scholarly journals GEOSTATISTICAL MODELING OF TIMBER VOLUME SPATIAL VARIABILITY FOR Tectona grandis L. F. PRECISION FORESTRY

CERNE ◽  
2017 ◽  
Vol 23 (1) ◽  
pp. 115-122 ◽  
Author(s):  
Allan Libanio Pelissari ◽  
Marcelo Roveda ◽  
Sidney Fernando Caldeira ◽  
Carlos Roberto Sanquetta ◽  
Ana Paula Dalla Corte ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Tectona Grandis ◽  
Wood Products ◽  
Geostatistical Modeling ◽  
Timber Volume ◽  
Silvicultural Treatments ◽  
Punctual Kriging ◽  
Precision Forestry ◽  
Taper Models

ABSTRACT Considering the hypothesis that the wood volumes present spatial dependence, whose knowledge contributes for the precision forestry, the aim of this work was to estimate the volume spatial variability for timber assortments and identify their spatial patterns on Tectona grandis stands. A dataset of 1,038 trees was used to fit taper models and estimate the total stem, sawlog, and firewood volumes in 273 plots allocated on T. grandis stands at eight years old, which represents the second thinning that enables commercial volumes. Semivariograms models was applied to fit the spatial dependence, and punctual kriging was used to compose volume maps. Geostatistical modeling allowed us to estimate the T. grandis spatial variability and develop timber volume maps. Thus, silvicultural treatments, such as thinning and pruning, as well as for planning spatial interventions, are possible to be recommended for aimed wood products.

Non-destructive estimation of fibre morphological parameters and chemical constituents of Tectona grandis L.f. wood by near infrared spectroscopy

2021 ◽  
pp. 096703352199911
Author(s):  
SR Shukla ◽  
S Shashikala ◽  
M Sujatha
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Chemical Constituents ◽  
Fibre Diameter ◽  
Tectona Grandis ◽  
Cost Effective ◽  
Wood Products ◽  
Timber Species ◽  
Morphological Parameters ◽  
Mean Square Errors

Near infrared (NIR) spectroscopy is developing as an advanced and non-invasive tool in the wood, wood products and forestry sectors. It may be applied as a rapid and cost effective technique for assessment of different wood quality parameters of timber species. In the present study, NIR spectra of heartwood samples of Tectona grandis (teak) were collected before measuring fibre morphological parameters (fibre length, fibre diameter and fibre lumen diameter)and main chemical constituents (cellulose, hemicellulose, lignin and extractives) using maceration and wet chemistry methods respectively. Multivariate partial least squares (PLS) regression was applied to develop the calibration models between measured values of wood parameters and NIR spectral data. Pre-processing of NIR spectra demonstrated better predictions based on higher values of correlation coefficient for estimation (R2), validation (Rcv 2 ), ratio of performance to deviation (RPD), and lower values of root mean square errors of estimation (RMSEE), cross-validation (RMSECV) and number of latent variable (rank). Internal cross-validation was used to find the optimum rank. Robust calibrations models with high R2 (>0.87), low errors and high RPD values (> 2.93) were observed from PLS analysis for fibre morphological parameters and main chemical constituents of teak. These linear models may be applied for rapid and cost effective estimation of different fibre parameters and chemical constituents in routine testing and evaluation procedures for teak.

scholarly journals Spatial variability and mapping of soil fertility status in a high-potential smallholder farming area under sub-humid conditions in Zimbabwe

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Gabriel Soropa ◽  
Olton M. Mbisva ◽  
Justice Nyamangara ◽  
Ermson Z. Nyakatawa ◽  
Newton Nyapwere ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Soil Ph ◽  
Strong Evidence ◽  
Spatial Dependence ◽  
Random Component ◽  
Smallholder Farming ◽  
Mineral N ◽  
Spatial Trend ◽  
Spatial Trends

