, Oliver L; Brienen, Roel J W; Feldpausch, Ted R; Lopez Gonzalez, Gabriela; Fauset, Sophie; Quesada, Carlos A; Christoffersen, Bradley; Ciais, Philippe; Sampaio, Gilvan; Kruijt, Bart; Meir, Patrick; Moorcroft, Paul; Zhang, Ke; Alvarez-Davila, Esteban; Alves de Oliveira, Atila; Amaral, Ieda; Andrade, Ana; Aragao, Luiz E O C; Araujo-Murakami, Alejandro; Arets, Eric J M M; Arroyo, Luzmila; Aymard, Gerardo A; Baraloto, Christopher; Barroso, Jocely; Bonal, Damien; Boot, Rene; Camargo, Jose; Chave, Jerome; Cogollo, Alvaro; Cornejo Valverde, Fernando; Lola da Costa, Antonio C; Di Fiore, Anthony; Ferreira, Leandro; Higuchi, Niro; Honorio, Euridice N; Killeen, Tim J; Laurance, Susan G; Laurance, William F; Licona, Juan; Lovejoy, Thomas; Malhi, Yadvinder; Marimon, Bia; Marimon, Ben Hur; Matos, Darley C L; Mendoza, Casimiro; Neill, David A; Pardo, Guido; Peña-Claros, Marielos; Pitman, Nigel C A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Roopsind, Anand; Rudas, Agustin; Salomao, Rafael P; Silveira, Marcos; Stropp, Juliana; Ter Steege, Hans; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van der Heijden, Geertje M F; Vasquez, Rodolfo; Guimarães Vieira, Ima Cèlia; Vilanova, Emilio; Vos, Vincent A; Baker, Timothy R

    2016-12-01

    Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

  11. Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon

    Science.gov (United States)

    Yunyun Feng; Dengsheng Lu; Qi Chen; Michael Keller; Emilio Moran; Maiza Nara dos-Santos; Edson Luis Bolfe; Mateus Batistella

    2017-01-01

    Previous research has explored the potential to integrate lidar and optical data in aboveground biomass (AGB) estimation, but how different data sources, vegetation types, and modeling algorithms influence AGB estimation is poorly understood. This research conducts a comparative analysis of different data sources and modeling approaches in improving AGB estimation....

  12. Using basal area to estimate aboveground carbon stocks in forests: La Primavera Biosphere's Reserve, Mexico

    NARCIS (Netherlands)

    Balderas Torres, Arturo; Lovett, Jonathan Cranidge

    2012-01-01

    Increasing use of woody plants for greenhouse gas mitigation has led to demand for rapid, cost-effective estimation of forest carbon stocks. Bole diameter is readily measured and basal area can be correlated to biomass and carbon through application of allometric equations. We explore different

  13. The effect of air elevated [CO2] on crown architecture and aboveground biomass in Norway spruce

    Czech Academy of Sciences Publication Activity Database

    Pokorný, Radek; Tomášková, Ivana; Slípková, Romana

    2012-01-01

    Roč. 18, č. 1 (2012), s. 2-11 ISSN 1392-1355 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073; GA MŽP(CZ) SP/2D1/70/08; GA MŽP(CZ) SP/2D1/93/07; GA AV ČR IAA600870701; GA MŠk(CZ) EE2.4.31.0056 Institutional research plan: CEZ:AV0Z60870520 Keywords : thinning * secondary shoots * biomass allocation * long-term experiment * dendrometry Subject RIV: EH - Ecology, Behaviour Impact factor: 0.379, year: 2012

  14. Determining aboveground biomass of the forest successional chronosequence in a test-site of Brazilian Amazon through X- and L-band data analysis

    Science.gov (United States)

    Santos, João. R.; Silva, Camila V. d. J.; Galvão, Lênio S.; Treuhaft, Robert; Mura, José C.; Madsen, Soren; Gonçalves, Fábio G.; Keller, Michael M.

    2014-08-01

    Secondary succession is an important process in the Amazonian region with implications for the global carbon cycle and for the sustainable regional agricultural and pasture activities. In order to better discriminate the secondary succession and to characterize and estimate the aboveground biomass (AGB), backscatter and interferometric SAR data generally have been analyzed through empirical-based statistical modeling. The objective of this study is to verify the capability of the full polarimetric PALSAR/ALOS (L-band) attributes, when combined with the interferometric (InSAR) coherence from the TanDEM-X (X-band), to improve the AGB estimates of the succession chronosequence located in the Brazilian Tapajós region. In order to perform this study, we carried out multivariate regression using radar attributes and biophysical parameters acquired during a field inventory. A previous floristic-structural analysis was performed to establish the chronosequence in three stages: initial vegetation regrowth, intermediate, and advanced regrowth. The relationship between PALSAR data and AGB was significant (p<0.001) and results suggested that the "volumetric scattering" (Pv) and "anisotropy" (A) attributes were important to explain the biomass content of the successional chronosequence (R2adjusted = 0.67; RMSE = 32.29 Mg.ha-1). By adding the TanDEM-derived interferometric coherence (Υi) into the regression modeling, better results were obtained (R2adjusted = 0.75; RMSE = 28.78Mg.ha-1). When we used both the L- and X-band attributes, the stock density prediction improved to 10.8 % for the secondary succession stands.

  15. A universal approach to estimate biomass and carbon stock in tropical forests using generic allometric models.

    Science.gov (United States)

    Vieilledent, G; Vaudry, R; Andriamanohisoa, S F D; Rakotonarivo, O S; Randrianasolo, H Z; Razafindrabe, H N; Rakotoarivony, C Bidaud; Ebeling, J; Rasamoelina, M

    2012-03-01

    Allometric equations allow aboveground tree biomass and carbon stock to be estimated from tree size. The allometric scaling theory suggests the existence of a universal power-law relationship between tree biomass and tree diameter with a fixed scaling exponent close to 8/3. In addition, generic empirical models, like Chave's or Brown's models, have been proposed for tropical forests in America and Asia. These generic models have been used to estimate forest biomass and carbon worldwide. However, tree allometry depends on environmental and genetic factors that vary from region to region. Consequently, theoretical models that include too few ecological explicative variables or empirical generic models that have been calibrated at particular sites are unlikely to yield accurate tree biomass estimates at other sites. In this study, we based our analysis on a destructive sample of 481 trees in Madagascar spiny dry and moist forests characterized by a high rate of endemism (> 95%). We show that, among the available generic allometric models, Chave's model including diameter, height, and wood specific gravity as explicative variables for a particular forest type (dry, moist, or wet tropical forest) was the only one that gave accurate tree biomass estimates for Madagascar (R2 > 83%, bias allometric models. When biomass allometric models are not available for a given forest site, this result shows that a simple height-diameter allometry is needed to accurately estimate biomass and carbon stock from plot inventories.

  16. Forest biomass estimation from polarimetric SAR interferometry

    Energy Technology Data Exchange (ETDEWEB)

    Mette, T.

    2007-07-01

    Polarimetric SAR interferometry (Pol-InSAR) is a radar remote sensing technique that allows extracting forest heights by means of model-based inversions. Forest biomass is closely related to forest height, and can be derived from it with allometric relations. This work investigates the combination of the two methods to estimate forest biomass from Pol-InSAR. It develops a concept for the use of height-biomass allometry, and outlines the Pol-InSAR height inversion. The methodology is validated against a set of forest inventory data and Pol-InSAR data at L-band of the test site Traunstein. The results allow drawing conclusions on the potential of Pol-InSAR forest biomass missions. (orig.)

  17. Allometric Equations for Estimating Above Ground Biomass

    African Journals Online (AJOL)

    Allometric Equations for Estimating Above Ground Biomass of Rhl'zophom mucronata Lamk. (Rhizophoraceae). Mangroves at Gazi Bay, Kenya. Kirui, B.,1 Kairo, 1.6.2 and Karachi, M.1. 'Egerton University. P. O. Box 536, Njoro. Kenya; 2Kenya Marine and Fisheries Research Institute. PO. Box 8165], Mombasa, Kenya.

  18. Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

    Directory of Open Access Journals (Sweden)

    Sandra Eckert

    2012-03-01

    Full Text Available Accurate estimation of aboveground biomass and carbon stock has gained importance in the context of the United Nations Framework Convention on Climate Change (UNFCCC and the Kyoto Protocol. In order to develop improved forest stratum–specific aboveground biomass and carbon estimation models for humid rainforest in northeast Madagascar, this study analyzed texture measures derived from WorldView-2 satellite data. A forest inventory was conducted to develop stratum-specific allometric equations for dry biomass. On this basis, carbon was calculated by applying a conversion factor. After satellite data preprocessing, vegetation indices, principal components, and texture measures were calculated. The strength of their relationships with the stratum-specific plot data was analyzed using Pearson’s correlation. Biomass and carbon estimation models were developed by performing stepwise multiple linear regression. Pearson’s correlation coefficients revealed that (a texture measures correlated more with biomass and carbon than spectral parameters, and (b correlations were stronger for degraded forest than for non-degraded forest. For degraded forest, the texture measures of Correlation, Angular Second Moment, and Contrast, derived from the red band, contributed to the best estimation model, which explained 84% of the variability in the field data (relative RMSE = 6.8%. For non-degraded forest, the vegetation index EVI and the texture measures of Variance, Mean, and Correlation, derived from the newly introduced coastal blue band, both NIR bands, and the red band, contributed to the best model, which explained 81% of the variability in the field data (relative RMSE = 11.8%. These results indicate that estimation of tropical rainforest biomass/carbon, based on very high resolution satellite data, can be improved by (a developing and applying forest stratum–specific models, and (b including textural information in addition to spectral information.

  19. Allometric equations for estimating standing biomass of Avicennia marina in Bushehr of Iran

    Directory of Open Access Journals (Sweden)

    Akbar Ghasemi

    2016-07-01

    Full Text Available Today, it is important to use of ecological indicators, such as biomass for recognizing the special status of ecosystems, such as mangrove forests and also monitoring and evaluating changes through a specific period. Because using the direct method of evaluating biomass would be destructive, it is common in all similar area to use determine exact Allometric equations by using the statistical relationship between the structural characteristics of trees and their biomass and use these equations to estimate the biomass of trees. The aim of this study is estimate the aboveground biomass of mangroves and determine Allometric models for Nayband area in Bushehr, located in southern Iran. A number of mangrove trees were randomly selected. Collar diameter, crown diameter and tree height of standing trees were measured. After logging and weighing fresh weight, dry weight, trunk and branches were obtained in laboratory and biomass of components was calculated. The relationship between quantities feature of trees and biomass for determination of allometric equation was studied by using linear, power and exponential regression. The equations were compared with each other based on the different modeling parameters. The highest significant correlation was found between crown diameters and dry weight (R > 0.90. The best equations were obtained by means of an exponential and power regression models (R2adj> 0.90. The models were obtained from explained factor, suggests that there might be a relationship between the characteristics of mangrove trees and biomass.

  20. Potential for post-closure radionuclide redistribution due to biotic intrusion: aboveground biomass, litter production rates, and the distribution of root mass with depth at material disposal area G, Los Alamos National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    French, Sean B [Los Alamos National Laboratory; Christensen, Candace [Los Alamos National Laboratory; Jennings, Terry L [Los Alamos National Laboratory; Jaros, Christopher L [Los Alamos National Laboratory; Wykoff, David S [Los Alamos National Laboratory; Crowell, Kelly J [Los Alamos National Laboratory; Shuman, Rob [URS

    2008-01-01

    Low-level radioactive waste (LLW) generated at the Los Alamos National Laboratories (LANL) is disposed of at LANL's Technical Area (T A) 54, Material Disposal Area (MDA) G. The ability of MDA G to safely contain radioactive waste during current and post-closure operations is evaluated as part of the facility's ongoing performance assessment (PA) and composite analysis (CA). Due to the potential for uptake and incorporation of radio nuclides into aboveground plant material, the PA and CA project that plant roots penetrating into buried waste may lead to releases of radionuclides into the accessible environment. The potential amount ofcontamination deposited on the ground surface due to plant intrusion into buried waste is a function of the quantity of litter generated by plants, as well as radionuclide concentrations within the litter. Radionuclide concentrations in plant litter is dependent on the distribution of root mass with depth and the efficiency with which radionuclides are extracted from contaminated soils by the plant's roots. In order to reduce uncertainties associated with the PA and CA for MDA G, surveys are being conducted to assess aboveground biomass, plant litter production rates, and root mass with depth for the four prominent vegetation types (grasses, forbs, shrubs and trees). The collection of aboveground biomass for grasses and forbs began in 2007. Additional sampling was conducted in October 2008 to measure root mass with depth and to collect additional aboveground biomass data for the types of grasses, forbs, shrubs, and trees that may become established at MDA G after the facility undergoes final closure, Biomass data will be used to estimate the future potential mass of contaminated plant litter fall, which could act as a latent conduit for radionuclide transport from the closed disposal area. Data collected are expected to reduce uncertainties associated with the PA and CA for MDA G and ultimately aid in the assessment and

  1. Non-Parametric Responses of Aboveground Biomass and NDVI to Land Surface Parameters in Arctic-Alpine Environments

    Science.gov (United States)

    Riihimäki, H. K.; Heiskanen, J.; Luoto, M.

    2015-12-01

    Aboveground biomass (AGB) is an important carbon pool and it affects various phenomena in Arctic and alpine areas, e.g. biodiversity, surface albedo and soil conditions. The growing availability of high-resolution digital elevation models (DEM) makes it possible to utilize topographical information for modeling local ground surface conditions globally. We investigated the effect of topography on field measured AGB (n = 359) and its commonly used proxy, the Normalized Difference Vegetation Index (NDVI) calculated from SPOT 5 imagery. The study area located in an Arctic-alpine treeline environment (69 °N, 21 °E). We performed the analyses with boosted regression trees method by using elevation and four land surface parameters (LSPs), derived from 10 m DEM, as predictors. The LSPs were namely Potential Incoming Solar Radiation (PISR, MJ m-2 a-1), Topographic Position Index (TPI, r = 300 m), Slope (angle in degrees) and Topographic Wetness Index (TWI). AGB varied from 0 to 5647 g m-2, while median AGB of the data was 449 g m-2. The explained deviance of the AGB and NDVI models were 53 % and 65 %, respectively. Elevation and PISR were the most important predictors. Their interaction was also significant in both cases as the highest AGB were at low-elevation, high-radiation sites, which implicates that PISR significantly improves the modelling of temperature related growing conditions. TWI had no clear effect to AGB nor to NDVI. TPI and Slope had a minor effect on AGB, but no effect to NDVI. Areas lower than their surroundings (negative TPI) had relatively high AGB. Furthermore, steeper slopes had higher AGB compared to flat sites. This is probably caused by the presence of mountain birch (Betula pubescens ssp. czerepanovii), which favors protected and steeper topography. Local topography is an important driver of the fine scale AGB patterns. Thus, DEM derived LSPs should be taken into account when modelling current and future biomass distributions in Arctic and alpine

  2. Mapping forest aboveground biomass using airborne hyperspectral and LiDAR data in the mountainous conditions of Central Europe

    Czech Academy of Sciences Publication Activity Database

    Brovkina, Olga; Novotný, Jan; Cienciala, E.; Zemek, František; Russ, R.

    2017-01-01

    Roč. 100, Mar (2017), s. 219-230 ISSN 0925-8574 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk OC09001 Institutional support: RVO:67179843 Keywords : biomass estimation * spruce * beech * airborne remote sensing * tree level * plot level Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7) Impact factor: 2.914, year: 2016

  3. Biomass statistics for the Northern United States

    Science.gov (United States)

    Eric H. Wharton; Gerhard K. Raile

    1984-01-01

    The USDA Forest Service now estimates biomass during periodic resource inventories. Such biomass estimates quantify more of the forest resource than do traditional volume inventories that concentrate on tree boles. More than 48 percent of the aboveground tree biomass in the northern United States can be found in woody material outside of the boles. Tree biomass in the...

  4. Intermediate herbivory intensity of an aboveground pest promotes soil labile resources and microbial biomass via modifying rice growth

    NARCIS (Netherlands)

    Huang, J.; Liu, M.; Chen, X.; Chen, J.; Chen, F.; Li, H.; Hu, F.

    2013-01-01

    The importance of aboveground herbivores for modifying belowground ecosystems has prompted numerous studies; however, studies can be biased by context dependent conditions which lead to extremely inconsistent results. So far, the impacts of herbivory inte

  5. National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

    Science.gov (United States)

    Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

    2017-12-01

    Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the

  6. Live above- and belowground biomass of a Mozambican evergreen forest: a comparison of estimates based on regression equations and biomass expansion factors

    Directory of Open Access Journals (Sweden)

    Tarquinio Mateus Magalhães

    2015-10-01

    Full Text Available Background Biomass regression equations are claimed to yield the most accurate biomass estimates than biomass expansion factors (BEFs. Yet, national and regional biomass estimates are generally calculated based on BEFs, especially when using national forest inventory data. Comparison of regression equations based and BEF-based biomass estimates are scarce. Thus, this study was intended to compare these two commonly used methods for estimating tree and forest biomass with regard to errors and biases. Methods The data were collected in 2012 and 2014. In 2012, a two-phase sampling design was used to fit tree component biomass regression models and determine tree BEFs. In 2014, additional trees were felled outside sampling plots to estimate the biases associated with regression equation based and BEF-based biomass estimates; those estimates were then compared in terms of the following sources of error: plot selection and variability, biomass model, model parameter estimates, and residual variability around model prediction. Results The regression equation based below-, aboveground and whole tree biomass stocks were, approximately, 7.7, 8.5 and 8.3 % larger than the BEF-based ones. For the whole tree biomass stock, the percentage of the total error attributed to first phase (random plot selection and variability was 90 and 88 % for regression- and BEF-based estimates, respectively, being the remaining attributed to biomass models (regression and BEF models, respectively. The percent bias of regression equation based and BEF-based biomass estimates for the whole tree biomass stock were −2.7 and 5.4 %, respectively. The errors due to model parameter estimates, those due to residual variability around model prediction, and the percentage of the total error attributed to biomass model were larger for BEF models (than for regression models, except for stem and stem wood components. Conclusions The regression equation based biomass stocks were found to

  7. Growth, aboveground biomass, and nutrient concentration of young Scots pine and lodgepole pine in oil shale post-mining landscapes in Estonia.

    Science.gov (United States)

    Kuznetsova, Tatjana; Tilk, Mari; Pärn, Henn; Lukjanova, Aljona; Mandre, Malle

    2011-12-01

    The investigation was carried out in 8-year-old Scots pine (Pinus sylvestris L.) and lodgepole pine (Pinus contorta var. latifolia Engelm.) plantations on post-mining area, Northeast Estonia. The aim of the study was to assess the suitability of lodgepole pine for restoration of degraded lands by comparing the growth, biomass, and nutrient concentration of studied species. The height growth of trees was greater in the Scots pine stand, but the tree aboveground biomass was slightly larger in the lodgepole pine stand. The aboveground biomass allocation to the compartments did not differ significantly between species. The vertical distribution of compartments showed that 43.2% of the Scots pine needles were located in the middle layer of the crown, while 58.5% of the lodgepole pine needles were in the lowest layer of the crown. The largest share of the shoots and stem of both species was allocated to the lowest layer of the crown. For both species, the highest NPK concentrations were found in the needles and the lowest in the stems. On the basis of the present study results, it can be concluded that the early growth of Scots pine and lodgepole pine on oil shale post-mining landscapes is similar.

  8. Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest

    Directory of Open Access Journals (Sweden)

    Ryan D. Sheridan

    2014-12-01

    Full Text Available The United States Forest Service Forest Inventory and Analysis (FIA Program provides a diverse selection of data used to assess the status of the nation’s forests using sample locations dispersed throughout the country. Airborne laser scanning (ALS systems are capable of producing accurate measurements of individual tree dimensions and also possess the ability to characterize forest structure in three dimensions. This study investigates the potential of discrete return ALS data for modeling forest aboveground biomass (AGBM and gross volume (gV at FIA plot locations in the Malheur National Forest, eastern Oregon utilizing three analysis levels: (1 individual subplot (r = 7.32 m; (2 plot, comprising four clustered subplots; and (3 hectare plot (r = 56.42 m. A methodology for the creation of three point cloud-based airborne LiDAR metric sets is presented. Models for estimating AGBM and gV based on LiDAR-derived height metrics were built and validated utilizing FIA estimates of AGBM and gV derived using regional allometric equations. Simple linear regression models based on the plot-level analysis out performed subplot-level and hectare-level models, producing R2 values of 0.83 and 0.81 for AGBM and gV, utilizing mean height and the 90th height percentile as predictors, respectively. Similar results were found for multiple regression models, where plot-level analysis produced models with R2 values of 0.87 and 0.88 for AGBM and gV, utilizing multiple height percentile metrics as predictor variables. Results suggest that the current FIA plot design can be used with dense airborne LiDAR data to produce area-based estimates of AGBM and gV, and that the increased spatial scale of hectare plots may be inappropriate for modeling AGBM of gV unless exhaustive tree tallies are available. Overall, this study demonstrates that ALS data can be used to create models that describe the AGBM and gV of Pacific Northwest FIA plots and highlights the potential of

  9. Object-Based Mapping of Aboveground Biomass in Tropical Forests Using LiDAR and Very-High-Spatial-Resolution Satellite Data

    Directory of Open Access Journals (Sweden)

    Yasumasa Hirata

    2018-03-01

    Full Text Available Developing countries that intend to implement the United Nations REDD-plus (Reducing Emissions from Deforestation and forest Degradation, and the role of forest conservation, sustainable management of forests, and enhancement of forest carbon stocks framework and obtain economic incentives are required to estimate changes in forest carbon stocks based on the IPCC guidelines. In this study, we developed a method to support REDD-plus implementation by estimating tropical forest aboveground biomass (AGB by combining airborne LiDAR with very-high-spatial-resolution satellite data. We acquired QuickBird satellite images of Kampong Thom, Cambodia in 2011 and airborne LiDAR measurements in some parts of the same area. After haze reduction and atmospheric correction of the satellite data, we calibrated reflectance values from the mean reflectance of the objects (obtained by segmentation from areas of overlap between dates to reduce the effects of the observation angle and solar elevation. Then, we performed object-based classification using the satellite data (overall accuracy = 77.0%, versus 92.9% for distinguishing forest from non-forest land. We used a two-step method to estimate AGB and map it in a tropical environment in Cambodia. First, we created a multiple-regression model to estimate AGB from the LiDAR data and plotted field-surveyed AGB values against AGB values predicted by the LiDAR-based model (R2 = 0.90, RMSE = 38.7 Mg/ha, and calculated reflectance values in each band of the satellite data for the analyzed objects. Then, we created a multiple-regression model using AGB predicted by the LiDAR-based model as the dependent variable and the mean and standard deviation of the reflectance values in each band of the satellite data as the explanatory variables (R2 = 0.73, RMSE = 42.8 Mg/ha. We calculated AGB of all objects, divided the results into density classes, and mapped the resulting AGB distribution. Our results suggest that this approach

  10. Measuring bulrush culm relationships to estimate plant biomass within a southern California treatment wetland

    Science.gov (United States)

    Daniels, Joan S. (Thullen); Cade, Brian S.; Sartoris, James J.

    2010-01-01

    Assessment of emergent vegetation biomass can be time consuming and labor intensive. To establish a less onerous, yet accurate method, for determining emergent plant biomass than by direct measurements we collected vegetation data over a six-year period and modeled biomass using easily obtained variables: culm (stem) diameter, culm height and culm density. From 1998 through 2005, we collected emergent vegetation samples (Schoenoplectus californicus andSchoenoplectus acutus) at a constructed treatment wetland in San Jacinto, California during spring and fall. Various statistical models were run on the data to determine the strongest relationships. We found that the nonlinear relationship: CB=β0DHβ110ε, where CB was dry culm biomass (g m−2), DH was density of culms × average height of culms in a plot, and β0 and β1 were parameters to estimate, proved to be the best fit for predicting dried-live above-ground biomass of the two Schoenoplectus species. The random error distribution, ε, was either assumed to be normally distributed for mean regression estimates or assumed to be an unspecified continuous distribution for quantile regression estimates.

  11. Estimation of above ground biomass for multi-stemmed short-rotation woody crops

    Science.gov (United States)

    Brian A. Byrd; Wilson G. Hood; Michael C. Tyree; Dylan N. Dillaway

    2015-01-01

    With the increasing interest in short-rotation woody crop (SRWC) systems, an accurate yet quick, non-destructive means for determining aboveground biomass is necessary from both management and research perspectives.

  12. Estimates of biomass in logging residue and standing residual inventory following tree-harvest activity on timberland acres in the southern region

    Science.gov (United States)

    Roger C. Conner; Tony G. Johnson

    2011-01-01

    This report provides estimates of biomass (green tons) in logging residue and standing residual inventory on timberland acres with evidence of tree cutting. Biomass as defined by Forest Inventory and Analysis is the aboveground dry weight of wood in the bole and limbs of live trees ≥ 1-inch diameter at breast height (d.b.h.), and excludes tree foliage, seedlings, and...

  13. Analyzing spatial and temporal trends in Aboveground Biomass within the Acadian New England Forests using the complete Landsat Archive

    Science.gov (United States)

    Kilbride, J. B.; Fraver, S.; Ayrey, E.; Weiskittel, A.; Braaten, J.; Hughes, J. M.; Hayes, D. J.

    2017-12-01

    Forests within the New England states and Canadian Maritime provinces, here described as the Acadian New England (ANE) forests, have undergone substantial disturbances due to insect, fire, and anthropogenic factors. Through repeated satellite observations captures by USGS's Landsat program, 45 years of disturbance information can be incorporated into modeling efforts to better understand the spatial and temporal trends in forest above ground biomass (AGB). Using Google's Earth Engine, annual mosaics were developed for the ANE study area and then disturbance and recovery metrics were developed using the temporal segmentation algorithm VeRDET. Normalization procedures were developed to incorporate the Landsat Multispectral Scanner (MSS, 1972 - 1985) data alongside the modern era of Landsat Thematic Mapper (TM, 1984-2013), Enhanced Thematic Mapper plus (ETM+, 1999 - present), and Operational Land Imager (OLI, 2013- present) data products. This has enabled the creation of a dataset with an unprecedented spatial and temporal view of forest landscape change. Model training was performed using was the Forest Inventory Analysis (FIA) and New Brunswick Permanent Sample Plot data datasets. Modeling was performed using parametric techniques such as mixed effects models and non-parametric techniques such as k-NN imputation and generalized boosted regression. We compare the biomass estimate and model accuracy to other inventory and modeling studies produced within this study area. The spatial and temporal patterns of stock changes are analyzed against resource policy, land ownership changes, and forest management.

