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No. of bitstreams: 1 lima_ns__me_botfca.pdf: 1987635 bytes, checksum: 362b53fdf9f1432de196e26249ec4371 (MD5) Previous issue date: 2018-02-23 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A elevada produtividade do eucalipto ocasiona a necessidade do domínio de técnicas e ferramentas precisas acerca dos povoamentos florestais, como o inventário florestal, procedimento fundamental para o monitoramento da produção que permite o conhecimento do máximo potencial das florestas, além disso, é essencial para o planejamento de atividades de corte, colheita e suprimento de madeira. As técnicas convencionais para o levantamento da produção florestal utilizam-se de métodos tradicionais de estatística (estatística clássica), considerando apenas a adoção de valores médios para a tomada de decisões, não explorando as correlações espaciais que possam existir entre as parcelas amostrais. Então, um tipo de interpolador geoestatístico que permite definir a estrutura de dependência espacial dos dados é a krigagem, que juntamente com a metodologia de amostras virtuais, pode-se tornar uma alternativa viável para obtenção de um variograma com modelagem aceitável. Desta forma, o objetivo geral deste estudo foi empregar a metodologia de amostras virtuais no planejamento da malha amostral do inventário florestal, a fim de possibilitar a determinação de um número de parcelas que possam ser estabelecidas na área para obtenção de produtividade, sem que haja perda de precisão ou aumento de custos. A área de estudo abrange uma área plantada de 287,66 ha, pertencente a empresa Eucatex S/A, localizada em Itatinga, no estado de São Paulo. Os dados dendrométricos de volume (m³.ha-1) foram obtidos por meio de inventários realizados pela própria empresa, utilizando-se 32 parcelas retangulares permanentes, para os inventários florestais contínuos (IFC) e 32 parcelas retangulares permanentes mais 66 temporárias, para o inventário pré-corte (IPC). Os seguintes passos foram realizados com os dados de IFC para espacialização dos dados originais, no programa ArcGIS: aplicação de uma estatística univariada sobre a variável volume/ha; geração do variograma experimental; ajuste do variograma; validação do modelo teórico; aplicação da krigagem; geração de mapas de produtividade ano a ano. Posteriormente, 47 amostras virtuais foram inseridas na malha amostral dos inventários contínuos, considerando apenas as parcelas permanentes (32 parcelas), sendo que 10 parcelas foram selecionadas previamente para a validação externa; a análise geoestatistica se deu com as amostras virtuais mais as amostras permanentes restantes, totalizando 69 parcelas. Comparando-se os métodos, observou-se pela validação cruzada que o erro médio e a correlação entre valores observados e estimados melhoraram adicionando-se amostras virtuais, possibilitando um melhor ajuste do variograma e obtenção de estimativas favoráveis. A comprovação da eficácia da metodologia de inserção das amostras, chamada de validação externa, deu-se pelo cálculo da média do erro médio, que foi igual a 6,8% em volume, em relação ao inventário real. Desta forma, a técnica de inserção de amostras virtuais pode ser utilizada, mostrando-se satisfatória para o planejamento da próxima malha para posteriores análises geoestatísticas, em plantios equiâneos. / The high productivity of eucalyptus trees makes it necessary to master accurate techniques and tools for forest, such as the forest inventory, a fundamental procedure for monitoring production that allows the knowledge of the maximum potential of forests, and is essential for planning of harvesting and supply of timber. Conventional techniques for surveying forest production use traditional statistical methods (classical statistics), considering only the adoption of average values for decision making, not exploring the spatial correlations that may exist between the sample plots. So, a kind of geostatistical interpolator that allows defining the structure of spatial dependence of data is kriging, which together with the methodology of virtual samples, can become a viable alternative to obtain a variogram with acceptable modeling. In this way, the aim of this study was to use the methodology of virtual samples in the planning of the sampling of the forest inventory, in order to allow the determination of a number of parcels that can be established in the area to obtain productivity, without losing accuracy or increasing costs. The study area covers a planted area of 287.66 ha, belonging to Eucatex S / A, located in Itatinga, in the state of São Paulo. The volume dendrometric data (m³.ha-1) were obtained through inventories carried out by the company and were estimated in 32 permanent rectangular plots for continuous forest inventories (CFI) and 32 permanent rectangular plots plus 66 temporary plots for the pre-cut inventory (PCI). The following steps were performed with the CFI data for spatialization of the original data in the ArcGIS program: application of an univariate statistic on the variable volume. ha-1; generation of the experimental variogram; variogram adjustment; validation of the theoretical model; application of kriging; generation of productivity maps year by year. Subsequently, 47 virtual samples were inserted into the sampling network of continuous inventories, considering only the permanent plots (32 plots), 10 plots were previously selected for external validation; the geostatistical analysis occurred with the virtual samples plus the remaining permanent samples, totaling 69 plots. Comparing the methods, it was observed through cross-validation that the mean error and the correlation between observed and estimated values were improved by adding the virtual samples, allowing better adjustment of the variogram and obtaining favorable estimates. The validity of the methodology of insertion of the samples, called external validation, was verified by means of the average error, which was 6.8% in volume, in relation to the original forest inventory. In this way, the technique of insertion of virtual samples can be used, proving to be satisfactory for the planning of the next mesh for later geostatistical analysis, in plantations that have the same age. / CAPES: 1582107

