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Several factors affect the management of natural forests, which many times are antagonistic, when dealing with the establishment and location of skid trails. The lack of detailed data about the forest structure and topography make the decision making process precarious. The use of airborne laser scanning may improve the capacity to obtain adequate...
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... Only the activities "Silvicultural treatments", predecessor of "Felling and log processing", and "Road maintenance", predecessor of "Final transport", are not critical. The study resulted in a total of 25 integer work crews, required for completing the activities within time limit of 168 days (7 months In its study using geotechnologies to support spatial optimization, Barbosa et al. (2017) developed a study with the aim to use multi-criteria optimization to determine the optimal logging routes based on information derived from an airborne laser scanning data combined into four different cost compositions. Four criteria to be considered in the optimization were derived from the LiDAR cloud: distance sloping to define optimal allocation of log landings in order to minimize total skid-trail's distance in the Amazon Forest. ...
... considers horizontal and vertical variation), slope, vegetation height and location of the preservation areas. The results indicated that the more suitable scenarios were: minimization of impact to the APP and balanced minimization(BARBOSA et al., 2017).The authors concluded that multi-criteria optimization proved to be of great value in allowing to combine different factors in the composition of the cost surface that will be optimized. Different combinations can be adopted aiming to prioritize one or a set of factors, resulting in differences between the results obtained in the optimization. ...
... Different combinations can be adopted aiming to prioritize one or a set of factors, resulting in differences between the results obtained in the optimization. The increasing availability of sensors has considerably increased the quantity and detailing the information available on the management area(BARBOSA et al., 2017).In their study,Silva et al. (2018a) had the main objective to optimize the location of wood log landings in forest management for the production of wood in the Brazilian Amazon. The research have taken the topography into account, with permanent preservation areas, restricted areas, and remaining trees-and using GIS tools, 7896 sites were identified that could be used as wood log landings. ...
Biodiversity is one of the main characteristics of tropical forests, distributed in micro sites with specific biophysical attributes. These factors are often poorly considered in forest management planning in the Amazon, through the spatial systematization of infrastructure for operations, generally not considering in decision making the distribution of forest stock of commercial species and other biotic factors. This study aimed to bring planning advances and contributions for the minimization of the infrastructure required in logging operations, through rational allocation of log landings and secondary roads, with use of environmental, operational and production constraints, keeping the same production capacity for the management of the Amazon Rainforests. Data granted by the company Precious Woods Amazon, which carries out large-scale forest management, were used, using a database of 06 consecutive logging UPAs (annual production units): 2013, 2014, 2015, 2016, 2017 and 2018. The data were analyzed in two stages: analysis and planning in digital geographic information system (QGIS) and infrastructure utilization improvements (QGIS qneat add-on package). In addition, a complementary analysis of climatic factors and costs of operations was performed. The geospatial analysis was intended to classify the restricted areas based on environmental and operational conditions that were excluded from the improvement step. Models for infrastructure improvements (roads, skid trails, and yards) were applied to minimize land use in operation support infrastructure subject to operational and environmental constraints. Finally, the results were included in planning maps with QGIS tools, demonstrating the process improvements. The reduction of infrastructure required in log landings ranged from 24.6% to 65.6%, with an average of 40.6%, which is relevant considering the agile planning improvement process applied to forest management in this study. The reduction in infrastructure required for secondary roads varied between 17.8% and 39.9%, with an average of 24.2% fewer roads (in meters), which is relevant when considering the area required for road construction (road width and removal of bordering vegetation), with great environmental and physical impact in tropical forests. Additionally, the highest expenses were concentrated between months July to November. This is the time when all operations are active. Cutting, which is one of the most crucial stages, ends in November, in order to avoid the beginning of the raining season in the region. The most expensive operations for the company were yard operations (27% of the total), transportation (18%) and pre-skidding (18%), respectively. We conclude that the study brought sensible contributions for the planning of logging in the Amazon, minimizing the necessary infrastructure while maintaining the same productive capacity. This work brings subsidies for the improvement of the processes of this activity in Amazon, as well as stimulates the replication of methods and contributes to new management enterprises in the region. We recommend the use, replication and dissemination of these rational methods presented herein for different logging contexts in Amazon, testing, if possible, different values for variables, especially those related to the maximum radius of skidding.
... Studies have shown the beneficial uses of LiDAR technology in the area of sustainable forest management (SFM) for the Amazon region, in determining preferred skid trail routes (Barbosa et al., 2017), identification and analysis of areas impacted by timber extraction in selectively harvested areas (Andersen et al., 2014;d'Oliveira et al., 2012;de Carvalho et al., 2017) and forest biomass estimates (Rex et al., 2018;Schuh et al., 2020). However, for commercial use in sustainable forest management plans (SFMP), the cost is still too expensive and is considered an unviable technology for many operations. ...
... At this location, areas that present operational challenges, such as different forest types, watercourses (SFB, 2018) and other variables which are difficult to be discerned by remote sensing technologies are identified on the ground during the forest inventory phase. This process is important to reduce the subjectivity problem at the microplanning stage for the logging units, that are characterized by a lack of specific details as related to environmental factors, a scenario caused by lower resolution satellite images and basic IBGE topographic maps currently used for the macroplanning of SFM in Amazonia (Barbosa et al., 2017). ...
... The AHP method has already proven efficient in determining the optimal locations for log landings, in sustainable forest management (SFM) areas within the Amazon (Silva et al., 2018). Another method that has already been used successfully in timber harvest planning in the Amazon, was Simple Additive Weighting (SAW), tested for optimization of log landings by Martinhago (2012) and for optimization of skid trails by Barbosa et al. (2017). ...
Forest Management in the Brazilian Amazon has social, economic and environmental relevance, as it allows for the sustainable use of natural resources, while at the same time conserving a majority of the ecological processes of the forest. Among forest operations, the construction of new roads is essential for effective sustainable forest management (SFM). However, it is the most expensive part of forest infrastructure and has the greatest environmental impact. Several methods to optimize forest road planning (FRP) have been studied worldwide, although the literature is scarce on the subject of FRP in areas of SFM in Amazonia. Thus, the objective of this study was to carry out a systematic review of the global literature, on FRP optimization in the last decade (2009-2019), as a way to support future planning activities for road infrastructure in SFM in the Amazon. To guide this objective, three questions were raised to determine what the dominant factors affecting FRP in the study period, specifically what were the: (i) spatial variables; (ii) spatial decision analysis and; (iii) optimization methods for road layout. The bibliographic search was conducted according to the Prisma methodology where a set of keywords was entered into the Scopus, Science Direct and Web of Science indexing databases. In this study, all articles published in English-language journals between 2009 and 2019 were considered, resulting in 62 articles for analysis. There was a growing trend in publications, with most studies developed at the level of strategic planning (46.8%). Also, it was observed that the majority of studies occurred in the forests of Iran (33.9%). The results to the questions of this study found that: (i) there were 45 spatial variables, with slope the most studied (54.7%); (ii) Eleven methods of analysis for spatial decisions, with methods based on Analytical Hierarchy Process-AHP the most studied (36.6%) and; (iii) Thirty different methodologies for optimizing the design of forest roads, mainly methods based on Dijkstra's algorithm (40.5%). Some of the encountered methods have already been implemented in Amazonia to optimize the planning of infrastructure in areas of SFM. In this context, the combination of approaches, variables and analysis for FRP optimization that have been successfully tested in other forests of the world, could feasibly be applied in future planning of logging operations in the Amazon in order to verify the potential of these different procedures and methods, provided that they meet the objectives of the SFM.
