Error analysis of leaf area estimates made from allometric regression models

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National Aeronautics and Space Administration, National Technical Information Service, distributor , [Washington, DC, Springfield, Va
Biomass., Canopies (Vegetation), Deciduous trees., Error analysis., Foliage., Forests., Leaves., Regression analysis., Remote sen
StatementA.H. Feiveson, and R.S. Chhikara.
SeriesNASA TM -- 89220, NASA technical memorandum -- 89220..
ContributionsChhikara, Raj S., 1941-., United States. National Aeronautics and Space Administration.
The Physical Object
Pagination1 v.
ID Numbers
Open LibraryOL17115320M

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PDF | Direct and semidirect estimations of leaf area (LA) and leaf area index (LAI) are scarce in dense tropical forests despite their importance in | Find, read and cite all the research you.

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A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Remote and non-destructive estimation of leaf area index (LAI) has been a challenge in the last few decades as the direct and indirect methods available are laborious and time-consuming.

The recent emergence of high-throughput plant phenotyping platforms has increased the need to develop new phenotyping tools for better decision-making by breeders.

In this paper, a novel model based on Author: Orly Enrique Apolo-Apolo, Manuel Pérez-Ruiz, Jorge Martínez-Guanter, Gregorio Egea. Forest plays a special role in carbon sequestration and thus mitigating climate change. However, the large uncertainty in biomass estimation is unable to meet the requirement of the accurate carbon accounting.

The use of a suitable and rigor method to accurately estimate forest biomass is significant. Moreover, the world is increasingly facing the conflicting pressures of economic growth and Cited by: 3.

Scatterplot of regression scores (i.e., the projection of shapes in the direction of the vector of regression coefficients, Drake and Klingenberg, ) vs centroid size; shapes at the opposite extremes of the range of allometric variation are shown using leaf outlines with no magnification.

There is a good body of work demonstrating the allometric correlation between sapwood area and leaf area [1,2,3,4,24,25,26,27,28,29,30,31,32].However, one of the biggest problems in using these allometric correlations is the species-specific physio- and morphological variations Cited by: 3.

Introduction. Vegetation biomass is the living organic matter that is produced by photosynthesis (Brown, ).Biomass can be partitioned into two components: (1) above-ground biomass, which includes the stems and any branches, leaves, flowers, and fruits above the soil surface; and (2) below-ground biomass, which is often divided for convenience into the root crowns, coarse roots (>2 mm Cited by: The allometric relationships are empirical functions that relate leaf area or leaf weight (gravimetric method) to any dimension of the woody element that carries leaves, including sapwood area, stem diameter, and crown base height (Colaizzi et al., ; Jonckheere et al., ).Cited by:   Introduction.

Basal area, the sum of cross-sectional area measured at breast height ( m) of all trees in a stand, expressed as m 2 ha −1, has frequently been used as a surrogate for biomass and carbon in tropical moist and dry forests.

1–12 The basal area is a good predictor for biomass and carbon since it integrates the effect of both the number and size of trees. 13 A correlation Cited by: Several factors can affect the remote sensing-based AGB estimation, such as insufficient sample data, atmospheric conditions, complex biophysical environments, scale of the study area, availability of software, spatial resolution of remotely sensed data, or mixed pixels, among others [6, 10].In order to introduce different approaches that have been developed to reduce the uncertainties Cited by: 5.

Regression of shape onto size pooling within populations. Scatterplot of regression scores (i.e., the projection of shapes in the direction of the vector of regression coefficients, Drake and Klingenberg, ) vs centroid size; shapes at the opposite extremes of the range of allometric variation are shown using leaf outlines with no by:   Margin hair number is positively associated with leaf hair density in Sinapisarvensis (regression of the number of marginal leaf hairs in 1 cm against number of leaf hairs in a 1‐cm area in the centre of the leaf for 10 randomly chosen individuals, r 2 =, F 1,9 =, P=).

To count hairs, each leaf was orientated with the abaxial Cited by: Maindonald J H Statistical design, analysis and presentation issues. New Zealand Journal of Agricultural Research Maindonald J H and Braun W J Data Analysis and Graphics Using R – An Example-Based Approach, 2nd edn.

Details Error analysis of leaf area estimates made from allometric regression models PDF

Cambridge University Press. Venables, W. and Ripley, B. D., 4th edn Introduction. Leaf morphology is central to plant taxonomy and systematics and it has mostly been studied using traditional morphometrics.In the last decade, however, there has been an increasing interest in the use of modern geometric morphometrics (GMM) to study the form of leaves.