O objetivo deste trabalho foi estimar o volume de madeira de um povoamento jovem de Pinus elliottii, localizado no litoral sudeste do Rio Grande do Sul, com imagens dos sensores LISS-III/ResourceSat-1 e TM/Landsat 5, comparando o desempenho destes para tal. Obtiveram-se imagens de setembro de 2010, mês coincidente com o inventário florestal feito na área de estudo. Os valores de reflectância espectral de superfície foram recuperados das imagens originais. Após o georreferenciamento, dos pixels coincidentes com a localização das unidades amostrais do inventário florestal foram extraídos os valores das reflectâncias nas quatro bandas espectrais equivalentes aos dois sensores, cujas respostas foram comparadas. Além das bandas espectrais foram utilizados os índices de vegetação (IV’s) SR, NDVI, SAVI, MVI e GNDVI. Também, foi proposto o ajuste destes IV’s originais pela idade do povoamento, os quais foram identificados por SR_i, NDVI_i, MVI_i e GNDVI_i. A aplicação do logaritmo nas bandas espectrais melhorou os valores dos coeficientes de correlação linear (r), à exceção do IVP, retornando valores entre 0,69 (IVP) a 0,83 (Verde) para o LISS-III e entre 0,68 (Vermelho) a 0,79 (IVM) para o TM; Com os IV’s o logaritmo melhorou os valores de r somente para os IV’s originais, retornando valores de r entre 0,77 (NDVI) a 0,84 (GNDVI) com o LISS-III e entre 0,73 (NDVI) a 0,82 (MVI) para o TM. Com os IV’s ajustados pela idade do povoamento a logaritimização não se mostrou necessária para melhorar a associação linear, retornando valores de r entre 0,79 (NDVI_i) a 0,82 (MVI_i) com o LISS-III e entre 0,74 (SR_i) a 0,80 (MVI_i) com o TM. Além disso, o ajuste pela idade aumentou o intervalo dinâmico dos IV’s ajustados, e, aparentemente, aumentou a sensibilidade nos povoamentos de maior volume. Diferenças significativas na associação linear entre os dados espectrais do TM e LISS-III com o volume só foram encontradas na banda equivalente do verde. Com dados TM, a equação melhor ajustada explicou 68% da variabilidade do volume; com dados LISS-III a equação explicou 72% da variabilidade. Estas equações geraram dois mapas de volume de madeira, onde as médias das estimativas obtidas com LISS-III estiveram dentro do intervalo de confiança da média do inventário florestal em 70% dos talhões considerados; para o TM a coincidência foi de 65% dos talhões. Conclui-se que os sensores LISS-III e TM apresentam alta similaridade e que a metodologia empregada pode ser utilizada para auxiliar no inventário florestal dos povoamentos jovens de P. elliottii na área de estudo principalmente pelo fato das estimativas obtidas pelas imagens cobrirem todo o talhão, ao passo que a amostragem do inventário florestal contempla menos de 2% da área. / The aim of this work was to estimate the wood volume of a young stand of Pinus elliottii, located on the southeastern coast of the state of Rio Grande do Sul, by imagery from LISS-III/ResourceSat-1 and TM/Landsat 5 sensors, comparing their performance for such. Images were obtained on September 2010, the month coincident with the forest inventory made in the study area. The surface spectral reflectance values were retrieved from the original images. After the georeferencing, the sampling units location from the forest inventory were used to select the pixels to extract the reflectance values on the four spectral bands equivalents for the two sensors, which answers were compared. In addition to the bands were used the Vegetation Indices (VI’s) SR, NDVI, SAVI, MVI and GNDVI. Also proposed was the adjusting of these original VI’s by the stand age, which ones were identified by SR_i, NDVI_i, MVI_i and GNDVI_i. The application of logarithm in the spectral bands improved the r values, with exception to NIR, achieving values between 0.69 (NIR) and 0.83 (Green) for LISS-III and between 0.68 (Red) and 0.79 (SWIR) for TM; With the VI’s, the logarithm improved the r values only for the original VI’s, returning r values from 0.77 (NDVI) to 0.84 (GNDVI) with LISS-III and r values from 0.73 (NDVI) to 0.82 (MVI) for TM. With the VI’s adjusted by stand age the logarithm was not necessary to improve the linear association, returning r values from 0.79 (NDVI_i) to 0.82 (MVI_i) with LISS-III and r values from 0.74 (SR_i) to 0.80 (MVI_i) with TM. Moreover, adjusting by age increased the dynamic range of the VI’s adjusted, and apparently increased the sensitivity in stands with larger volume. Significant differences in the linear association between TM and LISS-III spectral data with volume were just found on the green equivalent band. With TM data, the best fitted model explained 68% of the volume variability; with LISS-III data the model explained 72% of the variability. These models generated two wood volume maps, where the average of the estimates achieved with LISS-III were within the confidence level of the average from the forest inventory on 70% of the compartments considered; for TM the coincidence was on 65% of the compartments. It is conclude that the sensors LISS-III and TM presented high similarity and the methodology applied can be used to aid in forest inventory of young stands of P. elliottii in the study area mainly because the estimates obtained by the images cover the entire compartment, while the forest inventory sampling contemplates less than 2% of the area.

