Luiz Carlos Estraviz Rodriguez

Fitting a taper function to minimize the sum of absolute deviations

Multiple product inventories of forests require accurate estimates of the diameter, length and volume of each product. Taper functions have been used to precisely describe tree form, once they provide estimates for the diameter at any height or the height at any diameter. This study applied a goal programming technique to estimate the parameters of two taper functions to describe individual tree forms. The goal programming formulation generates parameters that minimize total absolute deviations (MOTAD). These parameters generated by the MOTAD method were compared to those of ordinary least squares (OLS) method. The analysis used a set of 178 trees cut from cloned eucalyptus plantations in the Southern part of the state of Bahia, Brazil. The values of the estimated parameters for the two taper functions resulted very similar when the two methods were compared. There was no significant difference between the two fitting methods according to the statistics used to evaluate the quality of the generated estimates. OLS and MOTAD resulted equally precise in the estimation of diameters and volumes outside and inside bark.

Comparison of ALS based models for estimating aboveground biomass in three types of Mediterranean forest

Abstract This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most cases.

A performance comparison of machine learning methods to estimate the fast-growing forest plantation yield based on laser scanning metrics

Machine learning models tackle high-dimensional problems.The machine learning models are not limited to a subset of predictor variables.The random forest had the best RMSE compared to neural network and support vector regression.The coefficient of determination and bias were similar to all modeling techniques. Machine learning models appear to be an attractive route towards tackling high-dimensional problems, particularly in areas where a lack of knowledge exists regarding the development of effective algorithms, and where programs must dynamically adapt to changing conditions. The objective of this study was to evaluate the performance of three machine learning tools for predicting stand volume of fast-growing forest plantations, based on statistical vegetation metrics extracted from an Airborne Laser Scanning (ALS) survey. The forests used in this study were composed of 1138ha of commercial plantations that consisted of hybrids of Eucalyptus grandis and Eucalyptus urophylla, managed for pulp production. Three machine learning tools were implemented: neural network (NN), random forest (RF) and support vector regression (SV); and their performance was compared to a regression model (RM). The RF and the RM presented an RMSE in the leave-one-out cross-validation of 31.80 and 30.56m3ha-1 respectively. The NN and SV presented a higher RMSE than the others, equal to 64.44 and 65.30m3ha-1. The coefficient of determination and bias were similar to all modeling techniques. The ranking of ALS metrics based on their relative importance for the estimation of stand volume showed some differences. Rather than being limited to a subset of predictor variables, machine learning techniques explored the complete metrics set, looking for patterns between them and the dependent variable.

Estudo de aspectos técnicos, econômicos e sociais da produção de carvão vegetal no Município de Pedra Bela, São Paulo, Brasil

Durante o ano de 2001 foi realizado um levantamento, visando avaliar a atividade da producao de carvao vegetal no Municipio de Pedra Bela, Estado de Sao Paulo. Esse pequeno municipio localizado, a 150 km da Cidade de Sao Paulo, caracteriza-se pela sua importante dependencia em relacao a producao de carvao vegetal, podendo ser considerado um exemplo tipico da atividade no estado paulista. Procurou-se obter informacoes basicas que pudessem servir para futuras definicoes de politicas publicas na regiao, ligadas a cadeia produtiva florestal e do carvao vegetal. Sao apresentados os principais resultados tecnicos e economicos, decorrentes da obtencao de dados coletados mediante a aplicacao de questionarios, entrevistas e coleta de informacoes secundarias pre-existentes nos produtores rurais, liderancas locais e orgaos oficiais de governo. Os resultados indicaram, sobretudo, que a madeira de eucalipto, principal materia-prima local para obtencao de carvao vegetal, esta se tornando cada vez mais escassa e a falta de novos plantios pode comprometer a atividade no municipio. O trabalho apontou a necessidade de acoes no sentido da melhoria e fortalecimento institucional das acoes ligadas a atividade na regiao.

Influence of Carbon Sequestration in an Optimal Set of Coppice Rotations for Eucalyptus Plantations

The coppice regeneration method used to manage eucalypts leads to a simultaneous optimization problem: the manager has to simultaneously define the optimal age in each coppice rotation and the optimal number of coppice rotations for each plantation full cycle. The dynamic nature of the problem justifies the use of methods like dynamic programming in order to achieve optimal solutions. Expected land value and the duration of the optimal rotation may change significantly when payments for carbon sequestration are added as revenues in the cash flow analysis of the project. In this chapter, we analyze the effects of considering carbon sequestration as a subsidized complementary product when defining the optimal set of coppice rotations. A Monte Carlo simulation technique was used to model the inherent risk of some variables and parameters like pulpwood price, carbon price, and discount rate. The variation in the land expectation value and in the optimal rotation length is reported when these stochastic variables are computed. Two study cases are shown, one with Eucalyptus urophylla S.T. Blake in Brazil, and another with Eucalyptus globulus Labill in Galicia, Spain.

