scholarly journals Spatial Dependence of the Site Index of Pinus taeda L. Production Forests, in the Southern Central Region of the State of Paraná, Brazil

2019 ◽  
Vol 11 (13) ◽  
pp. 319
Author(s):  
Maite dos Santos Ribeiro ◽  
Julio Eduardo Arce ◽  
Afonso Figueiredo Filho ◽  
Marcos Felipe Nicoletti
Keyword(s):  
Pinus Taeda ◽  
Spatial Dependence ◽  
Ordinary Kriging ◽  
Spherical Model ◽  
Site Index ◽  
Coefficient Of Determination ◽  
Site Classification ◽  
Optimal Method ◽  
Average Value ◽  
Production Forests

A spatial analysis of the site index used for the classification of Pinus taeda production forests was performed using dominant height data from 402 continuous inventory plots. The data were examined with simple descriptive statistics and fit with four semivariogram models by the GS + program. The best model was then used to predict the site index in unsampled areas by ordinary kriging in ArcView. All models showed that site index values exhibited spatial dependence, with the degree of spatial dependence ranging from strong to moderate. The spherical model was used for kriging. In this model, the degree of spatial dependence was 29% and the range was 5,330 m, with a residual sum of squares (RSS) of 3.00 and coefficient of determination (r²) of 0.776. Measured and predicted values were compared by cross-validation, which produced a linear regression of observed versus predicted value with a slope coefficient of 1.068, slope standard error of 0.070, and intercept coefficient of -1.45. The site classification map generated by kriging divided the studied forests into five classes. Before kriging, all of the forest stands had one global average value for the site index, but after kriging this was changed to there being two or three values of the site index for many stands. Ordinary kriging proved to be an optimal method for interpolating the site index of unsampled areas to permit their classification, as is the case for young plantations for which inventory samples have not yet been taken.

scholarly journals USO DE MODELOS ESTATÍSTICOS PARA CLASSIFICAÇÃO DE SÍTIOS EM POVOAMENTOS DE Pinus taeda NA REGIÃO DE CAÇADOR – SC

FLORESTA ◽  
2011 ◽  
Vol 41 (1) ◽  
Author(s):  
Saulo Jorge Téo ◽  
Diego Ricardo Bressan ◽  
Reinaldo Hoinacki da Costa
Keyword(s):  
Pinus Taeda ◽  
Loblolly Pine ◽  
Statistical Models ◽  
Site Index ◽  
Site Classification ◽  
Santa Catarina ◽  
Dominant Height ◽  
Pinus Taeda L ◽  
Santa Catarina State

Este trabalho teve como objetivo testar diferentes modelos estatísticos para ajuste de curvas de índice de sítio e verificar se as curvas anamórficas geradas foram satisfatórias para classificação de sítios em povoamentos de Pinus taeda L. na região de Caçador, SC. Os dados de altura dominante (hdom) utilizados nesta pesquisa foram obtidos de parcelas permanentes de área fixa e formato retangular, com áreas de 500 e 625 m². As parcelas foram distribuídas de forma aleatória nos povoamentos, a fim de abranger a maior variabilidade possível de produtividade. A seleção do melhor modelo estatístico ajustado foi feita por meio das seguintes estatísticas de ajuste e precisão: coeficiente de determinação ajustado (R²aj), erro padrão da estimativa (Syx), erro padrão da estimativa em porcentagem (Syx%) e distribuição de resíduos em porcentagem. O modelo monomolecular apresentou os melhores resultados para os critérios de seleção, portanto foi escolhido para a construção das curvas de índice de sítio pelo método da curva guia. Depois de se proceder à classificação de sítios, foram realizados testes de anamorfismo, os quais indicaram o padrão anamórfico das curvas geradas pelo modelo estatístico ajustado para classificação de sítios dos povoamentos de Pinus taeda na região de Caçador, SC.Palavras-chave:  Modelos estatísticos; teste de anamorfismo; curvas de índice de sítio; altura dominante. AbstractUse of statistical modells for site classification of Pinus taeda plantation in the region of Caçador, Santa Catarina State, Brazil. This study aimed to test different statistical models for fitting site index curves and check if the anamorphic curves generated were satisfactory to classify the loblolly pine (Pinus taeda L.) plantations in the region of Caçador, Santa Catarina State, Brazil. The data of dominant height (hdom) used in this study were obtained from permanent plots of fixed area and rectangular shape, with areas of 500 and 625 square meters. The plots were distributed randomly in the stands to cover the largest possible variability of productivity. The selection of the best equation was made by the following fitting and precision statistics: adjusted coefficient of determination (R²aj), standard error of estimation (Syx), standard error of estimate in percentage (Syx%) and graphical distribution of the residuals in percentage. The monomolecular model showed the best performance, so it was chosen for the construction of the site index curves by guide curve method. After construction of the site index curves, the stability of the curves was also tested, which indicated the anamorphic pattern of the curves generated by the equation for site classification of loblolly pine plantations in the region of Caçador, Santa Catarina State, Brazil.Keywords:  Statistical models; test of anamorphism; site index curves; dominant height.

