Light Detection and Ranging, or LIDAR, has become an effective ancillary tool to extract forest inventory data and for use in other forest studies. This work was aimed at establishing an effective methodology for using LIDAR for tree count in a stand of Eucalyptus sp. located in southern Bahia state. Information provided includes in-flight gross data processing to final tree count. Intermediate processing steps are of critical importance to the quality of results and include the following stages: organizing point clouds, creating a canopy surface model (CSM) through TIN and IDW interpolation and final automated tree count with a local maximum algorithm with 5 x 5 and 3 x 3 windows. Results were checked against manual tree count using Quickbird images, for verification of accuracy. Tree count using IDW interpolation with a 5x5 window for the count algorithm was found to be accurate to 97.36%. This result demonstrates the effectiveness of the methodology and its use potential for future applications.

Resumo -O objetivo deste trabalho foi avaliar a possibilidade de se estimar o diâmetro à altura do peito (DAP) com os dados de altura e de número de árvores derivados do escâner a laser aerotransportado (LiDAR, "light detection and ranging"), e determinar o volume de madeira de talhão de Eucalyptus sp. a partir dessas variáveis. O número total de árvores detectadas foi obtido com uso da filtragem de máxima local. A altura de plantas estimada pelo LiDAR apresentou tendência não significativa à subestimativa. A estimativa do DAP foi coerente com os valores encontrados no inventário florestal; porém, também mostrou tendência à subestimativa, em razão do comportamento observado quanto à altura. A variável número de fustes apresentou valores próximos aos observados nas parcelas do inventário. O LiDAR subestimou o volume total de madeira do talhão em 11,4%, em comparação ao volume posto na fábrica. A tendência de subestimação da altura das árvores (em média, cerca de 5%) impactou a estimativa do volume individual de árvores e, consequentemente, a do volume do talhão. No entanto, é possível gerar equações de regressão que estimam o DAP com boa precisão, a partir de dados de altura de plantas obtidos pelo LiDAR. O modelo parabólico é o que possibilita as melhores estimativas da produção volumétrica dos talhões de eucalipto.Termos para indexação: Eucalyptus, inventário florestal, LiDAR, modelos biométricos, sensoriamento remoto. Determining timber volume of eucalyptus stands by airborne laser scanningAbstract -The objective of this work was to evaluate the possibility of estimating the diameter at breast height (DBH) with tree height and number data derived from airborne laser scanning (LiDAR, light detection and ranging) dataset, and to determine the timber volume of an Eucalyptus sp. stand from these variables. The total number of detected trees was obtained using a local maxima filtering. Plant height estimated by LiDAR showed a nonsignificant tendency to underestimation. The estimate for DBH was coherent with the results found in the forest inventory; however, it also showed a tendency towards underestimation due to the observed behavior for height. The variable number of stems showed values close to the ones observed in the inventory plots. LiDAR underestimated the total timber volume in the stand in 11.4%, compared to the total volume delivered to the industry. The underestimation tendency of tree height (5% mean value) impacted the individual tree volume estimate and, consequently, the stand volume estimate. However, it is possible to obtain regression equations that estimate DBH with good precision, from the LiDAR plant height derived data. The parabolic model is the one that provides the best estimates for timber volumetric yield of eucalyptus stands.

This study constructed a fi re risk map for the Serra de São Domingos Municipal Park (SSDMP), southern Minas Gerais Sate, Brazil, which harbors Atlantic Forest remnants and endangered species. Geo-processing techniques were used for producing a preliminary risk map for altimetry (a), land slope (e), slope orientation (d), land-use/cover (u) and infl uence of roads and buildings (i). After, the risk maps were overlaid to produce a structural fi re index (SFI)-based risk map for the Park. The SFI was calculated by using the formula SFI = 0,35i + 0,30u + 0,15d + 0,10a + 0,10e. The risks classes were classifi ed as low (0.0-0.9), moderate (1.0-1.9), high (2.0-2.9), very high (3.0-3.9) and extreme (4.0-5.0). All data were processed with 2.5 m base spatial resolution by using the ArcView GIS. According to the SFI calculated, the SSMP area can be divided into the following fi re risk zones: Low (0.93%), Moderate (61.77%), High (31.32%), Very High (4.79%) and Extreme (1.19%). The main risk factor is due to the infl uence of roads and buildings and most fi res start due to anthropogenic causes. The low and moderate risk classes comprehend most of the rainforest area. Clearings and grasslands fi t mainly the High risk class. The most vulnerable area of SSDMP was the Northern area bordering pasture, crops and eucalypt fi elds. The SFI map can be a valuable tool for elaborating a fi re prevention plan in a small conservation unit when few climate and fi re occurrence data are available.Key words: Atlantic Forest, conservation unit, fi re prevention, on-the-screen visual image interpretation. Baixo (0,9), Moderado (1,[0][1]9), Alto (2,[0][1][2]9), Muito Alto (3,[0][1][2][3]9) e Extremo (4,(0)(1)(2)(3)(4)(5)0 ZONEAMENTO DE RISCO DE INCÊNDIOS PARA O PARQUE MUNICIPAL DA SERRA DE SÃO DOMINGOS, POÇOS DE CALDAS, MG RESUMO: Objetivou-se, com este estudo, produzir um mapa de risco de incêndio para o Parque Municipal da Serra de São Domingos (PMSSD), sul de Minas Gerais, Brasil, que abriga remanescentes de Mata Atlântica e espécies ameaçadas de extinção. Técnicas de Geoprocessamento foram utilizadas para produzir mapas de risco preliminares para altimetria (a), declividade do terreno (e), uso e cobertura do solo (u), orientação de encosta (d) e infl uência de estradas e construções (i). Os mapas foram integrados, gerando um mapa baseado no índice estrutural de risco de incêndio (SFI) calculado pela fórmula SFI = 0,35i + 0,30u + 0,15d + 0,10 a + 0,10e. As classes de risco foram defi nidas como