IDENTIFICAÇÃO DE ÁRVORES INDIVIDUAIS A PARTIR DE LEVANTAMENTOS LASER AEROTRANSPORTADO POR MEIO DE JANELA INVERSA

O ponto crucial do filtro de maximos locais e a definicao do tamanho da janela. Este trabalho propoe que a janela de busca seja determinada por uma relacao inversa a altura do modelo digital de alturas e testa a hipotese de que uma janela de busca, inversamente proporcional, tera melhor desempenho do que a janela de busca proporcional. A area de estudo esta localizada na regiao sudeste do Estado de British Columbia, Canada. A vegetacao natural e do tipo boreal e caracteriza-se pela predominância de duas especies Picea engelmannii Parry ex. Engelmann (picea de Engelmann) e Abies lasiocarpa (Hook.) Nutt. (abeto subalpino). O relevo e do tipo ondulado a montanhoso com altitudes que variam de 650 a 2400 metros. Foram lancadas 62 parcelas de campo com 256 metros quadrados. Foi usado um levantamento laser aerotransportado de retornos discretos, com densidade de 2 pontos por metro quadrado e small-footprint. As estimativas foram comparadas aos valores observados em campo durante a medicao das parcelas. O desempenho das janelas de busca foi avaliado quanto ao percentual de acertos e quanto ao desvio absoluto. O filtro de maximos locais subestimou o numero de arvores por hectare, considerando tanto a janela de busca proporcional quanto a inversamente proporcional. A relacao inversa para a determinacao da dimensao da janela resultou em melhores resultados, especialmente para regioes com maior densidade de arvores.

Comparison of ALS- and UAV(SfM)-derived high-density point clouds for individual tree detection in Eucalyptus plantations

ABSTRACT Highly accurate, rapid forest inventory techniques are needed to enable forest managers to address the increasing demand for sustainable forestry. In the last two decades, Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning have become internationally established as forest mapping and monitoring methods. However, recent advances in sensors and in image processing – particularly Structure from Motion (SfM) technology – have also enabled the extraction of dense point clouds from images obtained by Digital Aerial Photography (DAP). DAP is cheaper than ALS, especially when the systems are mounted on small unmanned aerial vehicles (UAVs), and the density of the point cloud can easily reach the levels yielded by ALS devices. The main objective of this study was to evaluate and compare the usefulness of ALS-derived and UAV(SfM)-derived high-density point clouds for detecting and measuring individual tree height in Eucalyptus spp. plantations established on complex terrain. A total of 325 reference trees were measured and located in 6 square plots (400 m2). The individual tree crown (ITC) delineation algorithm detected 311 from the ALS-derived data and 259 trees from the UAV(SfM)-derived data, representing accuracy levels of, respectively, 96% and 80%. The results suggest that at plot level, UAV(SfM)-generated point clouds are as good as ALS-derived point clouds for estimating individual tree height. Furthermore, analysis of the differences in digital elevation models at landscape level showed that the elevations of the UAV(SfM)-derived terrain surfaces were slightly higher than the ALS-derived surfaces (mean difference, 1.14 m and standard deviation, 1.93 m). Finally, we discuss how non-optimal UAV-image-acquisition conditions and slope terrain affect the ITC delineation process.

Assessing biomass based on canopy height profiles using airborne laser scanning data in eucalypt plantations

This study aimed to map the stem biomass of an even-aged eucalyptus plantation in southeastern Brazil based on canopy height profile (CHPs) statistics using wall-to-wall discrete return airborne laser scanning (ALS), and compare the results with alternative maps generated by ordinary kriging interpolation from field-derived measurements. The assessment of stem biomass with ALS data was carried out using regression analysis methods. Initially, CHPs were determined to express the distribution of laser point heights in the ALS cloud for each sample plot. The probability density function (pdf) used was the Weibull distribution, with two parameters that in a secondary task, were used as explanatory variables to model stem biomass. ALS metrics such as height percentiles, dispersion of heights, and proportion of points were also investigated. A simple linear regression model of stem biomass as a function of the Weibull scale parameter showed high correlation (adj.R2 = 0.89). The alternative model considering the 30th percentile and the Weibull shape parameter slightly improved the quality of the estimation (adj.R2 = 0.93). Stem biomass maps based on the Weibull scale parameter doubled the accuracy of the ordinary kriging approach (relative root mean square error = 6 % and 13 %, respectively).

Economics and Management of Industrial Forest Plantations

This chapter deals with the basic principles underlying the optimum economic management of the industrial forest plantations. With this purpose the presentation will start with the introduction of basic concepts of the investment analysis, which will serve as a basis for explaining the tools most usually employed for analysing the profitability of this kind of investments. After this, the concept as well as the optimum economic determination of the forest rotation age will be analysed. Once the investment analysis and optimal forest rotation concepts have been reviewed, we focus in the basic aspects of forest valuation. Finally, an operations research technique used to optimize stand management planning decisions, as dynamic programming, will be shown.

The Importance of Industrial Forest Plantations

The first chapter of the book initially addresses the definition of planted forests, industrial forests and industrial forest plantations. It also contextualizes historically the evolution of the term forest plantations, citing the several international organizations involved and different attempts to satisfy many actors and opinions. Facts and figures are also presented to illustrate the evolving roles that forest plantations have undertaken over the years. Some comprehensive statistics are included to emphasize the importance and benefits of its expansion. The chapter also presents some important future trends that guide the need for the forest planning and forest management techniques discussed in the book. These tools may overcome the challenges brought by the more complex and conflicting social, economic and environmental goals confronted by the forest sector. Although regularly challenged by new technological advances, it is important to realize that trees are still one of the most efficient ways to produce highly demanded materials, with minimal collateral negative impacts. The argument stands in the principle that, being a renewable organism that synthesizes carbon fueled by sun light, the sustainable use of planted forests reduces the impact over other natural resources and fossil fuels. Furthermore, the antagonism between planted forests and natural forests has diminished, as well as its complementary and compatible coexistence with wild land native forests in many different landscapes and regional contexts.