scholarly journals SITE INDEX IN EUCALYPTUS STANDS APPLYING ORDINARY KRIGING: AN APPROACH WITH DIFFERENT MODELS AND METHODS OF CLASSIFICATION

FLORESTA ◽  
2021 ◽  
Vol 51 (4) ◽  
pp. 1000
Author(s):  
Pedro Vaz da Rocha ◽  
Emanuel José Gomes de Araújo ◽  
Vinícius Augusto Morais ◽  
Marco Antonio Monte ◽  
Danilo Henrique dos Santos Ataíde ◽  
...  
Keyword(s):  
Difference Method ◽  
Spatial Dependence ◽  
Ordinary Kriging ◽  
Gaussian Model ◽  
Site Index ◽  
Site Quality ◽  
Productive Capacity ◽  
Dominant Height ◽  
Algebraic Difference ◽  
Predictive Validation

The objective of this work was to evaluate the efficiency of models and methods to obtain the site index, associated with ordinary kriging, to classify productive capacity in eucalyptus stands. Thus, the site quality was performed considering the traditional modeling in clonal stands (2,119 hectares) located in Minas Gerais state, Brazil. 170 plots of 400m2 were randomly allocated, representing a sampling intensity of 0.32%. The dominant height of trees (Assmann) was measured at 24, 36, 48, 60, 72, and 84 months. The site index (S) was estimated by the guide curve and algebraic difference methods, using the models of Schumacher, Chapman and Richards, and Bailey and Clutter. 136 plots were used in the fit and 34 plots in the predictive validation. The spatial dependence of site index was evaluated by experimental semivariogram and adjustment of exponential, spherical, and gaussian models. After confirming the spatial dependence, ordinary kriging was performed to spatialize the site index. For the predictive validation, the dominant height values at 72 months were used. The algebraic difference method provided excellent estimates of site index, which showed spatial dependence in all adjustments, from moderate to strong. In most cases, the gaussian model was the most accurate. It is concluded that the algebraic difference method was more efficient and the site index showed strong spatial dependence at all ages, regardless of the model used. Thus, regression models for site index estimation can be used in combination with ordinary kriging techniques.

Microwave Field Distribution Uniformity Coefficient in the Grain Mass

2020 ◽  
Vol 67 (2) ◽  
pp. 87-92
Author(s):  
Dmitriy A. Budnikov
Keyword(s):  
Electromagnetic Field ◽  
Numerical Experiment ◽  
Microwave Field ◽  
Research Purpose ◽  
Coefficient Of Determination ◽  
Material Research ◽  
Dense Layer ◽  
Uniformity Coefficient ◽  
Average Value ◽  
Processed Material