  14. Predicting tree heights for biomass estimates in tropical forests – a test from French Guiana

    Directory of Open Access Journals (Sweden)

    Q. Molto

    2014-06-01

    Full Text Available The recent development of REDD+ mechanisms requires reliable estimation of carbon stocks, especially in tropical forests that are particularly threatened by global changes. Even though tree height is a crucial variable for computing aboveground forest biomass (AGB, it is rarely measured in large-scale forest censuses because it requires extra effort. Therefore, tree height has to be predicted with height models. The height and diameter of all trees over 10 cm in diameter were measured in 33 half-hectare plots and 9 one-hectare plots throughout northern French Guiana, an area with substantial climate and environmental gradients. We compared four different model shapes and found that the Michaelis–Menten shape was most appropriate for the tree biomass prediction. Model parameter values were significantly different from one forest plot to another, and this leads to large errors in biomass estimates. Variables from the forest stand structure explained a sufficient part of plot-to-plot variations of the height model parameters to improve the quality of the AGB predictions. In the forest stands dominated by small trees, the trees were found to have rapid height growth for small diameters. In forest stands dominated by larger trees, the trees were found to have the greatest heights for large diameters. The aboveground biomass estimation uncertainty of the forest plots was reduced by the use of the forest structure-based height model. It demonstrated the feasibility and the importance of height modeling in tropical forests for carbon mapping. When the tree heights are not measured in an inventory, they can be predicted with a height–diameter model and incorporating forest structure descriptors may improve the predictions.

  15. Quantifying Live Aboveground Biomass and Forest Disturbance of Mountainous Natural and Plantation Forests in Northern Guangdong, China, Based on Multi-Temporal Landsat, PALSAR and Field Plot Data

    Directory of Open Access Journals (Sweden)

    Wenjuan Shen

    2016-07-01

    Full Text Available Spatially explicit knowledge of aboveground biomass (AGB in large areas is important for accurate carbon accounting and quantifying the effect of forest disturbance on the terrestrial carbon cycle. We estimated AGB from 1990 to 2011 in northern Guangdong, China, based on a spatially explicit dataset derived from six years of national forest inventory (NFI plots, Landsat time series imagery (1986–2011 and Advanced Land Observing Satellite (ALOS Phased Array L-band Synthetic Aperture Radars (PALSAR 25 m mosaic data (2007–2010. Four types of variables were derived for modeling and assessment. The random forest approach was used to seek the optimal variables for mapping and validation. The root mean square error (RMSE of plot-level validation was between 6.44 and 39.49 (t/ha, the normalized root-mean-square error (NRMSE was between 7.49% and 19.01% and mean absolute error (MAE was between 5.06 and 23.84 t/ha. The highest coefficient of determination R2 of 0.8 and the lowest NRMSE of 7.49% were reported in 2006. A clear increasing trend of mean AGB from the lowest value of 13.58 t/ha to the highest value of 66.25 t/ha was witnessed between 1988 and 2000, while after 2000 there was a fluctuating ascending change, with a peak mean AGB of 67.13 t/ha in 2004. By integrating AGB change with forest disturbance, the trend in disturbance area closely corresponded with the trend in AGB decrease. To determine the driving forces of these changes, the correlation analysis was adopted and exploratory factor analysis (EFA method was used to find a factor rotation that maximizes this variance and represents the dominant factors of nine climate elements and nine human activities elements affecting the AGB dynamics. Overall, human activities contributed more to short-term AGB dynamics than climate data. Harvesting and human-induced fire in combination with rock desertification and global warming made a strong contribution to AGB changes. This study provides

  16. Biomass of Sacrificed Spruce/Aspen (SNF)

    Data.gov (United States)

    National Aeronautics and Space Administration — Dimension analysis (diameter at breast high, tree height, depth of crown), estimated leaf area, and total aboveground biomass for sacrificed spruce and aspens in...

  17. Biomass of Sacrificed Spruce/Aspen (SNF)

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: Dimension analysis (diameter at breast high, tree height, depth of crown), estimated leaf area, and total aboveground biomass for sacrificed spruce and...

  18. NUTRIENT ACCUMULATION IN THE ABOVEGROUND BIOMASS, IN THE LITTER LAYER AND PHYLLODIES DECOMPOSITION OF Acacia mangium Willd.

    Directory of Open Access Journals (Sweden)

    Dieter Liebsch

    2010-08-01

    Full Text Available Nutrient concentrations and contents in the shoot (leaves, branches, bark and wood in a five-years-old stand of Acacia mangium Willd. (mangium, decomposition rate of mangium phyllodies (modified leaves and nutrient efficiency use were evaluated in a forest stand in Seropédica, Rio de Janeiro State, Brazil. The species presented a high nutrient use efficency and accumulated 135 t.ha-1 of above ground biomass, containing: 544.9 kg.ha-1 of N, 281.7 kg.ha-1 of Ca, 242.9 kg.ha-1 of K, 47 kg.ha-1 of Mg and 35.2 kg. ha-1 of P. There was an accumulation of 12.7 t.ha-1 of litter and this layer contained 251.0, 5.7, 14.6, 102.7 and 22.7 kg.ha-1, respectively, of N, P, K, Ca and Mg.  The decomposition constant (k estimated for the phyllodies decomposition was 0,00165 g.g-1.day-1 and the half-live was 421 days. The accumulation of litter on the ground may represent an advantage as nutrient supply for succeeding crops or disadvantage as fuel in areas subject to frequent fire.

  19. Comparing aboveground biomass predictions for an uneven-aged pine-dominated stand using local, regional, and national models

    Science.gov (United States)

    D.C. Bragg; K.M. McElligott

    2013-01-01

    Sequestration by Arkansas forests removes carbon dioxide from the atmosphere, storing this carbon in biomass that fills a number of critical ecological and socioeconomic functions. We need a better understanding of the contribution of forests to the carbon cycle, including the accurate quantification of tree biomass. Models have long been developed to predict...

  20. The short term influence of aboveground biomass cover crops on C sequestration and β–glucosidase in a vineyard ground under semiarid conditions

    Directory of Open Access Journals (Sweden)

    Fernando Peregrina

    2014-10-01

    Full Text Available Tillage and semiarid Mediterranean climatic conditions accelerate soil organic matter losses in Spanish vineyards. Previous studies showed that cover crops can increase soil organic carbon (SOC in Mediterranean vineyards. The objectives of this study were to evaluate the influence of two different cover crops in the short term on soil C sequestration in a semiarid vineyard and to study the potential use of both β–glucosidase enzimatic activity (GLU and the GLU/SOC ratio in order to assess the SOC increase. The experiment was carried out in a cv. Tempranillo (Vitis vinifera L. vineyard on a Oxyaquic Xerorthent soil in Rioja winegrowing region (NE, Spain. The experimental design was established in 2009 with three treatments: conventional tillage; sown barley cover crop (Hordeum vulgare, L.; sown Persian clover cover crop (Trifolium resupinatum L.. Carbon in the aboveground biomass with each cover crop was monitored. Soil was sampled in June 2011 and June 2012, and SOC, GLU and the GLU/SOC ratio were determined. After 3 years both cover crops increased SOC at soil surface with C sequestration rates of 0.47 and 1.19 t C ha-1 yr-1 for BV and CV respectively. GLU and GLU/SOC ratio increased in both cover crops at 0-5 cm soil depth. The C sequestration rates and GLU were related to the cover crops aboveground biomass. In consequence, in semiarid vineyards under cover crops GLU could be an appropriate indicator to asses the increase of SOC and the soil quality improvement in the short-term (2-3 years.

  1. Allometric Equations for Estimating Biomass and Carbon Stocks in the Temperate Forests of North-Western Mexico

    Directory of Open Access Journals (Sweden)

    Benedicto Vargas-Larreta

    2017-07-01

    Full Text Available This paper presents new equations for estimating above-ground biomass (AGB and biomass components of seventeen forest species in the temperate forests of northwestern Mexico. A data set corresponding to 1336 destructively sampled oak and pine trees was used to fit the models. The generalized method of moments was used to simultaneously fit systems of equations for biomass components and AGB, to ensure additivity. In addition, the carbon content of each tree component was calculated by the dry combustion method, in a TOC analyser. The results of cross-validation indicated that the fitted equations accounted for on average 91%, 82%, 83% and 76% of the observed variance in stem wood and stem bark, branch and foliage biomass, respectively, whereas the total AGB equations explained on average 93% of the total observed variance in AGB. The inclusion of total height (h or diameter at breast height2 × total height (d2h as a predictor in the d-only based equations systems slightly improved estimates for stem wood, stem bark and total above-ground biomass, and greatly improved the estimates produced by the branch and foliage biomass equations. The predictive power of the proposed equations is higher than that of existing models for the study area. The fitted equations were used to estimate stand level AGB stocks from data on growing stock in 429 permanent sampling plots. Three machine-learning techniques were used to model the estimated stand level AGB and carbon contents; the selected models were used to map the AGB and carbon distributions in the study area, for which mean values of respectively 129.84 Mg ha−1 and 63.80 Mg ha−1 were obtained.

  2. Above-ground biomass models for Seabuckthorn (Hippophae salicifolia) in Mustang District, Nepal

    DEFF Research Database (Denmark)

    Rajchal, Rajesh; Meilby, Henrik

    2013-01-01

    weight of fruit and oven-dry weight of wood (stem and branches) and leaves were measured and used as a basis for developing biomass models. Diameters of the trees were measured at 30 cm above ground whereas the heights were measured in terms of the total tree height (m). Among several models tested.......91 for wood, fruit, and leaves, respectively. The models suggested for a slightly broader range of environmental conditions were: ln (woody biomass, oven-dry, kg) = -3.277 + 0.924 ln(diameter2 × height), ln(Fruit biomass, fresh, kg) = -3.146 + 0.485 ln(diameter2 × height) and ln(leaf biomass, oven-dry, kg...... of this study was to develop local biomass models for wood, fruit, and leaves of Seabuckthorn. In November 2006, a diameter-stratified sample of 30 trees was harvested in Lete and Kunjo Village Development Committees at an altitude of about 2300 m amsl in the lower part of Mustang District, Nepal. The fresh...

  3. Spatial complexities in aboveground carbon stocks of a semi-arid mangrove community: A remote sensing height-biomass-carbon approach

    Science.gov (United States)

    Hickey, S. M.; Callow, N. J.; Phinn, S.; Lovelock, C. E.; Duarte, C. M.

    2018-01-01

    Mangroves are integral to ecosystem services provided by the coastal zone, in particular carbon (C) sequestration and storage. Allometric relationships linking mangrove height to estimated biomass and C stocks have been developed from field sampling, while various forms of remote sensing has been used to map vegetation height and biomass. Here we combine both these approaches to investigate spatial patterns in living biomass of mangrove forests in a small area of mangrove in north-west Australia. This study used LiDAR data and Landsat 8 OLI (Operational Land Imager) with allometric equations to derive mangrove height, biomass, and C stock estimates. We estimated the study site, Mangrove Bay, a semi-arid site in north-western Australia, contained 70 Mg ha-1 biomass and 45 Mg C ha-1 organic C, with total stocks of 2417 Mg biomass and 778 Mg organic C. Using spatial statistics to identify the scale of clustering of mangrove pixels, we found that living biomass and C stock declined with increasing distance from hydrological features (creek entrance: 0-150 m; y = -0.00041x + 0.9613, R2 = 0.96; 150-770 m; y = -0.0008x + 1.6808, R2 = 0.73; lagoon: y = -0.0041x + 3.7943, R2 = 0.78). Our results illustrate a set pattern of living C distribution within the mangrove forest, and then highlight the role hydrologic features play in determining C stock distribution in the arid zone.

  4. Verification of the Jenkins and FIA sapling biomass equations for hardwood species in Maine

    Science.gov (United States)

    Andrew S. Nelson; Aaron R. Weiskittel; Robert G. Wagner; Michael R. Saunders

    2012-01-01

    In 2009, the Forest Inventory and Analysis Program (FIA) updated its biomass estimation protocols by switching to the component ratio method to estimate biomass of medium and large trees. Additionally, FIA switched from using regional equations to the current FIA aboveground sapling biomass equations that predict woody sapling (2.5 to 12.4 cm d.b.h.) biomass using the...

  5. Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

    Science.gov (United States)

    Nelson, Ross; Naesset, Erik; Gobakken, T.; Gregoire, T.; Stahl, G.

    2009-01-01

    A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

  6. Refined estimates of South African pelagic fish biomass from hydro ...

    African Journals Online (AJOL)

    The biomass of small pelagic fish species off the coast of South Africa has been monitored since 1984 using hydro-acoustic survey techniques. These time-series of spawner biomass and recruitment estimates form the basis for management of both the South African sardine Sardinops sagax and anchovy Engraulis ...

  7. Sampling strategies for efficient estimation of tree foliage biomass

    Science.gov (United States)

    Hailemariam Temesgen; Vicente Monleon; Aaron Weiskittel; Duncan Wilson

    2011-01-01

    Conifer crowns can be highly variable both within and between trees, particularly with respect to foliage biomass and leaf area. A variety of sampling schemes have been used to estimate biomass and leaf area at the individual tree and stand scales. Rarely has the effectiveness of these sampling schemes been compared across stands or even across species. In addition,...

  8. Structural, physiognomic and above-ground biomass variation in savanna–forest transition zones on three continents – how different are co-occurring savanna and forest formations?

    Directory of Open Access Journals (Sweden)

    E. M. Veenendaal

    2015-05-01

    Full Text Available Through interpretations of remote-sensing data and/or theoretical propositions, the idea that forest and savanna represent "alternative stable states" is gaining increasing acceptance. Filling an observational gap, we present detailed stratified floristic and structural analyses for forest and savanna stands located mostly within zones of transition (where both vegetation types occur in close proximity in Africa, South America and Australia. Woody plant leaf area index variation was related to tree canopy cover in a similar way for both savanna and forest with substantial overlap between the two vegetation types. As total woody plant canopy cover increased, so did the relative contribution of middle and lower strata of woody vegetation. Herbaceous layer cover declined as woody cover increased. This pattern of understorey grasses and herbs progressively replaced by shrubs as the canopy closes over was found for both savanna and forests and on all continents. Thus, once subordinate woody canopy layers are taken into account, a less marked transition in woody plant cover across the savanna–forest-species discontinuum is observed compared to that inferred when trees of a basal diameter > 0.1 m are considered in isolation. This is especially the case for shrub-dominated savannas and in taller savannas approaching canopy closure. An increased contribution of forest species to the total subordinate cover is also observed as savanna stand canopy closure occurs. Despite similarities in canopy-cover characteristics, woody vegetation in Africa and Australia attained greater heights and stored a greater amount of above-ground biomass than in South America. Up to three times as much above-ground biomass is stored in forests compared to savannas under equivalent climatic conditions. Savanna–forest transition zones were also found to typically occur at higher precipitation regimes for South America than for Africa. Nevertheless, consistent across all three

  9. Estimating biomass and macronutrient content of some ...

    African Journals Online (AJOL)

    The ratios may underestimate on fertile sites where luxury consumption of nutrients may occur and not accurately predict where stand management practices have altered wood density, allometry or canopy architecture. Although genus and species impacted on the quantity of nutrients held in the plantation biomass, ...

  10. Biomass models to estimate carbon stocks for hardwood tree species

    Energy Technology Data Exchange (ETDEWEB)

    Ruiz-Peinado, R.; Montero, G.; Rio, M. del

    2012-11-01

    To estimate forest carbon pools from forest inventories it is necessary to have biomass models or biomass expansion factors. In this study, tree biomass models were developed for the main hardwood forest species in Spain: Alnus glutinosa, Castanea sativa, Ceratonia siliqua, Eucalyptus globulus, Fagus sylvatica, Fraxinus angustifolia, Olea europaea var. sylvestris, Populus x euramericana, Quercus canariensis, Quercus faginea, Quercus ilex, Quercus pyrenaica and Quercus suber. Different tree biomass components were considered: stem with bark, branches of different sizes, above and belowground biomass. For each species, a system of equations was fitted using seemingly unrelated regression, fulfilling the additivity property between biomass components. Diameter and total height were explored as independent variables. All models included tree diameter whereas for the majority of species, total height was only considered in the stem biomass models and in some of the branch models. The comparison of the new biomass models with previous models fitted separately for each tree component indicated an improvement in the accuracy of the models. A mean reduction of 20% in the root mean square error and a mean increase in the model efficiency of 7% in comparison with recently published models. So, the fitted models allow estimating more accurately the biomass stock in hardwood species from the Spanish National Forest Inventory data. (Author) 45 refs.

  11. Simulation Study Based Analysis of the Statistical Properties of Biomass Estimators that use a Sample of GEDI Lidar Measurements

    Science.gov (United States)

    Patterson, P. L.; Healey, S. P.; Ståhl, G.; Holm, S.; Magnussen, S.; Dubayah, R.; Hancock, S.; Duncanson, L.; Andersen, H. E.

    2016-12-01

    The forthcoming NASA GEDI (Global Ecosystem Dynamics Investigation) mission will install a full-waveform lidar instrument on the International Space Station for the purpose of measuring global forest structure. The resulting waveform data is expected to be strongly correlated with aboveground forest biomass, and one of the mission's primary science products will be a 1-km gridded biomass product. Grid cell-level estimates must be accompanied by formally estimated precision. Waveforms will be collected in spatially discontinuous "footprints" that will sample, instead of census, each 1-km cell. Biomass will be modeled at each footprint using relationships derived from sets of co-located field and lidar measurements. GEDI's spatially discontinuous measurements, combined with the fact that biomass will be modeled instead of measured at each footprint, argues for methods based upon a hybrid of design- and model-based inference. Hybrid estimators (sensu Ståhl et al., 2016) have been employed in large-area estimation problems, but their performance at the scale of 1-km grid cells has not been thoroughly demonstrated. Two activities are under way to assess such estimators for use with GEDI waveforms. First, a simulation-based study is investigating the general relationship between estimator performance and variables such as the size of an estimation unit and spatial autocorrelation of model residual error. Second, an empirical study is assessing proposed estimators using GEDI waveforms simulated from small-footprint airborne lidar data collected in six diverse sites in the United States. This latter study addresses GEDI-specific concerns such as density of instrument overpasses and strength of the footprint-level biomass relationship. Relevance of these studies extends to estimation of biomass across irregularly shaped areas (e.g. watersheds or countries), as well as to other sensors that collect high-quality but spatially discontinuous forest structure information.

  12. Spatial complexities in aboveground carbon stocks of a semi-arid mangrove community: A remote sensing height-biomass-carbon approach

    KAUST Repository

    Hickey, S.M.

    2017-11-10

    Mangroves are integral to ecosystem services provided by the coastal zone, in particular carbon (C) sequestration and storage. Allometric relationships linking mangrove height to estimated biomass and C stocks have been developed from field sampling, while various forms of remote sensing has been used to map vegetation height and biomass. Here we combine both these approaches to investigate spatial patterns in living biomass of mangrove forests in a small area of mangrove in north-west Australia. This study used LiDAR data and Landsat 8 OLI (Operational Land Imager) with allometric equations to derive mangrove height, biomass, and C stock estimates. We estimated the study site, Mangrove Bay, a semi-arid site in north-western Australia, contained 70 Mg ha−1 biomass and 45 Mg C ha−1 organic C, with total stocks of 2417 Mg biomass and 778 Mg organic C. Using spatial statistics to identify the scale of clustering of mangrove pixels, we found that living biomass and C stock declined with increasing distance from hydrological features (creek entrance: 0–150 m; y = −0.00041x + 0.9613, R2 = 0.96; 150–770 m; y = −0.0008x + 1.6808, R2 = 0.73; lagoon: y = −0.0041x + 3.7943, R2 = 0.78). Our results illustrate a set pattern of living C distribution within the mangrove forest, and then highlight the role hydrologic features play in determining C stock distribution in arid zone.

  13. Fire and the distribution and uncertainty of carbon sequestered as above-ground tree biomass in Yosemite and Sequoia & Kings Canyon National Parks

    Science.gov (United States)

    Lutz, James A.; Matchett, John R.; Tarnay, Leland W.; Smith, Douglas F.; Becker, Kendall M.L.; Furniss, Tucker J.; Brooks, Matthew L.

    2017-01-01

    Fire is one of the principal agents changing forest carbon stocks and landscape level distributions of carbon, but few studies have addressed how accurate carbon accounting of fire-killed trees is or can be. We used a large number of forested plots (1646), detailed selection of species-specific and location-specific allometric equations, vegetation type maps with high levels of accuracy, and Monte Carlo simulation to model the amount and uncertainty of aboveground tree carbon present in tree species (hereafter, carbon) within Yosemite and Sequoia & Kings Canyon National Parks. We estimated aboveground carbon in trees within Yosemite National Park to be 25 Tg of carbon (C) (confidence interval (CI): 23–27 Tg C), and in Sequoia & Kings Canyon National Park to be 20 Tg C (CI: 18–21 Tg C). Low-severity and moderate-severity fire had little or no effect on the amount of carbon sequestered in trees at the landscape scale, and high-severity fire did not immediately consume much carbon. Although many of our data inputs were more accurate than those used in similar studies in other locations, the total uncertainty of carbon estimates was still greater than ±10%, mostly due to potential uncertainties in landscape-scale vegetation type mismatches and trees larger than the ranges of existing allometric equations. If carbon inventories are to be meaningfully used in policy, there is an urgent need for more accurate landscape classification methods, improvement in allometric equations for tree species, and better understanding of the uncertainties inherent in existing carbon accounting methods.

  14. Response of aboveground biomass and diversity to nitrogen addition - a five-year experiment in semi-arid grassland of Inner Mongolia, China

    Science.gov (United States)

    He, Kejian; Qi, Yu; Huang, Yongmei; Chen, Huiying; Sheng, Zhilu; Xu, Xia; Duan, Lei

    2016-08-01

    Understanding the response of the plant community to increasing nitrogen (N) deposition is helpful for improving pasture management in semi-arid areas. We implemented a 5-year N addition experiment in a Stipa krylovii steppe of Inner Mongolia, northern China. The aboveground biomass (AGB) and species richness were measured annually. Along with the N addition levels, the species richness declined significantly, and the species composition changed noticeably. However, the total AGB did not exhibit a noticeable increase. We found that compensatory effects of the AGB occurred not only between the grasses and the forbs but also among Gramineae species. The plant responses to N addition, from the community to species level, lessened in dry years compared to wet or normal years. The N addition intensified the reduction of community productivity in dry years. Our study indicated that the compensatory effects of the AGB among the species sustained the stability of grassland productivity. However, biodiversity loss resulting from increasing N deposition might lead the semi-arid grassland ecosystem to be unsustainable, especially in dry years.

  15. Assessment of variations in taxonomic diversity, forest structure, and aboveground biomass using remote sensing along an altitudinal gradient in tropical montane forest of Costa Rica

    Science.gov (United States)

    Robinson, C. M.; Saatchi, S. S.; Clark, D.; Fricker, G. A.; Wolf, J.; Gillespie, T. W.; Rovzar, C. M.; Andelman, S.

    2012-12-01

    This research sought to understand how alpha and beta diversity of plants vary and relate to the three-dimensional vegetation structure and aboveground biomass along environmental gradients in the tropical montane forests of Braulio Carrillo National Park in Costa Rica. There is growing evidence that ecosystem structure plays an important role in defining patterns of species diversity and along with abiotic factors (climate and edaphic) control the phenotypic and functional variations across landscapes. It is well documented that strong subdivisions at local and regional scales are found mainly on geologic or climate gradients. These general determinants of biodiversity are best demonstrated in regions with natural gradients such as tropical montane forests. Altitudinal gradients provide a landscape scale changes through variations in topography, climate, and edaphic conditions on which we tested several theoretical and biological hypotheses regarding drivers of biodiversity. The study was performed by using forest inventory and botanical data from nine 1-ha plots ranging from 100 m to 2800 m above sea level and remote sensing data from airborne lidar and radar sensors to quantify variations in forest structure. In this study we report on the effectiveness of relating patterns of tree taxonomic alpha diversity to three-dimensional structure of a tropical montane forest using lidar and radar observations of forest structure and biomass. We assessed alpha and beta diversity at the species, genus, and family levels utilizing datasets provided by the Terrestrial Ecology Assessment and Monitoring (TEAM) Network. Through the comparison to active remote sensing imagery, our results show that there is a strong relationship between forest 3D-structure, and alpha and beta diversity controlled by variations in abiotic factors along the altitudinal gradient. Using spatial analysis with the aid of remote sensing data, we find distinct patterns along the environmental gradients

  16. Countrywide Forest Biomass Estimates from PALSAR L-Band Backscatter to Improve Greenhouse Gas Inventory in Estonia

    Science.gov (United States)

    Olesk, A.; Voormansik, K.; Luud, Aarne; Renne, M.; Zalite, K.; Noorma, M.; Reinart, A.

    2013-08-01

    Accurately estimated forest biomass and its distribution is a key parameter for forest inventories, vegetation modeling and understanding the global carbon cycle. It is also required by the United Nations and Intergovernmental Panel on Climate Change (IPCC) to provide a comprehensive analysis on estimates of terrestrial carbon fluxes for climate change reports. To improve the understanding of the carbon balance in Estonia, where forests cover over half of the land, a methodology has been worked out to map the changes in the forest biomass in yearly basis using satellite and forest inventory data. To assess the above-ground biomass in temperate deciduous, coniferous and mixed forest of Estonia, measurements and imagery from dual polarimetric L-band SAR (Synthetic Aperature Radar) and optical remote sensing satellites were used. A country-specific model allows easily regenerating the forest biomass estimations with the newest satellite data and producing up-to-date biomass maps that can be used to assist the national inventory reporting under the Intergovernmental Negotiating Committee for a Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol.

  17. Forest volume and biomass estimation using small-footprint lidar-distributional parameters on a per-segment basis

    CSIR Research Space (South Africa)

    Van Aardt, JAN

    2006-05-01

    Full Text Available This study assessed a lidar-based, object-oriented (segmentation) approach to forest volume and aboveground biomass modeling. The study area in the Piedmont physiographic region of Virginia is composed of temperate coniferous, deciduous, and mixed...

  18. Non-destructive estimation of Oecophylla smaragdina colony biomass

    DEFF Research Database (Denmark)

    Pinkalski, Christian Alexander Stidsen; Offenberg, Joachim; Jensen, Karl-Martin Vagn

    In most ecosystems, ants are a dominant part of the arthropod community. However, understanding of their importance has been hampered by limited availability of data on ant abundance. We developed a model to estimate the size (biomass and number of workers) of Oecophylla smaragdina colonies...... in mango plantations in Darwin, Australia. The total nest volume of O. smaragdina colonies in a tree was related to the activity of the ants (R2=0.85), estimated as the density of ant trails in the tree. Subsequently, the relation between nest volume and ant biomass (R2=0.70) was added to enable...... a prediction of ant biomass directly from ant activity. With this combined regression the ant biomass in a tree equaled 244.5 g fresh mass*ant activity. Similarly, the number of workers in trees was estimated using the relationship between nest volume and worker numbers (R2=0.84). Based on the model, five O...

  19. Developing above-ground woody biomass equations for open-grown, multiple-stemmed tree species: shelterbelt-grown Russian-olive

    Science.gov (United States)

    Xinhau Zhour; James R. Brandle; Michele M. Schoeneberger; Tala Awada

    2007-01-01

    Multiple-stemmed tree species are often used in agricultural settings, playing a significant role in natural resource conservation and carbon sequestration. Biomass estimation, whether for modeling growth under different climate scenarios, accounting for carbon sequestered, or inclusion in natural resource inventories, requires equations that can accurately describe...