AbstractA study was conducted to examine spatial variability of soil properties related to fertility in maize fields across varying soil types in ward 10 of Hurungwe district, Zimbabwe; a smallholder farming area with sub-humid conditions and high yield potential. Purposively collected and geo-referenced soil samples were analyzed for texture, pH, soil organic carbon (OC), mineral N, bicarbonate P, and exchangeable K. Linear mixed model was used to analyze spatial variation of the data. The model allowed prediction of soil properties at unsampled sites by the empirical best linear unbiased predictor (EBLUP). Evidence for spatial dependence in the random component of the model was evaluated by calculating Akaike’s information criterion. Soil pH ranged from 4.0 to 6.9 and showed a strong spatial trend increasing from north to south, strong evidence for a difference between the home and outfields with homefields significantly higher and between soil textural classes with the sand clay loam fraction generally higher. Soil OC ranged from 0.2 to 2.02% and showed no spatial trend, but there was strong evidence for a difference between home and outfields, with mean soil OC in homefields significantly larger, and between soil textural classes, with soil OC largest in the sandy clay loams. Both soil pH and OC showed evidence for spatial dependence in the random effect, providing a basis for spatial prediction by the EBLUP, which was presented as a map. There were significant spatial trends in mineral N, available P and exchangeable K, all increasing from north to south; significant differences between homefields and outfields (larger concentrations in homefields), and differences between the soil textural classes with larger concentrations in the sandy clay loams. However, there was no evidence for spatial dependence in the random component, so no attempt was made to map these variables. These results show how management (home fields vs outfields), basic soil properties (texture) and other factors emerging as spatial trends influence key soil properties that determine soil fertility in these conditions. This implies that the best management practices may vary spatially, and that site-specific management is a desirable goal in conditions such as those which apply in Ward 10 of Hurungwe district in Zimbabwe.

Effect of Savanna windrow wood burning on the spatial variability of soil properties

2021 ◽  
Vol 51 ◽  
Author(s):  
Diogo Neia Eberhardt ◽  
Robélio Leandro Marchão ◽  
Pedro Rodolfo Siqueira Vendrame ◽  
Marc Corbeels ◽  
Osvaldo Guedes Filho ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Spatial Arrangement ◽  
Nugget Effect ◽  
Tropical Savannas ◽  
Geostatistical Methods ◽  
Exchangeable Ca ◽  
Spherical Models

ABSTRACT Tropical Savannas cover an area of approximately 1.9 billion hectares around the word and are subject to regular fires every 1 to 4 years. This study aimed to evaluate the influence of burning windrow wood from Cerrado (Brazilian Savanna) deforestation on the spatial variability of soil chemical properties, in the field. The data were analysed by using geostatistical methods. The semivariograms for pH(H2O), pH(CaCl2), Ca, Mg and K were calculated according to spherical models, whereas the phosphorus showed a nugget effect. The cross semi-variograms showed correlations between pH(H2O) and pH(CaCl2) with other variables with spatial dependence (exchangeable Ca and Mg and available K). The spatial variability maps for the pH(H2O), pH(CaCl2), Ca, Mg and K concentrations also showed similar patterns of spatial variability, indicating that burning the vegetation after deforestation caused a well-defined spatial arrangement. Even after 20 years of use with agriculture, the spatial distribution of pH(H2O), pH(CaCl2), Ca, Mg and available K was affected by the wood windrow burning that took place during the initial deforestation.

scholarly journals Spatial variability of soil chemical properties after coffee tree removal

2009 ◽  
Vol 33 (5) ◽  
pp. 1507-1514 ◽  
Author(s):  
Sidney Rosa Vieira ◽  
Osvaldo Guedes Filho ◽  
Márcio Koiti Chiba ◽  
Heitor Cantarella
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Crop Yields ◽  
Management Strategies ◽  
Chemical Properties ◽  
Spherical Model ◽  
Soil Chemical Properties ◽  
Kriging Interpolation ◽  
Geostatistical Methods ◽  
Plant Removal