The article considers the microwave electromagnetic fields as one of the options for improving the thermal drying of grain. Their application is limited by the high unevenness of the field propagation in the layer of the processed material. (Research purpose) The research purpose is in justifying the uniformity of distribution of microwave field in the layer of the processed grain. (Materials and methods) The article presents the scheme of computer models of microwave processing zones and waveguides, properties of materials for conducting a numerical experiment. (Results and discussion) A numerical experiment was performed to determine the uniformity coefficient of propagation of the microwave field in a layer of grain material. The article presents the dependencies. (Conclusions) It was found that the results of modeling the distribution of the electromagnetic field in the zone of microwave convective influence of the installation containing two sources of microwave power for processing the grain layer indicate a high level of its unevenness in the volume of the product pipeline. To assess the uniformity of the distribution of the electromagnetic field in the working area of a laboratory installation, there used a coefficient that is the ratio of the average value of the intensity in the zone of microwave convective action to its average value of the wave strength passing through the output of the waveguide. The values of the uniformity coefficient in the considered implementation options are in the range of 0.1757-0.4946 for a dense layer of wheat. To ensure a sufficient level of uniformity of the electromagnetic wave distribution in the volume of the microwave convective zone, the uniformity coefficient must be higher than 0.37. The article presents the dependence of the uniformity coefficient of the electromagnetic field on the humidity of the processed material by a third-degree polynomial with a coefficient of determination higher than 0.98.

scholarly journals Species richness and diversity in shrub savanna using ordinary kriging

2016 ◽  
Vol 51 (8) ◽  
pp. 958-966 ◽  
Author(s):  
Anderson Pedro Bernardina Batista ◽  
José Márcio de Mello ◽  
Marcel Régis Raimundo ◽  
Henrique Ferraço Scolforo ◽  
Aliny Aparecida dos Reis ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Species Richness ◽  
Spatial Dependence ◽  
Ordinary Kriging ◽  
Diversity Index ◽  
Spatial Models ◽  
Shannon Diversity Index ◽  
Shannon Diversity ◽  
Species Richness And Diversity ◽  
Number Of Species

Abstract: The objective of this work was to analyze the spatial distribution and the behavior of species richness and diversity in a shrub savanna fragment, in 2003 and 2014, using ordinary kriging, in the state of Minas Gerais, Brazil. In both evaluation years, the measurements were performed in a fragment with 236.85 hectares, in which individual trees were measured and identified across 40 plots (1,000 m2). Species richness was determined by the total number of species in each plot, and diversity by the Shannon diversity index. For the variogram study, spatial models were fitted and selected. Then, ordinary kriging was applied and the spatial distribution of the assessed variables was described. A strong spatial dependence was observed between species richness and diversity by the Shannon diversity index (<25% spatial dependence degree). Areas of low and high species diversity and richness were found in the shrub savanna fragment. Spatial distribution behavior shows relative stability regarding the number of species and the Shannon diversity index in the evaluated years.

scholarly journals Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium

2011 ◽  
Vol 15 (7) ◽  
pp. 2259-2274 ◽  
Author(s):  
S. Ly ◽  
C. Charles ◽  
A. Degré
Keyword(s):  
Ordinary Kriging ◽  
Spatial Interpolation ◽  
Gaussian Model ◽  
Daily Rainfall ◽  
Spherical Model ◽  
Daily Basis ◽  
Catchment Scale ◽  
Multivariate Geostatistics ◽  
Variogram Models ◽  
Thiessen Polygon