  20. LBA-ECO LC-08 Ecosystem Demography Model Estimated C, NPP, and Biomass For Amazonia

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides Ecosystem Demography Model (ED) estimates of potential above-ground net primary production (NPP) (kg C/m2/y), potential average live...

  1. A comparative analysis of extended water cloud model and backscatter modelling for above-ground biomass assessment in Corbett Tiger Reserve

    Science.gov (United States)

    Kumar, Yogesh; Singh, Sarnam; Chatterjee, R. S.; Trivedi, Mukul

    2016-04-01

    Forest biomass acts as a backbone in regulating the climate by storing carbon within itself. Thus the assessment of forest biomass is crucial in understanding the dynamics of the environment. Traditionally the destructive methods were adopted for the assessment of biomass which were further advanced to the non-destructive methods. The allometric equations developed by destructive methods were further used in non-destructive methods for the assessment, but they were mostly applied for woody/commercial timber species. However now days Remote Sensing data are primarily used for the biomass geospatial pattern assessment. The Optical Remote Sensing data (Landsat8, LISS III, etc.) are being used very successfully for the estimation of above ground biomass (AGB). However optical data is not suitable for all atmospheric/environmental conditions, because it can't penetrate through clouds and haze. Thus Radar data is one of the alternate possible ways to acquire data in all-weather conditions irrespective of weather and light. The paper examines the potential of ALOS PALSAR L-band dual polarisation data for the estimation of AGB in the Corbett Tiger Reserve (CTR) covering an area of 889 km2. The main focus of this study is to explore the accuracy of Polarimetric Scattering Model (Extended Water Cloud Model (EWCM) with respect to Backscatter model in the assessment of AGB. The parameters of the EWCM were estimated using the decomposition components (Raney Decomposition) and the plot level information. The above ground biomass in the CTR ranges from 9.6 t/ha to 322.6 t/ha.

  2. Use of GIS for estimating potential and actual forest biomass for continental South and Southeast Asia.

    Science.gov (United States)

    L. R. Iverson; S. Brown; A. Prasad; H. Mitasova; A. J. R. Gillespie; A. E. Lugo

    1994-01-01

    A geographic information system (GIS) was used to estimate total biomass and biomass density of the tropical forest in south and southeast Asia because available data from forest inventories were insufficient to extrapolate biomass-density estimates across the region.

  3. Visual obstruction as a method to quantify herbaceous biomass in ...

    African Journals Online (AJOL)

    Biomass of aboveground vegetation is a useful descriptor for studies of grazing, fire and wildlife habitat use in grassland systems. The traditional method to estimate biomass, hand-clipping, is time intensive and other indices of biomass have been used successfully. In southern Africa, the disc pasture meter has been the ...

  4. Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data

    Science.gov (United States)

    Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin

    2013-04-01

    The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the

  5. OPTIMAL WAVELENGTH SELECTION ON HYPERSPECTRAL DATA WITH FUSED LASSO FOR BIOMASS ESTIMATION OF TROPICAL RAIN FOREST

    Directory of Open Access Journals (Sweden)

    T. Takayama

    2016-06-01

    Full Text Available Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.

  6. ESTIMATION OF BIOMASS POTENTIAL BASED ON CLASSIFICATION AND HEIGHT INFORMATION

    Directory of Open Access Journals (Sweden)

    S. Müller

    2013-05-01

    Full Text Available On the way to make energy supply independent from fossil resources more and more renewable energy sources have to be explored. Biomass has become an important energy resource during the last years and the consumption is rising steadily. Common sources of biomass are agricultural production and forestry but the production of these sources is stagnating due to limited space. To explore new sources of biomass like in the field of landscape conservation the location and available amount of biomass is unknown. Normally, there are no reliable data sources to give information about the objects of interest such as hedges, vegetation along streets, railways and rivers, field margins and ruderal sites. There is a great demand for an inventory of these biomass sources which could be answered by applying remote sensing technology. As biomass objects considered here are sometimes only a few meters wide, spectral unmixing is applied to separate different material mixtures reflected in one image pixel. The spectral images are assumed to have a spatial resolution of 5–20 m with multispectral or hyperspectral band configurations. Combining the identified material part fractions with height information and GIS data afterwards will give estimates about the location of biomass objects. The method is applied to test data of a Sentinel-2 simulation and the results are evaluated visually.

  7. Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review

    Energy Technology Data Exchange (ETDEWEB)

    none,

    2011-10-01

    This independent review is the conclusion arrived at from data collection, document reviews, interviews and deliberation from December 2010 through April 2011 and the technical potential of Hydrogen Production Cost Estimate Using Biomass Gasification. The Panel reviewed the current H2A case (Version 2.12, Case 01D) for hydrogen production via biomass gasification and identified four principal components of hydrogen levelized cost: CapEx; feedstock costs; project financing structure; efficiency/hydrogen yield. The panel reexamined the assumptions around these components and arrived at new estimates and approaches that better reflect the current technology and business environments.

  8. Productivity of aboveground coarse wood biomass and stand age related to soil hydrology of Amazonian forests in the Purus-Madeira interfluvial area

    Science.gov (United States)

    Cintra, B. B. L.; Schietti, J.; Emillio, T.; Martins, D.; Moulatlet, G.; Souza, P.; Levis, C.; Quesada, C. A.; Schöngart, J.

    2013-04-01

    The ongoing demand for information on forest productivity has increased the number of permanent monitoring plots across the Amazon. Those plots, however, do not comprise the whole diversity of forest types in the Amazon. The complex effects of soil, climate and hydrology on the productivity of seasonally waterlogged interfluvial wetland forests are still poorly understood. The presented study is the first field-based estimate for tree ages and wood biomass productivity in the vast interfluvial region between the Purus and Madeira rivers. We estimate stand age and wood biomass productivity by a combination of tree-ring data and allometric equations for biomass stocks of eight plots distributed along 600 km in the Purus-Madeira interfluvial area that is crossed by the BR-319 highway. We relate stand age and wood biomass productivity to hydrological and edaphic conditions. Mean productivity and stand age were 5.6 ± 1.1 Mg ha-1 yr-1 and 102 ± 18 yr, respectively. There is a strong relationship between tree age and diameter, as well as between mean diameter increment and mean wood density within a plot. Regarding the soil hydromorphic properties we find a positive correlation with wood biomass productivity and a negative relationship with stand age. Productivity also shows a positive correlation with the superficial phosphorus concentration. In addition, superficial phosphorus concentration increases with enhanced soil hydromorphic condition. We raise three hypotheses to explain these results: (1) the reduction of iron molecules on the saturated soils with plinthite layers close to the surface releases available phosphorous for the plants; (2) the poor structure of the saturated soils creates an environmental filter selecting tree species of faster growth rates and shorter life spans and (3) plant growth on saturated soil is favored during the dry season, since there should be low restrictions for soil water availability.

  9. Comparative study of above ground biomass estimates for conterminous US

    Science.gov (United States)

    Neeti, N.; Kennedy, R. E.

    2013-12-01

    Accurate estimates of forest biomass are important for carbon accounting at both regional and national scale. There are four above ground biomass (AGB) maps available for conterminous US, one from the National Aeronautics and Space Administration (NASA), two from the United States Forest Service (USFS) (Blackard and Wilson) and one from the Woods Hole Research Center (WHRC). Although all four maps are meant to represent similar quantities, spatial patterns of AGB vary considerably from map to map. To use any of these AGB maps for carbon accounting, it is important to understand sources of uncertainty in individual maps and agreement and disagreement among them. Therefore, we compared the four AGB maps at ecoregion and state level to gain understanding of map consistency, leveraging discrepancies among maps to gain insight into the method and data sources. We also developed statewide summaries to compare with FIA forest AGB estimates, which are typically reported at the state level. We examined both absolute differences among these aggregated maps, and relative differences among regions within each map. The result shows that NASA biomass estimates are highest and Blackard estimates are lowest compared to other maps at both ecoregion and state level. The AGB for WHRC and Wilson are very similar at both ecoregion and state level specifically in the lower biomass regions compared to higher biomass regions. This could be associated with the differences in the spatial resolution of the data sources uses to generate these maps. At state level, WHRC map is found to be most similar and NASA biomass estimates least similar to FIA plot data. We discuss these differences in light of the different methods and data sources used to generate the maps.

  10. Methyl halide emission estimates from domestic biomass burning in Africa

    Science.gov (United States)

    Mead, M. I.; Khan, M. A. H.; White, I. R.; Nickless, G.; Shallcross, D. E.

    Inventories of methyl halide emissions from domestic burning of biomass in Africa, from 1950 to the present day and projected to 2030, have been constructed. By combining emission factors from Andreae and Merlet [2001. Emission of trace gases and aerosols from biomass burning. Global Biogeochemical Cycles 15, 955-966], the biomass burning estimates from Yevich and Logan [2003. An assessment of biofuel use and burning of agricultural waste in the developing world. Global Biogeochemical Cycles 17(4), 1095, doi:10.1029/2002GB001952] and the population data from the UN population division, the emission of methyl halides from domestic biomass usage in Africa has been estimated. Data from this study suggest that methyl halide emissions from domestic biomass burning have increased by a factor of 4-5 from 1950 to 2005 and based on the expected population growth could double over the next 25 years. This estimated change has a non-negligible impact on the atmospheric budgets of methyl halides.

  11. Allometric Biomass, Biomass Expansion Factor and Wood Density Models for the OP42 Hybrid Poplar in Southern Scandinavia

    DEFF Research Database (Denmark)

    Nielsen, Anders Tærø; Nord-Larsen, Thomas; Stupak, Inge

    2015-01-01

    Biomass and biomass expansion factor functions are important in wood resource assessment, especially with regards to bioenergy feedstocks and carbon pools. We sampled 48 poplar trees in seven stands with the purpose of estimating allometric models for predicting biomass of individual tree...... components, stem-to-aboveground biomass expansion factors (BEF) and stem basic densities of the OP42 hybrid poplar clone in southern Scandinavia. Stand age ranged from 3 to 31 years, individual tree diameter at breast height (dbh) from 1.2 to 41 cm and aboveground tree biomass from 0.39 to 670 kg. Models...

  12. Estimating Aboveground Forest Carbon Stock of Major Tropical Forest Land Uses Using Airborne Lidar and Field Measurement Data in Central Sumatra

    Science.gov (United States)

    Thapa, R. B.; Watanabe, M.; Motohka, T.; Shiraishi, T.; shimada, M.

    2013-12-01

    Tropical forests are providing environmental goods and services including carbon sequestration, energy regulation, water fluxes, wildlife habitats, fuel, and building materials. Despite the policy attention, the tropical forest reserve in Southeast Asian region is releasing vast amount of carbon to the atmosphere due to deforestation. Establishing quality forest statistics and documenting aboveground forest carbon stocks (AFCS) are emerging in the region. Airborne and satellite based large area monitoring methods are developed to compliment conventional plot based field measurement methods as they are costly, time consuming, and difficult to implement for large regions. But these methods still require adequate ground measurements for calibrating accurate AFCS model. Furthermore, tropical region comprised of varieties of natural and plantation forests capping higher variability of forest structures and biomass volumes. To address this issue and the needs for ground data, we propose the systematic collection of ground data integrated with airborne light detection and ranging (LiDAR) data. Airborne LiDAR enables accurate measures of vertical forest structure, including canopy height and volume demanding less ground measurement plots. Using an appropriate forest type based LiDAR sampling framework, structural properties of forest can be quantified and treated similar to ground measurement plots, producing locally relevant information to use independently with satellite data sources including synthetic aperture radar (SAR). In this study, we examined LiDAR derived forest parameters with field measured data and developed general and specific AFCS models for tropical forests in central Sumatra. The general model is fitted for all types of natural and plantation forests while the specific model is fitted to the specific forest type. The study region consists of natural forests including peat swamp and dry moist forests, regrowth, and mangrove and plantation forests

  13. Allometric Equations for Estimating Biomass of Euterpe precatoria, the Most Abundant Palm Species in the Amazon

    Directory of Open Access Journals (Sweden)

    Fernando Da Silva

    2015-02-01

    Full Text Available Allometric models to estimate biomass components such as stem mass Ms, foliage mass Ml, root mass Mr and aboveground mass Ma, were developed for the palm species Euterpe precatoria Mart., which is the most abundant tree species in the Amazon. We harvested twenty palms including above- and below-ground parts in an old growth Amazonian forest in Brazil. The diameter at breast height D ranged from 3.9–12.7 cm, and the stem height H ranged from 2.3–16.4 m. The D, diameter at ground basis D0, crown diameter CD, H, stem specific gravity ρ, and number of fronds Nf were considered as independent variables and incorporated into a power function model. The best predictors were D2Hρ for Ms and Ma, D2HNf for Ml, and D for Mr. Slender index (H/D ranged from 0.56–1.46 m·cm−1, and the D-H relationship suggested that the stem shape becomes more slender with increasing D. On the other hand, ρ increased with D implying a stiffening of stem tissue. The average root/shoot ratio was estimated as 0.29 which was higher than that reported for the non-palm tree species in the Amazon. Comparisons of several models to estimate Ma of different palm species, suggested that the variations of the D-H relationship and ρ should be considered to develop allometric models for estimating biomass in palm species. In particular the ρ largely varied depending on individual size, which should be important to consider, when developing the allometric models for palms.

  14. Biomass estimation in forest ecosystems - a review | Wakawa ...

    African Journals Online (AJOL)

    Forest ecosystems plays an important role in global warming serving as both sink and source of one of the prominent green house gases, carbon dioxide (CO2). Biomass estimation in forest ecosystems is an important aspect of forest management processes aimed at ensuring sustainability. The choice of appropriate ...

  15. Research Note Estimation of browse biomass of Ficus thonningii ...

    African Journals Online (AJOL)

    Ficus thonningii is a multipurpose browse tree in northern Ethiopia. Despite its importance, techniques for quantifying its browsable biomass have not been developed. To develop best-estimation equations, the dendrometric parameters total height (H), crown height (CH), crown diameter (CD), diameter at stump height ...

  16. Biomass burning losses of carbon estimated from ecosystem modeling and satellite data analysis for the Brazilian Amazon region

    Science.gov (United States)

    Potter, Christopher; Brooks Genovese, Vanessa; Klooster, Steven; Bobo, Matthew; Torregrosa, Alicia

    To produce a new daily record of gross carbon emissions from biomass burning events and post-burning decomposition fluxes in the states of the Brazilian Legal Amazon (Instituto Brasileiro de Geografia e Estatistica (IBGE), 1991. Anuario Estatistico do Brasil, Vol. 51. Rio de Janeiro, Brazil pp. 1-1024). We have used vegetation greenness estimates from satellite images as inputs to a terrestrial ecosystem production model. This carbon allocation model generates new estimates of regional aboveground vegetation biomass at 8-km resolution. The modeled biomass product is then combined for the first time with fire pixel counts from the advanced very high-resolution radiometer (AVHRR) to overlay regional burning activities in the Amazon. Results from our analysis indicate that carbon emission estimates from annual region-wide sources of deforestation and biomass burning in the early 1990s are apparently three to five times higher than reported in previous studies for the Brazilian Legal Amazon (Houghton et al., 2000. Nature 403, 301-304; Fearnside, 1997. Climatic Change 35, 321-360), i.e., studies which implied that the Legal Amazon region tends toward a net-zero annual source of terrestrial carbon. In contrast, our analysis implies that the total source fluxes over the entire Legal Amazon region range from 0.2 to 1.2 Pg C yr -1, depending strongly on annual rainfall patterns. The reasons for our higher burning emission estimates are (1) use of combustion fractions typically measured during Amazon forest burning events for computing carbon losses, (2) more detailed geographic distribution of vegetation biomass and daily fire activity for the region, and (3) inclusion of fire effects in extensive areas of the Legal Amazon covered by open woodland, secondary forests, savanna, and pasture vegetation. The total area of rainforest estimated annually to be deforested did not differ substantially among the previous analyses cited and our own.

  17. Multi-stage approach to estimate forest biomass in degraded area by fire and selective logging

    Science.gov (United States)

    Santos, E. G.; Shimabukuro, Y. E.; Arai, E.; Duarte, V.; Jorge, A.; Gasparini, K.

    2017-12-01

    The Amazon forest has been the target of several threats throughout the years. Anthropogenic disturbances in the region can significantly alter this environment, affecting directly the dynamics and structure of tropical forests. Monitoring these threats of forest degradation across the Amazon is of paramount to understand the impacts of disturbances in the tropics. With the advance of new technologies such as Light Detection and Ranging (LiDAR) the quantification and development of methodologies to monitor forest degradation in the Amazon is possible and may bring considerable contributions to this topic. The objective of this study was to use remote sensing data to assess and estimate the aboveground biomass (AGB) across different levels of degradation (fire and selective logging) using multi-stage approach between airborne LiDAR and orbital image. The study area is in the northern part of the state of Mato Grosso, Brazil. It is predominantly characterized by agricultural land and remnants of the Amazon Forest intact and degraded by either anthropic or natural reasons (selective logging and/or fire). More specifically, the study area corresponds to path/row 226/69 of OLI/Landsat 8 image. With a forest mask generated from the multi-resolution segmentation, agriculture and forest areas, forest biomass was calculated from LiDAR data and correlated with texture images, vegetation indices and fraction images by Linear Spectral Unmixing of OLI/Landsat 8 image and extrapolated to the entire scene 226/69 and validated with field inventories. The results showed that there is a moderate to strong correlation between forest biomass and texture data, vegetation indices and fraction images. With that, it is possible to extract biomass information and create maps using optical data, specifically by combining vegetation indices, which contain forest greening information with texture data that contains forest structure information. Then it was possible to extrapolate the biomass

  18. FIA's volume-to-biomass conversion method (CRM) generally underestimates biomass in comparison to published equations

    Science.gov (United States)

    David. C. Chojnacky

    2012-01-01

    An update of the Jenkins et al. (2003) biomass estimation equations for North American tree species resulted in 35 generalized equations developed from published equations. These 35 equations, which predict aboveground biomass of individual species grouped according to a taxa classification (based on genus or family and sometimes specific gravity), generally predicted...

  19. LBA-ECO LC-05 Biomass and Soil Properties of Fragmented Forests, Amazonas, Brazil

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set reports (1) total aboveground dry biomass based on detailed estimates of all live and dead plant material, (2) results from repeated surveys of...

  20. CMS: LiDAR-derived Biomass, Canopy Height and Cover, Sonoma County, California, 2013

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides estimates of above-ground biomass (AGB), canopy height, and percent tree cover at 30-m spatial resolution for Sonoma County, California, USA,...

  1. LBA-ECO CD-37 Secondary Forest Biomass and Age Class, Rondonia, Brazil

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides tree age, forest formation, and land cover classification maps, and estimates of landscape-level above-ground live woody biomass (AGLB) for...

  2. LBA-ECO CD-37 Secondary Forest Biomass and Age Class, Rondonia, Brazil

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides tree age, forest formation, and land cover classification maps, and estimates of landscape-level above-ground live woody biomass...

  3. LBA-ECO LC-05 Biomass and Soil Properties of Fragmented Forests, Amazonas, Brazil

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set reports (1) total aboveground dry biomass based on detailed estimates of all live and dead plant material, (2) results from repeated surveys...

  4. A hyperspectral approach to estimating biomass and plant production in a heterogeneous restored temperate peatland

    Science.gov (United States)

    Byrd, K. B.; Schile, L. M.; Windham-Myers, L.; Kelly, M.; Hatala, J.; Baldocchi, D. D.

    2012-12-01

    Restoration of drained peatlands that are managed to reverse subsidence through organic accretion holds significant potential for large-scale carbon storage and sequestration. This potential has been demonstrated in an experimental wetland restoration site established by the U.S. Geological Survey in 1997 on Twitchell Island in the Sacramento-San Joaquin River Delta, where soil carbon storage is up to 1 kg C m-2 and root and rhizome production can reach over 7 kg m-2 annually. Remote sensing-based estimation of biomass and productivity over a large spatial extent helps to monitor carbon storage potential of these restored peatlands. Extensive field measurements of plant biophysical characteristics such as biomass, leaf area index, and the fraction of absorbed photosynthetically active radiation (fAPAR) [an important variable in light-use efficiency (LUE) models] have been collected for agricultural systems and forests. However the small size and local spatial variability of U.S. Pacific Coast wetlands pose new challenges for measuring these variables in the field and generating estimates through remote sensing. In particular background effects of non-photosynthetic vegetation (NPV), floating aquatic vegetation, and inundation of wetland vegetation influence the relationship between field measurements and multispectral or hyperspectral indices. Working at the USGS experimental wetland site, characterized by variable water depth and substantial NPV, or thatch, we collected field data on hardstem bulrush (Schoenoplectus acutus) and cattail (Typha spp.) coupled with reflectance data from a field spectrometer (350-2500 nm) every two to three weeks during the summers of 2011 and 2012. We calculated aboveground biomass with existing allometric relationships, and fAPAR was measured with line and point quantum sensors. We analyzed reflectance data to develop hyperspectral and multispectral indices that predict biomass and fAPAR and account for background effects of water

  5. Grazing capacity estimates: why include biomass estimates from ...

    African Journals Online (AJOL)

    Forage for ruminants in the dry season were assessed and matched with feed requirements in three villages in Zimbabwe, namely; Chiweshe, Makande and Mudzimu. Stocking rates were compared with grazing capacity to determine grazing intensities. Grazing capacities were estimated with and without crop residues to ...

  6. Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica

    Science.gov (United States)

    Dubayah, R. O.; Sheldon, S. L.; Clark, D. B.; Hofton, M. A.; Blair, J. B.; Hurtt, G. C.; Chazdon, R. L.

    2010-06-01

    In this paper we present the results of an experiment to measure forest structure and biomass dynamics over the tropical forests of La Selva Biological Station in Costa Rica using a medium resolution lidar. Our main objective was to observe changes in forest canopy height, related height metrics, and biomass, and from these map sources and sinks of carbon across the landscape. The Laser Vegetation Imaging Sensor (LVIS) measured canopy structure over La Selva in 1998 and again in 2005. Changes in waveform metrics were related to field-derived changes in estimated aboveground biomass from a series of old growth and secondary forest plots. Pairwise comparisons of nearly coincident lidar footprints between years showed canopy top height changes that coincided with expected changes based on land cover types. Old growth forests had a net loss in height of -0.33 m, while secondary forests had net gain of 2.08 m. Multiple linear regression was used to relate lidar metrics with biomass changes for combined old growth and secondary forest plots, giving an r2 of 0.65 and an RSE of 10.5 Mg/ha, but both parametric and bootstrapped confidence intervals were wide, suggesting weaker model performance. The plot level relationships were then used to map biomass changes across La Selva using LVIS at a 1 ha scale. The spatial patterns of biomass changes matched expected patterns given the distribution of land cover types at La Selva, with secondary forests showing a gain of 25 Mg/ha and old growth forests showing little change (2 Mg/ha). Prediction intervals were calculated to assess uncertainty for each 1 ha cell to ascertain whether the data and methods used could confidently estimate the sign (source or sink) of the biomass changes. The resulting map showed most of the old growth areas as neutral (no net biomass change), with widely scattered and isolated sources and sinks. Secondary forests in contrast were mostly sinks or neutral, but were never sources. By quantifying both the

  7. Dynamics of aboveground phytomass of the circumpolar Arctic tundra during the past three decades

    International Nuclear Information System (INIS)

    Epstein, Howard E; Raynolds, Martha K; Walker, Donald A; Bhatt, Uma S; Tucker, Compton J; Pinzon, Jorge E

    2012-01-01

    Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982–2010). We found that the southernmost tundra subzones (C–E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field. (letter)

  8. Dynamics of Aboveground Phytomass of the Circumpolar Arctic Tundra During the Past Three Decades

    Science.gov (United States)

    Epstein, Howard E.; Raynolds, Martha K.; Walker, Donald A.; Bhatt, Uma S.; Tucker, Compton J.; Pinzon, Jorge E.

    2012-01-01

    Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.

  9. Lidar and Ground Assessment of Diversity, Wood Density, and Aboveground Biomass Along an Elevation Gradient in Tropical Montane Forest of Costa Rica

    Science.gov (United States)

    Robinson, C. M.; Saatchi, S. S.; Clark, D.; Andelman, S.; Gillespie, T.

    2013-12-01

    This research seeks to understand how tree diversity relates to three-dimensional vegetation structure along environmental gradients in the tropical montane forest of Braulio Carrillo National Park in Costa Rica. Elevation gradients along mountains provide landscape-size scales through which variations in topography and climatic conditions can be tested as drivers of biodiversity. In this study we report on the effectiveness of relating patterns of tree alpha diversity to three-dimensional structure of a tropical montane forest using remote sensing observations of forest structure. The study was utilized forest inventory and botanical data from nine 1-ha plots ranging from 100m-2800m above sea level and remote sensing data from an airborne lidar sensor (NASA's Land, Vegetation, and Ice Sensor [LVIS]) to quantify variations in forest structure. In addition to calculating alpha diversity, we report on the variations in wood density with elevation, important for biomass and carbon estimations. Tree cores were analyzed for wood density and compared to existing database values for the same species, often collected only in the lowlands. In this manner we were able to test the effect of the gradient on effective wood density. Through the comparison to the lidar, our results show that there is a strong relationship between forest 3D structure and alpha diversity controlled by variations in abiotic factors along the elevational gradient. Using spatial analysis with the aid of remote sensing data, we found distinct patterns along the environmental gradients defining species composition. Wood density values with elevation change were found to vary significantly from database values for the same species. These wood density values are directly tied to biomass estimates, and it is possible that carbon storage has been overestimated along this gradient using prior methods. This variation in individual tree growth has repercussions on overall forest structure, as well as

  10. Estimating externalities of biomass fuel cycles, Report 7

    Energy Technology Data Exchange (ETDEWEB)

    Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.

    1998-01-01

    This report documents the analysis of the biomass fuel cycle, in which biomass is combusted to produce electricity. The major objectives of this study were: (1) to implement the methodological concepts which were developed in the Background Document (ORNL/RFF 1992) as a means of estimating the external costs and benefits of fuel cycles, and by so doing, to demonstrate their application to the biomass fuel cycle; (2) to develop, given the time and resources, a range of estimates of marginal (i.e., the additional or incremental) damages and benefits associated with selected impact-pathways from a new wood-fired power plant, using a representative benchmark technology, at two reference sites in the US; and (3) to assess the state of the information available to support energy decision making and the estimation of externalities, and by so doing, to assist in identifying gaps in knowledge and in setting future research agendas. The demonstration of methods, modeling procedures, and use of scientific information was the most important objective of this study. It provides an illustrative example for those who will, in the future, undertake studies of actual energy options and sites. As in most studies, a more comprehensive analysis could have been completed had budget constraints not been as severe. Particularly affected were the air and water transport modeling, estimation of ecological impacts, and economic valuation. However, the most important objective of the study was to demonstrate methods, as a detailed example for future studies. Thus, having severe budget constraints was appropriate from the standpoint that these studies could also face similar constraints. Consequently, an important result of this study is an indication of what can be done in such studies, rather than the specific numerical estimates themselves.