Assessing the spatial variability of soil chemical properties has become an important aspect of soil management strategies with a view to higher crop yields with minimal environmental degradation. This study was carried out at the Centro Experimental of the Instituto Agronomico, in Campinas, São Paulo, Brazil. The aim was to characterize the spatial variability of chemical properties of a Rhodic Hapludox on a recently bulldozer-cleaned area after over 30 years of coffee cultivation. Soil samples were collected in a 20 x 20 m grid with 36 sampling points across a 1 ha area in the layers 0.0-0.2 and 0.2-0.4 m to measure the following chemical properties: pH, organic matter, K+, P, Ca2+, Mg2+, potential acidity, NH4-N, and NO3-N. Descriptive statistics were applied to assess the central tendency and dispersion moments. Geostatistical methods were applied to evaluate and to model the spatial variability of variables by calculating semivariograms and kriging interpolation. Spatial dependence patterns defined by spherical model adjusted semivariograms were made for all cited soil properties. Moderate to strong degrees of spatial dependence were found between 31 and 60 m. It was still possible to map soil spatial variability properties in the layers 0-20 cm and 20-40 cm after plant removal with bulldozers.

scholarly journals Spatial variability of Soil Nutrients Using Geospatial Techniques: A case study in soils of Sanwer Tehsil of Indore district of Madhya Pradesh

2014 ◽  
Vol XL-8 ◽  
pp. 1353-1363 ◽  
Author(s):  
G. S. Tagore ◽  
G. D. Bairagi ◽  
R. Sharma ◽  
P. K. Verma
Keyword(s):  
Spatial Variability ◽  
Soil Nutrients ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Sampling Strategy ◽  
Spatial Prediction ◽  
Accurate Estimation ◽  
Suitable Alternative ◽  
Available N ◽  
Physico Chemical

A study was conducted to explore the spatial variability of major soil nutrients in a soybean grown region of Malwa plateau. From the study area, one hundred sixty two surface soil samples were collected by a random sampling strategy using GPS. Then soil physico-chemical properties i.e., pH, EC, organic carbon, soil available nutrients (N, P, K, S and Zn) were measured in laboratory. After data normalization, classical and geo-statistical analyses were used to describe soil properties and spatial correlation of soil characteristics. Spatial variability of soil physico-chemical properties was quantified through semi-variogram analysis and the respective surface maps were prepared through ordinary Kriging. Exponential model fits well with experimental semi-variogram of pH, EC, OC, available N, P, K, S and Zn. pH, EC, OC, N, P, and K has displayed moderate spatial dependence whereas S and Zn showed weak spatial dependence. Cross validation of kriged map shows that spatial prediction of soil nutrients using semi-variogram parameters is better than assuming mean of observed value for any un-sampled location. Therefore it is a suitable alternative method for accurate estimation of chemical properties of soil in un-sampled positions as compared to direct measurement which has time and costs concerned.

scholarly journals Mineralogy of the clay fraction of Alfisols in two slope curvatures: III - spatial variability

2013 ◽  
Vol 37 (2) ◽  
pp. 295-306 ◽  
Author(s):  
Livia Arantes Camargo ◽  
José Marques Júnior ◽  
Gener Tadeu Pereira
Keyword(s):  
Spatial Variability ◽  
Iron Oxides ◽  
Spatial Dependence ◽  
Clay Fraction ◽  
X Ray Diffraction ◽  
X Ray ◽  
Half Height ◽  
Mineralogical Properties ◽  
Crystallite Dimension ◽  
Xrd Patterns

A good knowledge of the spatial distribution of clay minerals in the landscape facilitates the understanding of the influence of relief on the content and crystallographic attributes of soil minerals such as goethite, hematite, kaolinite and gibbsite. This study aimed at describing the relationships between the mineral properties of the clay fraction and landscape shapes by determining the mineral properties of goethite, hematite, kaolinite and gibbsite, and assessing their dependence and spatial variability, in two slope curvatures. To this end, two 100 × 100 m grids were used to establish a total of 121 regularly spaced georeferenced sampling nodes 10 m apart. Samples were collected from the layer 0.0-0.2 m and analysed for iron oxides, and kaolinite and gibbsite in the clay fraction. Minerals in the clay fraction were characterized from their X-ray diffraction (XRD) patterns, which were interpreted and used to calculate the width at half height (WHH) and mean crystallite dimension (MCD) of iron oxides, kaolinite, and gibbsite, as well as aluminium substitution and specific surface area (SSA) in hematite and goethite. Additional calculations included the goethite and hematite contents, and the goethite/(goethite+hematite) [Gt/(Gt+Hm)] and kaolinite/(kaolinite+gibbsite) [Kt/(Kt+Gb)] ratios. Mineral properties were established by statistical analysis of the XRD data, and spatial dependence was assessed geostatistically. Mineralogical properties differed significantly between the convex area and concave area. The geostatistical analysis showed a greater number of mineralogical properties with spatial dependence and a higher range in the convex than in the concave area.