ABSTRACT:In view of the need to improve the planning of timber harvest and transportation, with both activities being the most infl uential in determining the fi nal cost of timber delivered to the mill yard, this work aims to develop a new methodological proposal using operations research and geotechnology tools in order to determine optimal locations for log stacking and also the amount of timber to be allocated to each selected stack. Analysis was performed using two software applications, geographic information system (GIS) and operations research (OR). GIS spatial analyses were based on layers of the study site, which is a property owned by Votorantim Celulose e Papel, located in the municipality of São José dos Campos, in order to obtain three variables: degree of diffi culty in operating forestry equipment, degree of diffi culty in log stacking, and distance between log stacks and existing roadways. To obtain these variables, layers containing information on terrain inclination and existing roadways were combined in another analysis named weighted overlay. Results were then fi ltered and inserted into an operations research environment for maximization of the timber volume in each selected stack. With results obtained from the geographic information system, 80 potential sites were selected for log stacking. By using operations research, 59 of these sites were ruled out, a 73% reduction in the number of potential sites, with only 21 sites remaining as potentially optimal for log storage. For each of these 21 sites, an optimal amount of timber was determined to be allocated to each one of them.Key words: Geographic information system, linear programming, log stacking. METODOLOGIA PARA PLANEJAMENTO DAS PILHAS DE MADEIRA UTILIZANDOGEOTECNOLOGIA E PESQUISA OPERACIONAL RESUMO: Verifi cando a necessidade de aperfeiçoar o planejamento da colheita e transporte de madeira, já que estas atividades são as que mais infl uenciam no custo fi nal da madeira posta em fábrica, neste trabalho, objetivou-se desenvolver uma nova proposta metodológica que utiliza ferramentas de geotecnologia e pesquisa operacional visando à determinação de melhores locais para o empilhamento de madeira e a quantidade de madeira alocada em cada pilha selecionada. As análises foram feitas, utilizando dois softwares de sistema de informação geográfi ca (SIG) e de pesquisa operacional (PO), respectivamente. As análises espaciais no

RESUMO:O presente trabalho foi realizado com o objetivo de analisar a influência da idade na detecção automática de árvores em talhões de Eucalyptus sp. por meio de dados LIDAR. Foram analisados 3 talhões com as idades de 3, 5, e 7 anos. Esses talhões tiveram os dados da nuvem de pontos do LIDAR referentes ao primeiro retorno, divididos em dois estratos verticais, o que gerou duas classes: Classe 1 (nuvem de pontos para toda a vegetação) e Classe 2 (nuvem de pontos para a vegetação acima de 10 metros). Os resultados da detecção do número de fustes para as duas classes foram comparados com o censo da área por meio de contagem visual em uma imagem de alta resolução espacial e com dados de inventário florestal. Na comparação com o censo, encontrouse pouca diferença entre as idades para o número de fustes para a Classe 1, sendo mais indicado para as idades de 3 e 5 anos e a Classe 2, apesar de se observar uma tendência de subestimativa dos valores, é mais indicada para a idade de 7 anos. Quando se comparou com os dados do inventário florestal, observou-se uma coerência entre o número de fustes nos dois estratos verticais, desta forma o método proposto mostrou-se compatível com o inventário florestal para a intensidade amostral testada, para a obtenção da variável número de fustes. INFLUENCE OF Eucalyptus sp. STAND AGE ON TREE COUNTING WITH LIDAR DATAABSTRACT: The objective of this work was to determine the influence of stand age on the automatic detection of Eucalyptus sp. trees using LIDAR datasets. Three different stands 3, 5 and 7 years old were analyzed. The LIDAR cloud point data of the first return was split into two datasets: Class 1 (points for all vegetation), Class 2 (points for vegetation above 10m). Results for obtaining the number of stems for each dataset were compared to the census of the area, which was done by visual interpretation using an auxiliary high spatial resolution remote sensing image, and to forest inventory estimates. In comparison to the census data, tree counting using Class 1 dataset agreed well for all considered ages, with best results achieved in 3 and 5 year old stands. On the other hand, Class 2 biased toward underestimated values. The best results for this class were verified in 7 year old stands. When compared to the forest inventory data, this methodology proved to be more efficient. The number of stems derived from the forest inventory was biased towards overestimation. In order to achieve better estimates using forest inventory data, an intensification of the sampling procedure would be necessary.