EVALUATION OF OPTIMAL ECOLOGICAL TOURISM ROUTES OBTAINED VIA GOOGLE EARTH SOFTWARE IN AN ENVIRONMENTAL PROTECTION AREA

Ecological tourism stands out as an economic activity that can be reconciled with nature conservation. Such activities have been carried out in several conservation units in Brazil. However, for satisfactory implementation, it is necessary to effectively plan the activities to be conducted, places to be visited, and paths to reach those places. In this context, we aimed to assess whether Google Earth software can assist in the expansion of the plan to use these areas for ecotourism, especially the routes that may be taken by tourists within the conservation unit. For this purpose, tourist interest sites were defined in the State Environmental Protection Area of Rio Pandeiros in the northern region of the state of Minas Gerais. The shortest routes between the pairs of locations obtained using Google Earth and QGIS software were evaluated. Additionally, it was necessary to perform vectorization and classification of all roads in the area. The lengths of the paths obtained were compared using a method identity test. The results showed that for most routes, Google Earth showed longer paths than QGIS. It can be concluded that for the purpose of ecotourism, precise planning should consider the vectorization of roads in areas with many rural roads

Management Recommendation Generation for Areas Under Forest Restoration Process through Images Obtained by UAV and LiDAR

Evaluating and monitoring forest areas during a restoration process is indispensable to estimate the success or failure of management intervention and to correct the restoration trajectory through adaptive management. However, the field measurement of several indicators in large areas can be expensive and laborious, and establishing reference values for indicators is difficult. The use of supervised classification techniques of high resolution images, combined with an expert system to generate management recommendations, can be considered promising tools for monitoring and evaluating restoration areas. The objective of the present study was to elaborate an expert system of management recommendation generation for areas under restoration, which were monitored by two different remote sensors: UAV (Unmanned Aerial Vehicle) and LiDAR (Light Detection and Ranging). The study was carried out in areas under restoration with about 54 ha and five years of implementation, owned by Fibria Celulose S.A. (recently acquired by Suzano S.A.), in the southern region of Bahia State, Brazil. We used images from Canon S110 NIR (green, red, near infrared) on UAV and LiDAR data compositions (intensity image, digital surface model, digital terrain model, normalized digital surface model). The monitored restoration indicator entailed land cover separated into three classes: Canopy cover, bare soil and grass cover. The images were classified using the Random Forest (RF) and Maximum Likelihood (ML) algorithms and the area occupied by each land cover classes was calculated. An expert system was developed in ArcGIS to define management recommendations according to the land cover classes, and then we compared the recommendations generated by both algorithms and images. There was a slight difference between the recommendations generated by the different combinations of images and classifiers. The most frequent management recommendation was “weed control + plant seedlings” (34%) for all evaluated methods. The image monitoring methods suggested by this study proved to be efficient, mainly by reducing the time and cost necessary for field monitoring and increasing the accuracy of the generated management recommendations

