Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/34514
Title: Optimal selective logging regime and log landing location models: a case study in the Amazon forest
Other Titles: Regime de corte seletivo ótimo em modelos de locação de pátios de estocagem de madeira: um estudo de caso na floresta amazônica
Keywords: Forest planning
Reduced-impact logging
Integer linear programming
Sustainable forest management
Liocourt quocient
Planejamento florestal
Registro de impacto reduzido
Programação linear inteira
Manejo florestal sustentável
Quociente de Lioncourt
Issue Date: Jan-2018
Publisher: Instituto Nacional de Pesquisas da Amazônia
Citation: SILVA, P. H. da et al. Optimal selective logging regime and log landing location models: a case study in the Amazon Forest. Acta Amazonica, Manaus, v. 48, n. 1, p. 18-27, jan./mar. 2018.
Abstract: Reduced-impact logging is a well known practice applied in most sustainable forest management plans in the Amazon. Nevertheless, there are still ways to improve the operational planning process. Therefore, the aim of this study was to create an integer linear programming (ILP) to fill in the knowledge gaps in the decision support system of reduced impact logging explorations. The minimization of harvest tree distance to wood log landing was assessed. Forest structure aspects, income and wood production were set in the model, as well as the adjacency constraints. Data are from a dense ombrophylous forest in the western Brazilian Amazon. We applied the phytosociological analysis and BDq method to define the selective logging criteria. Then, ILP models were formulated to allow the application of the constraints. Finally, 32 scenarios (unbalanced forest, UF, and balanced forest, BF) were generated and compared with real executed plans (RE). Robust results were achieved and the expected finding of each scenario was met. The feasibility to integrate ILP models in uneven-aged forest management projects was endorsed. Consequently, the UF and BF scenarios tested were efficient and concise, introducing new advances for forest management plans in the Amazon. The proposed models have a high potential to improve the selective logging activities in the Amazon forest.
URI: http://repositorio.ufla.br/jspui/handle/1/34514
Appears in Collections:DCF - Artigos publicados em periódicos



This item is licensed under a Creative Commons License Creative Commons