Abstract. Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (kriging) are widely applied in spatial interpolation from point measurement to continuous surfaces. The first step in kriging computation is the semi-variogram modelling which usually used only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km2 regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. This study leaned on 30-yr daily rainfall data of 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km2). This area lies between 35 and 693 m in elevation and consists of river networks, which are tributaries of the Meuse River. For geostatistical algorithms, seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) were fitted to daily sample semi-variogram on a daily basis. These seven variogram models were also adopted to avoid negative interpolated rainfall. The elevation, extracted from a digital elevation model, was incorporated into multivariate geostatistics. Seven validation raingages and cross validation were used to compare the interpolation performance of these algorithms applied to different densities of raingages. We found that between the seven variogram models used, the Gaussian model was the most frequently best fit. Using seven variogram models can avoid negative daily rainfall in ordinary kriging. The negative estimates of kriging were observed for convective more than stratiform rain. The performance of the different methods varied slightly according to the density of raingages, particularly between 8 and 70 raingages but it was much different for interpolation using 4 raingages. Spatial interpolation with the geostatistical and Inverse Distance Weighting (IDW) algorithms outperformed considerably the interpolation with the Thiessen polygon, commonly used in various hydrological models. Integrating elevation into Kriging with an External Drift (KED) and Ordinary Cokriging (OCK) did not improve the interpolation accuracy for daily rainfall. Ordinary Kriging (ORK) and IDW were considered to be the best methods, as they provided smallest RMSE value for nearly all cases. Care should be taken in applying UNK and KED when interpolating daily rainfall with very few neighbourhood sample points. These recommendations complement the results reported in the literature. ORK, UNK and KED using only spherical model offered a slightly better result whereas OCK using seven variogram models achieved better result.

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 DENSITY MANAGEMENT DIAGRAM FOR Eucalyptus grandis W. Hill. ex Maiden STANDS CONTROLLED BY DOMINANT HEIGHT

FLORESTA ◽  
2020 ◽  
Vol 51 (1) ◽  
pp. 240
Author(s):  
Gabriel Paes Marangon ◽  
Emanuel Arnoni Costa ◽  
César Augusto Guimarães Finger ◽  
Paulo Renato Schneider ◽  
Matheus Teixeira Martins
Keyword(s):  
Eucalyptus Grandis ◽  
Strong Relationship ◽  
Site Index ◽  
Graphical Analysis ◽  
Coefficient Of Determination ◽  
Permanent Plots ◽  
Volume Number ◽  
Dominant Height ◽  
Development Site ◽  
Relationship Of

Density management diagram for eucalyptus stands controlled by dominant height. The present study aimed to elaborate Density Management Diagrams (DMD) for Eucalyptus grandis W. Hill. ex Maiden stands including the dominant height. Data were obtained from permanent plots installed in the Centro Oriental Riograndense region and the Porto Alegre Metropolitan area, both located in the state of Rio Grande do Sul. The models to describe the relationships between average volume, number of trees per hectare, mean diameter, and dominant height were assessed by the statistical criteria of coefficient of determination (R²), standard error of the estimate in percentage (Syx%), and graphical analysis of residuals. The developed DMD allows for a better control of stocks in the management of stands due to the strong relationship of dominant height with stand development site and forest yield.Keywords: Growth, Site index, Forest regulation, Yield.

scholarly journals Geostatistical modeling of “lethal coconut palm crown atrophy”, a new disease in the State of Pará

2021 ◽  
Vol 42 (6supl2) ◽  
pp. 3603-3616
Author(s):  
Adriano da Silva Gama ◽  
◽  
Paulo Roberto Silva Farias ◽  
Keyword(s):  
Distribution Pattern ◽  
Temporal Distribution ◽  
Spherical Model ◽  
Coconut Palm ◽  
Coefficient Of Determination ◽  
Data Variability ◽  
Range Vector ◽  
Spatial Estimates ◽  
Spreading Disease ◽  
Kriging Maps

