In recent years, the need for reliable signal transmission in forested areas has increasingly grown, and the past few decades have witnessed significant developments in related research. With the emergence of smart forestry and precision forestry, understanding the science behind enhancing signal reliability in forests—specifically, studying the patterns and models of radio wave attenuation in these environments—has become crucial. To this end, we conducted a comprehensive review based on bibliometrics to summarize and construct the existing academic literature, revealing current research trends and hotspots. Utilizing bibliometric techniques, we analyzed the literature on radio wave attenuation in forests to summarize and evaluate previous studies. Our analysis indicates that empirical models (67%), hybrid models (21%), and equivalent models (12%) are the three main research clusters in this field. We observed that studies on radio attenuation are more prevalent in urban and artificial forests, while there is a scarcity of research in complex conditions like tropical rainforests and extreme weather; studies are more focused on UHF, VHF, and SHF frequency bands, with lesser attention given to other bands. Previous research has not adequately considered the impact of seasonal factors on signal attenuation patterns nor the influence of forest working environments.

The hydraulic system is a key component of intelligent forestry harvesters. In the testing of a forestry harvester, researchers need to analyze the operating efficiency and energy consumption of the forestry harvester based on the pressure and flow rate data in the hydraulic system of the forestry harvester and formulate energy-efficient control strategies. In order to enable researchers to monitor and extract the parameters of the hydraulic system of an intelligent forestry harvester in real time, this paper designs a hydraulic online monitoring system for forestry harvesters based on the LabVIEW 2019 software platform. This system realizes the following functions by reading the CAN (controller area network, a serial communication protocol for multi-host localized networks) bus of the harvester: (1) it collects and stores hydraulic system pressure, flow, and other data and displays the value curve in the system interface in real time, and (2) it monitors the control signals received by the hydraulic system and displays the control signal status and value received by the system interface in real time. This paper used this system to carry out on-site testing of an actual machine, and compared and analyzed the online monitoring data of the hydraulic system and the theoretical pressure data of the main hydraulic valve manifold. The average value of the relative error between the two was 1.65%, and the maximum value of the relative error was 2.75%. The results show that the designed system has good accuracy and stability, and can effectively realize online monitoring of the working status of the hydraulic system of forestry harvesters during their operation.

Forest harvesting transportation planning must balance operational efficiency with environmental sustainability, because timber transportation can cause both soil disturbance and carbon emissions. However, most vehicle routing studies primarily focus on economic objectives such as distance or cost minimization, whereas environmental impacts are often considered separately. The integrated optimization of ecological disturbance and carbon emissions remains limited in forest transportation planning. To address this gap, this study formulates a multi-vehicle routing optimization model for timber transportation that simultaneously minimizes transportation distance, makespan, soil disturbance, and CO₂ emissions within a hierarchical forest road network. An enhanced evolutionary algorithm, Eco-Constrained Lévy-flight Local Search NSGA-II (ECLS-NSGA-II), is proposed to improve convergence and maintain environmentally favorable routing solutions. Simulation experiments comparing ECLS-NSGA-II with NSGA-II, MOPSO, MOEA/D, and WS-GA demonstrate that the proposed method achieves superior performance across all objectives, producing shorter routes, lower completion times, and reduced CO₂ emissions while maintaining minimal ecological disturbance. Additional experiments on randomly generated networks further confirm the robustness of the proposed approach. These results indicate that the proposed framework provides an effective methodological tool for environmentally sustainable timber transportation planning in forest operations.