Bilici, E.Eker, M.Hasdemir, M.Akay, Abdullah Emin2021-03-202021-03-2020170373-1332https://hdl.handle.net/20.500.12885/1314Various problems such as massive volume loss, erosion, degradation of water resources, and air pollution emerge after forest fire incidents. Thus, necessary forest operations should be quickly planned and implemented after forest fires so that afforestation activities can take place immediately to maintain forest vegetation in burned areas.The aim of this study was developing a Post-fire Action Planning (PFAP) model to minimize the time spent on salvage logging activities. PFAP model will assist decision makers for removing salvage timber in a timely manner after large scale forest fires, while considering economic and environmental constraints, and dealing with available employment conditions in local forest industry. The capabilities of this model were examined by standardizing the operational planning and developing a fast decision-making process. The model was implemented in Taşa?il Forest Enterprise Chiefs (FEC) of Antalya Forest Regional Directorate where the forests are sensitivity to fire at the first degree level and the second largest forest fire in the history of Turkish Forestry occurred in this area in 2008. The findings of PFAP model were compared with the data of actual salvage logging operation obtained from the FEC. The results indicated that using operational planning based PFAP model is capable of reducing total time spent on salvage logging operation by about 60%. Based on the forestry compartments of the study area, estimated durations of salvage logging operations were 15 to 75 days less than that of actual operations taken place in the field. Therefore, it is highly anticipated that using operational planning based PFAP model has great potential to provide economically and environmentally sound forest operations after forest fires.eninfo:eu-repo/semantics/openAccessForest fireForest transportationModellingOperational PlanningSalvage loggingConference Object1417-83633732-s2.0-85028927832Q3