’Lethal Coconut Palm Crown Atrophy’ (LCCA) is a rapidly spreading disease in Brazil, capable of quickly killing coconut trees and threatening the commercial exploration of this plant. The objective of this work was to characterize the spatial and temporal distribution pattern of LCCA in green dwarf coconut commercial plantation areas, located the municipality of Santa Izabel, mesoregion of Northeastern Pará, Brazil. Surveys were carried out at monthly intervals between January 2014 and December 2018, checking for plants with LCCA-characteristic symptoms. Geostatistics was applied to perform spatial-temporal disease estimates based on semivariogram modeling and preparation of ordinary kriging maps. These spatial estimates are conducted through interpolations that characterize data variability in the area. The spherical model yielded the best fit to the spatial distribution of the disease, as it presented the best coefficient of determination (R²), with the range varying between 14m and 45m. The Spatial Dependence Index (SDI) was moderate in the evaluations carried out between 2014 and 2017 (in the 0.26-0.64 range), but not in 2018, when it was strong (0.23). The values of the clustering intensity of LCCA-symptomatic plants were estimated in non-sampled points. The spherical fit model of the data indicates an aggregated distribution pattern, shown by aggregation patches in the plantation, graded by values of dissemination intensity. The kriging maps allowed the observation that the disease expands between plants in the same line, suggesting the possibility of the presence of a short-range vector.

scholarly journals FUZZY LOGIC IN THE SPATIAL AND TEMPORAL DISTRIBUTION IN THE QUALITY OF THE BEVERAGE IN CONILON COFFEE

2019 ◽  
Vol 14 (2) ◽  
pp. 163
Author(s):  
Abel Souza Da Fonseca ◽  
Julião Soares De Souza Lima ◽  
Samuel De Assis Silva ◽  
Maria Christina Junger Delôgo Dardengo ◽  
Alexandre Candido Xavier
Keyword(s):  
Spatial Dependence ◽  
Temporal Variability ◽  
Temporal Distribution ◽  
Spherical Model ◽  
Coffea Canephora ◽  
Descriptive Statistics ◽  
Fuzzy Classification ◽  
Spatial And Temporal Variability ◽  
Mouth Feel

<p>The objective in this study was to evaluate the spatial and temporal variability of the beverage quality by applying the fuzzy classification in the final global sensory analysis, for Coffea canephora Pierre ex A. Froehner, in two consecutive harvests. The studied variables were: fragrance (aroma), flavor, bitterness (sweetness), set, balance, cleaning, aftertaste, mouth feel, uniformity, salinity (acidity) and drink (global note). To the average overall scores of the drinks obtained on the cup-tasting at 80.0 points of a sampling, the mesh has applied the function of association of the fuzzy classification linear model to determine the degree of pertinence. The data were analyzed by the descriptive statistics and then by geostatistics to verify the existence and quantify the degree of spatial dependence of the variables. In the interval classified as “very good coffee” is found in the global average grade, in the two harvests. The methodology fuzzy applied in the global beverage note of the coffee conilon seminal made it possible to determine their spatial variability in the same distribution pattern in the two harvests, close ranges, and adjustments to the spherical model, which was confirmed by the spatial correlation of 61.6% among the fuzzy maps for the global score</p>

A Habitat Suitability Index for White-Tailed Deer in the Piedmont

1989 ◽  
Vol 13 (1) ◽  
pp. 12-16 ◽  
Author(s):  
Hewlette S. Crawford ◽  
R. Larry Marchinton
Keyword(s):  
Pinus Taeda ◽  
Loblolly Pine ◽  
Habitat Suitability ◽  
Agricultural Land ◽  
Basal Area ◽  
Site Index ◽  
Habitat Suitability Index ◽  
Suitability Index ◽  
Private And Public ◽  
Autumn And Winter

Abstract A habitat suitability index based on winter foods was designed to evaluate habitat changes affecting white-tailed deer (Odocoileus virginianus) in the Piedmont region of the southeastern United States. Habitat components incorporated in the index were (1) the standing crop of availableherbaceous vegetation and leaves of woody plants remaining green during late autumn and winter, (2) basal area of oak (Quercus spp.) 10" dbh and larger, (3) number of oak species in the stand ≥5% of total basal area, (4) site index of loblolly pine (Pinus taeda) or mixed oak, (5) percentageof agricultural land, and (6) distance from agricultural land to forest or shrub cover. The rationale for inclusion of each component of the index is given, and methods for sampling each habitat component are described. The index should be useful on private small landownerships as well ason larger private and public holdings. South. J. Appl. For. 13(1):12-16

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