  11. Allometric relationships for the estimation of dry mass of aboveground organs in young highland Norway spruce stand

    Czech Academy of Sciences Publication Activity Database

    Marková, I.; Pokorný, Radek

    2011-01-01

    Roč. 59, č. 6 (2011), s. 217-223 ISSN 1211-8516 R&D Projects: GA MŽP(CZ) SP/2D1/70/08 Institutional research plan: CEZ:AV0Z60870520 Keywords : allometry * biomass expansions factors * biomass * Picea abies Subject RIV: EH - Ecology, Behaviour

  12. Ground Penetrating Radar For Estimating Root Biomass Through Empirical Analysis

    Science.gov (United States)

    Wolfe, M.; Dobreva, I. D.; Delgado, A.; Hays, D. B.; Bishop, M. P.; Huo, D.; Wang, X.; Teare, B. L.; Burris, S.

    2017-12-01

    Variability in soil carbon storage due to agricultural practices is an important component of the carbon cycle. Enhancing soil organic content is a means for restoring degraded soils and for improving soil quality, but also for carbon sequestration. In particular, accurate estimates of soil organic content are essential for quantifying carbon sequestration capabilities of agricultural systems. This project aims to advance the technological and analytical capabilities of Ground Penetrating Radar (GPR) for diagnoses of the soil carbon storage occurring due to the perennial grasses which are often utilized as biofuels. A new GPR processing workflow applied via a prototype software was tested on simulated GPR data of roots with different densities and depths to determine the sensitivity and capability of this technology to quantify these parameters. Field experiments were also conducted in long-term trials of different genotypes of perennial grasses over field sites in Texas to determine the application in authentic environments. GPR scans and soil samples were collected, and root dry biomass was obtained. Evaluation of pre-processing techniques was conducted to provide optimal resolution for assessment. The novel backscatter spatial structure workflow was implemented, and empirical relationships between root biomass and GPR derived observations were developed. Preliminary results suggest that the backscatter spatial structure changes in the presence of high density root biomass conditions, and these variations are indicative of root zone depth and density. Our results illustrate promising applications in root detection, and therefore, the soil organic content accumulation that is pertinent to a healthy soil system.

  13. A hybrid model for mapping relative differences in belowground biomass and root: Shoot ratios using spectral reflectance, foliar N and plant biophysical data within coastal marsh

    Science.gov (United States)

    Jessica L. O'Connell,; Byrd, Kristin B.; Maggi Kelly,

    2015-01-01

    Broad-scale estimates of belowground biomass are needed to understand wetland resiliency and C and N cycling, but these estimates are difficult to obtain because root:shoot ratios vary considerably both within and between species. We used remotely-sensed estimates of two aboveground plant characteristics, aboveground biomass and % foliar N to explore biomass allocation in low diversity freshwater impounded peatlands (Sacramento-San Joaquin River Delta, CA, USA). We developed a hybrid modeling approach to relate remotely-sensed estimates of % foliar N (a surrogate for environmental N and plant available nutrients) and aboveground biomass to field-measured belowground biomass for species specific and mixed species models. We estimated up to 90% of variation in foliar N concentration using partial least squares (PLS) regression of full-spectrum field spectrometer reflectance data. Landsat 7 reflectance data explained up to 70% of % foliar N and 67% of aboveground biomass. Spectrally estimated foliar N or aboveground biomass had negative relationships with belowground biomass and root:shoot ratio in both Schoenoplectus acutus and Typha, consistent with a balanced growth model, which suggests plants only allocate growth belowground when additional nutrients are necessary to support shoot development. Hybrid models explained up to 76% of variation in belowground biomass and 86% of variation in root:shoot ratio. Our modeling approach provides a method for developing maps of spatial variation in wetland belowground biomass.

  14. A Hybrid Model for Mapping Relative Differences in Belowground Biomass and Root:Shoot Ratios Using Spectral Reflectance, Foliar N and Plant Biophysical Data within Coastal Marsh

    Directory of Open Access Journals (Sweden)

    Jessica L. O’Connell

    2015-12-01

    Full Text Available Broad-scale estimates of belowground biomass are needed to understand wetland resiliency and C and N cycling, but these estimates are difficult to obtain because root:shoot ratios vary considerably both within and between species. We used remotely-sensed estimates of two aboveground plant characteristics, aboveground biomass and % foliar N to explore biomass allocation in low diversity freshwater impounded peatlands (Sacramento-San Joaquin River Delta, CA, USA. We developed a hybrid modeling approach to relate remotely-sensed estimates of % foliar N (a surrogate for environmental N and plant available nutrients and aboveground biomass to field-measured belowground biomass for species specific and mixed species models. We estimated up to 90% of variation in foliar N concentration using partial least squares (PLS regression of full-spectrum field spectrometer reflectance data. Landsat 7 reflectance data explained up to 70% of % foliar N and 67% of aboveground biomass. Spectrally estimated foliar N or aboveground biomass had negative relationships with belowground biomass and root:shoot ratio in both Schoenoplectus acutus and Typha, consistent with a balanced growth model, which suggests plants only allocate growth belowground when additional nutrients are necessary to support shoot development. Hybrid models explained up to 76% of variation in belowground biomass and 86% of variation in root:shoot ratio. Our modeling approach provides a method for developing maps of spatial variation in wetland belowground biomass.

  15. Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods

    Science.gov (United States)

    Zhaodi Guo; Jingyun Fang; Yude Pan; Richard. Birdsey

    2010-01-01

    Several studies have reported different estimates for forest biomass carbon (C) stocks in China. The discrepancy among these estimates may be largely attributed to the methods used. In this study, we used three methods [mean biomass density method (MBM), mean ratio method (MRM), and continuous biomass expansion factor (BEF) method (abbreviated as CBM)] applied to...

  16. Prediction models for estimating foliar and fruit dry biomasses of five ...

    African Journals Online (AJOL)

    Prediction models for estimating foliar and fruit dry biomasses of five Savannah tree species in the West African Sahel. ... Direct evaluation of leaf and fruit biomass through destructive method was used to estimate the biomasses of fruits and leaves. Diameter at breast height and crown diameter were candidate explanatory ...

  17. Biomass estimation by allometric relationships, nutrients, and carbon associated to heart-of-palm plantations in Costa Rica

    International Nuclear Information System (INIS)

    Ares, A.; Boniche, Y.; Quesada, J.P.; Yost, R.; Molina, E.; Smyth, T.J.

    2002-01-01

    Peach palm (Bactris gasipaes) agroecosystems constitute a productive and sustainable land use for the humid tropics. Allometric methods allow to predict biomass non-destructively at any time and, subsequently, to determine the span of growth phases, biomass and nutrient pools, and economic yields. The overall goals of this study were to obtain and validate predictive functions of aboveground dry biomass, and to relate standing biomass with heart-of-palm yields as well. Towards this purpose, peach palm shoots were harvested and separated into components: foliage, petiole and stem, in the Atlantic region of Costa Rica. A non-linear seemingly unrelated regression (NSUR) procedure, which simultaneously fits the component equations that predict leaf, petiole and stem in order to assure biomass additivity, was used to generate the allometric equations. Basal diameter (BD) was a more effective predictor of biomass than height to the fork between the spear leaf and the first fully expanded leaf, total height and number of leaves. Regression models explained 70-89% of the variance in biomass components (foliage, petiole and stem) or total shoot biomass. Three growth stages were identified: establishment (0-1 years), fast growth (1-3 or 1-8 years depending on plant density) and maturity (> 8 years). Nutrient contents associated to above- and below-ground biomass were measured. For above-ground biomass nutrient contents were N (up to 150 kg ha-1)>K (up to 119 kg ha-1)>Ca (up to 45 kg ha-1)>Mg=S=P (between 15-17 kg ha-1). The below-ground biomass: above-ground biomass ratio increased with the plantation age [es

  18. Geospatial Estimation of above Ground Forest Biomass in the Sierra Madre Occidental in the State of Durango, Mexico

    Directory of Open Access Journals (Sweden)

    Pablito M. López-Serrano

    2016-03-01

    Full Text Available Combined use of new geospatial techniques and non-parametric multivariate statistical methods enables monitoring and quantification of the biomass of large areas of forest ecosystems with acceptable reliability. The main objective of the present study was to estimate the aboveground forest biomass (AGB in the Sierra Madre Occidental (SMO in the state of Durango, Mexico, using the M5 model tree (M5P technique and the analysis of medium-resolution satellite-based multi-spectral data, and field data collected from a network of 201 permanent forest growth and soil research sites (SPIFyS. Research plots were installed by systematic sampling throughout the study area in 2011. The digital levels of the images were converted to apparent reflectance (ToA and surface reflectance (SR. The M5P technique that constructs tree-based piecewise linear models was used. The fitted model with SR and tree abundance by species group as predictive variables (ASG explained 73% of the observed AGB variance (the root mean squared error (RMSE = 39.40 Mg·ha−1. The variables that best discriminated the AGB, in order of decreasing importance, were the normalized difference vegetation index (NDVI, tree abundance of other broadleaves species (OB, Band 4 of Landsat 5 TM (Thematic Mapper satellite and tree abundance of pines (Pinus. The results demonstrate the potential usefulness of the M5P method for estimating AGB based in the surface reflectance values (SR.

  19. Uav-Based Automatic Tree Growth Measurement for Biomass Estimation

    Science.gov (United States)

    Karpina, M.; Jarząbek-Rychard, M.; Tymków, P.; Borkowski, A.

    2016-06-01

    Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.

  20. A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)

    Science.gov (United States)

    Sean P. Healey; Paul L. Patterson; Sassan S. Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman

    2012-01-01

    Lidar height data collected by the Geosciences Laser Altimeter System (GLAS) from 2002 to 2008 has the potential to form the basis of a globally consistent sample-based inventory of forest biomass. GLAS lidar return data were collected globally in spatially discrete full waveform "shots," which have been shown to be strongly correlated with aboveground forest...

  1. Partitioning Uncertainty In Aboveground Carbon Density Estimates: Relative Contributions From Lidar and Forest Inventory In The Brazilian Amazon.

    Science.gov (United States)

    Duffy, P.; Keller, M. M.; Morton, D. C.

    2016-12-01

    Carbon accounting for REDD+ requires knowledge of deforestation, degradation, and associated changes in forest carbon stocks. Degradation is more difficult to detect than deforestation so SilvaCarbon, an US inter-agency effort, has set a priority to better characterize forest degradation effects on carbon loss. By combining information from forest inventory and lidar data products, impacts of deforestation, degradation, and associated changes in forest carbon stocks can be more accurately characterized across space. Our approach employs a hierarchical Bayesian modeling (HBM) framework where the assimilation of information from multiple sources is accomplished using a change of support (COS) technique. The COS formulation allows data from multiple spatial resolutions to be assimilated into an intermediate resolution. This approach is being applied in Paragominas, a jurisdiction in the eastern Brazilian Amazon with a high proportion of logged and burned degraded forests where political change has opened the way for REDD+. We build on a long history of research including our extensive studies of logging damage. Our primary objective is to quantify above-ground carbon stocks and corresponding uncertainty in a spatially explicit manner. A secondary objective is to quantify the relative contribution of lower level data products to the overall uncertainty, allowing for more focused subsequent data collection in the context of uncertainty reduction. This approach provides a mechanism to assimilate information from multiple sources to produce spatially-explicit maps of carbon stocks and changes with corresponding spatially explicit maps of uncertainty. Importantly, this approach also provides a mechanism that can be used to assess the value of information from specific data products.

  2. Functions for biomass estimation of young Pinus sylvestris, Picea abies and Betula spp. from stands in northern Sweden with high stand densities

    Energy Technology Data Exchange (ETDEWEB)

    Claesson, Svante; Sahlen, Kenneth; Lundmark, Tomas [Swedish Univ. of Agricultural Sciences, Vindeln (Sweden). Dept. of Silviculture, Vindeln Experimental Forests

    2001-07-01

    New silvicultural regimes with high within-stand competition require new functions for estimation of standing stock and growth of biomass components, since the allometry of trees is changed by light competition. This paper presents functions for estimation of the above-ground biomass dry weights for stem wood, stem bark, branches and leaves of young (diameter at breast height < 10 cm) Scots pine (Pinus sylvestris L.), Norway spruce [Picea abies (L.) Karst.] and birch (Betula pendula Roth. and Betula pubescens Ehrh.) trees growing in dense mixed stands. The functions were derived from a sample consisting of 84 Scots pine, 43 Norway spruce and 66 birch trees from six stands in northern Sweden with high stand densities ( > 10 000 st ha{sup -1}). The logarithmically transformed power function displayed a good ability to stabilize the variance of dry weights and showed a good fit to the material (0.37 < R{sup 2} < 0.99). A comparison with the most commonly used biomass functions in Sweden today showed that they overestimated the weight of stem wood and branches, while the weight of foliage was underestimated. The nature of these discrepancies suggested that the precision of biomass estimations might also be improved for young trees at wider spacing.

  3. ESTIMATION OF BIOMASS COMMERCIAL SPROUTS OF Ilex paraguariensis A.ST.-HIL

    Directory of Open Access Journals (Sweden)

    Elisabete Vuaden

    2009-10-01

    Full Text Available This study aimed at developing some models that allow estimating the biomass of commercial green shoots of Ilex paraguariensis after pruning, at 10 years-old. In September 2007, 40 Ilex paraguariensis were pruned. One year after the first pruning, in 2008, they were evaluated dendrometrically and their biomass was determined from the commercial harvest of 16 individuals. To the others, the commercial biomass was estimated by the sum of the biomass of shoots.  The result obtained is that the biomass of commercial sprouts can be estimated as a function of the length of the rolls sprouting, with specific models for sprouts short, simple and compound average sprouts and long sprouts compounds. The models used to estimate the biomass of commercial sprouts using the length sum rolls and rolls of the length as independent variables underestimate the values of biomass with a margin of error of only 2.6%.

  4. Estimating the Heat of Formation of Foodstuffs and Biomass

    Energy Technology Data Exchange (ETDEWEB)

    Burnham, Alan K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2010-11-23

    Calorie estimates for expressing the energy content of food are common, however they are inadequate for the purpose of estimating the chemically defined heat of formation of foodstuffs for two reasons. First, they assume utilization factors by the body.1,2,3 Second, they are usually based on average values for their components. The best way to solve this problem would be to measure the heat of combustion of each material of interest. The heat of formation can then be calculated from the elemental composition and the heats of formation of CO2, H2O, and SO2. However, heats of combustion are not always available. Sometimes elemental analysis only is available, or in other cases, a breakdown into protein, carbohydrates, and lipids. A simple way is needed to calculate the heat of formation from various sorts of data commonly available. This report presents improved correlations for relating the heats of combustion and formation to the elemental composition, moisture content, and ash content. The correlations are also able to calculate heats of combustion of carbohydrates, proteins, and lipids individually, including how they depend on elemental composition. The starting point for these correlations are relationships commonly used to estimate the heat of combustion of fossil fuels, and they have been modified slightly to agree better with the ranges of chemical structures found in foodstuffs and biomass.

  5. Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands

    Science.gov (United States)

    O’Halloran, Lydia R.; Borer, Elizabeth T.; Seabloom, Eric W.; MacDougall, Andrew S.; Cleland, Elsa E.; McCulley, Rebecca L.; Hobbie, Sarah; Harpole, W. Stan; DeCrappeo, Nicole M.; Chu, Cheng-Jin; Bakker, Jonathan D.; Davies, Kendi F.; Du, Guozhen; Firn, Jennifer; Hagenah, Nicole; Hofmockel, Kirsten S.; Knops, Johannes M.H.; Li, Wei; Melbourne, Brett A.; Morgan, John W.; Orrock, John L.; Prober, Suzanne M.; Stevens, Carly J.

    2013-01-01

    Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.

  6. Biomass estimates of small diameter planted and natural-origin loblolly pines show major departures from the National Biomass Estimator equations

    Science.gov (United States)

    Jamie Schuler; Don C. Bragg; Kristin McElligott

    2017-01-01

    As southern pine forests (both planted and naturally regenerated) are more heavily used to provide biomass for the developing energy sectors and carbon sequestration, a better understanding of models used to characterize regional biomass estimates is needed. We harvested loblolly pines (Pinus taeda L.) between 0.5 and 15 cm dbh from several...

  7. Estimating root biomass and distribution after fire in a Great Basin woodland using cores and pits

    Science.gov (United States)

    Benjamin M. Rau; Dale W. Johnson; Jeanne C. Chambers; Robert R. Blank; Annmarie Lucchesi

    2009-01-01

    Quantifying root biomass is critical to an estimation and understanding of ecosystem net primary production, biomass partitioning, and belowground competition. We compared 2 methods for determining root biomass: a new soil-coring technique and traditional excavation of quantitative pits. We conducted the study in an existing Joint Fire Sciences demonstration area in...

  8. A call to improve methods for estimating tree biomass for regional and national assessments

    Science.gov (United States)

    Aaron R. Weiskittel; David W. MacFarlane; Philip J. Radtke; David L.R. Affleck; Hailemariam Temesgen; Christopher W. Woodall; James A. Westfall; John W. Coulston

    2015-01-01

    Tree biomass is typically estimated using statistical models. This review highlights five limitations of most tree biomass models, which include the following: (1) biomass data are costly to collect and alternative sampling methods are used; (2) belowground data and models are generally lacking; (3) models are often developed from small and geographically limited data...

  9. NPP Grassland: NPP Estimates from Biomass Dynamics for 31 Sites, 1948-1994, R1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes monthly grassland biomass data, net primary productivity (NPP) estimates, and climate (rainfall amounts and temperature) data for multiple...

  10. The Utilization of ALOS PALSAR Image to Estimate Natural Forest Biomass: Case Study at Bogani Nani Wartabone National Park (Pemanfaatan Citra ALOS PALSAR dalam Menduga Biomasa Hutan Alam: Studi Kasus di Taman Nasional Bogani Nani Wartabone

    Directory of Open Access Journals (Sweden)

    Nurlita Indah Wahyuni

    2014-12-01

    Full Text Available The development of remote sensing technology makes it possible to utilize its data in many sectors including forestry. Remote sensing image has been used to map land cover and monitor deforestation. This paper presents utilization of ALOS PALSAR image to estimate and map aboveground biomass at natural forest of Bogani Nani Wartabone National Park especially SPTN II Doloduo and SPTN III Maelang. We used modeling method between biomass value from direct measurement and digital number of satellite image. There are two maps which present the distribution of biomass and carbon from ALOS PALSAR image with 50 m spatial resolution. These maps were built based on backscatter polarization of HH and HV bands. The maps indicate most research area dominated with biomass stock 0-5.000 ton/ha.

  11. Estimating leaf area and above-ground biomass of forest regeneration areas using a corrected normalized difference vegetation index

    Science.gov (United States)

    Tommy L. Coleman; James H. Miller; Bruce R. Zutter

    1992-01-01

    The objective of this study was to investigate the regression relations between vegetation indices derived from remotely-sensed data of single and mixed forest regeneration plots. Loblolly pine (Pinus taeda L.) seedlings, sweelgum (Liquidambar styraciflua L.) seedlings and broomsedge (Andropogon virginicus L.)...

  12. The effect of precipitation changes on above-ground biomass production of Beskydy mountain grassland in comparison with grassland in lowland and highland

    Czech Academy of Sciences Publication Activity Database

    Holub, Petr

    2007-01-01

    Roč. 20, - (2007), s. 69-76. ISBN 978-80-7375-069-5 R&D Projects: GA ČR(CZ) GA526/06/0556 Institutional research plan: CEZ:AV0Z60050516 Keywords : different altitudes * biomass * plant litter Subject RIV: EF - Botanics

  13. Effect of culture and density on aboveground biomass allocation of 12 years old loblolly pine trees in the upper coastal plain and piedmont of Georgia and Alabama

    Science.gov (United States)

    Santosh Subedi; Dr. Michael Kane; Dr. Dehai Zhao; Dr. Bruce Borders; Dr. Dale Greene

    2012-01-01

    We destructively sampled a total of 192 12-year-old loblolly pine trees from four installations established by the Plantation Management Research Cooperative (PMRC) to analyze the effects of planting density and cultural intensity on tree level biomass allocation in the Piedmont and Upper Coastal Plain of Georgia and Alabama. Each installation had 12 plots, each plot...

  14. Harvesting tree biomass at the stand level to assess the accuracy of field and airborne biomass estimation in savannas.

    Science.gov (United States)

    Colgan, Matthew S; Asner, Gregory P; Swemmer, Tony

    2013-07-01

    Tree biomass is an integrated measure of net growth and is critical for understanding, monitoring, and modeling ecosystem functions. Despite the importance of accurately measuring tree biomass, several fundamental barriers preclude direct measurement at large spatial scales, including the facts that trees must be felled to be weighed and that even modestly sized trees are challenging to maneuver once felled. Allometric methods allow for estimation of tree mass using structural characteristics, such as trunk diameter. Savanna trees present additional challenges, including limited available allometry and a prevalence of multiple stems per individual. Here we collected airborne lidar data over a semiarid savanna adjacent to the Kruger National Park, South Africa, and then harvested and weighed woody plant biomass at the plot scale to provide a standard against which field and airborne estimation methods could be compared. For an existing airborne lidar method, we found that half of the total error was due to averaging canopy height at the plot scale. This error was eliminated by instead measuring maximum height and crown area of individual trees from lidar data using an object-based method to identify individual tree crowns and estimate their biomass. The best object-based model approached the accuracy of field allometry at both the tree and plot levels, and it more than doubled the accuracy compared to existing airborne methods (17% vs. 44% deviation from harvested biomass). Allometric error accounted for less than one-third of the total residual error in airborne biomass estimates at the plot scale when using allometry with low bias. Airborne methods also gave more accurate predictions at the plot level than did field methods based on diameter-only allometry. These results provide a novel comparison of field and airborne biomass estimates using harvested plots and advance the role of lidar remote sensing in savanna ecosystems.

  15. Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications.

    Directory of Open Access Journals (Sweden)

    Sebastian Doetterl

    Full Text Available African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors.Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock were only half compared to an area with lower tree height (= smaller aboveground carbon stock. This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system.We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to the terrestrial C budget.

  16. Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications.

    Science.gov (United States)

    Doetterl, Sebastian; Kearsley, Elizabeth; Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, Pascal

    2015-01-01

    African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors. Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock) were only half compared to an area with lower tree height (= smaller aboveground carbon stock). This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system. We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to the terrestrial C budget.

  17. Estimating volume, biomass, and potential emissions of hand-piled fuels

    Science.gov (United States)

    Clinton S. Wright; Cameron S. Balog; Jeffrey W. Kelly

    2009-01-01

    Dimensions, volume, and biomass were measured for 121 hand-constructed piles composed primarily of coniferous (n = 63) and shrub/hardwood (n = 58) material at sites in Washington and California. Equations using pile dimensions, shape, and type allow users to accurately estimate the biomass of hand piles. Equations for estimating true pile volume from simple geometric...

  18. Comparing algorithms for estimating foliar biomass of conifers in the Pacific Northwest

    Science.gov (United States)

    Crystal L. Raymond; Donald. McKenzie

    2013-01-01

    Accurate estimates of foliar biomass (FB) are important for quantifying carbon storage in forest ecosystems, but FB is not always reported in regional or national inventories. Foliar biomass also drives key ecological processes in ecosystem models. Published algorithms for estimating FB in conifer species of the Pacific Northwest can yield signifi cantly different...

  19. Biomass equations for shrub species of Tamualipan thornscrub of North-Eastern Mexico

    Science.gov (United States)

    J. Navar; E. Mendez; A. Najera; J. Graciano; V. Dale; B. Parresol

    2004-01-01

    Nine additive allometric equations for computing above-ground, standing biomass were developed for the plant community and for each of 18 single species typical of the Tamaulipan thornscrub of north-eastern Mexico. Equations developed using additive procedures in seemingly unrelated linear regression provided statistical efficiency in total biomass estimates at the...

  20. SAFARI 2000 1-Degree Estimates of Burned Biomass, Area, and Emissions, 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: A new method is used to generate spatial estimates of monthly averaged biomass burned area and spatial and temporal estimates of trace gas and aerosol...

  1. SAFARI 2000 1-Degree Estimates of Burned Biomass, Area, and Emissions, 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — A new method is used to generate spatial estimates of monthly averaged biomass burned area and spatial and temporal estimates of trace gas and aerosol emissions from...

  2. Non-Destructive Lichen Biomass Estimation in Northwestern Alaska: A Comparison of Methods

    Science.gov (United States)

    Rosso, Abbey; Neitlich, Peter; Smith, Robert J.

    2014-01-01

    Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa “community” samples, n = 144) at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count), among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume) as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4%) using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m−2). Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community) approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska. PMID:25079228

  3. Non-destructive lichen biomass estimation in northwestern Alaska: a comparison of methods.

    Directory of Open Access Journals (Sweden)

    Abbey Rosso

    Full Text Available Terrestrial lichen biomass is an important indicator of forage availability for caribou in northern regions, and can indicate vegetation shifts due to climate change, air pollution or changes in vascular plant community structure. Techniques for estimating lichen biomass have traditionally required destructive harvesting that is painstaking and impractical, so we developed models to estimate biomass from relatively simple cover and height measurements. We measured cover and height of forage lichens (including single-taxon and multi-taxa "community" samples, n = 144 at 73 sites on the Seward Peninsula of northwestern Alaska, and harvested lichen biomass from the same plots. We assessed biomass-to-volume relationships using zero-intercept regressions, and compared differences among two non-destructive cover estimation methods (ocular vs. point count, among four landcover types in two ecoregions, and among single-taxon vs. multi-taxa samples. Additionally, we explored the feasibility of using lichen height (instead of volume as a predictor of stand-level biomass. Although lichen taxa exhibited unique biomass and bulk density responses that varied significantly by growth form, we found that single-taxon sampling consistently under-estimated true biomass and was constrained by the need for taxonomic experts. We also found that the point count method provided little to no improvement over ocular methods, despite increased effort. Estimated biomass of lichen-dominated communities (mean lichen cover: 84.9±1.4% using multi-taxa, ocular methods differed only nominally among landcover types within ecoregions (range: 822 to 1418 g m-2. Height alone was a poor predictor of lichen biomass and should always be weighted by cover abundance. We conclude that the multi-taxa (whole-community approach, when paired with ocular estimates, is the most reasonable and practical method for estimating lichen biomass at landscape scales in northwest Alaska.

