Integrated planning of forest exploration infrastructures in an amazonian sustainable forest management area.

• Autor(a) principal: AGUIAR, M. O.
• Data de Publicação: 2023
• Outros Autores: SILVA, G. F. da, MAURI, G. R., MENDONÇA, A. R. de, SILVA, E. V. da, FIGUEIREDO, E. O., SILVA, J. P. M., SILVA, V. A. da, SILVA, R. F., LAVAGNOLI, G. L.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
• Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1161840; https://doi.org/10.1016/j.foreco.2023.121265
• topic: Bosques primarios; Manejo forestal; Explotación forestal; Planificación; Terra Santa (PA); Oriximiná (PA); Pará; Amazônia Oriental; Eastern Amazon; Floresta Nativa; Manejo; Exploração Florestal; Planejamento Florestal; Primary forests; Forest management; Logging; Planning

Planning the allocation of infrastructure exploration in native forests plays an important role in reducing costs and environmental damage. Traditionally, companies manually plan the infrastructure for exploration, which requires a lot of time and effort and implies low planning precision. Additionally, it makes it impossible for decision-makers to explore different scenarios and plan such structures in an integrated way. This research aims to evaluate two strategies that combine computational techniques for allocating the necessary exploration infrastructures in native forests. The study area was a native forest under a sustainable management regime located in the Brazilian Amazon. Three instances were formulated for resolution. Both employed strategies use exact and approximate methods for allocating infrastructures. The results indicate that the location of yards directly influences the optimization of road allocation and skid trails. However, it is essential that the manager evaluates several scenarios considering different numbers of yards to make the decision. It was also concluded that integrated planning makes it possible to obtain better results, as it allows for the choice of planning based on the best global solution by combining the set of infrastructures.