Nowadays the spread of precision forestry has led to the possibility of collecting data related to forest machines for an extended period and with enough precision to support decisions in the optimization of harvesting strategies in terms of technological and environmental efficiency. This study aims to evaluate the effective benefit of automatic data collection through the fleet management system (FMS) of two forest harvesters and two forwarders in pine forests in Poland. The study also aims to determine how the use of FMS can help forest companies to manage their fleet and take advantage of long-term monitoring. Focusing on performance indicators of fuel consumption and CO2 emissions, as well as on the engine parameters from the Can Bus data, the exploration of data was performed following a Big Data approach, from the creation of an aggregate dataset, pre-elaboration (data cleaning, exploration, selection, etc.) using GIS and R software. The investigation has considered the machine productivity, in the case of the harvesters, and the specific fuel consumption of each machine studied, as well as the time used by each of them during the different working cycle activities and the total amount of timber processed. The main results indicate an average emission of 2.1 kg of CO2 eq/m3 for the harvesters and 2.56 kg of CO2 eq/m3 for the forwarders, which equates in total to 0.24% of the carbon stored in one cubic meter of wood.

Post-wildfire regenerated Mediterranean pine stands have a high risk of wildfire recurrence. Preventive clearings are frequently applied in a mix of systematic and selective ways, being a potential biomass source using technologies such as the collector-bundler BioBaler WB55. Our research aimed to compare the BioBaler with a chain mulcher performing systematic mulching of 50% vs. 67% of stand surface over 11.4 ha dominated by Pinus pinaster Ait. regenerated after a severe wildfire. Time studies included the machinery GPS follow-up and the weighing of each produced bale. Environmental aspects were also assessed. A regression curve related BioBaler weight productivity (odt·Workh−1) to pine biovolume (cover (%) average tree height, m). Surface productivity (stand ha·Workh−1) was greater for both technologies when a lower percentage of the total surface was cleared, but less than theoretically predicted. The BioBaler’s economic balance, including the cost of further selective clearing and the income from biomass selling, was costlier than that of the mulcher—in the most representative strata, 475 EUR·ha−1 vs. 350 EUR·ha−1. Under the studied conditions, BioBaler was not economically competitive with the conventional treatment, its main constraint being low collection efficiency (31% of the standing biomass in the cleared surface, 5.33 out of 17.1 fresh tonnes·ha−1).