  4. Modelling tree biomasses in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Repola, J.

    2013-06-01

    Biomass equations for above- and below-ground tree components of Scots pine (Pinus sylvestris L), Norway spruce (Picea abies [L.] Karst) and birch (Betula pendula Roth and Betula pubescens Ehrh.) were compiled using empirical material from a total of 102 stands. These stands (44 Scots pine, 34 Norway spruce and 24 birch stands) were located mainly on mineral soil sites representing a large part of Finland. The biomass models were based on data measured from 1648 sample trees, comprising 908 pine, 613 spruce and 127 birch trees. Biomass equations were derived for the total above-ground biomass and for the individual tree components: stem wood, stem bark, living and dead branches, needles, stump, and roots, as dependent variables. Three multivariate models with different numbers of independent variables for above-ground biomass and one for below-ground biomass were constructed. Variables that are normally measured in forest inventories were used as independent variables. The simplest model formulations, multivariate models (1) were mainly based on tree diameter and height as independent variables. In more elaborated multivariate models, (2) and (3), additional commonly measured tree variables such as age, crown length, bark thickness and radial growth rate were added. Tree biomass modelling includes consecutive phases, which cause unreliability in the prediction of biomass. First, biomasses of sample trees should be determined reliably to decrease the statistical errors caused by sub-sampling. In this study, methods to improve the accuracy of stem biomass estimates of the sample trees were developed. In addition, the reliability of the method applied to estimate sample-tree crown biomass was tested, and no systematic error was detected. Second, the whole information content of data should be utilized in order to achieve reliable parameter estimates and applicable and flexible model structure. In the modelling approach, the basic assumption was that the biomasses of

  5. Mapping and estimating the total living biomass and carbon in low-biomass woodlands using Landsat 8 CDR data

    Directory of Open Access Journals (Sweden)

    Belachew Gizachew

    2016-06-01

    Full Text Available Abstract Background A functional forest carbon measuring, reporting and verification (MRV system to support climate change mitigation policies, such as REDD+, requires estimates of forest biomass carbon, as an input to estimate emissions. A combination of field inventory and remote sensing is expected to provide those data. By linking Landsat 8 and forest inventory data, we (1 developed linear mixed effects models for total living biomass (TLB estimation as a function of spectral variables, (2 developed a 30 m resolution map of the total living carbon (TLC, and (3 estimated the total TLB stock of the study area. Inventory data consisted of tree measurements from 500 plots in 63 clusters in a 15,700 km2 study area, in miombo woodlands of Tanzania. The Landsat 8 data comprised two climate data record images covering the inventory area. Results We found a linear relationship between TLB and Landsat 8 derived spectral variables, and there was no clear evidence of spectral data saturation at higher biomass values. The root-mean-square error of the values predicted by the linear model linking the TLB and the normalized difference vegetation index (NDVI is equal to 44 t/ha (49 % of the mean value. The estimated TLB for the study area was 140 Mt, with a mean TLB density of 81 t/ha, and a 95 % confidence interval of 74–88 t/ha. We mapped the distribution of TLC of the study area using the TLB model, where TLC was estimated at 47 % of TLB. Conclusion The low biomass in the miombo woodlands, and the absence of a spectral data saturation problem suggested that Landsat 8 derived NDVI is suitable auxiliary information for carbon monitoring in the context of REDD+, for low-biomass, open-canopy woodlands.

  6. Estimation of Above Ground Biomass in the Everglades National Park using X-, C-, and L-band SAR data and Ground-based LiDAR

    Science.gov (United States)

    Feliciano, E. A.; Wdowinski, S.; Potts, M.; Kim, S.

    2011-12-01

    Anthropogenic activities are disrupting bio-diverse wetland ecosystems including the South Florida Everglades. To quantify these acute changes is difficult given its limited accessibility. Remote sensing is widely used for successful ecosystem monitoring. We use ground-based LiDAR a.k.a. Terrestrial Laser Scanning (TLS) and space-based Synthetic Aperture Radar (SAR) observations to estimate vegetation structure, above-ground biomass, and track their changes over time in the Everglades National Park. These surveys were conducted in six vegetation communities: short-mangrove, intermediate-mangrove, tall-mangrove, pine, dwarf cypress and hammock. The TLS surveys provided detailed 3-D estimates of the vegetation structure and above ground biomass. The upscaling approach started with the SAR acquisitions at the three different wavelengths, showing the interacted signal with different aspects of the vegetation. We use single- (HH and VV), dual- (HH/VV, HH/HV and VV/HV) and quad-polarization observations of the TerraSAR-X, RadarSAT-2, and ALOS satellites, acquired around same dates as the ground TLS surveys were conducted. The different polarization data reflect radar signal interaction with different sections of the vegetation due to different scattering mechanisms. The processing of the SAR included: Sigma Nought backscattering coefficient calibration, speckle noise suppression filtering and geocoding with the TLS data. A comparative analysis of the three bands of SAR to quantify above ground biomass in the different communities will be presented. We also plan to determine the essential bands needed to most efficiently estimate biomass. We expect to find that the performance of SAR upscaling differs by community types. We are optimistic that the integration of TLS and SAR could be applied to monitor different ecosystems around the world. This will increase the chance that the Reducing Emissions from Deforestation and Forest Degradation (REDD+), in which large

  7. Biomass expansion factors for Eucalyptus globulus stands in Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Soares, P.; Tome, M.

    2012-11-01

    One of several procedures for estimating carbon stocks in forests is the estimation of tree or stand biomass based on forest inventory data. The two approaches normally used to convert field measurements of trees to stand biomass values are allometric biomass equations and biomass expansion factors (BEFs). BEFs are used in published National Forest Inventory results in which biomass is not estimated or as a complement of growth models that do not include biomass predictions. In this paper, the effectiveness of BEFs for estimating total stand biomass in Portuguese Eucalyptus globulus plantations was analyzed. Here, BEF is defined as the ratio of total stand biomass (aboveground biomass plus root biomass) to stand volume with bark. To calculate total biomass, an equation was developed to estimate root biomass as a function of aboveground biomass. Changes of BEF with stand variables were analyzed. Strong relationships were observed between BEF and stand age, stand basal area, stand volume and dominant height. Consequently, an equation to predict BEF as a function of stand variables was fitted, and dominant height was selected as the predictor stand variable. Estimates of total stand biomass based on individual tree allometric equations were compared with estimates obtained with a constant BEF (0.77), used in the Portuguese National Inventory Report on Greenhouse Gases, and with estimates obtained using the dominant height-dependent BEF equation developed in this work. The BEF prediction model proposed in this work may be used to improve E. globulus Portuguese biomass estimates when tree allometric equations cannot be used. (Author) 40 refs.

  8. Tree Biomass Estimation of Chinese fir (Cunninghamia lanceolata) Based on Bayesian Method

    Science.gov (United States)

    Zhang, Jianguo

    2013-01-01

    Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass. PMID:24278198

  9. Tree biomass estimation of Chinese fir (Cunninghamia lanceolata based on Bayesian method.

    Directory of Open Access Journals (Sweden)

    Xiongqing Zhang

    Full Text Available Chinese fir (Cunninghamia lanceolata (Lamb. Hook. is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation W = a(D2Hb was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass.

  10. Aboveground Biomass and Carbon Stocks of an Undisturbed Regenerating Sal (Shorea Robusta Gaertn. F. Forest Of Goalpara District, Assam, Northeast India

    Directory of Open Access Journals (Sweden)

    Debajit Rabha

    2014-12-01

    Full Text Available The present paper deals with the above ground biomass and carbon stocks of an undisturbed Sal forest of Goalpara district, Assam, Northeast India. The average AGB and C were recorded 239.45 ± 12.8 Mg ha-1 and 119.73 ± 6.4 Mg ha-1. Density distribution curve indicates the high carbon sequestration potential of the stand in near future which further helps in climate change mitigation. Currently, conservation measures are well imposed in combine effort of local community and government. Legal involvement of local community in conservation exercises along with the forest department might be very effective in management of Sal forests.DOI: http://dx.doi.org/10.3126/ije.v3i4.11743   International Journal of EnvironmentVolume-3, Issue-4, Sep-Nov 2014Page: 147-155 

  11. Developing in situ non-destructive estimates of crop biomass to address issues of scale in remote sensing

    Science.gov (United States)

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

    Ground-based estimates of aboveground wet (fresh) biomass (AWB) are an important input for crop growth models. In this study, we developed empirical equations of AWB for rice, maize, cotton, and alfalfa, by combining several in situ non-spectral and spectral predictors. The non-spectral predictors included: crop height (H), fraction of absorbed photosynthetically active radiation (FAPAR), leaf area index (LAI), and fraction of vegetation cover (FVC). The spectral predictors included 196 hyperspectral narrowbands (HNBs) from 350 to 2500 nm. The models for rice, maize, cotton, and alfalfa included H and HNBs in the near infrared (NIR); H, FAPAR, and HNBs in the NIR; H and HNBs in the visible and NIR; and FVC and HNBs in the visible; respectively. In each case, the non-spectral predictors were the most important, while the HNBs explained additional and statistically significant predictors, but with lower variance. The final models selected for validation yielded an R2 of 0.84, 0.59, 0.91, and 0.86 for rice, maize, cotton, and alfalfa, which when compared to models using HNBs alone from a previous study using the same spectral data, explained an additional 12%, 29%, 14%, and 6% in AWB variance. These integrated models will be used in an up-coming study to extrapolate AWB over 60 × 60 m transects to evaluate spaceborne multispectral broad bands and hyperspectral narrowbands.

  12. Developing in situ Non-Destructive Estimates of Crop Biomass to Address Issues of Scale in Remote Sensing

    Directory of Open Access Journals (Sweden)

    Michael Marshall

    2015-01-01

    Full Text Available Ground-based estimates of aboveground wet (fresh biomass (AWB are an important input for crop growth models. In this study, we developed empirical equations of AWB for rice, maize, cotton, and alfalfa, by combining several in situ non-spectral and spectral predictors. The non-spectral predictors included: crop height (H, fraction of absorbed photosynthetically active radiation (FAPAR, leaf area index (LAI, and fraction of vegetation cover (FVC. The spectral predictors included 196 hyperspectral narrowbands (HNBs from 350 to 2500 nm. The models for rice, maize, cotton, and alfalfa included H and HNBs in the near infrared (NIR; H, FAPAR, and HNBs in the NIR; H and HNBs in the visible and NIR; and FVC and HNBs in the visible; respectively. In each case, the non-spectral predictors were the most important, while the HNBs explained additional and statistically significant predictors, but with lower variance. The final models selected for validation yielded an R2 of 0.84, 0.59, 0.91, and 0.86 for rice, maize, cotton, and alfalfa, which when compared to models using HNBs alone from a previous study using the same spectral data, explained an additional 12%, 29%, 14%, and 6% in AWB variance. These integrated models will be used in an up-coming study to extrapolate AWB over 60 × 60 m transects to evaluate spaceborne multispectral broad bands and hyperspectral narrowbands.

  13. Novel and lost forests in the Upper Midwestern United States, from new estimates of settlement-era composition, stem density, and biomass

    Science.gov (United States)

    Goring, Simon; Mladenoff, David J.; Cogbill, Charles; Record, Sydne; Paciorek, Christopher J.; Dietze, Michael C.; Dawson, Andria; Matthes, Jaclyn; McLachlan, Jason S.; Williams, John W.

    2016-01-01

    EuroAmerican land-use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Here we present new gridded (8x8km) reconstructions of pre-settlement (1800s) forest composition and structure from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan), using 19th Century Public Land Survey System (PLSS), with estimates of relative composition, above-ground biomass, stem density, and basal area for 28 tree types. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection.

  14. Tree STEM and Canopy Biomass Estimates from Terrestrial Laser Scanning Data

    Science.gov (United States)

    Olofsson, K.; Holmgren, J.

    2017-10-01

    In this study an automatic method for estimating both the tree stem and the tree canopy biomass is presented. The point cloud tree extraction techniques operate on TLS data and models the biomass using the estimated stem and canopy volume as independent variables. The regression model fit error is of the order of less than 5 kg, which gives a relative model error of about 5 % for the stem estimate and 10-15 % for the spruce and pine canopy biomass estimates. The canopy biomass estimate was improved by separating the models by tree species which indicates that the method is allometry dependent and that the regression models need to be recomputed for different areas with different climate and different vegetation.

  15. TREE STEM AND CANOPY BIOMASS ESTIMATES FROM TERRESTRIAL LASER SCANNING DATA

    Directory of Open Access Journals (Sweden)

    K. Olofsson

    2017-10-01

    Full Text Available In this study an automatic method for estimating both the tree stem and the tree canopy biomass is presented. The point cloud tree extraction techniques operate on TLS data and models the biomass using the estimated stem and canopy volume as independent variables. The regression model fit error is of the order of less than 5 kg, which gives a relative model error of about 5 % for the stem estimate and 10–15 % for the spruce and pine canopy biomass estimates. The canopy biomass estimate was improved by separating the models by tree species which indicates that the method is allometry dependent and that the regression models need to be recomputed for different areas with different climate and different vegetation.

  16. Quantitative Estimation of Above Ground Crop Biomass using Ground-based, Airborne and Spaceborne Low Frequency Polarimetric Synthetic Aperture Radar

    Science.gov (United States)

    Koyama, C.; Watanabe, M.; Shimada, M.

    2016-12-01

    Estimation of crop biomass is one of the important challenges in environmental remote sensing related to agricultural as well as hydrological and meteorological applications. Usually passive optical data (photographs, spectral data) operating in the visible and near-infrared bands is used for such purposes. The virtue of optical remote sensing for yield estimation, however, is rather limited as the visible light can only provide information about the chemical characteristics of the canopy surface. Low frequency microwave signals with wavelength longer 20 cm have the potential to penetrate through the canopy and provide information about the whole vertical structure of vegetation from the top of the canopy down to the very soil surface. This phenomenon has been well known and exploited to detect targets under vegetation in the military radar application known as FOPEN (foliage penetration). With the availability of polarimetric interferometric SAR data the use PolInSAR techniques to retrieve vertical vegetation structures has become an attractive tool. However, PolInSAR is still highly experimental and suitable data is not yet widely available. In this study we focus on the use of operational dual-polarization L-band (1.27 GHz) SAR which is since the launch of Japan's Advanced Land Observing Satellite (ALOS, 2006-2011) available worldwide. Since 2014 ALOS-2 continues to deliver such kind of partial polarimetric data for the entire land surface. In addition to these spaceborne data sets we use airborne L-band SAR data acquired by the Japanese Pi-SAR-L2 as well as ultra-wideband (UWB) ground based SAR data operating in the frequency range from 1-4 GHz. By exploiting the complex dual-polarization [C2] Covariance matrix information, the scattering contributions from the canopy can be well separated from the ground reflections allowing for the establishment of semi-empirical relationships between measured radar reflectivity and the amount of fresh-weight above-ground

  17. Aboveground biomass in Prosopis pallida (Humb. and Bonpl. ex Willd. H. B. K. ecosystems using Landsat 7 ETM+ images Biomasa aérea en ecosistemas de Prosopis pallida (Humb. and Bonpl. ex Willd. H. B. K. usando imágenes Landsat 7 ETM+

    Directory of Open Access Journals (Sweden)

    EVA PADRÓN

    2007-03-01

    Full Text Available The significance of field work in remote sensing studies when applied to large areas has often been underestimated. The combination of specific forest inventories for the estimation of aboveground biomass in large dry tropical forest areas with remote sensor data has scarcely been explored to date. In this work, a systematic, stratified forest inventory involving 100 X 100 m square plots in an area of Peruvian Prosopis pallida dry forest, roughly one million hectares in size in the Piura province (Peru has been compiled. The inventory encompassed the principal silvicultural variables defining the ecosystem studied, which were used in allometric equations for the different species, genera and plant associations in the area in order to estimate the amount of aboveground biomass present in each plot. Field data were related to a Landsat 7 ETM+ image by using six different vegetation indices derived from an image mosaic for the area. Two regression equations (relating the amount of aboveground phytomass to the different vegetation indices provided reasonably acceptable phytomass predictions for the type of ecosystem concerned (R² between 0.72 and 0.52La importancia del trabajo de campo en estudios de teledetección radica en la necesidad de proveer una validación a los valores de reflectividad incluidos en los datos de los sensores remotos. La diversidad ecológica del medio forestal y la evaluación de grandes superficies de difícil acceso hacen de la combinación del inventario forestal y de la teledetección una herramienta compleja y útil en el análisis del medio terrestre. El presente trabajo muestra la aplicación de un inventario sistemático estratificado sobre un millón de hectáreas de bosque tropical seco de Prosopis pallida en el Departamento de Piura (Perú en la validación de diferentes tipos de clasificación realizadas sobre dicho ecosistema mediante el uso de imágenes Landsat ETM+. El inventario recoge las principales

  18. Estimating tree biomass regressions and their error, proceedings of the workshop on tree biomass regression functions and their contribution to the error

    Science.gov (United States)

    Eric H. Wharton; Tiberius Cunia

    1987-01-01

    Proceedings of a workshop co-sponsored by the USDA Forest Service, the State University of New York, and the Society of American Foresters. Presented were papers on the methodology of sample tree selection, tree biomass measurement, construction of biomass tables and estimation of their error, and combining the error of biomass tables with that of the sample plots or...

  19. A comparison of selected parametric and non-parametric imputation methods for estimating forest biomass and basal area

    Science.gov (United States)

    Donald Gagliasso; Susan Hummel; Hailemariam. Temesgen

    2014-01-01

    Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future...

  20. Estimation and mapping of above ground biomass and carbon of ...

    African Journals Online (AJOL)

    In addition, field data from 35 sample plots comprising of the Diameter at Breast Height (DBH), co-ordinates of centroids and angles to the top and bottom of the individual trees was used for the analysis. The relationship between biomass and radar backscatter for selected sample plots was established using pairwise ...

  1. Is biomass a reliable estimate of plant fitness?

    Czech Academy of Sciences Publication Activity Database

    Younginger, B.S.; Sirová, Dagmara; Cruzan, M.B.; Ballhorn, D.J.

    2017-01-01

    Roč. 5, č. 2 (2017), č. článku 1600094. ISSN 2168-0450 Institutional support: RVO:60077344 Keywords : biomass * fecundity * fitness * plant performance * selection Subject RIV: EH - Ecology, Behaviour OBOR OECD: Plant sciences, botany Impact factor: 1.492, year: 2016

  2. Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

    Directory of Open Access Journals (Sweden)

    Nora Tilly

    2015-09-01

    Full Text Available Plant biomass is an important parameter for crop management and yield estimation. However, since biomass cannot be determined non-destructively, other plant parameters are used for estimations. In this study, plant height and hyperspectral data were used for barley biomass estimations with bivariate and multivariate models. During three consecutive growing seasons a terrestrial laser scanner was used to establish crop surface models for a pixel-wise calculation of plant height and manual measurements of plant height confirmed the results (R2 up to 0.98. Hyperspectral reflectance measurements were conducted with a field spectrometer and used for calculating six vegetation indices (VIs, which have been found to be related to biomass and LAI: GnyLi, NDVI, NRI, RDVI, REIP, and RGBVI. Furthermore, biomass samples were destructively taken on almost the same dates. Linear and exponential biomass regression models (BRMs were established for evaluating plant height and VIs as estimators of fresh and dry biomass. Each BRM was established for the whole observed period and pre-anthesis, which is important for management decisions. Bivariate BRMs supported plant height as a strong estimator (R2 up to 0.85, whereas BRMs based on individual VIs showed varying performances (R2: 0.07–0.87. Fused approaches, where plant height and one VI were used for establishing multivariate BRMs, yielded improvements in some cases (R2 up to 0.89. Overall, this study reveals the potential of remotely-sensed plant parameters for estimations of barley biomass. Moreover, it is a first step towards the fusion of 3D spatial and spectral measurements for improving non-destructive biomass estimations.

  3. A method to estimate the biomass of Spirulina platensis cultivated on a solid medium.

    Science.gov (United States)

    Pelizer, Lúcia Helena; Moraes, Iracema de Oliveira

    2014-01-01

    This paper presents a method to estimate the biomass of Spirulina cultivated on solid medium with sugarcane bagasse as a support, in view of the difficulty in determining biomass concentrations in bioprocesses, particularly those conducted in semi-solid or solid media. The genus Spirulina of the family Oscillatoriaceae comprises the group of multicellular filamentous cyanobacteria (blue-green microalgae). Spirulina is used as fish feed in aquaculture, as a food supplement, a source of vitamins, pigments, antioxidants and fatty acids. Therefore, its growth parameters are extremely important in studies of the development and optimization of bioprocesses. For studies of biomass growth, Spirulina platensis was cultured on solid medium using sugarcane bagasse as a support. The biomass thus produced was estimated by determining the protein content of the material grown during the process, based on the ratio of dry weight to protein content obtained in the surface growth experiments. The protein content of the biomass grown in Erlenmeyer flasks on surface medium was examined daily to check the influence of culture time on the protein content of the biomass. The biomass showed an average protein content of 42.2%. This methodology enabled the concentration of biomass adhering to the sugarcane bagasse to be estimated from the indirect measurement of the protein content associated with cell growth.

  4. Stand biomass and volume estimation for Miombo woodlands at ...

    African Journals Online (AJOL)

    Stand variables such as number of stems per ha, basal area, biomass, volume and plant diversity, were computed for each stratum. The study has revealed the presence of average volumes (m3ha-1) and basal areas (m2ha-1) of: 76.02 + 9.14 and 9.13 + 0.78 for the Government forest reserve, 76.03 + 9.34 and 8.95 + 0.73 ...

  5. Estimating Terrestrial Wood Biomass from Observed Concentrations of Atmospheric Carbon Dioxide

    NARCIS (Netherlands)

    Schaefer, K. M.; Peters, W.; Carvalhais, N.; van der Werf, G.; Miller, J.

    2008-01-01

    We estimate terrestrial disequilibrium state and wood biomass from observed concentrations of atmospheric CO2 using the CarbonTracker system coupled to the SiBCASA biophysical model. Starting with a priori estimates of carbon flux from the land, ocean, and fossil fuels, CarbonTracker estimates net

  6. DINÁMICA DE LA BIOMASA AÉREA EN UN BOSQUE PLUVIAL TROPICAL DEL CHOCÓ BIOGEOGRÁFICO DYNAMICS OF TREE ABOVEGROUND BIOMASS IN A TROPICAL RAIN FOREST OF THE CHOCÓ BIOGEOGRÁFICO

    Directory of Open Access Journals (Sweden)

    Harley Quinto Mosquera

    2011-06-01

    Full Text Available El estudio de la biomasa aérea (BA de los bosques tropicales es fundamental para entender el balance del C global en el contexto del cambio climático. La BA se cuantificó en un bosque maduro de Salero (Chocó Biogeográfico, mediante ecuaciones diseñadas para bosques húmedos tropicales, a partir de datos de densidad de madera, diámetro (DAP y altura de árboles (con DAP = 10 cm medidos en dos sub-parcelas permanentes ("E" y "U" de 1 ha, las cuales se monitorearon en los años 1998, 2005 y 2008. La BA fue 237,31 t·ha-1, 259,99 t·ha-1 y 217,97 t·ha-1 respectivamente en la sub-parcela "E". Mientras que en la "U" fue de 178,94 t·ha-1y 179,17 t·ha-1 en los años 2005 y 2008; las diferencias de BA a través del tiempo fueron no significativas. Los incrementos promedios anuales de BA de sobrevivientes fueron 4,42 y 3,18 t·ha-1 año-1 en las sub-parcelas "E" y "U" respectivamente. Además, en sub-parcela "E" en condiciones imperturbadas, se presentó una tasa de incremento neto de la BA (TINBA de 2,61 t·ha-1 año-1, en concordancia con la hipótesis del incremento en la BA en los bosques húmedos tropicales. La productividad primaria neta aérea (PPNA en Salero de carbono fue de 5,21 t· ha-1 año-1, por lo tanto los resultados no apoyaron la hipótesis de la disminución en la productividad de los bosques tropicales con el incremento en la precipitación.The study of the aboveground biomass (AB of tropical forests is fundamental to understand the balance of the global C in the context of the climatic change. We quantified the AB in a mature forest of Salero (Chocó Biogeográfico, by means of equations designed for tropical humid forests, starting from data of wooden density, diameter (D and height of trees (with D = 10 cm measured in two permanent sub-parcels (E and U of 1 hectare (ha, which were measured in the years 1998, 2005 and 2008. Inthis years the AB was of 237.31 t·ha-1, 259.99 t·ha-1 and 217.97 t·ha-1 respectively in the E

  7. From a tree to a stand in Finnish boreal forests - biomass estimation and comparison of methods

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Chunjiang

    2009-07-01

    There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61deg50' N, 24deg22' E). In particular, a comparison of the results of different estimation methods was conducted to assess the reliability and suitability of their applications. For the trees in Mature-Stand, annual stem biomass increment fluctuated following a sigmoid equation, and the fitting curves reached a maximum level (from about 1 kg yr-1 for understorey spruce to 7 kg yr-1 for dominant pine) when the trees were 100 years old). Tree biomass was estimated to be about 70 Mg ha-1 in Young-Stand and about 220 Mg ha-1 in Mature-Stand. In the region (58.00-62.13 degN, 14-34 degE, <= 300 m a.s.l.) surrounding the study stands, the tree biomass accumulation in Norway spruce and Scots pine stands followed a sigmoid equation with stand age, with a maximum of 230 Mg ha-1 at the age of 140 years. In Mature-Stand, lichen biomass on the trees was 1.63 Mg ha-1 with more than half of the biomass occurring on dead branches, and the standing crop of litter lichen on the ground was about 0.09 Mg ha-1. There were substantial differences among the results estimated by different methods in the stands. These results imply that a possible estimation error should be taken into account when calculating tree biomass in a stand with an indirect approach. (orig.)

  8. Biomass

    International Nuclear Information System (INIS)

    Hernandez, L.A.

    1998-01-01

    Biomass constitutes the energetic form more important and of greater potential after solar energy (source of origin), being consumed in direct form through the combustion, or indirectly through the fossil fuels (those which originates) or by means of different technical of thermochemical and of biochemistry for its conversion and utilization. The current document describes the origin and the energetic characteristics of biomass, its energetic and environmental importance for a developing Country as Colombia, its possibilities of production and the technologies developed for its utilization and transformation, mainly, of the residual biomass

  9. Direct single-cell biomass estimates for marine bacteria via Archimedes' principle.

    Science.gov (United States)

    Cermak, Nathan; Becker, Jamie W; Knudsen, Scott M; Chisholm, Sallie W; Manalis, Scott R; Polz, Martin F

    2017-03-01

    Microbes are an essential component of marine food webs and biogeochemical cycles, and therefore precise estimates of their biomass are of significant value. Here, we measured single-cell biomass distributions of isolates from several numerically abundant marine bacterial groups, including Pelagibacter (SAR11), Prochlorococcus and Vibrio using a microfluidic mass sensor known as a suspended microchannel resonator (SMR). We show that the SMR can provide biomass (dry mass) measurements for cells spanning more than two orders of magnitude and that these estimates are consistent with other independent measures. We find that Pelagibacterales strain HTCC1062 has a median biomass of 11.9±0.7 fg per cell, which is five- to twelve-fold smaller than the median Prochlorococcus cell's biomass (depending upon strain) and nearly 100-fold lower than that of rapidly growing V. splendidus strain 13B01. Knowing the biomass contributions from various taxonomic groups will provide more precise estimates of total marine biomass, aiding models of nutrient flux in the ocean.