The Mississippi Institute for Forest Inventory (MIFI) is the only cost-effective large-scale forest inventory system in the United States with sufficient precision for producing reliable volume/weight/biomass estimates for small working circle areas (procurement areas). When forest industry is recruited to Mississippi, proposed working circles may overlap existing boundaries of bordering states leaving a gap of inventory information, and a remote sensing-based system for augmenting missing ground inventory data is desirable. The feasibility of obtaining acceptable cubic foot volume estimates from a Landsat-derived volume estimation model (Wilkinson 2011) was assessed by: 1) an initial study to temporally validate Landsat-derived cubic foot volume outside bark to a pulpwood top estimates in comparison with MIFI ground truth inventory plot estimates at two separate time periods, and 2) re-developing a regression model based on remotely sensed imagery in combination with available MIFI plot data. Initial results failed to confirm the relationships shown in past research between radiance values and volume estimation. The complete lack of influence of radiance values in the model led to a re-assessment of volume estimation schemes. Data outlier trimming manipulation was discovered to lead to false relationships with radiance values reported in past research. Two revised volume estimation models using age, average stand height, and trees per-acre and age and height alone as independent variables were found sufficient to explain variation of volume across the image. These results were used to develop a procedure for other remote sensing technologies that could produce data with sufficient precision for volume estimation where inventory data are sparse or non-existent.

Forests cover a large portion of the global land area and provide critical resources such as timber, food, and medicine in addition to playing a significant role in the global carbon cycle. As such, sustainable forest management practices are required to balance forest economies and climate change mitigation with other non-timber objectives. A key aspect of many sustainable forest management programs is forest monitoring, for which technological and methodological development has led to enhanced forest inventory (EFI) methods, many of which rely on remote sensing data from high-resolution light detection and ranging (LiDAR) and optical imagery. However, to date, current applications of EFI methods have mostly focused on timber attributes with limited research on non-timber attributes or analyses regarding multi-temporal monitoring, method scaling, or method transferability. The objective of this thesis is to expand applications of EFIs in monitoring and analysis through two distinct studies, first evaluating the utility of LiDAR-based EFI methods in multi-temporal silvicultural treatment assessment and secondly in the pre-harvest estimation of merchantable wood and non-merchantable wood left as logging residues. The first study evaluates a process that expands the sampling of fertilization treatment effects on forest stands to the wider treatment area by utilizing paired LiDAR blocks made up of raster cell estimates from a multi-temporal area-based model. Results showed promise for detecting treatment impacts on stand volume, biomass, and height and highlights the potential for the methods to be used as a means to rapidly expand analysis from sample plots to the entire treatment area. The second study focuses on the use of a hybrid area-based and individual tree EFI approach to model merchantable and non-merchantable forest wood volumes while exploring the scalability of these models to harvest blocks and the transferability to additional blocks without prior training. Results from this study indicated that models for both volume attributes are successfully scalable and transferable to harvest blocks. Overall, the research results presented in this thesis demonstrate the potential of enhanced forest inventory methods for the monitoring and assessment of timber attributes, such as wood volume or biomass, as well as alternative attributes, such as stand height, or non-merchantable wood volume, over multiple years. This work further demonstrates the potential for these methods to expand areas of assessment and increase prediction accuracies. / Graduate / 2022-08-17

The main study objective was to develop robust processing and analysis techniques to facilitate the use of small-footprint lidar data for estimating forest biophysical parameters measuring individual trees identifiable on the three-dimensional lidar surface. This study derived the digital terrain model from lidar data using an iterative slope-based algorithm and developed processing methods for directly measuring tree height, crown diameter, and stand density. The lidar system used for this study recorded up to four returns per pulse, with an average footprint of 0.65 m and an average distance between laser shots of 0.7 m. The lidar data set was acquired over deciduous, coniferous, and mixed stands of varying age classes and settings typical of the southeastern United States (37° 25' N, 78° 41' W). Lidar processing techniques for identifying and measuring individual trees included data fusion with multispectral optical data and local filtering with both square and circular windows of variable size. The window size was based on canopy height and forest type. The crown diameter was calculated as the average of two values measured along two perpendicular directions from the location of each tree top, by fitting a four-degree polynomial on both profiles. The ground-truth plot design followed the U.S. National Forest Inventory and Analysis (FIA) field data layout. The lidar-derived tree measurements were used with regression models and cross-validation to estimate plot level field inventory data, including volume, basal area, and biomass. FIA subplots of 0.017 ha each were pooled together in two categories, deciduous trees and pines. For the pine plots, lidar measurements explained 97% of the variance associated with the mean height of dominant trees. For deciduous plots, regression models explained 79% of the mean height variance for dominant trees. Results for estimating crown diameter were similar for both pines and deciduous trees, with R2 values of 0.62-0.63 for the dominant trees. R2 values for estimating biomass were 0.82 for pines (RMSE 29 Mg/ha) and 0.32 for deciduous (RMSE 44 Mg/ha). Overall, plot level tree height and crown diameter calculated from individual tree lidar measurements were particularly important in contributing to model fit and prediction of forest volume and biomass. / Ph. D.