Econometric analysis of sawn timber production in Brazil

ResumoEstudos que objetivam analisar o mercado madeira serrada no Brasil merecem destaque por fornecerem orientações sobre sua tendência. Após o avanço no uso de painéis de madeira, o mercado sofreu influências por esse substituto, se fazendo necessárias análises econométricas para dimensionar e planejar a produção, diminuindo riscos e incertezas de comercialização. Esse mercado é dividido em madeiras de não coníferas e coníferas, que contribuem atualmente com 62% e 38% do mercado, respectivamente. Com base em uma série temporal anual da produção brasileira de madeira serrada de não coníferas e coníferas no período de 1961 a 2009, publicada pela Food and Agriculture Organization (FAO, 2011), o presente trabalho objetivou avaliar a metodologia Box & Jenkins (Box; Jenkins, 1976) para realizar previsões da produção desse mercado. Os modelos foram avaliados com base nos critérios de Akaike e Schwarz, na significância dos coeficientes, no princípio de parcimônia e no comportamento dos resíduos. Pelos resultados, conclui-se que o modelo autorregressivo de média móvel (ARIMA) (2,1,1) foi adequado para prever a produção de madeira serrada de não coníferas, e o modelo ARIMA (1,1,1) para prever a produção de madeira serrada de coníferas. A metodologia pode ser utilizada para previsão desse mercado. AbstractEconometric analysis of sawn timber production in Brazil. Studies that aim to analyze the lumber market in Brazil are noteworthy for providing guidance on its trend. After advance in wood panels using the market has been influenced by this replacement, and it was necessary an econometric analysis to scale and plan production, reducing risks and uncertainties. Such market is divided into non-coniferous woods and conifers, which currently contribute to 62% and 38% of the market, respectively. Based on an annual time series of non-coniferous and coniferous sawn timber Brazilian production in the 1960 to 2009 period, published by the Food and Agriculture Organization (FAO, 2011),the present research aimed to evaluate the methodology Box & Jenkins (BOX; JENKINS, 1976) to forecast the production of this market. The models were evaluated based on the Akaike and Schwarz criteria, at the coefficients significance, at the parsimony principle and at the waste behavior. According to results, the moving average auto-regressive model (ARIMA) (2,1,1) was adequate to predict the non-coniferous sawn timber production and the ARIMA (1,1,1) model to predict the conifers sawn wood production. The methodology can be used for such market prediction.Keywords: Lumber production; time series; Box & Jenkins methodology.AbstractStudies that aim to analyze the lumber market in Brazil are noteworthy for providing guidance on its trend. After advance in wood panels using the market has been influenced by this replacement, and it was necessary an econometric analysis to scale and plan production, reducing risks and uncertainties. Such market is divided into non-coniferous woods and conifers, which currently contribute to 62% and 38% of the market, respectively. Based on an annual time series of non-coniferous and coniferous sawn timber Brazilian production in the 1960 to 2009 period, published by the Food and Agriculture Organization (FAO, 2011),the present research aimed to evaluate the methodology Box & Jenkins (BOX; JENKINS, 1976) to forecast the production of this market. The models were evaluated based on the Akaike and Schwarz criteria, at the coefficients significance, at the parsimony principle and at the waste behavior. According to results, the moving average auto-regressive model (ARIMA) (2,1,1) was adequate to predict the non-coniferous sawn timber production and the ARIMA (1,1,1) model to predict the conifers sawn wood production. The methodology can be used for such market prediction.Keywords: Lumber production; time series; Box & Jenkins methodology

Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data

Tropical savanna ecosystems play a major role in the seasonality of the global carbon cycle. However, their ability to store and sequester carbon is uncertain due to combined and intermingling effects of anthropogenic activities and climate change, which impact wildfire regimes and vegetation dynamics. Accurate measurements of tropical savanna vegetation aboveground biomass (AGB) over broad spatial scales are crucial to achieve effective carbon emission mitigation strategies. UAV-lidar is a new remote sensing technology that can enable rapid 3-D mapping of structure and related AGB in tropical savanna ecosystems. This study aimed to assess the capability of high-density UAV-lidar to estimate and map total (tree, shrubs, and surface layers) aboveground biomass density (AGBt) in the Brazilian Savanna (Cerrado). Five ordinary least square regression models esti-mating AGBt were adjusted using 50 field sample plots (30 m × 30 m). The best model was selected under Akaike Information Criterion, adjusted coefficient of determination (adj.R2), absolute and relative root mean square error (RMSE), and used to map AGBt from UAV-lidar data collected over 1,854 ha spanning the three major vegetation formations (forest, savanna, and grassland) in Cerrado. The model using vegetation height and cover was the most effective, with an overall model adj-R2 of 0.79 and a leave-one-out cross-validated RMSE of 19.11 Mg/ha (33.40%). The uncertainty and errors of our estimations were assessed for each vegetation formation separately, resulting in RMSEs of 27.08 Mg/ha (25.99%) for forests, 17.76 Mg/ha (43.96%) for savannas, and 7.72 Mg/ha (44.92%) for grasslands. These results prove the feasibility and potential of the UAV-lidar technology in Cerrado but also emphasize the need for further developing the estimation of biomass in grasslands, of high importance in the characterization of the global carbon balance and for supporting integrated fire management activities in tropical savanna ecosystems. Our results serve as a benchmark for future studies aiming to generate accurate biomass maps and provide baseline data for efficient management of fire and predicted climate change impacts on tropical savanna ecosystems