  10. National scale biomass estimators for United States tree species

    Science.gov (United States)

    Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

    2003-01-01

    Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the literature is inconsistent and incomplete with respect to large-scale forest C estimation. We compiled all available diameter-based allometric regression equations for estimating total...

  11. Estimation of biomass and canopy height in bermudagrass, alfalfa, and wheat using ultrasonic, laser, and spectral sensors.

    Science.gov (United States)

    Pittman, Jeremy Joshua; Arnall, Daryl Brian; Interrante, Sindy M; Moffet, Corey A; Butler, Twain J

    2015-01-28

    Non-destructive biomass estimation of vegetation has been performed via remote sensing as well as physical measurements. An effective method for estimating biomass must have accuracy comparable to the accepted standard of destructive removal. Estimation or measurement of height is commonly employed to create a relationship between height and mass. This study examined several types of ground-based mobile sensing strategies for forage biomass estimation. Forage production experiments consisting of alfalfa (Medicago sativa L.), bermudagrass [Cynodon dactylon (L.) Pers.], and wheat (Triticum aestivum L.) were employed to examine sensor biomass estimation (laser, ultrasonic, and spectral) as compared to physical measurements (plate meter and meter stick) and the traditional harvest method (clipping). Predictive models were constructed via partial least squares regression and modeled estimates were compared to the physically measured biomass. Least significant difference separated mean estimates were examined to evaluate differences in the physical measurements and sensor estimates for canopy height and biomass. Differences between methods were minimal (average percent error of 11.2% for difference between predicted values versus machine and quadrat harvested biomass values (1.64 and 4.91 t·ha(-1), respectively), except at the lowest measured biomass (average percent error of 89% for harvester and quad harvested biomass 6.4 t·ha(-1)). These data suggest that using mobile sensor-based biomass estimation models could be an effective alternative to the traditional clipping method for rapid, accurate in-field biomass estimation.

  12. Carbon stock estimates for forests in the Castilla y Leon region, Spain. A GIS based method for evaluating spatial distribution of residual biomass for bio-energy

    Energy Technology Data Exchange (ETDEWEB)

    Gil, Maria Victoria; Blanco, Daniel; Carballo, Maria Teresa; Calvo, Luis Fernando [Chemical Engineering, Institute of Natural Resources, University of Leon, Avenida de Portugal, 41, 24071 Leon (Spain)

    2011-01-15

    Analysis of aboveground biomass and carbon stocks (as equivalent CO{sub 2}) was performed in the Castilla y Leon region, Spain. Data from the second and third Spanish Forest Inventories (1996 and 2006) were used. Total aboveground biomass was calculated using allometric biomass equations and biomass expansion factors (BEF), the first method giving higher values. Forests of Castilla y Leon stored 77,051,308 Mg of biomass, with a mean of 8.18 Mg ha{sup -1}, in 1996 and 135,531,737 Mg of biomass, with a mean of 14.4 Mg ha{sup -1}, in 2006. The total equivalent CO{sub 2} in this region's forests increased 9,608,824 Mg year{sup -1} between 1996 and 2006. In relation to the Kyoto Protocol, the Castilla y Leon forests have sequestered 3 million tons of CO{sub 2} per year, which represents 6.4% of the total regional emission of CO{sub 2}. A Geographic Information System (GIS) based method was also used to assess the geographic distribution of residual forest biomass for bio-energy in the region. The forest statistics data on area of each species were used. The fraction of vegetation cover, land slope and protected areas were also considered. The residual forest biomass in Castilla y Leon was 1,464,991 Mg year{sup -1}, or 1.90% of the total aboveground biomass in 1996. The residual forest biomass was concentrated in specific zones of the Castilla y Leon region, suitable for the location of industries that utilize biomass as energy source. The energy potential of the residual forest biomass in the Castilla y Leon region is 7350 million MJ per year. (author)

  13. Aboveground storage tanks

    International Nuclear Information System (INIS)

    Rizzo, J.A.

    1992-01-01

    With the 1988 promulgation of the comprehensive Resource Conservation and Recovery Act (RCRA) regulations for underground storage of petroleum and hazardous substances, many existing underground storage tank (UST) owners have been considering making the move to aboveground storage. While on the surface, this may appear to be the cure-all to avoiding the underground leakage dilemma, there are many other new and different issues to consider with aboveground storage. The greatest misconception is that by storing materials above ground, there is no risk of subsurface environmental problems. it should be noted that with the aboveground storage tank (AGST) systems, there is still considerable risk of environmental contamination, either by the failure of onground tank bottoms or the spillage of product onto the ground surface where it subsequently finds its way to the ground water. In addition, there are added safety concerns that must be addressed. So what are the other specific areas of concern besides environmental to be addressed when making the decision between underground and aboveground tanks? The primary issues that will be addressed in this paper are: Safety, Product Losses, Cost Comparison of USTs vs AGSTs, Space Availability/Accessibility, Precipitation Handling, Aesthetics and Security, Pending and Existing Regulations

  14. Regional distribution of forest height and biomass from multisensor data fusion

    Science.gov (United States)

    Yifan Yu; Sassan Saatch; Linda S. Heath; Elizabeth LaPoint; Ranga Myneni; Yuri. Knyazikhin

    2010-01-01

    Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM...

  15. The utilization of false color aerial photography for macrophyte biomass estimation in the Oosterschelde (the Netherlands)

    Science.gov (United States)

    Meulstee, C.; Vanstokkom, H.

    1985-01-01

    The correlation between the biomass of sea grass and seaweed samples in a sidebranch of the Oosterschelde delta (Netherlands) and density ratios of this area on color infrared aerial photographs was investigated. As the Oosterschelde will become more divided from the North Sea after pier dam completion, an increase of macrophytes is expected. In an area where the weeds Ulva, Cheatomorpha, Entermorpha, Cladophora, Fucus vesuculosis, and the grasses Zostera noltii and Zostera marina are found, 53 biomass samples of a 0.054 sq m surface each were collected. The relation between covering degree and biomass was estimated. Using a transmission-densitometer adjusted to 3 to 1 mm, densities on 1:10,000 and 1:20,000 scale photographs were measured. A gage line was determined in a density-biomass diagram. The method is shown to be useful for an efficient, accurate biomass determination in the Oosterschelde.

  16. A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

    Science.gov (United States)

    Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie

    2018-05-01

    estuarine emergent marshes (2.03 ± 0.004 Mg/ha). Estimated C stocks for predefined jurisdictional areas ranged from 1023 ± 39 Mg in the Nisqually National Wildlife Refuge in Washington to 507,761 ± 14,822 Mg in the Terrebonne and St. Mary Parishes in Louisiana. This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included in the coastal wetland section of the U.S. National Greenhouse Gas Inventory. With the increased availability of free post-processed satellite data, we provide a tractable means of modeling tidal marsh aboveground biomass and carbon at the global extent as well.

  17. High-resolution three-dimensional mapping of forest structure and aboveground biomass stocks in blue carbon ecosystems with airborne Lidar, TanDEM-X and WorldView Stereo

    Science.gov (United States)

    Fatoyinbo, T.; Lagomasino, D.; Simard, M.; Lee, S. K.; Feliciano, E. A.; Trettin, C.

    2017-12-01

    Vegetated coastal ecosystems, also called Blue Carbon ecosystems are highly efficient carbon sinks and have been shown to play a role in ameliorating the effect of increasing global climate change by capturing significant amounts of carbon into sediments and plant biomass. Mangrove-lined estuaries and coastal ecosystems are significant to global biogeochemical processes and regulate the structure, productivity and function of adjacent coastal ecosystems disproportionately to their land cover. Here we present recent efforts by the CMS Total Blue Carbon Stocks in Africa Project to estimate total (above and belowground) carbon stocks in East and Central Africa using in situ, high resolution stereo, airborne lidar and spaceborne SAR data. We generated Mangrove extent and change maps and canopy height estimates for the 2000 and 2015 eras that were used as input to carry out stratified field plot samples of above, below and soil Carbon stocks in the Rufiji Delta, Tanzania, Zambezi Delta, Mozambique and Pongara National Park, Gabon. By combining the field measurements and remotely sensed data, we estimated countrywide mangrove total carbon stocks. Uncertainties of estimates associated with different remote sensing input data were also calculated and will be presented. In this talk, we will give an overview of recent efforts to quantify mangrove forest 3-D structure, composition and change at high resolution globally in the context of estimating forest biomass and blue carbon stocks. Our presentation covers field and remotely sensed investigations and describes unique remotely sensed datasets produced and collected at NASA, with an emphasis on recently collected airborne Lidar and Radar from the AfriSAR campaign. Specifically, we will present new results focusing on the validation and comparison of independent mangrove canopy height and biomass measurements from commercial airborne lidar, LVIS, TanDEM-X, UAVSAR and World View, from Gabon, Mozambique and Tanzania.

  18. Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Silva

    2017-10-01

    Full Text Available Airborne lidar is a technology well-suited for mapping many forest attributes, including aboveground biomass (AGB stocks and changes in selective logging in tropical forests. However, trade-offs still exist between lidar pulse density and accuracy of AGB estimates. We assessed the impacts of lidar pulse density on the estimation of AGB stocks and changes using airborne lidar and field plot data in a selectively logged tropical forest located near Paragominas, Pará, Brazil. Field-derived AGB was computed at 85 square 50 × 50 m plots in 2014. Lidar data were acquired in 2012 and 2014, and for each dataset the pulse density was subsampled from its original density of 13.8 and 37.5 pulses·m−2 to lower densities of 12, 10, 8, 6, 4, 2, 0.8, 0.6, 0.4 and 0.2 pulses·m−2. For each pulse density dataset, a power-law model was developed to estimate AGB stocks from lidar-derived mean height and corresponding changes between the years 2012 and 2014. We found that AGB change estimates at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg·ha−1 when pulse density decreased from 12 to 0.2 pulses·m−2. The effects of pulse density were more pronounced in areas of steep slope, especially when the digital terrain models (DTMs used in the lidar derived forest height were created from reduced pulse density data. In particular, when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and the estimated AGB stock and changes did not exceed 20 Mg·ha−1. The results suggest that AGB change can be monitored in selective logging in tropical forests with reasonable accuracy and low cost with low pulse density lidar surveys if a baseline high-quality DTM is available from at least one lidar survey. We recommend the results of this study to be considered in developing projects and national

  19. Appendix C: Biomass Program inputs for FY 2008 benefits estimates

    Energy Technology Data Exchange (ETDEWEB)

    None, None

    2009-01-18

    Document summarizes the results of the benefits analysis of EERE’s programs, as described in the FY 2008 Budget Request. EERE estimates benefits for its overall portfolio and nine Research, Development, Demonstration, and Deployment (RD3) programs.

  20. BIOMASS FROM CROP RESIDUES: COST AND SUPPLY ESTIMATES

    OpenAIRE

    Gallagher, Paul W.; Dikeman, Mark; Fritz, John; Wailes, Eric J.; Gauthier, Wayne M.; Shapouri, Hosein

    2003-01-01

    The supply of harvested crop residues as a feed stock for energy products is estimated in this report. The estimates account for economic and environmental factors governing residue supply. The supply results span major agricultural crops in four distinct cropping regions of the United States, taking into account local variation in cost-determining factors such as residue yield, geographic density of residues, and competition for livestock feed use.

  1. The effect of cassava-based bioethanol production on above-ground carbon stocks: A case study from Southern Mali

    International Nuclear Information System (INIS)

    Vang Rasmussen, Laura; Rasmussen, Kjeld; Birch-Thomsen, Torben; Kristensen, Søren B.P.; Traoré, Oumar

    2012-01-01

    Increasing energy use and the need to mitigate climate change make production of liquid biofuels a high priority. Farmers respond worldwide to this increasing demand by converting forests and grassland into biofuel crops, but whether biofuels offer carbon savings depends on the carbon emissions that occur when land use is changed to biofuel crops. This paper reports the results of a study on cassava-based bioethanol production undertaken in the Sikasso region in Southern Mali. The paper outlines the estimated impacts on above-ground carbon stocks when land use is changed to increase cassava production. The results show that expansion of cassava production for bioethanol will most likely lead to the conversion of fallow areas to cassava. A land use change from fallow to cassava creates a reduction in the above-ground carbon stocks in the order of 4–13 Mg C ha −1 , depending on (a) the age of the fallow, (b) the allometric equation used and (c) whether all trees are removed or the larger, useful trees are preserved. This ‘carbon debt’ associated with the above-ground biomass loss would take 8–25 years to repay if fossil fuels are replaced with cassava-based bioethanol. - Highlights: ► Demands for biofuels make production of cassava-based bioethanol a priority. ► Farmers in Southern Mali are likely to convert fallow areas to cassava production. ► Converting fallow to cassava creates reductions in above-ground carbon stocks. ► Estimates of carbon stock reductions include that farmers preserve useful trees. ► The carbon debt associated with above-ground biomass loss takes 8–25 years to repay.

  2. The Use of Fire Radiative Power to Estimate the Biomass Consumption Coefficient for Temperate Grasslands in the Atlantic Forest Biome

    Directory of Open Access Journals (Sweden)

    Bibiana Salvador Cabral da Costa

    Full Text Available Abstract Every year, many active fire spots are identified in the satellite images of the southern Brazilian grasslands in the Atlantic Forest biome and Pampa biome. Fire Radiative Power (FRP is a technique that uses remotely sensed data to quantify burned biomass. FRP measures the radiant energy released per time unit by burning vegetation. This study aims to use satellite and field data to estimate the biomass consumption rate and the biomass consumption coefficient for the southern Brazilian grasslands. Three fire points were identified in satellite FRP products. These data were combined with field data, collected through literature review, to calculate the biomass consumption coefficient. The type of vegetation is an important variable in the estimation of the biomass consumption coefficient. The biomass consumption rate was estimated to be 2.237 kg s-1 for the southern Brazilian grasslands in Atlantic Forest biome, and the biomass consumption coefficient was estimated to be 0.242 kg MJ-1.

  3. Landsat Imagery-Based Above Ground Biomass Estimation and Change Investigation Related to Human Activities

    Directory of Open Access Journals (Sweden)

    Chaofan Wu

    2016-02-01

    Full Text Available Forest biomass is a significant indicator for substance accumulation and forest succession, and a spatiotemporal biomass map would provide valuable information for forest management and scientific planning. In this study, Landsat imagery and field data cooperated with a random forest regression approach were used to estimate spatiotemporal Above Ground Biomass (AGB in Fuyang County, Zhejiang Province of East China. As a result, the AGB retrieval showed an increasing trend for the past decade, from 74.24 ton/ha in 2004 to 99.63 ton/ha in 2013. Topography and forest management were investigated to find their relationships with the spatial distribution change of biomass. In general, the simulated AGB increases with higher elevation, especially in the range of 80–200 m, wherein AGB acquires the highest increase rate. Moreover, the forest policy of ecological forest has a positive effect on the AGB increase, particularly within the national level ecological forest. The result in this study demonstrates that human activities have a great impact on biomass distribution and change tendency. Furthermore, Landsat image-based biomass estimates would provide illuminating information for forest policy-making and sustainable development.

  4. Inference for lidar-assisted estimation of forest growing stock volume

    Science.gov (United States)

    Ronald E. McRoberts; Erik Næsset; Terje. Gobakken

    2013-01-01

    Estimates of growing stock volume are reported by the national forest inventories (NFI) of most countries and may serve as the basis for aboveground biomass and carbon estimates as required by an increasing number of international agreements. The probability-based (design-based) statistical estimators traditionally used by NFIs to calculate estimates are generally...

  5. Estimation of Biomass and Canopy Height in Bermudagrass, Alfalfa, and Wheat Using Ultrasonic, Laser, and Spectral Sensors

    Directory of Open Access Journals (Sweden)

    Jeremy Joshua Pittman

    2015-01-01

    Full Text Available Non-destructive biomass estimation of vegetation has been performed via remote sensing as well as physical measurements. An effective method for estimating biomass must have accuracy comparable to the accepted standard of destructive removal. Estimation or measurement of height is commonly employed to create a relationship between height and mass. This study examined several types of ground-based mobile sensing strategies for forage biomass estimation. Forage production experiments consisting of alfalfa (Medicago sativa L., bermudagrass [Cynodon dactylon (L. Pers.], and wheat (Triticum aestivum L. were employed to examine sensor biomass estimation (laser, ultrasonic, and spectral as compared to physical measurements (plate meter and meter stick and the traditional harvest method (clipping. Predictive models were constructed via partial least squares regression and modeled estimates were compared to the physically measured biomass. Least significant difference separated mean estimates were examined to evaluate differences in the physical measurements and sensor estimates for canopy height and biomass. Differences between methods were minimal (average percent error of 11.2% for difference between predicted values versus machine and quadrat harvested biomass values (1.64 and 4.91 t·ha−1, respectively, except at the lowest measured biomass (average percent error of 89% for harvester and quad harvested biomass < 0.79 t·ha−1 and greatest measured biomass (average percent error of 18% for harvester and quad harvested biomass >6.4 t·ha−1. These data suggest that using mobile sensor-based biomass estimation models could be an effective alternative to the traditional clipping method for rapid, accurate in-field biomass estimation.

  6. Indirect methods of tree biomass estimation and their uncertainties ...

    African Journals Online (AJOL)

    Depending on data availability (dbh only or both dbh and total tree height) either of the models may be applied to generate satisfactory estimates of tree volume needed for planning and decision-making in management of mangrove forests. The study found an overall mean FF value of 0.65 ± 0.03 (SE), 0.56 ± 0.03 (SE) and ...

  7. Evaluation of the reference unit method for herbaceous biomass estimation in native grasslands of southwestern South Dakota

    Science.gov (United States)

    Eric D. Boyda

    2013-01-01

    The high costs associated with physically harvesting plant biomass may prevent sufficient data collection, which is necessary to account for the natural variability of vegetation at a landscape scale. A biomass estimation technique was previously developed using representative samples or "reference units", which eliminated the need to harvest biomass from all...

  8. Extension of biomass estimates to pre-assessment periods using density dependent surplus production approach

    Science.gov (United States)

    Horbowy, Jan

    2017-01-01

    Biomass reconstructions to pre-assessment periods for commercially important and exploitable fish species are important tools for understanding long-term processes and fluctuation on stock and ecosystem level. For some stocks only fisheries statistics and fishery dependent data are available, for periods before surveys were conducted. The methods for the backward extension of the analytical assessment of biomass for years for which only total catch volumes are available were developed and tested in this paper. Two of the approaches developed apply the concept of the surplus production rate (SPR), which is shown to be stock density dependent if stock dynamics is governed by classical stock-production models. The other approach used a modified form of the Schaefer production model that allows for backward biomass estimation. The performance of the methods was tested on the Arctic cod and North Sea herring stocks, for which analytical biomass estimates extend back to the late 1940s. Next, the methods were applied to extend biomass estimates of the North-east Atlantic mackerel from the 1970s (analytical biomass estimates available) to the 1950s, for which only total catch volumes were available. For comparison with other methods which employs a constant SPR estimated as an average of the observed values, was also applied. The analyses showed that the performance of the methods is stock and data specific; the methods that work well for one stock may fail for the others. The constant SPR method is not recommended in those cases when the SPR is relatively high and the catch volumes in the reconstructed period are low. PMID:29131850

  9. Extension of biomass estimates to pre-assessment periods using density dependent surplus production approach.

    Directory of Open Access Journals (Sweden)

    Jan Horbowy

    Full Text Available Biomass reconstructions to pre-assessment periods for commercially important and exploitable fish species are important tools for understanding long-term processes and fluctuation on stock and ecosystem level. For some stocks only fisheries statistics and fishery dependent data are available, for periods before surveys were conducted. The methods for the backward extension of the analytical assessment of biomass for years for which only total catch volumes are available were developed and tested in this paper. Two of the approaches developed apply the concept of the surplus production rate (SPR, which is shown to be stock density dependent if stock dynamics is governed by classical stock-production models. The other approach used a modified form of the Schaefer production model that allows for backward biomass estimation. The performance of the methods was tested on the Arctic cod and North Sea herring stocks, for which analytical biomass estimates extend back to the late 1940s. Next, the methods were applied to extend biomass estimates of the North-east Atlantic mackerel from the 1970s (analytical biomass estimates available to the 1950s, for which only total catch volumes were available. For comparison with other methods which employs a constant SPR estimated as an average of the observed values, was also applied. The analyses showed that the performance of the methods is stock and data specific; the methods that work well for one stock may fail for the others. The constant SPR method is not recommended in those cases when the SPR is relatively high and the catch volumes in the reconstructed period are low.

  10. Estimate of biomass and carbon pools in disturbed and undisturbed oak forests in Tunisia

    Directory of Open Access Journals (Sweden)

    Lobna Zribi

    2016-07-01

    Full Text Available Aim of the study. To estimate biomass and carbon accumulation in a young and disturbed forest (regenerated after a tornado and an aged cork oak forest (undisturbed forest as well as its distribution among the different pools (tree, litter and soil. Area of study. The north west of Tunisia Material and methods. Carbon stocks were evaluated in the above and belowground cork oak trees, the litter and the 150 cm of the soil. Tree biomass was estimated in both young and aged forests using allometric biomass equations developed for wood stem, cork stem, wood branch, cork branch, leaves, roots and total tree biomass based on combinations of diameter at breast height, total height and crown length as independent variables. Main results. Total tree biomass in forests was 240.58 Mg ha-1 in the young forest and 411.30 Mg ha-1 in the aged forest with a low root/shoot ratio (0.41 for young forest and 0.31 for aged forest. Total stored carbon was 419.46 Mg C ha-1 in the young forest and 658.09 Mg C ha-1 in the aged forest. Carbon stock (Mg C ha-1 was estimated to be113.61(27.08% and 194.08 (29.49% in trees, 3.55 (0.85% and 5.73 (0.87% in litter and 302.30 (72.07% and 458.27 (69.64% in soil in the young and aged forests, respectively. Research highlights. Aged undisturbed forest had the largest tree biomass but a lower potential for accumulation of carbon in the future; in contrast, young disturbed forest had both higher growth and carbon storage potential. Keywords: Tree biomass; disturbance; allometry; cork oak forests; soil organic carbon stock.

  11. Evaluation of the Environmental DNA Method for Estimating Distribution and Biomass of Submerged Aquatic Plants.

    Science.gov (United States)

    Matsuhashi, Saeko; Doi, Hideyuki; Fujiwara, Ayaka; Watanabe, Sonoko; Minamoto, Toshifumi

    2016-01-01

    The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants.

  12. Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms. [Guyton, Oklahoma and Dalhart, Texas

    Science.gov (United States)

    Rosenthal, W. D.; Mcfarland, M. J.; Theis, S. W.; Jones, C. L. (Principal Investigator)

    1982-01-01

    Agricultural crop classification models using two or more spectral regions (visible through microwave) are considered in an effort to estimate biomass at Guymon, Oklahoma Dalhart, Texas. Both grounds truth and aerial data were used. Results indicate that inclusion of C, L, and P band active microwave data, from look angles greater than 35 deg from nadir, with visible and infrared data improve crop discrimination and biomass estimates compared to results using only visible and infrared data. The microwave frequencies were sensitive to different biomass levels. The K and C band were sensitive to differences at low biomass levels, while P band was sensitive to differences at high biomass levels. Two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass. It is implied that inclusion of active microwave sensors with visible and infrared sensors on future satellites could aid in crop discrimination and biomass estimation.

  13. Rainforest burning and the global carbon budget: Biomass, combustion efficiency, and charcoal formation in the Brazilian Amazon

    Science.gov (United States)

    Fearnside, Philip M.; Leal, Niwton; Fernandes, Fernando Moreira

    1993-01-01

    Biomass present before and after burning was measured in forest cleared for pasture in a cattle ranch (Fazenda Dimona) near Manaus, Amazonas, Brazil. Aboveground dry weight biomass loading averaged 265 t ha-1 (standard deviation (SD) = 110, n = 6 quadrats) at Fazenda Dimona, which corresponds to approximately 311 t ha-1 total dry weight biomass. A five-category visual classification at 200 points showed highly variable burn quality. Postburn aboveground biomass loading was evaluated by cutting and weighing of 100 m2 quadrats and by line intersect sampling. Quadrats had a mean dry weight of 187 t ha-1 (SD = 69, n = 10), a 29.3% reduction from the preburn mean in the same clearing. Line intersect estimates in 1.65 km of transects indicated that 265 m3 ha-1 (approximately 164 t ha-1 of aboveground dry matter) survived burning. Using carbon contents measured for different biomass components (all ˜50% carbon) and assuming a carbon content of 74.8% for charcoal (from other studies near Manaus), the destructive measurements imply a 27.6% reduction of aboveground carbon pools. Charcoal composed 2.5% of the dry weight of the remains in the postburn destructive quadrats and 2.8% of the volume in the line intersect transects. Thus approximately 2.7% of the preburn aboveground carbon stock was converted to charcoal, substantially less than is generally assumed in global carbon models. The findings confirm high values for biomass in central Amazonia. High variability indicates the need for further studies in many localities and for making maximum use of less laborious indirect methods of biomass estimation. While indirect methods are essential for regional estimates of average biomass, only direct weighing such as that reported here can yield information on combustion efficiency and charcoal formation. Both high biomass and low percentage of charcoal formation suggest the significant potential contribution of forest burning to global climate changes from CO2 and trace gases.

  14. [Fungal biomass estimation in soils from southwestern Buenos Aires province (Argentina) using calcofluor white stain].

    Science.gov (United States)

    Vázquez, María B; Amodeo, Martín R; Bianchinotti, María V

    Soil microorganisms are vital for ecosystem functioning because of the role they play in soil nutrient cycling. Agricultural practices and the intensification of land use have a negative effect on microbial activities and fungal biomass has been widely used as an indicator of soil health. The aim of this study was to analyze fungal biomass in soils from southwestern Buenos Aires province using direct fluorescent staining and to contribute to its use as an indicator of environmental changes in the ecosystem as well as to define its sensitivity to weather conditions. Soil samples were collected during two consecutive years. Soil smears were prepared and stained with two different concentrations of calcofluor, and the fungal biomass was estimated under an epifluorescence microscope. Soil fungal biomass varied between 2.23 and 26.89μg fungal C/g soil, being these values in the range expected for the studied soil type. The fungal biomass was positively related to temperature and precipitations. The methodology used was reliable, standardized and sensitive to weather conditions. The results of this study contribute information to evaluate fungal biomass in different soil types and support its use as an indicator of soil health for analyzing the impact of different agricultural practices. Copyright © 2016 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

  15. Interest of Integrating Spaceborne LiDAR Data to Improve the Estimation of Biomass in High Biomass Forested Areas

    Directory of Open Access Journals (Sweden)

    Mohammad El Hajj

    2017-02-01

    Full Text Available Mapping forest AGB (Above Ground Biomass is of crucial importance to estimate the carbon emissions associated with tropical deforestation. This study proposes a method to overcome the saturation at high AGB values of existing AGB map (Vieilledent’s AGB map by using a map of correction factors generated from GLAS (Geoscience Laser Altimeter System spaceborne LiDAR data. The Vieilledent’s AGB map of Madagascar was established using optical images, with parameters calculated from the SRTM Digital Elevation Model, climatic variables, and field inventories. In the present study, first, GLAS LiDAR data were used to obtain a spatially distributed (GLAS footprints geolocation estimation of AGB (GLAS AGB covering Madagascar forested areas, with a density of 0.52 footprint/km2. Second, the difference between the AGB from the Vieilledent’s AGB map and GLAS AGB at each GLAS footprint location was calculated, and additional spatially distributed correction factors were obtained. Third, an ordinary kriging interpolation was thus performed by taking into account the spatial structure of these additional correction factors to provide a continuous correction factor map. Finally, the existing and the correction factor maps were summed to improve the Vieilledent’s AGB map. The results showed that the integration of GLAS data improves the precision of Vieilledent’s AGB map by approximately 7 t/ha. By integrating GLAS data, the RMSE on AGB estimates decreases from 81 t/ha (R2 = 0.62 to 74.1 t/ha (R2 = 0.71. Most importantly, we showed that this approach using LiDAR data avoids underestimating high biomass values (new maximum AGB of 650 t/ha compared to 550 t/ha with the first approach.