Nontimber forest products (NTFPs) play an important role in the lives of people who rely on forests. An absence of data on the size of harvests, their location, and the economic value of NTFPs prevents effective management and full utilization by all stakeholder groups. We set out to measure one important NTFP sector -- the medicinal plant trade in the diverse deciduous forests of the eastern United States, by surveying licensed buyers of ginseng (Panax quinquefolius) in 15 states about purchasing of other untracked species. To combat potential coverage and non-response bias we created a place-based model that predicted the probability of purchasing non-ginseng medicinals based on buyer location and used this to build more robust estimates. This viable method for estimating NTFP output is a replicable system that can be applied in other regions and for other products. We reviewed the literature and hypothesized biophysical and socioeconomic factors that might contribute to the prevalence of non-ginseng purchasing, and tested them on the respondents using multinomial logistic regression. The significant variables were used in two-step cluster analysis to categorize respondents and non-respondents in high or low production areas. Volume was assigned to non-respondents based on respondent behavior within each cluster. Both were then summed to estimate total output. The results depict trade volume and prices paid to harvesters for 11 medicinal NTFP species. There was significant variation between products. Two species, black cohosh (Actaea racemosa) and goldenseal (Hydrastis canadensis), accounted for 72 percent of trade volume and 77 percent of the value paid to harvesters. The total first-order value for all species estimated was 4.3 million $USD. The discrepancy between point-of-sale and retail value implies room for increasing value for all stakeholders at the base of the supply chain. Harvests for most species were concentrated in the central Appalachian coalfields. We also sought to understand what motivated or deterred participation by conducting qualitative interviews with buyers and other stakeholders. Buyers were interested in knowing the size and value of the trade, but had concerns about losing access to the resource, which was rooted in past experience with land managers and policy-makers, and conflicting discourse between stakeholders about the state of the trade and of wild populations. Many institutional deliverables are not well matched with the realities or priorities of the traditional trade. We describe potential avenues for collaboration and reciprocity, including providing market research and certifying or providing technical support for sustainably wild harvested material in addition to ongoing support for cultivation. / PHD / Nontimber forest products (NTFPs) are sources of sustenance and livelihood for people around the world. This broad category includes parts of plants such as barks, roots, and fruits, and fungi harvested for food, medicine, decoration, for use in crafts and cultural and spiritual ceremonies. They are harvested for personal use, and sold into local and global supply chains. Commercially harvested NTFPs have a dual nature. They have the potential for providing income without having the kind of large-scale disturbance caused by logging or other more impactful extractive industry. At the same time, most forests are not managed for NTFP production, and the ecological impacts of most NTFP activity are difficult to assess. Habitat loss and harvesting pressure has led to the monitoring and regulation in the trade of one iconic medicinal NTFP American ginseng (Panax quinquefolius) For the majority of NTFPs, the scale, value and distribution of the trade is unknown, presenting a barrier to effective management and institutional investment in the trade. We sought to better understand one important NTFP supply chain, the trade in medicinal plants occurring in eastern deciduous forests using a voluntary survey program. To accomplish this, we surveyed and interviewed registered ginseng buyers in 15 states about the other products they purchase. This dissertation is divided into three parts with three different objectives. The first is to describe the trade in medicinal NTFPs from eastern forests. This includes what species are being harvested, how harvests are distributed throughout the study area, the value of surveyed species to producers, and market structure close to the point of sale. We found that the majority of the trade was taking place in central Appalachia. The majority of the trade in terms of value and total output was concentrated in two species, goldenseal (Hydrastis canadensis) and black cohosh (Actaea racemosa). The second chapter seeks to create a replicable method for projecting total volume for the most commonly harvested species, including predicting the buying of the majority of respondents who did not participated. We created a model that predicted the likelihood of a respondent purchasing non-ginseng based on characteristics of their location associated with the trade. The third chapter uses interviews with buyers and other participants to explore how to improve participation in NTFP studies and make the results more useful for stakeholders.