scholarly journals Geostatistical analysis for soil moisture content under the no tillage cropping system

2006 ◽  
Vol 63 (4) ◽  
pp. 341-350 ◽  
Author(s):  
Célia Regina Grego ◽  
Sidney Rosa Vieira ◽  
Aline Maria Antonio ◽  
Simone Cristina Della Rosa
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Spatial Variability ◽  
Water Content ◽  
Spatial Dependence ◽  
Soil Moisture Content ◽  
No Tillage ◽  
Moisture Contents ◽  
Classical Statistics ◽  
Evaluation Point

Experiments in agriculture usually consider the topsoil properties to be uniform in space and, for this reason, often make inadequate use of the results. The objective of this study was to assess the variability for soil moisture content using geostatistical techniques. The experiment was carried out on a Rhodic Ferralsol (typic Haplorthox) in Campinas, SP, Brazil, in an area of 3.42 ha cultivated under the no tillage system, and the sampling was made in a grid of 102 points spaced 10 m x 20 m. Access tubes were inserted down to one meter at each evaluation point in order to measure soil moisture contents (cm³ cm-3) at depths of 30, 60 and 90 cm with a neutron moisture gauge. Samplings were made between the months of August and September of 2003 and in January 2004. The soil moisture content for each sampling date was analyzed using classical statistics in order to appropriately describe the central tendency and dispersion on the data and then using geostatistics to describe the spatial variability. The comparison between the spatial variability for different samplings was made examining scaled semivariograms. Water content was mapped using interpolated values with punctual kriging. The semivariograms showed that, at the 60 cm depth, soil water content had moderate spatial dependence with ranges between 90 and 110 m. However, no spatial dependence was found for 30 and 90 cm depths in 2003. Sampling density was insufficient for an adequate characterization of the spatial variability of soil moisture contents at the 30 and 90 cm depths.

Spatial Probabilistic Modeling of Corrosion in Ship Structures

2017 ◽  
Vol 3 (3) ◽  
Author(s):  
Jesus Luque ◽  
Rainer Hamann ◽  
Daniel Straub
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Measurement Data ◽  
Corrosion Process ◽  
Model Parameters ◽  
Plate Element ◽  
Structural Element ◽  
Ship Structures ◽  
Operational Conditions ◽  
Corrosion Model

Corrosion in ship structures is influenced by a variety of factors that are varying in time and space. Existing corrosion models used in practice only partially address the spatial variability of the corrosion process. Typical estimations of corrosion model parameters are based on averaging measurements for one ship type over structural elements from different ships and operational conditions. Most models do not explicitly predict the variability and correlation of the corrosion process among multiple locations in the structure. This correlation is of relevance when determining the necessary inspection coverage, and it can influence the reliability of the ship structure. In this paper, we develop a probabilistic spatiotemporal corrosion model based on a hierarchical approach, which represents the spatial variability and correlation of the corrosion process. The model includes as hierarchical levels vessel–compartment–frame–structural element–plate element. At all levels, variables representing common influencing factors (e.g., coating life) are introduced. Moreover, at the lowest level, which is the one of the plate element, the corrosion process can be modeled as a spatial random field. For illustrative purposes, the model is trained through Bayesian analysis with measurement data from a group of tankers. In this application, the spatial dependence among corrosion processes in different parts of the ships is identified and quantified using the proposed hierarchical model. Finally, how this spatial dependence can be exploited when making inference on the future condition of the ships is demonstrated.