  16. Top-down estimates of biomass burning emissions of black carbon in the western United States

    Science.gov (United States)

    Y. H. Mao; Q. B. Li; D. Chen; L. Zhang; W. -M. Hao; K.-N. Liou

    2014-01-01

    We estimate biomass burning and anthropogenic emissions of black carbon (BC) in the western US for May-October 2006 by inverting surface BC concentrations from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network using a global chemical transport model. We first use active fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS...

  17. Survey estimates of fishable biomass following a mass mortality in an Australian molluscan fishery.

    Science.gov (United States)

    Mayfield, S; McGarvey, R; Gorfine, H K; Peeters, H; Burch, P; Sharma, S

    2011-04-01

    Mass mortality events are relatively uncommon in commercially fished populations, but when they occur, they reduce production and degrade ecosystems. Observing and documenting mass mortalities is simpler than quantifying the impact on stocks, monitoring or predicting recovery, and re-establishing commercial fishing. Direct survey measures of abundance, distribution and harvestable biomass provide the most tenable approach to informing decisions about future harvests in cases where stock collapses have occurred because conventional methods have been disrupted and are less applicable. Abalone viral ganglioneuritis (AVG) has resulted in high levels of mortality across all length classes of blacklip abalone, Haliotis rubra Leach, off western Victoria, Australia, since May 2006. Commercial catches in this previously valuable fishery were reduced substantially. This paper describes the integration of research surveys with commercial fishermen's knowledge to estimate the biomass of abalone on AVG-impacted reefs. Experienced commercial abalone divers provided credible information on the precise locations of historical fishing grounds within which fishery-independent surveys were undertaken. Abalone density estimates remained low relative to pre-AVG levels, and total biomass estimates were similar to historical annual catch levels, indicating that the abalone populations have yet to adequately recover. Survey biomass estimates were incorporated into harvest decision tables and used with prior accumulated knowledge of the populations to determine a conservative harvest strategy for the fishery. © 2011 Blackwell Publishing Ltd.

  18. Allometric equations for estimating tree biomass in restored mixed-species Atlantic Forest stands

    Science.gov (United States)

    Lauro Rodrigues Nogueira; Vera Lex Engel; John A. Parrotta; Antonio Carlos Galvão de Melo; Danilo. Scorzoni Ré

    2014-01-01

    Restoration of Atlantic Forests is receiving increasing attention because of its role in both biodiversity conservation and carbon sequestration for global climate change mitigation. This study was carried out in an Atlantic Forest restoration project in the south-central region of São Paulo State – Brazil to develop allometric equations to estimate tree biomass of...

  19. Wood Specific Gravity Variation with Height and Its Implications for Biomass Estimation

    Science.gov (United States)

    Michael C. Wiemann; G. Bruce Williamson

    2014-01-01

    Wood specific gravity (SG) is widely employed by ecologists as a key variable in estimates of biomass. When it is important to have nondestructive methods for sampling wood for SG measurements, cores are extracted with an increment borer. While boring is a relatively difficult task even at breast height sampling, it is impossible at ground level and arduous at heights...

  20. Uncertainty of Forest Biomass Estimates in North Temperate Forests Due to Allometry: Implications for Remote Sensing

    Directory of Open Access Journals (Sweden)

    Razi Ahmed

    2013-06-01

    Full Text Available Estimates of above ground biomass density in forests are crucial for refining global climate models and understanding climate change. Although data from field studies can be aggregated to estimate carbon stocks on global scales, the sparsity of such field data, temporal heterogeneity and methodological variations introduce large errors. Remote sensing measurements from spaceborne sensors are a realistic alternative for global carbon accounting; however, the uncertainty of such measurements is not well known and remains an active area of research. This article describes an effort to collect field data at the Harvard and Howland Forest sites, set in the temperate forests of the Northeastern United States in an attempt to establish ground truth forest biomass for calibration of remote sensing measurements. We present an assessment of the quality of ground truth biomass estimates derived from three different sets of diameter-based allometric equations over the Harvard and Howland Forests to establish the contribution of errors in ground truth data to the error in biomass estimates from remote sensing measurements.

  1. Estimating single-tree branch biomass of Norway spruce by airborne laser scanning

    Science.gov (United States)

    Hauglin, Marius; Dibdiakova, Janka; Gobakken, Terje; Næsset, Erik

    2013-05-01

    The use of forest biomass for bioenergy purposes, directly or through refinement processes, has increased in the last decade. One example of such use is the utilization of logging residues. Branch biomass constitutes typically a considerable part of the logging residues, and should be quantified and included in future forest inventories. Airborne laser scanning (ALS) is widely used when collecting data for forest inventories, and even methods to derive information at the single-tree level has been described. Procedures for estimation of single-tree branch biomass of Norway spruce using features derived from ALS data are proposed in the present study. As field reference data the dry weight branch biomass of 50 trees were obtained through destructive sampling. Variables were further derived from the ALS echoes from each tree, including crown volume calculated from an interpolated crown surface constructed with a radial basis function. Spatial information derived from the pulse vectors were also incorporated when calculating the crown volume. Regression models with branch biomass as response variable were fit to the data, and the prediction accuracy assessed through a cross-validation procedure. Random forest regression models were compared to stepwise and simple linear least squares models. In the present study branch biomass was estimated with a higher accuracy by the best ALS-based models than by existing allometric biomass equations based on field measurements. An improved prediction accuracy was observed when incorporating information from the laser pulse vectors into the calculation of the crown volume variable, and a linear model with the crown volume as a single predictor gave the best overall results with a root mean square error of 35% in the validation.

  2. A forward-looking, national-scale remote sensing-based model of tidal marsh aboveground carbon stocks

    Science.gov (United States)

    Holmquist, J. R.; Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Windham-Myers, L.; Thomas, N.

    2017-12-01

    Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our goal was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). To meet this objective we developed the first national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest algorithm we tested Sentinel-1 radar backscatter metrics and Landsat vegetation indices as predictors of biomass. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n=409, RMSE=310 g/m2, 10.3% normalized RMSE), successfully predicted biomass and carbon for a range of marsh plant functional types defined by height, leaf angle and growth form. Model error was reduced by scaling field measured biomass by Landsat fraction green vegetation derived from object-based classification of National Agriculture Imagery Program imagery. We generated 30m resolution biomass maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map for each region. With a mean plant %C of 44.1% (n=1384, 95% C.I.=43.99% - 44.37%) we estimated mean aboveground carbon densities (Mg/ha) and total carbon stocks for each wetland type for each region. Louisiana palustrine emergent marshes had the highest C density (2.67 ±0.08 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ±0.06 Mg/ha). This modeling and data synthesis effort will allow for aboveground

  3. Pattern and control of biomass allocation across global forest ecosystems.

    Science.gov (United States)

    Jiang, Yongtao; Wang, Limei

    2017-07-01

    The underground part of a tree is an important carbon sink in forest ecosystems. Understanding biomass allocation between the below- and aboveground parts ( root:shoot ratios ) is necessary for estimation of the underground biomass and carbon pool. Nevertheless, large-scale biomass allocation patterns and their control mechanisms are not well identified. In this study, a large database of global forests at the community level was compiled to investigate the root:shoot ratios and their responses to environmental factors. The results indicated that both the aboveground biomass ( AGB ) and belowground biomass ( BGB ) of the forests in China (medians 73.0 Mg/ha and 17.0 Mg/ha, respectively) were lower than those worldwide (medians 120.3 Mg/ha and 27.7 Mg/ha, respectively). The root:shoot ratios of the forests in China (median = 0.23), however, were not significantly different from other forests worldwide (median = 0.24). In general, the allocation of biomass between the belowground and aboveground parts was determined mainly by the inherent allometry of the plant but also by environmental factors. In this study, most correlations between root:shoot ratios and environmental factors (development parameter, climate, altitude, and soil) were weak but significant ( p  BGB based on AGB across the entire database.

  4. First-order estimate of the planktic foraminifer biomass in the modern ocean

    Directory of Open Access Journals (Sweden)

    R. Schiebel

    2012-09-01

    Full Text Available Planktic foraminifera are heterotrophic mesozooplankton of global marine abundance. The position of planktic foraminifers in the marine food web is different compared to other protozoans and ranges above the base of heterotrophic consumers. Being secondary producers with an omnivorous diet, which ranges from algae to small metazoans, planktic foraminifers are not limited to a single food source, and are assumed to occur at a balanced abundance displaying the overall marine biological productivity at a regional scale. With a new non-destructive protocol developed from the bicinchoninic acid (BCA method and nano-photospectrometry, we have analysed the protein-biomass, along with test size and weight, of 754 individual planktic foraminifers from 21 different species and morphotypes. From additional CHN analysis, it can be assumed that protein-biomass equals carbon-biomass. Accordingly, the average individual planktic foraminifer protein- and carbon-biomass amounts to 0.845 μg. Samples include symbiont bearing and symbiont-barren species from the sea surface down to 2500 m water depth. Conversion factors between individual biomass and assemblage-biomass are calculated for test sizes between 72 and 845 μm (minimum test diameter. Assemblage-biomass data presented here include 1128 sites and water depth intervals. The regional coverage of data includes the North Atlantic, Arabian Sea, Red Sea, and Caribbean as well as literature data from the eastern and western North Pacific, and covers a wide range of oligotrophic to eutrophic waters over six orders of magnitude of planktic-foraminifer assemblage-biomass (PFAB. A first order estimate of the average global planktic foraminifer biomass production (>125 μm ranges from 8.2–32.7 Tg C yr−1 (i.e. 0.008–0.033 Gt C yr−1, and might be more than three times as high including neanic and juvenile individuals adding up to 25–100 Tg C yr−1. However, this is a first

  5. Estimates of Forest Biomass Carbon Storage in Liaoning Province of Northeast China: A Review and Assessment

    Science.gov (United States)

    Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J.; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

    2014-01-01

    Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha−1 in 1980 to 31.0 Mg ha−1 in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations. PMID:24586881

  6. Estimate of biomass and carbon pools in disturbed and undisturbed oak forests in Tunisia

    Energy Technology Data Exchange (ETDEWEB)

    Zribi, L.; Chaar, H.; Khaldi, A.; Henchi, B.; Mouillot, F.; Gharbi, F.

    2016-07-01

    Aim of the study. To estimate biomass and carbon accumulation in a young and disturbed forest (regenerated after a tornado) and an aged cork oak forest (undisturbed forest) as well as its distribution among the different pools (tree, litter and soil). Area of study. The north west of Tunisia. Material and methods. Carbon stocks were evaluated in the above and belowground cork oak trees, the litter and the 150 cm of the soil. Tree biomass was estimated in both young and aged forests using allometric biomass equations developed for wood stem, cork stem, wood branch, cork branch, leaves, roots and total tree biomass based on combinations of diameter at breast height, total height and crown length as independent variables. Main results. Total tree biomass in forests was 240.58 Mg ha-1 in the young forest and 411.30 Mg ha-1 in the aged forest with a low root/shoot ratio (0.41 for young forest and 0.31 for aged forest). Total stored carbon was 419.46 Mg C ha-1 in the young forest and 658.09 Mg C ha-1 in the aged forest. Carbon stock (Mg C ha-1) was estimated to be113.61(27.08%) and 194.08 (29.49%) in trees, 3.55 (0.85%) and 5.73 (0.87%) in litter and 302.30 (72.07%) and 458.27 (69.64%) in soil in the young and aged forests, respectively. Research highlights. Aged undisturbed forest had the largest tree biomass but a lower potential for accumulation of carbon in the future; in contrast, young disturbed forest had both higher growth and carbon storage potential. (Author)

  7. The Importance of Tree Height in Estimating Individual Tree Biomass While Considering Errors in Measurements and Allometric Models

    OpenAIRE

    Phalla, Thuch; Ota, Tetsuji; Mizoue, Nobuya; Kajisa, Tsuyoshi; Yoshida, Shigejiro; Vuthy, Ma; Heng, Sokh

    2018-01-01

    This study evaluated the uncertainty of individual tree biomass estimated by allometric models by both including and excluding tree height independently. Using two independent sets of measurements on the same trees, the errors in the measurement of diameter at breast height and tree height were quantified, and the uncertainty of individual tree biomass estimation caused by errors in measurement was calculated. For both allometric models, the uncertainties of the individual tree biomass estima...

  8. Investigating the capabilities of new microwave ALOS-2/PALSAR-2 data for biomass estimation

    Science.gov (United States)

    Anh, L. V.; Paull, D. J.; Griffin, A. L.

    2016-10-01

    Most studies indicate that L-band synthetic aperture radar (SAR) has a great capacity to estimate biomass due to its ability to penetrate deeply through canopy layers. Many applications using L-band space-borne data have showcased their own significant contribution in biomass estimation but some limitations still exist. New data have been released recently that are designed to overcome limitations and drawbacks of previous sensor generations. The Japan Aerospace Exploration Agency (JAXA) launched the new sensor ALOS-2 to improve wide and high-resolution observation technologies in order to further meet social and environmental objectives. In the list of priority tasks addressed by JAXA there are experiments utilizing these new data for vegetation biomass distribution measurement. This study, therefore, focused on investigating the capabilities of these new microwave data in above ground biomass (AGB) estimation. The data mode used in this study was a full polarimetric ALOS-2/PALSAR-2 (L-band) scene. The experiment was conducted on a portion of a tropical forest in a Central Highland province in Vietnam.

  9. Recent changes in the estimation of standing dead tree biomass and carbon stocks in the U.S. forest inventory

    Science.gov (United States)

    Grant M. Domke; Christopher W. Woodall; James E. Smith

    2012-01-01

    Until recently, standing dead tree biomass and carbon (C) has been estimated as a function of live tree growing stock volume in the U.S. Forest Service, Forest Inventory and Analysis (FIA) Program. Traditional estimates of standing dead tree biomass/C attributes were based on merchantability standards that did not reflect density reductions or structural loss due to...

  10. A Simultaneous Density-Integral System for Estimating Stem Profile and Biomass: Slash Pine and Willow Oak

    Science.gov (United States)

    Bernard R. Parresol; Charles E. Thomas

    1996-01-01

    In the wood utilization industry, both stem profile and biomass are important quantities. The two have traditionally been estimated separately. The introduction of a density-integral method allows for coincident estimation of stem profile and biomass, based on the calculus of mass theory, and provides an alternative to weight-ratio methodology. In the initial...

  11. Non-destructive biomass estimation of tree seedlings using image analysis

    Energy Technology Data Exchange (ETDEWEB)

    Norgren, O.; Elfving, B. [Swedish Univ. of Agricultural Sciences, Umeaa (Sweden). Dept. of Silviculture; Olsson, Olof [Swedish Univ. of Agricultural Sciences, Umeaa (Sweden). Dept. of Forest Genetics and Plant Physiology

    1995-12-31

    The biomass of Pinus sylvestris, Pinus contorta and Pinus cembra seedlings that were raised in three different growing media, as well as of naturally regenerated P. sylvestris saplings, was estimated using functions based on variables measured non-destructively. These included stem diameter, seedling height, number of needles and branches, length of the longest needle, and projected seedling or sapling crown area. Projected area of a two-dimensional video image of the seedling or sapling was measured using computer-based image analysis. The variables were tested in all possible combinations to achieve the best biomass estimate. Projected area alone explained more than 97% of the variation in seedling or sapling mass. Addition of stem diameter increased the degree of explanation to more than 98%, whereas the other variables did not contribute further. Separate functions for species and growing media resulted in more precise estimates than if general functions were used. 22 refs, 2 figs, 3 tabs

  12. Comparison of data mining and allometric model in estimation of tree biomass.

    Science.gov (United States)

    Sanquetta, Carlos R; Wojciechowski, Jaime; Dalla Corte, Ana P; Behling, Alexandre; Péllico Netto, Sylvio; Rodrigues, Aurélio L; Sanquetta, Mateus N I

    2015-08-07

    The traditional method used to estimate tree biomass is allometry. In this method, models are tested and equations fitted by regression usually applying ordinary least squares, though other analogous methods are also used for this purpose. Due to the nature of tree biomass data, the assumptions of regression are not always accomplished, bringing uncertainties to the inferences. This article demonstrates that the Data Mining (DM) technique can be used as an alternative to traditional regression approach to estimate tree biomass in the Atlantic Forest, providing better results than allometry, and demonstrating simplicity, versatility and flexibility to apply to a wide range of conditions. Various DM approaches were examined regarding distance, number of neighbors and weighting, by using 180 trees coming from environmental restoration plantations in the Atlantic Forest biome. The best results were attained using the Chebishev distance, 1/d weighting and 5 neighbors. Increasing number of neighbors did not improve estimates. We also analyze the effect of the size of data set and number of variables in the results. The complete data set and the maximum number of predicting variables provided the best fitting. We compare DM to Schumacher-Hall model and the results showed a gain of up to 16.5% in reduction of the standard error of estimate. It was concluded that Data Mining can provide accurate estimates of tree biomass and can be successfully used for this purpose in environmental restoration plantations in the Atlantic Forest. This technique provides lower standard error of estimate than the Schumacher-Hall model and has the advantage of not requiring some statistical assumptions as do the regression models. Flexibility, versatility and simplicity are attributes of DM that corroborates its great potential for similar applications.

  13. Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia

    Science.gov (United States)

    Sousa, Adélia M. O.; Gonçalves, Ana Cristina; Mesquita, Paulo; Marques da Silva, José R.

    2015-03-01

    Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands.

  14. Allometric relationships for volume and biomass for stone pine (Pinus pinea L.) in Italian coastal stands

    OpenAIRE

    Chianucci F; Cutini A; Manetti Maria Chiara

    2013-01-01

    Tree biomass plays a key role in sustainable forest management and in determining forest carbon stocks. Accurate estimates based on species-specific empirical data are necessary for regional and national inventories and forest carbon management. In this study, we obtained allometric relationships for volume and aboveground biomass for stone pine (Pinus pinea) based on empirical data collected in four coastal stands in Italy. Root sampling was also performed. The results enabled generalized eq...

  15. Fluorometric detection and estimation of fungal biomass on cultural heritage materials.

    Science.gov (United States)

    Konkol, Nick; McNamara, Christopher J; Mitchell, Ralph

    2010-02-01

    A wide variety of cultural heritage materials are susceptible to fungal deterioration. The paper, canvas, and stone constituents of our cultural heritage are subjected to harmful physical and chemical processes as they are slowly consumed by fungi. Remediation of fungal contamination can be costly and risk further damage to cultural artifacts. Early detection of fungal growth would permit the use of relatively noninvasive treatments to remediate fungal contamination before visible or lasting damage to the object has occurred. Current methods used for the detection and measurement of microbial biomass, such as colony counts, microscopic biovolume estimation, and ergosterol analysis are expensive and time consuming, or are inappropriate for use with fungi. Beta-N-acetylhexosaminidase (3.2.1.52) activity provides a reliable estimation of fungal biomass in soil and on building materials. Adapted for use on cultural heritage materials' fluorogenic 4-methylumbelliferyl (MUF) labeled substrate N-acetyl-beta-d-glucosaminide (NAG) was used to detect beta-N-acetylhexosaminidase activity in the fungus Aspergillus niger. Fluorescence increased linearly with fungal biomass and the sensitivity of the assay was comparable to other biochemical techniques. The fluorometric assay was used to monitor fungal biomass on a variety of cultural heritage materials non-destructively, and without the introduction of chemicals or solvents to the surfaces. Copyright 2009 Elsevier B.V. All rights reserved.

  16. Precise plant height monitoring and biomass estimation with Terrestrial Laser Scanning in paddy rice

    Directory of Open Access Journals (Sweden)

    N. Tilly

    2013-10-01

    Full Text Available Optimizing crop management is a major topic in the field of precision agriculture as the growing world population puts pressure on the efficiency of field production. Accordingly, methods to measure plant parameters with the needed precision and within-field resolution are required. Studies show that Terrestrial Laser Scanning (TLS is a suitable method to capture small objects like crop plants. In this contribution, the results of multi-temporal surveys on paddy rice fields with the TLS system Riegl LMS-Z420i are presented. Three campaigns were carried out during the key vegetative stage of rice plants in the growing period 2012 to monitor the plant height. The TLS-derived point clouds are interpolated to visualize plant height above ground as crop surface models (CSMs with a high resolution of 0.01 m. Spatio-temporal differences within the data of one campaign and between consecutive campaigns can be detected. The results were validated against manually measured plant heights with a high correlation (R2 = 0.71. Furthermore, the dependence of actual biomass from plant height was evaluated. To the present, no method for the non-destructive determination of biomass is found yet. Thus, plant parameters, like the height, have to be used for biomass estimations. The good correlation (R2 = 0.66 leads to the assumption that biomass can be estimated from plant height measurements. The results show that TLS can be considered as a very promising tool for precision agriculture.

  17. Relative contributions of sampling effort, measuring, and weighing to precision of larval sea lamprey biomass estimates

    Science.gov (United States)

    Slade, Jeffrey W.; Adams, Jean V.; Cuddy, Douglas W.; Neave, Fraser B.; Sullivan, W. Paul; Young, Robert J.; Fodale, Michael F.; Jones, Michael L.

    2003-01-01

    We developed two weight-length models from 231 populations of larval sea lampreys (Petromyzon marinus) collected from tributaries of the Great Lakes: Lake Ontario (21), Lake Erie (6), Lake Huron (67), Lake Michigan (76), and Lake Superior (61). Both models were mixed models, which used population as a random effect and additional environmental factors as fixed effects. We resampled weights and lengths 1,000 times from data collected in each of 14 other populations not used to develop the models, obtaining a weight and length distribution from reach resampling. To test model performance, we applied the two weight-length models to the resampled length distributions and calculated the predicted mean weights. We also calculated the observed mean weight for each resampling and for each of the original 14 data sets. When the average of predicted means was compared to means from the original data in each stream, inclusion of environmental factors did not consistently improve the performance of the weight-length model. We estimated the variance associated with measures of abundance and mean weight for each of the 14 selected populations and determined that a conservative estimate of the proportional contribution to variance associated with estimating abundance accounted for 32% to 95% of the variance (mean = 66%). Variability in the biomass estimate appears more affected by variability in estimating abundance than in converting length to weight. Hence, efforts to improve the precision of biomass estimates would be aided most by reducing the variability associated with estimating abundance.

  18. Évaluation de la diversité et estimation de la biomasse des arbres d ...

    African Journals Online (AJOL)

    SARAH

    31 janv. 2016 ... végétation originelle est de type forêt dense humide caractérisée par Turraeanthus africanus (Welw. ex DC) ... Pour estimer l'aire basale (S), nous avons utilisé le diamètre (D) des arbres selon la formule ... la largeur et la longueur de la voie. Pour les paramètres densité, aire basale, biomasse, nous avons ...

  19. Plot size recommendations for biomass estimation in a midwestern old-growth forest

    Science.gov (United States)

    Martin A. Spetich; George R Parker

    1998-01-01

    The authors examine the relationship between disturbance regime and plot size for woody biomass estimation in a midwestern old-growth deciduous forest from 1926 to 1992. Analysis was done on the core 19.6 ac of a 50.1 ac forest in which every tree 4 in. d.b.h. and greater has been tagged and mapped since 1926. Five windows of time are compared—1926, 1976, 1981, 1986...

  20. Experimental validation of in silico estimated biomass yields of Pseudomonas putida KT2440.

    Science.gov (United States)

    Hintermayer, Sarah Beate; Weuster-Botz, Dirk

    2017-06-01

    Pseudomonas putida is rapidly becoming a microbial cell platform for biotechnological applications. In order to understand genotype-phenotype relationships genome scale models represent helpful tools. However, the validation of in silico predictions of genome scale models is a task that is rarely performed. In this study the theoretical biomass yields of Pseudomonas putida KT2440 were estimated for 57 different carbon sources based on a genome scale stoichiometric model applying flux balance analysis. The batch growth of P. putida KT2440 with six individual carbon sources covering the range of maximal to minimal in silico biomass yields (acetate, glycerol, citrate, succinate, malate and methanol, respectively) was studied in a defined mineral medium in a fully controlled stirred-tank bioreactor on a 3 L scale. The highest growth rate of P. putida KT2440 was measured with succinate as carbon source (0.51 h -1 ). Among the 57 carbon sources tested, glycerol resulted in the highest estimated biomass yield (0.61 molC Biomass molC -1 Glycerol ) which was experimentally confirmed. The comparison of experimental determined biomass yields with a modified version of the model iJP815 showed deviations of only up to 10%. The experimental data generated in this study can also be used in future studies to further improve the genome scale models of P. putida KT2440. Improved models will then help to gain deeper insights in genotype-phenotype relationships. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Forest biomass variation in Southernmost Brazil: the impact of Araucaria trees.

    Science.gov (United States)

    Rosenfield, Milena Fermina; Souza, Alexandre F

    2014-03-01

    A variety of environmental and biotic factors determine vegetation growth and affect plant biomass accumulation. From temperature to species composition, aboveground biomass storage in forest ecosystems is influenced by a number of variables and usually presents a high spatial variability. With this focus, the aim of the study was to evaluate the variables affecting live aboveground forest biomass (AGB) in Subtropical Moist Forests of Southern Brazil, and to analyze the spatial distribution of biomass estimates. Data from a forest inventory performed in the State of Rio Grande do Sul, Southern Brazil, was used in the present study. Thirty-eight 1-ha plots were sampled and all trees with DBH > or = 9.5cm were included for biomass estimation. Values for aboveground biomass were obtained using published allometric equations. Environmental and biotic variables (elevation, rainfall, temperature, soils, stem density and species diversity) were obtained from the literature or calculated from the dataset. For the total dataset, mean AGB was 195.2 Mg/ha. Estimates differed between Broadleaf and Mixed Coniferous-Broadleaf forests: mean AGB was lower in Broadleaf Forests (AGB(BF)=118.9 Mg/ha) when compared to Mixed Forests (AGB(MF)=250.3 Mg/ha). There was a high spatial and local variability in our dataset, even within forest types. This condition is normal in tropical forests and is usually attributed to the presence of large trees. The explanatory multiple regressions were influenced mainly by elevation and explained 50.7% of the variation in AGB. Stem density, diversity and organic matter also influenced biomass variation. The results from our study showed a positive relationship between aboveground biomass and elevation. Therefore, higher values of AGB are located at higher elevations and subjected to cooler temperatures and wetter climate. There seems to be an important contribution of the coniferous species Araucaria angustifolia in Mixed Forest plots, as it presented

  2. Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA

    Science.gov (United States)

    Wenli Huang; Anu Swatantran; Kristofer Johnson; Laura Duncanson; Hao Tang; Jarlath O' Neil Dunne; George Hurtt; Ralph. Dubayah

    2015-01-01

    Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-...