Este estudo foi conduzido com objetivo de avaliar o emprego de equações hipsométricas em cerrado sensu stricto, focalizando o método de amostragem dos dados de relação hipsométrica. Para isso utilizou-se cinco amostras de 1000 m² (20x50m), em uma área de cerrado sensu stricto localizado no sul do Tocantins. Foram avaliados quarenta modelos hipsométricos e cinco métodos de amostragem com área relativa a área total. Nessa avaliação, além da análise de distribuição dos resíduos, erro padrão residual e coeficiente de determinação, foram adotados os critérios estatísticos: delineamento inteiramente casualizado no esquema de parcelas subdivididas, teste Dunnett, desvio médio absoluto, desvio padrão das diferenças, soma dos quadrados dos resíduos relativos, resíduo percentual, raiz quadrada do erro médio, desvio padrão das diferenças absolutas e correlação linear múltipla. Concluiu-se que a relação funcional Ln (h)=f[Ln(N/d);Ln(dq/d);1/d; Ln(G)] foi a melhor opção para se caracterizar a relação hipsométrica em inventários florestais de cerrado sensu stricto e que deve ser ajustada com dados obtidos em uma área com 40 % da área total da parcela. / This study aimed to avaliate the hypsometric equations utilization in cerrado sensu stricto, focusing on the sampling method of hypsometric relationship data. To this end, five samples of 1000m² (20x50m) were used, in a cerrado sensu stricto area situated in south Tocantins. Forty hypsometric models and five sampling methods were used with relative area to total area. In this avaliation, besides the waste distribution analysis, standart error of waste and coefficient of determination, this statistc criteria were also adopted: completely randomized design in a split plot scheme, Dunett test, absolute mean deviation, standart deviation of differences, squares sum of relative residues, percentage residue, medium error square root, standart deviation of absolutes differences and multiple linear correlation. It was concluded that the funcional relation Ln (h)=f[Ln(N/d);Ln(dq/d);1/d; Ln(G)] was the best option to characterize the hyposometric relationship in forest inventory of cerrado sensu stricto and it must be ajusted with the obtained data in a 40% area of the plot total area.

O bioma Cerrado possui uma rica flora e apresenta alto nível de endemismo. Em relação ao contexto estadual, o Tocantins está situado na zona de transição geográfica entre o Cerrado e Amazônia. O objetivo desta pesquisa foi avaliar a florística, fitossociologia e aplicação de técnicas de amostragem para levantamentos florestais, tais como, tamanho e forma de parcelas, intensidade e processos amostral em uma área de Cerrado stricto senso. Por meio de um censo, em uma área de 6,7 hectares, foram identificados indivíduos arbóreos com limite de inclusão de circunferência a altura do peito (CAP) maior ou igual a 15 cm, assim também tiveram sua altura total medida. Foram amostrados 15.434 indivíduos, pertencentes a 78 espécies, 72 gêneros e 37 famílias das quais predominaram as famílias Myrtaceae e Fabaceae. A densidade total da área e área basal foram, respectivamente, de 2.303 ind.ha-1 e 14,07 m².ha-1. Na área de estudo as espécies que se destacaram em relação aos parâmetros fitossociológicos foram: Myrcia splendens, Astronium fraxinifolium, Magonia pubescens, Qualea parviflora, Protium heptaphyllum, Qualea multiflora, Vatairea macrocarpa, Tachigali aurea e Byrsonima stipulacea. Após essa etapa foram definidas variações das simulações de amostragem, considerando as combinações: dois processos de amostragem, aleatório e sistemático, diferentes tamanhos de parcelas (250, 500, 1000, 1500 m²) e formas (quadrada, retangular e circular) com as diferentes intensidades de amostragem (2,5, 5, 7,5 e 10%) avaliando três variáveis florestais: volume, área basal e número de árvores. De modo geral, o aumento da intensidade amostral apresentou estreita relação com a melhoria das estimativas das variáveis. No entanto, verificou-se que ao utilizar parcelas de 250 m², para as variáveis de interesse, apresentaram tendências de menores valores dos erros amostral e real, ao contrário do que ocorre em parcelas de tamanhos maiores. Portanto, parcelas de 250 m² tendem a captar de forma mais precisa a variação da distribuição espacial das variáveis de interesse, produzindo resultados mais confiáveis do que ao utilizar parcelas de 1.000 e 1.500 m², sob uma mesma intensidade de amostragem. De modo que, utilizando uma intensidade superior a 5%, com parcelas de 250 e 500 m², obteve erro amostral menor que 20%, resultado aceitável para área de matas nativas. Concluindo que, com base no exposto, é recomendável que, para a estimativa de variáveis florestais, sejam utilizadas parcelas pequenas, 250 ou 500 m² e intensidade amostral variável em função dos recursos de tempo e financeiros disponíveis. / The Cerrado biome has a rich flora and presents a high level of endemism. In relation to the state context, the Tocantins is