Stem eccentricity, crown dry mass distribution, and longitudinal growth strain of plantation-grown Eucalyptus nitens after thinning

2011 ◽  
Vol 41 (11) ◽  
pp. 2209-2218 ◽  
Author(s):  
Jane Medhurst ◽  
Maria Ottenschlaeger ◽  
Matthew Wood ◽  
Chris Harwood ◽  
Chris Beadle ◽  
...  
Keyword(s):  
Mass Distribution ◽  
Dry Mass ◽  
Solid Wood ◽  
Wood Products ◽  
Eucalyptus Nitens ◽  
Cross Sectional ◽  
The North ◽  
Silvicultural Treatments ◽  
Wind Exposure ◽  
Pith Eccentricity

Silvicultural treatments that aim to improve tree growth rates also have the potential to alter physical characteristics of the tree stem and thus affect the recovery of solid-wood products. We tested the hypothesis that manifest crown asymmetry in thinned Eucalyptus nitens (Deane & Maiden) Maiden plantations was affecting the development of stem shape. The crown and stem characteristics of 15 E. nitens trees from a 22-year-old thinning trial in northeastern Tasmania were examined. The trial had been thinned 16 years previously. Lowering the intensity of local intraspecific competition through thinning increased the crown dry mass in the north-facing aspect. No direct link was found between crown dry mass distribution and stem eccentricity. The direction of pith eccentricity at 3.0 m height was confined to the northwest and southeast sectors and averaged 11%; the degree of noncircularity in stems at 3.0 m height was strongly related to the ratio of stem diameter to total height squared. These results suggest that the dynamic loading from wind exposure plays a greater role in determining the extent and direction of pith eccentricity and stem cross-sectional circularity in E. nitens than does the static load from asymmetrical crown dry mass distribution.

scholarly journals VARIABILIDADE ESPACIAL E CORRELAÇÃO DOS ATRIBUTOS DO SOLO COM PRODUTIVIDADE DO MILHO E DA SOJA

Nativa ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 536-543
Author(s):  
Evandro Gelain ◽  
Eduardo Leonel Bottega ◽  
Anamari Viegas de Araujo Motomiya ◽  
Zanandra Boff de Oliveira
Keyword(s):  
Decision Making ◽  
Zea Mays ◽  
Glycine Max ◽  
Spatial Variability ◽  
Spatial Dependence ◽  
Soil Samples ◽  
Geostatistical Analysis ◽  
Sample Point ◽  
Iron And Zinc ◽  
Potential Acidity

O emprego de técnicas de agricultura de precisão, associadas a análises geoestatísticas, possibilita mapear a variabilidade espacial existente em um campo de produção. O conhecimento da variabilidade é importante ferramenta na tomada de decisões quanto ao manejo da área, uma vez que possibilita que este seja realizado de forma localizada. O estudo foi realizado em um talhão da Fazenda Planalto, localizada no município de Maracaju – MS, com o objetivo de avaliar a variabilidade espacial e correlação entre os atributos químicos e granulométricos do solo e a produtividade do milho e da soja. Foi utilizada uma grade amostral contendo 187 pontos, utilizando-se 10 amostras simples de solo por ponto amostral. Não foi detectado dependência espacial para o cálcio, alumínio, acidez potencial, soma de bases, ferro e zinco. As melhores estimativas em locais não amostrados foram obtidos para a areia e argila. A produtividade da soja apresentou forte dependência espacial e se correlacionou positivamente de forma forte com o fósforo e moderada com o magnésio. Palavras-chave: Latossolo; dependência espacial; Glycine max; Zea mays.   Spatial variability and correlation of chemicals and physical soil attributes with corn and soybean yield   ABSTRACT: The use of precision farming techniques, associated with geostatistical analysis, makes it possible to map the spatial variability in a production field. The knowledge of variability is an important tool in decision making regarding the management of the area, since it allows it to be carried out in a localized manner. The study was carried out in a plot of Fazenda Planalto, located in the municipality of Maracaju - MS, with the objective of evaluating the spatial variability and correlation between the chemical and granulometric attributes of the soil and the corn and soybeans yield. A sampling grid containing 187 points was used, using 10 simple soil samples per sample point. No spatial dependence was detected for calcium, aluminum, potential acidity, sum of bases, iron and zinc. The best estimates in unsampled locations were obtained for sand and clay. The soybeans yield showed strong spatial dependence and was positively correlated strongly with phosphorus and moderately with magnesium. Keywords: Oxisol; spatial dependence; Glycine max; Zea mays.

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