Optimization of the geometric alignment of forest roads

Estradas desempenham diversas funções para a sociedade. No setor florestal esse meio de transporte é fundamental, pois é utilizado em praticamente todas as atividades do empreendimento. Dentre essas atividades, o transporte de madeira merece destaque pois, juntamente com a colheita, é a operação mais onerosa do processo produtivo. Diversos elementos podem influenciar o custo do transporte; no entanto, a estrada pode ser considerada como um dos mais importantes, pois possui forte relação com os demais elementos, estando associada a impactos ambientais, além de ter elevados custo de construção e manutenção. O principal desafio dos gestores é determinar o local ideal de construção de estrada, de forma a permitir o tráfego com eficiência e segurança. Neste estudo é proposto um método desenvolvido para otimização do traçado geométrico de estradas florestais, implementado em ambiente de sistema de informações geográficas (SIG). A metaheurística simulated annealing foi utilizada para implementar um algoritmo com o objetivo de minimizar o custo total da estrada, atendendo restrições técnicas dos alinhamentos horizontal e vertical. O custo total incluiu: construção, manutenção, utilização e fatores ambientais e sociais. O método desenvolvido é apropriado para a otimização do traçado geométrico de estradas, por atender as condições necessárias: considera todos os custos dominantes e sensíveis, respeitando as restrições técnicas; otimiza as atribuições horizontais e verticais de modo simultâneo; é capaz de retornar uma boa solução para um problema de grande porte em um tempo aceitável; e é compatível com um SIG, o que favorece o processo de tomada de decisão, permitindo lidar com bases de dados extensas e complexas.Roads perform many functions for society. In the forestry sector, it is a key factor, because it is used in practically all the activities of the enterprise. Among these activities, timber transportation deserves special mention because, together with harvesting, it is the most costly operation of the production process. Several elements can influence the cost of transport; however, the road can be considered as one of the most important because it has a strong relationship with other elements, for instance, being associated with environmental impacts, and also having high construction and maintenance costs. The main challenge for managers is to determine the ideal local for road construction in order to allow efficient and safe traffic. In this study, a method developed for optimization of the geometric alignment of forest roads, implemented in a geographic information system (GIS) environment, is proposed. The simulated annealing metaheuristic was used to implement an algorithm with the objective of minimizing the total cost of the road, addressing technical restrictions of the horizontal and vertical alignment. The total cost included: construction, maintenance, use and environmental and social factors. The developed method is suitable for optimization of the geometric alignment of roads, considering the needed conditions: it considers all the dominant and sensitive costs, respecting the technical restrictions; it optimizes horizontal and vertical assignments simultaneously; it is able to return a good solution to a large problem in an acceptable time; and it is compatible with a GIS, which favors the decision- making process, allowing to deal with extensive and complex databases.Conselho Nacional de Desenvolvimento Científico e Tecnológic