situated in the geographical transition zone between the Cerrado and the Amazon. The objective of this research was to evaluate floristic, phytosociology and application of sampling techniques for forest surveys, such as size and shape of plots, intensity and sampling processes in an area of Cerrado stricto senso. Through a census, in an area of 6.7 hectares, arboreal individuals with a limit of inclusion of chest circumference (CAP) greater than or equal to 15 cm were identified, as well as their total height measured. We sampled 15,434 individuals belonging to 78 species, 72 genera and 37 families of which the families Myrtaceae and Fabaceae predominated. The total density of the area and basal area were, respectively, 2,303 ind.ha-1 and 14,07 m².ha-1. In the study area the species that stood out in relation to phytosociological parameters were: Myrcia splendens, Astronium fraxinifolium, Magonia pubescens, Qualea parviflora, Protium heptaphyllum, Qualea multiflora, Vatairea macrocarpa, Tachigali aurea and Byrsonima stipulacea. After this step, variations of the sampling simulations were defined, considering the combinations: two sampling processes, random and systematic, different sizes of plots (250, 500, 1.000, 1.500 m²) and shapes (square, rectangular and circular) with the different sampling intensities (2,5, 5, 7,5 and 10%) evaluating three forest variables: volume, basal area and number of trees. In general, the increase in sample intensity showed a close relationship with the improvement of the estimates of the variables. However, it was verified that when using plots of 250 m², for the variables of interest, they presented tendencies of smaller values of the sampling and real errors, unlike what occurs in plots of larger sizes. Therefore, plots of 250 m² tend to more accurately capture the variation of the spatial distribution of the variables of interest, producing more reliable results than using plots of 1,000 and 1,500 m², under the same sampling intensity. So, using an intensity of more than 5%, with plots of 250 and 500 m², obtained a sampling error of less than 20%, an acceptable result for native forest area. Based on the above, it is recommended that, for the estimation of forest variables, small plots, 250 or 500 m² are used, and the sampling intensity should be as great as the available time and money resources allow

O manejo florestal madeireiro é uma atividade que promove a manutenção da cobertura florestal em áreas de floresta primária no Brasil. Atualmente, as técnicas de manejo estão sendo aperfeiçoadas pelo desenvolvimento de novas tecnologias da área de geoprocessamento, como o Sistema Global de Posicionamento por Satélite (GNSS), Lidar (Ligth detection and ranging) aerotransportado (ALS) e Aeronaves Remotamente Pilotadas (ARPs). O objetivo geral deste trabalho é apresentar os princípios do manejo florestal de precisão aplicados para a região amazônica e avaliar a capacidade dos dados do Lidar na redução da intensidade amostral no inventário florestal. Para tal, foi utilizada uma área demonstrativa de manejo florestal de precisão localizada no campo experimental da Embrapa, no município de Rio Branco, Acre. O estudo foi desenvolvido em uma área contínua de 800 hectares, com presença de floresta primária do tipo umbrófila, aberta, com presença de palmeiras, bambu e manchas de floresta alta. Foram realizadas duas coletas de dados nesta área: o censo florestal das árvores com DAP >= 40 cm, com o qual calculou-se a área seccional de cada árvore; e o voo Lidar feito a uma altitude de 600 metros, com footprint de 30 cm e densidade de 14 pts.m2. A partir dos dados Lidar foram extraídas os modelos digitais de superfície (MDS), do terreno (MDT) e altura (MAD), e as métricas Altmd (altura média do dossel), rugosidade (desvio padrão da altura média do dossel), Altdossel (abertura do dossel a 15 metros), LAI (índice de área foliar) e LAIsub (LAI do sub-bosque - faixa entre 5 a 12 metros de altura). No capítulo 01, os dados foram analisados de forma a demonstrar a aplicação do Lidar no aperfeiçoamento das atividades técnicas do manejo florestal na amazônia, sendo elas: (i) macroplanejamento da Área de Manejo Florestal (AMF); (ii) microplanejamento do terreno e hidrografia da Unidade de Produção Anual (UPA); (iii) censo e amostragem florestal; (iv) planejamento da infraestrutura de exploração; e (v) monitoramento. Na análise dos dados do capítulo 02, foram feitas: (i) estimativa dos atributos estruturais derivados do inventário de campo e da nuvem de retornos Lidar para três tamanhos de célula; (ii) correlação de Pearson entre os atributos do campo e do dossel derivados do Lidar; (iii) análise de agrupamento para formação dos estratos pelo método de Ward; (iv) validação (ANOVA) e caracterização dos estratos (PCA); e (v) estimativa de redução da intensidade amostral por meio de uma simulação computacional. Como resultado, os mapas gerados mostram a acurácia e qualidade dos dados do