Urban Tree Database and Allometric Equations expected to accumulate six times more carbon in the Central Florida ( kg) than in the Inland Valleys region ( kg), nearly a sixfold difference. Estimated d.b.h ranged from cm (tree height = m) in the Inland Valleys to cm in Central Florida region (tree height = m.

Description Error analysis of leaf area estimates made from allometric regression models PDF

The precision of these models was substantially greater when 1) the seemingly unrelated regression (SUR) fitting method was used instead of the separate multiple linear regression (MLR) or composite fitting method, and 2) branch position from the tip of the tree relative to tree height (zi1) was used rather than relative to crown length (zi2).

Abstract. Individual-tree basal area increment (BAI) models were developed for major tree species in the boreal forest of Ontario, Canada. A composite distance-independent individual-tree BAI model was structured based on the log-linearized gamma base function using a dataset derived from a network of ∼ permanent growth by: Remote Sensing and Geosciences for Archaeology.

Author: Deodato Tapete (Ed.) ISBN: Year: Pages: X, Language: English Publisher: MDPI - Multidisciplinary Digital Publishing Institute Subject: Archaeology Environmental Sciences Added to DOAB on: Regressions are commonly used in biology to determine the causal relationship between two variables.

This analysis is most commonly used in morphological studies, where the allometric relationship between two morphological variables is of fundamental interest. Allometric analysis detected adjustments in plant allometry, although direct, i. nonallometric, experimental influences on dry mass per plant also occurred.

Yield component analysis indicated that for both species leaf area index was the most important direct contributor to yield variation, while for beans pod filling was also important. The same models were used to predict AGB, AGB stem, AGB crown, and AGB leaf.

In order to correct for heterogeneous variation of the regression, a logarithmic transformation was applied (Wang ) for the predicted total weight (BM) and the predictor variables (e.g., D, H) resulting in, for example, ln(BM) = ln(a) + b ln(D) (see M04–M11).Cited by: The variation in biomass and carbon stock estimates of forests can be due to the allometric models selected to calculate the biomass and/or carbon stocks.

For example, Mehari et al. () indicated that the generalized allometric models by Brown, Gillespie, and Lugo () showed the poorest results with 32–59% average deviation for AGB Cited by: 5.

Proc. SPIERemote Sensing for Agriculture, Ecosystems, and Hydrology VII, (18 October ); doi: /   If multiple traits are involved in the analysis, then the contrasts calculated separately for each trait are used to compute a correlation, regression, multiple regression, etc.

Worked examples for bivariate correlations can be found in Garland (, fig. ) and Garland and Adolph (, fig. 2; also reproduced in boxpp.of Cited by: The results showed that forest parameter prediction using DAP works well when applied to a large area.

The model fits of the timber volume, biomass and basal area models were good with R2 of, and RMSEs of m3 ha−1 (55% of the mean observed value), t ha−1 (47%), m2 ha−1 (41%), respectively. View Jari Vauhkonen’s profile on LinkedIn, the world's largest professional community.

Jari has 5 jobs listed on their profile. See the complete profile on LinkedIn and discover Jari’s connections and jobs at similar : Professor, Forest Resources. Box Mixture models and regression trees Mixture models estimate the proportion of different land cover components within a pixel.

For example, each pixel is described as percentage vegetation, shade, and bare soil components. Components sum to %. Image processing softwareFile Size: 8MB. This banner text can have markup. web; books; video; audio; software; images; Toggle navigation. between and in term of K.

While the prediction made with land cover change models for the area showed an expected deforestation trend, land cover analysis revealed a decrease of agricultural areas and an increase of forest cover in the last 10 years. Results can be explained as an effect of the progressive abandon of agriculturalFile Size: 3MB.

Worldwide Historical Estimates of Leaf Area Index, SciTech Connect. Scurlock, JMO. Approximately published estimates of leaf area index (LAI) from nearly unique field sites, covering the periodhave been compiled into a single data set.

LA1 is a key parameter for global and regional models of biosphere. An allometric scaling relation based on logistic growth of cities.

NASA Astrophysics Data System (ADS) Chen, Yanguang. The relationships between urban area and populat.unit leaf area (or unit leaf mass) 8 – 1 0, with the implicit assumption that declines at these scales must also apply at the scale of the individual ing tree growth is also sometimes inferred from life-history theory to be a necessary corollary of increasing resource allocation to reproduc- tion 1 1, 1 the other hand, metabolic scaling theory predicts that mass growth rate.