Pathway Optimization for Access to Forest Inventory Plots

O objetivo desse estudo foi desenvolver metodologias para otimização do acesso e do caminhamento às parcelas de inventário florestal, bem como implementá-las em um ambiente com interface gráfica para o usuário e integradas a um sistema de informações geográficas. Foram utilizados dados provenientes da empresa florestal Floresteca, de plantios de teca (Tectona grandis) situados no município de Rosário Oeste, Mato Grosso. A base de dados espaciais foi composta da localização de 80 parcelas de inventário distribuídas em 15 talhões e da rede de estradas florestais existentes no local. Normalmente as empresas florestais brasileiras adotam variações ou combinações de duas estratégias de acesso às parcelas: (1ª) caminhamento da estrada até a parcela e posteriormente da parcela até a estrada, e (2ª) caminhamento da estrada até a parcela e da parcela até uma série de outras parcelas, retornando-se, posteriormente, à estrada. Neste estudo adotou-se a 1ª estratégia. A otimização do acesso foi baseada no algoritmo do vizinho mais próximo. Este algoritmo, basicamente, determina os pontos da estrada mais próximos a cada parcela. Esses pontos são, então, considerados como a entrada da parcela. O problema do caminhamento entre as parcelas foi formulado como um problema do caixeiro-viajante (PCV) permitindo-se, contudo, a imposição da malha viária no processo de otimização. O PCV foi resolvido via formulação de programação linear inteira, sendo otimizado pelo algoritmo cutting-plane, disponível no software Concorde. Para fins de comparação, o problema foi também resolvido pelo método aproximativo do vizinho mais próximo, uma vez que o executor do inventário aplica esse algoritmo intuitivamente em campo. As metodologias foram implementadas usando-se a linguagem de programação Python e integradas ao software ArcGIS. A metodologia de acesso às parcelas otimiza o caminhamento entre a estrada e as parcelas de inventário florestal, e sua implementação computacional permite que a tarefa seja feita de forma automatizada. Com isso, obtêm-se aumento de eficiência tanto no planejamento do inventário quanto em sua execução. A metodologia de caminhamento otimiza o percurso entre as parcelas a serem inventariadas. A solução exata mostrou-se superior à solução aproximada, algo em torno de 17% em média.The aim of this study was to develop methods for optimizing access and pathway to forest inventory plots, and to implement them in an environment with graphical user interface and integrated into a geographic information system. We used data from a plantation of teak (Tectona grandis) owned by the forestry company Floresteca, located in the city of Rosário Oeste, Mato Grosso. The spatial database was composed of localization of 80 inventory plots distributed in 15 stands, as the network of forest roads located on site. Usually, the Brazilian forestry companies adopt variations or combinations of two strategies to access the portions: (1st) moving from the road to the parcel and then, from parcel to the road, and (2nd) moving from the road to the plot, then from the plot to a series of other plots, to finally return to the road. In this study we adopted the 1st strategy. The optimization of access was based on the nearest neighbor algorithm. This algorithm basically determines the points of the road closest to each plot. These points are then considered as the parcel entrance. The problem of the pathway between plots was formulated as a traveling salesman problem (TSP) allowing, however, the imposition of the road network in the optimization process. The TSP was solved via integer linear programming formulation, followed by an optimization from the algorithm cutting-plane available on Concorde software. For comparison purposes, the problem has also been solved by the method of approximate nearest neighbor, since the inventory executor intuitively applies this algorithm in the field. These methods were implemented using the Python programming language and integrated into the ArcGIS software. The parcel access methodology optimizes the path among the roads and the forest inventory plots, and its computational implementation allows the task to be done in an automated fashion. Thus, we obtain increased efficiency both in inventory planning and in execution. The methodology optimizes the traversal path between plots to be inventoried. The exact solution was superior to the approximate solution, something around 17% on average.Conselho Nacional de Desenvolvimento Científico e Tecnológic

Distribuição espacial dos danos de Heilipodus naevulus em plantio de clones de eucalipto

As espécies Heilipodus naevulus (Mannerheim, 1836) foi detectado, em 2008, no município de Barão de Cocais, MG, em plantios comerciais de clones de eucalipto, danificando o ponteiro principal e o lateral. Devido ao seu hábito noturno, o seu tamanho reduzido, coloração acinzentada, e , por se abrigar na área de serapilheira durante o dia, a sua detecção é dificultada, sendo a sua presença apenas evidenciada através dos ponteiros tombados. Este trabalho teve como objetivo conhecer a distribuição desta espécie durante o primeiro ano de crescimento clones eucalipto, a fim de fornecer subsídios para a elaboração de um plano de amostragem. O trabalho foi realizado no município de Barão de Cocais, MG, a partir de outubro/2008 a março/2009. Nos dois talhões de avaliação foram estratificados em baixada, encosta e topo. Foram distribuídas 18 porções, de 10 x 10 árvores, sendo nove por talhão, e, três por estrato. Foi adotado como indicador da presença de H.naevulus na planta a presença ponteiro recém danificado. Para o cálculo da distribuição espacial foram empregados a Razão Variância/Média, o Índice de Morisita, o Parâmetro kda distribuição binomial negativa, o Coeficiente de Green, a Distribuição de Poisson e a Lei de potência de Taylor. Ao longo do período de avaliação da presença de H. naevulus,os índices calculados apresentaram um padrão agregado de ocorrência dos danos, indicando que a espécie apresenta um padrão agregado de distribuição, mesmo em baixa incidência