Lidar para o mapeamento de unidades de produção anual dentro da área de manejo florestal, microzoneamento da topografia, modelagem da rede de drenagem, identificação de áreas de relevo acidentado, delimitação da APP e planejamento da infraestrutura de exploração respeitando as condições ambientais e potecial madeireiro da área de estudo. A altura média do dossel da floresta (Altmd), obtida com o Lidar, apresentou a maior correlação (r = 0,74) com a área basal e foi utilizada para estratificar a vegetação em quatro padrões de floresta, com diferença significativa entre eles para a variável de campo. A estratificação com a Altmd distinguiu bem a floresta quanto ao seu gradiente de variação estrutural e perfil de densidade da vegetação. A simulação do inventário estratificado versus o inventário inteiramente casualizado evidenciou a capacidade da variável Lidar Altmd em reduzir o número de parcelas em até 41% quando utilizado 4 estratos para uma mesma incerteza relativa de 10%. O uso de uma única métrica de dossel, derivada do Lidar, foi capaz de estratificar uma área de floresta tropical primária, além de gerar informações adicionais, como o índice de área foliar do sub-bosque e o modelo do terreno que podem auxiliar na tomada de decisão para o manejo, conservação e monitoramento de florestas tropicais. / Timber forest management is an activity that promotes the maintenance of forest cover in primary forest areas in Brazil. Currently, management techniques are being improved by the development of new geoprocessing technologies such as the Global Positioning Satellite System (GNSS), Airborne Lidar Scanning (ALS) and Remotely Piloted Aircraft (ARPs). The general objective of this work is to present the principles of precision forest management applied to the Amazon region and evaluate the reduction of sampling intensity in the forest inventory from vegetation stratification using Lidar variables. For this, was used a demonstration area of precision forest management located in the experimental field of Embrapa, in Rio Branco, Acre. The study was located in a continuous area of 800 hectares, in open ombrphylous forest with presence of palms, bamboo and dense forest portions. Two data collections were carried out in this area: the census inventory of trees with DBH >= 40 cm, which the sectional area of each tree was calculated; and the Lidar flight made at an altitude of 600 meters, with footprint of 30 cm and density of 14 pts.m2. From the Lidar data were processed the digital surface models (DSM), terrain (DTM) and height (CHM), CHmean (average canopy height), roughness (standard deviation of the canopy), CHopenness (canopy openness of 15 meters), LAI (leaf area index) and LAIunder (LAI between 5 to 12 meters of height). In chapter 01, the data were analyzed in order to demonstrate the application of Lidar to improve the technical activities of the forest management in the Amazon, being: (i) macroplanning of the forest management area (AMF); (ii) micro-planning of the land and hydrography of the annual production unit (UPA); (iii) forest census and sampling; (iv) exploration infrastructure planning; and (v) monitoring. The analysis performed on the data of chapter 02 were: (i) estimation of the structural attributes derived from the field inventory and of the return cloud Lidar for three cell sizes; (ii) Pearson correlation between the field and canopy attributes derived from the Lidar; (iii) cluster analysis for classify strata by the Ward method; (iv) validation (ANOVA) and characterization of stratas (PCA); and (v) reduction of sample estimation intensity by a computer simulation. As result, the generated maps show the accuracy and quality of the Lidar data for mapping of annual production units within the area of forest management, microzoning of the topography, drainage network modeling, identification of rugged relief areas, APP boundary and planning the exploration infrastructure respecting the environmental conditions and timber potential of the study area. The average height of the forest canopy (CHmean), obtained with the Lidar, presented the highest correlation (r = 0.74) with the basal area and was used to stratify the vegetation in four forest patterns, with significant difference between them for the field variable. The stratification with CHmean distinguished the forest well for its structural variation gradient and vegetation density profile. The simulation of the stratified inventory versus the completely randomized inventory evidenced the ability of the Lidar Altmd variable to reduce the number of plots by up to 41% when using 4 strata for the same relative uncertainty of 10%. The use of a single canopy metric derived from Lidar was able to stratify an area of primary rainforest, in addition to generating additional information such as understory leaf area index and the terrain model that can assist in decision making for management, conservation and monitoring of tropical forests.