  3. A review of the challenges and opportunities in estimating above ground forest biomass using tree-level models

    Science.gov (United States)

    Hailemariam Temesgen; David Affleck; Krishna Poudel; Andrew Gray; John Sessions

    2015-01-01

    Accurate biomass measurements and analyses are critical components in quantifying carbon stocks and sequestration rates, assessing potential impacts due to climate change, locating bio-energy processing plants, and mapping and planning fuel treatments. To this end, biomass equations will remain a key component of future carbon measurements and estimation. As...

  4. Estimation of merchantable bole volume and biomass above sawlog top in the National Forest inventory of the United States

    Science.gov (United States)

    Grant M. Domke; Christopher M. Oswalt; Christopher W. Woodall; Jeffery A. Turner

    2013-01-01

    Emerging markets for small-diameter roundwood along with a renewed interest in forest biomass for energy have created a need for estimates of merchantable biomass above the minimum sawlog top diameter for timber species in the national forest inventory of the United States. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service recently adopted the...

  5. Impact of biomass burning on urban air quality estimated by organic tracers: Guangzhou and Beijing as cases

    International Nuclear Information System (INIS)

    Qiaoqiao Wang; Min Shao; Ying Liu; Kuster, William; Goldan, Paul; Xiaohua Li; Yuan Liu; Sihua Lu

    2007-01-01

    The impacts of biomass burning have not been adequately studied in China. In this work, chemical compositions of volatile organic compounds and particulate organic matters were measured in August 2005 in Beijing and in October 2004 in Guangzhou city. The performance of several possible tracers for biomass burning is compared by using acetonitrile as a reference compound. The correlations between the possible tracers and acetonitrile show that the use of K + as a tracer could result in bias because of the existence of other K+ sources in urban areas, while chloromethane is not reliable due to its wide use as industrial chemical. The impact of biomass burning on air quality is estimated using acetonitrile and levoglucosan as tracers. The results show that the impact of biomass burning is ubiquitous in both suburban and urban Guangzhou, and the frequencies of air pollution episodes significantly influenced by biomass burning were 100% for Xinken and 58% for downtown Guangzhou city. Fortunately, the air quality in only 2 out of 22 days was partly impacted by biomass burning in August in Beijing, the month that 2008 Olympic games will take place. The quantitative contribution of biomass burning to ambient PM 2.5 concentrations in Guangzhou city was also estimated by the ratio of levoglocusan to PM 2.5 in both the ambient air and biomass burning plumes. The results show that biomass burning contributes 3.02013;16.8% and 4.02013;19.0% of PM 2.5 concentrations in Xinken and Guangzhou downtown, respectively. (Author)

  6. Evaluation of Above Ground Biomass Estimation Accuracy for Alpine Meadow Based on MODIS Vegetation Indices

    Directory of Open Access Journals (Sweden)

    Meng Bao-Ping

    2017-01-01

    Full Text Available Animal husbandry is the main agricultural type over the Tibetan Plateau, above ground biomass (AGB is very important to monitor the productivity for administration of grassland resources and grazing balance. The MODIS vegetation indices have been successfully used in numerous studies on grassland AGB estimation in the Tibetan Plateau area. However, there are considerable differences of AGB estimation models both in the form of the models and the accuracy of estimation. In this study, field measurements of AGB data at Sangke Town, Gansu Province, China in four years (2013-2016 and MODIS indices (NDVI and EVI are combined to construct AGB estimation models of alpine meadow grassland. The field measured AGB are also used to evaluate feasibility of models developed for large scale in applying to small area. The results show that (1 the differences in biomass were relatively large among the 5 sample areas of alpine meadow grassland in the study area during 2013-2016, with the maximum and minimum biomass values of 3,963 kg DW/ha and 745.5 kg DW/ha, respectively, and mean value of 1,907.7 kg DW/ha; the mean of EVI value range (0.42-0.60 are slightly smaller than the NDVI’s (0.59-0.75; (2 the optimum estimation model of grassland AGB in the study area is the exponential model based on MODIS EVI, with root mean square error of 656.6 kg DW/ha and relative estimation errors (REE of 36.3%; (3 the estimation errors of grassland AGB models previously constructed at different spatial scales (the Tibetan Plateau, the Gannan Prefecture, and Xiahe County are higher than those directly constructed based on the small area of this study by 9.5%–31.7%, with the increase of the modeling study area scales, the REE increasing as well. This study presents an improved monitoring algorithm of alpine natural grassland AGB estimation and provides a clear direction for future improvement of the grassland AGB estimation and grassland productivity from remote sensing

  7. Estimation of Viable Biomass In Wastewater And Activated Sludge By Determination of ATP, Oxygen Utilization Rate And FDA Hydrolysis

    DEFF Research Database (Denmark)

    Jørgensen, Poul-Erik; Eriksen, T.; Jensen, B.K.

    1992-01-01

    ATP content, oxygen utilization rate (OUR) and fluorescein diacetate (FDA) hydrolysis were tested for the ability to express the amount of viable biomass in wastewater and activated sludge. The relationship between biomass and these activity parameters was established in growth cultures made...... with biomass, while FDA hydrolysis in the sludge failed to show any such correlation. Conversion factors of 3 mg ATP/g dw, 300 mg O2/h g dw and 0.4 A/h (mg dw/ml) for ATP, OUR and FDA methods, respectively, were calculated. When the methods were applied for in situ determinations in four different wastewater...... plants, it was found that ATP content and respiration rate estimated viable biomass to range from 81 to 293 mg dw/g SS for raw wastewater and from 67 to 187 mg dw/g SS for activated sludge with a rather weak correlation between ATP and respiration measurements. The FDA hydrolysis estimated viable biomass...

  8. Estimating Consumption to Biomass Ratio in Non-Stationary Harvested Fish Populations.

    Directory of Open Access Journals (Sweden)

    Rodrigo Wiff

    Full Text Available The food consumption to biomass ratio (C is one of the most important population parameters in ecosystem modelling because its quantifies the interactions between predator and prey. Existing models for estimating C in fish populations are per-recruit cohort models or empirical models, valid only for stationary populations. Moreover, empirical models lack theoretical support. Here we develop a theory and derive a general modelling framework to estimate C in fish populations, based on length frequency data and the generalised von Bertalanffy growth function, in which models for stationary populations with a stable-age distributions are special cases. Estimates using our method are compared with estimates from per-recruit cohort models for C using simulated harvested fish populations of different lifespans. The models proposed here are also applied to three fish populations that are targets of commercial fisheries in southern Chile. Uncertainty in the estimation of C was evaluated using a resampling approach. Simulations showed that stationary and non-stationary population models produce different estimates for C and those differences depend on the lifespan, fishing mortality and recruitment variations. Estimates of C using the new model exhibited smoother inter-annual variation in comparison with a per-recruit model estimates and they were also smaller than C predicted by the empirical equations in all population assessed.

  9. The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest Gradient

    Science.gov (United States)

    Montesano, P. M.; Rosette, J.; Sun, G.; North, P.; Nelson, R. F.; Dubayah, R. O.; Ranson, K. J.; Kharuk, V.

    2014-01-01

    The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model

  10. Morphology and LPS content for the estimation of marine bacterioplankton biomass in the Ionian Sea

    Directory of Open Access Journals (Sweden)

    Rosabruna La Ferla

    2004-03-01

    Full Text Available The abundance, morphotypes and biomass of the bacterial assemblages were investigated in the Ionian Sea by using two different methods: the epifluorescent microscopy technique for enumerating and sizing bacterial cells, and the determination of bacterial lipopolysaccharides (LPS. Five bacterial morphotypes were distinguished: cocci, rods, coccobacilli, vibrios and spirillae. The proportions of cocci were higher than those of other morphotypes at every depth, ranging from 39% to 73%. Both rod-shaped bacteria and coccobacilli were homogenously distributed in the water column, while the proportions of vibrios were rather variable. Spirillae occurred only in surface samples and disappeared below 100 m. The two methodologies were compared: LPS concentrations showed a highly significant correlation with the bacterial numbers (P< 0.01; n= 88; r= 0.68, but not with biovolumes, and different ratios between LPS concentrations and bacterial volumes were recorded for the photic and aphotic zones (3.11 ± 1.35 and 0.96 ± 0.37 ng LPS per µm3 respectively. LPS-derived cell carbon content on average was 23 fg C cell-1, similar to the C amount derived by mean cell biovolume (19 fg C cell-1 and the biomass from two highly correlated methods (P< 0.01; n= 95; r= 0.59. Our results confirm that the widely used factor of 20 fg C cell-1 (Lee and Furhman, 1987 should be plausible for studying the biomass of the natural microbial populations in the study area. Nevertheless, the wide variability of the cell size classes, also along the whole water columns, questions the applicability of a constant conversion factor for all the marine ecosystems. Consequently, locally derived biomass estimates of bacteria are essential in order to obtain an accurate evaluation of the bacterial role in biogeochemical cycles.

  11. Allometric equations for estimating belowground biomass ofAndrostachys johnsoniiPrain.

    Science.gov (United States)

    Magalhães, Tarquinio Mateus

    2015-12-01

    The belowground component of the trees is still poorly known because it needs labour- and time-intensive in situ measurements. However, belowground biomass (BGB) constitutes a significant share of the total forest biomass. I analysed the BGB allocation patterns, fitted models for estimating root components and root system biomasses, and called attention for its possible use in predicting anchoring functions of the different root components. More than half and almost one third of BGB is allocated to the lateral roots and to the root collar, respectively. More than 80% of the BGB is found at a depth range of 9.6-61.2 cm. As the tree size increased, the proportion of BGB allocated to taproots decreased and that allocated to lateral roots increased. All independent models performed almost equally, with the predictors explaining, on average, 98% of the variation in the BGB. It was hypothesised that BGB allocation patterns are a response of the anchoring functions of the tap and lateral roots and therefore, root component biomass models can be used as a methodology to predict anchoring functions of the different root components. Based on the fact that all models performed almost equally, the models using either diameter at breast height (DBH) exclusively as a predictor should be preferred, as tree height is difficult to measure. Models using the root collar diameter (RCD) only should be preferred when the tree is found cut down, as sometimes the RCD is affected by root buttress. Given the large sample size, the validation results, and the coverage of a wide geographical, soil and climatic range, the models fitted can be applied in all A. johnsonii stands in Mozambique.

  12. Assessing the influence of return density on estimation of lidar-based aboveground biomass in tropical peat swamp forests of Kalimantan, Indonesia

    Science.gov (United States)

    Solichin Manuri; Hans-Erik Andersen; Robert J. McGaughey; Cris Brack

    2017-01-01

    The airborne lidar system (ALS) provides a means to efficiently monitor the status of remote tropical forests and continues to be the subject of intense evaluation. However, the cost of ALS acquisition canvary significantly depending on the acquisition parameters, particularly the return density (i.e., spatial resolution) of the lidar point cloud. This study assessed...

  13. Biomass of elephant grass and leucaena for bioenergy production

    Directory of Open Access Journals (Sweden)

    Fernanda Aparecida Sales

    2015-12-01

    Full Text Available The objective of this study was to evaluate the biomass production of elephant grass and leucaena in Paraná state, Brazil, for the generation of renewable energy. Two field studies were conducted in the municipality of Ibiporã (23° S, 51° 01?W. In the first study, the dry matter accumulation curves were calculated, with sampling at 30, 60, 90, 120, and 180 days after cultivation. The second study was conducted in a randomized complete block design with split plots. The total aboveground biomass production of elephant grass and leucaena was estimated in the main plot. Cutting times of 60 and 120 days after cultivation were evaluated in the subplots. The productivity of dry matter (kg.ha-1 was estimated using the biomass data. In addition, the potential production of energy from the burning of elephant grass biomass, and the potential production of total aboveground biomass and energy of elephant grass (in Paraná was estimated using an agrometeorological model. Elephant grass can be potentially used as an alternative energy source. Leucaena has slow initial growth, and it must therefore be evaluated over a longer period in order to determine its potential. Simulation analyses of the capability of power generation, conducted based on the annual dry matter production, revealed that elephant grass could be an important source of renewable energy in the state of Paraná.

  14. Challenges to estimating whole forest root biomass with ground penetrating radar

    Science.gov (United States)

    Butnor, J. R.

    2016-12-01

    Over the past two decades, substantial technical advances have been made in detecting tree roots with ground penetrating radar (GPR). Under favorable soil dielectric conditions, root location, depth, diameter and mass estimates are possible in the field. With careful notation of survey lines, three dimensional reconstructions of root architecture may also be achieved. The technique has been very useful for quantifying lateral root biomass in silvicultural studies, but is not yet a standalone technique for estimating root biomass in forests. The purpose of this presentation is to highlight the limitations of GPR in the field to stimulate discussion on how to overcome these challenges. Under field conditions, surface-based antennas with frequencies of 400 to 1500 MHz cannot detect fine roots (detected. Lack of automation of data processing and interpretation steps currently makes data analysis arduous and in some cases subject to interpretation by an expert user. Forests have a high degree of heterogeneity in surface conditions (e.g., holes, soil moisture, stems, woody and herbaceous plants) that may prevent antennas from coupling with the surface to propagate EM waves and receive reflections. What is the potential for open source data analysis programs to be developed and shared? How will new digital, multi-frequency antennas improve resolution? Can air launched antennas be developed that have both the depth penetration and resolution to detect roots? Are purpose-designed bore hole antenna needed for imaging taproots?

  15. Evaluating the Impact of Spatial Resolution of Landsat Predictors on the Accuracy of Biomass Models for Large-area Estimation Across the Eastern USA

    Science.gov (United States)

    Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

    2017-12-01

    Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively

  16. Some effects of soil-moisture availability on above-ground production and reproductive allocation in Larrea tridentata (DC) Cov.

    Science.gov (United States)

    Cunningham, G L; Syvertsen, J P; Reynolds, J F; Willson, J M

    1979-01-01

    Data from the US/IBP Desert Biome validation studies indicate that above-ground production and biomass allocated to reproduction in Larrea tridentata vary from one year to another depending upon the timing and extent of soil-moisture availability. In an attempt to verify these observations and determine to what extent water availability can affect total aboveground production and reproductive allocation in this widely distributed warm desert shrub, a series of soil-moisture augmentation experiments were conducted. High levels of soil moisture had a greater effect on reproductive allocation than on total above-ground production. Enhanced soil moisture during the period of active growth increased total above-ground production and reduced the percentage of biomass allocated to reproduction. Enhanced soil moisture during the normal periods of little or no growth did not increase total above-ground production.

  17. Quantifying the Model-Related Variability of Biomass Stock and Change Estimates in the Norwegian National Forest Inventory

    Science.gov (United States)

    Johannes Breidenbach; Clara Antón-Fernández; Hans Petersson; Ronald E. McRoberts; Rasmus Astrup

    2014-01-01

    National Forest Inventories (NFIs) provide estimates of forest parameters for national and regional scales. Many key variables of interest, such as biomass and timber volume, cannot be measured directly in the field. Instead, models are used to predict those variables from measurements of other field variables. Therefore, the uncertainty or variability of NFI estimates...

  18. Evaluation of alternative approaches for landscape-scale biomass estimation in a mixed-species northern forest

    Science.gov (United States)

    Coeli M. Hoover; Mark J. Ducey; R. Andy Colter; Mariko. Yamasaki

    2018-01-01

    There is growing interest in estimating and mapping biomass and carbon content of forests across large landscapes. LiDAR-based inventory methods are increasingly common and have been successfully implemented in multiple forest types. Asner et al. (2011) developed a simple universal forest carbon estimation method for tropical forests that reduces the amount of required...

  19. Multiscale analysis of tree cover and aboveground carbon stocks in pinyon-juniper woodlands.

    Science.gov (United States)

    Huang, Cho-Ying; Asner, Gregory P; Martin, Roberta E; Barger, Nichole N; Neff, Jason C

    2009-04-01

    Regional, high-resolution mapping of vegetation cover and biomass is central to understanding changes to the terrestrial carbon (C) cycle, especially in the context of C management. The third most extensive vegetation type in the United States is pinyon-juniper (P-J) woodland, yet the spatial patterns of tree cover and aboveground biomass (AGB) of P-J systems are poorly quantified. We developed a synoptic remote-sensing approach to scale up pinyon and juniper projected cover (hereafter "cover") and AGB field observations from plot to regional levels using fractional photosynthetic vegetation (PV) cover derived from airborne imaging spectroscopy and Landsat satellite data. Our results demonstrated strong correlations (P satellite PV estimates (r2 = 0.61). Field data also indicated that P-J AGB can be estimated from canopy cover using a unified allometric equation (r2 = 0.69; P < 0.001). Using these multiscale cover-AGB relationships, we developed high-resolution, regional maps of P-J cover and AGB for the western Colorado Plateau. The P-J cover was 27.4% +/- 9.9% (mean +/- SD), and the mean aboveground woody C converted from AGB was 5.2 +/- 2.0 Mg C/ha. Combining our data with the southwest Regional Gap Analysis Program vegetation map, we estimated that total contemporary woody C storage for P-J systems throughout the Colorado Plateau (113 600 km2) is 59.0 +/- 22.7 Tg C. Our results show how multiple remote-sensing observations can be used to map cover and C stocks at high resolution in drylands, and they highlight the role of P-J ecosystems in the North American C budget.

  20. Estimation of black carbon content for biomass burning aerosols from multi-channel Raman lidar data

    Science.gov (United States)

    Talianu, Camelia; Marmureanu, Luminita; Nicolae, Doina

    2015-04-01

    Biomass burning due to natural processes (forest fires) or anthropical activities (agriculture, thermal power stations, domestic heating) is an important source of aerosols with a high content of carbon components (black carbon and organic carbon). Multi-channel Raman lidars provide information on the spectral dependence of the backscatter and extinction coefficients, embedding information on the black carbon content. Aerosols with a high content of black carbon have large extinction coefficients and small backscatter coefficients (strong absorption), while aerosols with high content of organic carbon have large backscatter coefficients (weak absorption). This paper presents a method based on radiative calculations to estimate the black carbon content of biomass burning aerosols from 3b+2a+1d lidar signals. Data is collected at Magurele, Romania, at the cross-road of air masses coming from Ukraine, Russia and Greece, where burning events are frequent during both cold and hot seasons. Aerosols are transported in the free troposphere, generally in the 2-4 km altitude range, and reaches the lidar location after 2-3 days. Optical data are collected between 2011-2012 by a multi-channel Raman lidar and follows the quality assurance program of EARLINET. Radiative calculations are made with libRadTran, an open source radiative model developed by ESA. Validation of the retrievals is made by comparison to a co-located C-ToF Aerosol Mass Spectrometer. Keywords: Lidar, aerosols, biomass burning, radiative model, black carbon Acknowledgment: This work has been supported by grants of the Romanian National Authority for Scientific Research, Programme for Research- Space Technology and Advanced Research - STAR, project no. 39/2012 - SIAFIM, and by Romanian Partnerships in priority areas PNII implemented with MEN-UEFISCDI support, project no. 309/2014 - MOBBE

  1. A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

    Science.gov (United States)

    Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie

    2018-01-01

    the highest C density of all estuarine emergent marshes (2.03 ± 0.004 Mg/ha). Estimated C stocks for predefined jurisdictional areas ranged from 1023 ± 39 Mg in the Nisqually National Wildlife Refuge in Washington to 507,761 ± 14,822 Mg in the Terrebonne and St. Mary Parishes in Louisiana. This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included in the coastal wetland section of the U.S. National Greenhouse Gas Inventory. With the increased availability of free post-processed satellite data, we provide a tractable means of modeling tidal marsh aboveground biomass and carbon at the global extent as well.

  2. Production of Nicotiana glauca R. C. Graham aerial biomass in relation to irrigation regime

    Energy Technology Data Exchange (ETDEWEB)

    Curt, M.D.; Fernandez, Jesus (Ciudad Univ., Madrid (ES). Dept. de Produccion Vegetal)

    1990-01-01

    Nicotiana glauca R. C. Graham is a member of the Solanaceae, naturalized in the areas of warm-arid climates of the Iberian Peninsula. This species could have a great importance as a possible energy crop, because of its drought hardiness, sprouting capacity, large biomass productivity and high content of non-structural carbohydrates. In this work the production of the above-ground biomass of Nicotiana glauca was studied in relation to the irrigation regime in a cycle of cultivation. It is concluded that Nicotiana glauca could be cultivated in marginal lands of warm-arid climates; and a production of above-ground biomass of 3.9 t d.m. ha{sup -1} year{sup -1} was estimated, from which it would be possible to extract about 900 kg of easily fermentable carbohydrates. (author).

  3. Merging glider and ocean color data to accurately estimate phytoplankton biomass in Oregon's coastal waters

    Science.gov (United States)

    McKibben, M.; Shearman, R. K.; Barth, J. A.; White, A. E.

    2016-02-01

    Long-term deployments of vertically-profiling platforms are becoming more common, providing a data-rich source of in situ ocean parameters ideal for pairing with satellite remote sensing data, particularly in areas with persistent cloud coverage. Regional development of methods that couple satellite and in situ data in ways that maximize the descriptive power of each is one of the crucial next steps in oceanographic research. For example, subsurface chlorophyll-a (chl-a) maxima often occur below the first optical depth (FOD), the maximum depth covered by satellite chl-a. In these cases, the sensors effectively miss a majority of phytoplankton biomass. Here we develop methods to merge 5 years of Slocum glider profiles and ocean color data in Oregon's coastal waters in order to quantify the occurrence of chl-a within the full euphotic zone and to improve biomass estimations in this region. This work includes two primary goals. First, the relative accuracy, precision, and uncertainty of the datasets are assessed, including comparison of vertical glider profiles of chl-a concentration, corrected to account for non-photochemical quenching, to satellite retrievals. Secondly, we have characterized the vertical distribution of chl-a and scattering and determined the seasonality and frequency of chl-a features below the FOD. We will discuss results of this study relative to physical and chemical forcing within the region.

  4. Geostationary satellite estimation of biomass burning in Amazonia during BASE-A

    International Nuclear Information System (INIS)

    Menzel, W.P.; Cutrim, E.C.; Prins, E.M.

    1991-01-01

    This chapter presents the results of using Geostationary Operational Environmental Satellite (GOES) Visible Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) infrared window (3.9 and 11.2 microns) data to monitor biomass burning several times per day in Amazonia. The technique of Matson and Dozier using two window channels was adapted to GOES VAS infrared data to estimate the size and temperature of fires associated with deforestation in the vicinity of Alta Floresta, Brazil, during the Biomass Burning Airborne and Spaceborne Experiment - Amazonia (BASE-A). Although VAS data do not offer the spatial resolution available with AVHRR data 97 km versus 1 km, respectively, this decreased resolution does not seem to hinder the ability of the VAS instrument to detect fires; in some cases it proves to be advantageous in that saturation does not occur as often. VAS visible data are additionally helpful in verifying that the hot spots sensed in the infrared are actually related to fires. Furthermore, the fire plumes can be tracked in time to determine their motion and extent. In this way, the GOES satellite offers a unique ability to monitor diurnal variations in fire activity and transport of related aerosols

  5. Reduced biomass burning emissions reconcile conflicting estimates of the post-2006 atmospheric methane budget.

    Science.gov (United States)

    Worden, John R; Bloom, A Anthony; Pandey, Sudhanshu; Jiang, Zhe; Worden, Helen M; Walker, Thomas W; Houweling, Sander; Röckmann, Thomas

    2017-12-20

    Several viable but conflicting explanations have been proposed to explain the recent ~8 p.p.b. per year increase in atmospheric methane after 2006, equivalent to net emissions increase of ~25 Tg CH 4 per year. A concurrent increase in atmospheric ethane implicates a fossil source; a concurrent decrease in the heavy isotope content of methane points toward a biogenic source, while other studies propose a decrease in the chemical sink (OH). Here we show that biomass burning emissions of methane decreased by 3.7 (±1.4) Tg CH 4 per year from the 2001-2007 to the 2008-2014 time periods using satellite measurements of CO and CH 4 , nearly twice the decrease expected from prior estimates. After updating both the total and isotopic budgets for atmospheric methane with these revised biomass burning emissions (and assuming no change to the chemical sink), we find that fossil fuels contribute between 12-19 Tg CH 4 per year to the recent atmospheric methane increase, thus reconciling the isotopic- and ethane-based results.

  6. Estimation of Winter Wheat Biomass and Yield by Combining the AquaCrop Model and Field Hyperspectral Data

    Directory of Open Access Journals (Sweden)

    Xiuliang Jin

    2016-11-01

    Full Text Available Knowledge of spatial and temporal variations in crop growth is important for crop management and stable crop production for the food security of a country. A combination of crop growth models and remote sensing data is a useful method for monitoring crop growth status and estimating crop yield. The objective of this study was to use spectral-based biomass values generated from spectral indices to calibrate the AquaCrop model using the particle swarm optimization (PSO algorithm to improve biomass and yield estimations. Spectral reflectance and concurrent biomass and yield were measured at the Xiaotangshan experimental site in Beijing, China, during four winter wheat-growing seasons. The results showed that all of the measured spectral indices were correlated with biomass to varying degrees. The normalized difference matter index (NDMI was the best spectral index for estimating biomass, with the coefficient of determination (R2, root mean square error (RMSE, and relative RMSE (RRMSE values of 0.77, 1.80 ton/ha, and 25.75%, respectively. The data assimilation method (R2 = 0.83, RMSE = 1.65 ton/ha, and RRMSE = 23.60% achieved the most accurate biomass estimations compared with the spectral index method. The estimated yield was in good agreement with the measured yield (R2 = 0.82, RMSE = 0.55 ton/ha, and RRMSE = 8.77%. This study offers a new method for agricultural resource management through consistent assessments of winter wheat biomass and yield based on the AquaCrop model and remote sensing data.

  7. Impact of biomass burning on urban air quality estimated by organic tracers: Guangzhou and Beijing as cases

    Energy Technology Data Exchange (ETDEWEB)

    Qiaoqiao Wang; Min Shao; Ying Liu [State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences, Peking University, Beijing 100871, (China); Kuster, William; Goldan, Paul [Earth System Research Laboratory, U.S. Department of Commerce, Boulder, CO 80305, (United States); Xiaohua Li; Yuan Liu; Sihua Lu [State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences, Peking University, Beijing 100871, (China)

    2007-12-15

    The impacts of biomass burning have not been adequately studied in China.