A aplicação da tecnologia LASER aerotransportado (ALS) para realização de inventários florestais, tem se apresentado como excelente alternativa para a área de planejamento florestal, principalmente pelos ótimos resultados em termos de precisão das estimativas, pelas facilidades de uso e demais produtos e benefícios advindos do sobrevôo com o LASER. A evolução e o menor custo das tecnologias GPS e Sistemas de Medição Inercial têm sido o principal fator de sucesso para a aplicação da tecnologia ALS. Vários trabalhos de análise da tecnologia LASER aerotransportado, em inventários florestais, alguns até mesmo em escalas comerciais (NAESSET, 2007), têm sido realizados principalmente na Europa e no Canadá. Os resultados têm sido muito atraentes, dentre os quais se destacam as estimativas de volume e de área basal que têm apresentado erros de no máximo 8,4%, dependendo das configurações da área amostrada. Sendo assim, este trabalho teve por objetivo analisar o uso da tecnologia ALS para a realização de inventários florestais em níveis de parcela e talhão em plantios clonais de Eucalyptus sp, no sul do estado da Bahia. Para tanto foram realizados levantamentos de campos que permitiram a estimação de parâmetros como área basal, altura de árvores média e das dominantes e volume, em parcelas circulares de treze metros de raio, nas quais foram coletados o diâmetro de todas as árvores e a altura de uma a cada sete árvores da parcela. A área sobrevoada para coleta dos dados LASER foram duas faixas de aproximadamente 2x20km. Os dados LASER foram processados para se obter os percentís das observações ALS nos níveis 10 (f_h10), 30 (f_h30), 50 (f_h50), 70 (f_h70) e 90 (f_h90), bem como a densidade de pontos nos respectivos percentís (f_p10, f_p30, f_p50, f_p70 e f_p90), e a altura média (f_havg) e o desvio padrão (f_hstd) desses pontos. Essas estatísticas foram utilizadas em modelos de regressão para estimar diâmetro médio, altura média, altura dominante, área basal e volume das parcelas amostradas. Para o volume, uma avaliação exploratória de diferentes combinações de variáveis permitiu a definição das relações mais promissoras e a utilização dessas variáveis mais promissoras no ajuste de modelos já consagrados na área de biometria e inventário florestal. As observações ALS que melhor ajustaram diâmetro médio foram f_h30 e f_p30, com R²=0,88 e RQEM%=0,0004; para altura média, f_h10 e f_h90 geraram boas estimativas, com R²=0,94 e RQEM%=0,0003, enquanto que para altura dominante, as melhores estimativas foram obtidas com f_h90, apresentando R²=0,96 e RQEM%=0,0003; e para área basal, os melhores ajustes usaram idade, f_h10 e f_havg, sendo R²=0,92 e RQEM%=0,0016. No caso de volume, os dois melhores modelos exploratórios apontam para o uso de idade, f_h30 e f_p90, em ambos os casos, e ambos com R² entre 0,94 e 0,95 e RQEM% entre 0,002 e 0,003. Já, dentre os modelos biométricos testados, os melhores foram os de Schumacher ajustado com idade e f_h90; Clutter ajustado com idade, f_havg e f_h70; e de Buckman ajustado com idade, f_havg e f_h10. / The application of the airborne laser scanning (ALS) technology for forest inventories execution, have been presented as an excellent alternative to the forest planning area, particularly by the excellent results in terms of accuracy of the estimates, by the facilities of usage and other products and benefits derived from LASER overflight. The technology evolution and lower cost for GPS and Inertial Measurement Units have been the main factor of the success for ALS technology application. Several studies of ALS technology analysis in forest inventories, some even in commercial scales (NAESSET, 2007), have been conducted mainly in Europe and Canada. The results have been very attractive, among which there are the volume and basal area estimates which have made errors of up to 8.4% depending on the settings of the sampled area. Thus, this study aimed to examine the use of the ALS technology for forest inventories executions at plot and stands levels in clonal Eucalyptus sp plantations in the south of Bahia state. Field surveys were conducted to provide the parameters estimation such as diameter, tree heights, basal area and volume in circular plots of thirteen-meter radius, which were the diameter of all trees and height of a the seven trees of each plot. The overflown areas for LASER data collection were two bands of approximately 2x20km. LASER data were processed to obtain the percentiles of the ALS observations in the following levels 10 (f_h10), 30 (f_h30), 50 (f_h50), 70 (f_h70) e 90 (f_h90), and 90 (f_h90) and the density of points in the respective percentiles (f_p10, f_p30, f_p50, f_p70 and f_p90), the average height of the points (f_havg) and the standard deviation (f_hstd). These statistics were used in the regression models to estimate mean diameter, mean height, dominant height, basal area and volume of the sampled plots. For the volume, an exploration of different combinations of the variables supported the definition of the most promising relations and most promising use of these variables in the set of models already established in the biometrics and forest inventory area.The ALS observations that better fit to the average diameter were f_h30 and f_p30, resulting in a R²=0.88 and RQEM%=0.0004; for the average height, f_h10 and f_h90 generate good estimates, having R²=0.94 and RQEM%=0. 0003, therefore for the dominant height, the best estimates were obtained with f_h90, showing R²=0.96 and RQEM%=0.0003. For the basal area, the best fit used age, f_h10 and f_havg, presenting a R²=0.92 and RQEM%=0.0016. In the volume case, the two best exploratory models point to the use of age, f_h30 and f_p90, both with R ² between 0.94 and 0.95 and RQEM% between 000.2 and 000.3. Among the biometric tested models, the best were Schumacher fitted by age and f_h90; Clutter fitted by age, f_havg and f_h70; Buckman fitted by age, f_havg and f_h10.