To address the needs of forest fire prevention and suppression, an evaluation method was developed for assessing the fire-protection function of forest road networks. The method characterizes the spatial distribution of firefighting capacity, identifies areas with functional deficiencies, and proposes targeted improvement strategies, thereby supporting sustainable forest management and multifunctional development.

Based on geographic information system technology and multi-criteria decision-making methods, this study takes the Lutou experimental forest farm as the research area. From technical, economic, and environmental dimensions, ten evaluation indicators are selected, including road network density and the proportion of high kernel density areas, road coverage, accessibility to water sources, proportion of roads within the 2 km service area of firefighting facilities, mileage-based benefit, mileage-based cost, proportion of routes passing through slope-restricted areas, terrain undulation-restricted areas, and NDVI-restricted areas. The analytic hierarchy process and entropy weight method are employed to determine the subjective and objective weights of influencing factors, respectively, and the comprehensive weights are calculated using the weighted average method. On the basis of indicator interval assignment and weight integration, a fire-protection capacity evaluation model for the forest road network is constructed.

The overall fire-protection performance of the forest road network is evaluated as excellent, with particularly strong performance in terms of firefighting accessibility and water source availability, ensuring that most areas can receive timely assistance in the event of a wildfire. However, insufficient firefighting coverage is identified in the southwestern and northern parts of the forest farm, indicating the need for targeted upgrades and improvements to the road network in these areas.

A multi-dimensional evaluation index system and model was established for the fire-protection function of forest road networks provides a theoretical foundation for assessing forest fire response capacity and offers a systematic and scientific basis for the quality improvement and upgrading of forest road networks.

Furniture, as the end product of the wood supply chain, has accumulated the most important carbon flow. In order to reduce the great burden on the environment caused by the high pollution link of the furniture manufacturing industry, the key influencing factors of carbon emission reduction in the furniture supply chain were analyzed, and the structural level model of influencing factors of carbon emission reduction in the furniture supply chain was constructed, so as to provide decision support for promoting carbon emission reduction in the furniture industry.

The key influencing factors of carbon emission reduction in furniture supply chain were screened by literature research method, and the influencing factors were analyzed by combining decision and laboratory method and interpretive structure model to analyze the correlation among the influencing factors and determine the level of influencing factors.

1) Low carbon energy supply, low carbon material supply, low carbon equipment supply and low carbon production technology level were located in the first layer of the structural hierarchy model of carbon emission reduction influencing factors of furniture supply chain, which were direct influencing factors and had a direct impact on carbon emission reduction of furniture supply chain. 2) Government technology subsidies and low-carbon transportation were located at the second layer of the structural hierarchy model of influencing factors of carbon emission reduction in the furniture supply chain, while low-carbon product design, low-carbon product promotion, recycling strategy and low-carbon packaging were located at the third layer of the structural hierarchy, all of which were intermediate influencing factors and indirectly affected the carbon emission reduction of the furniture supply chain through influencing direct factors. 3) Low-carbon product publicity, low-carbon product preference, consumption subsidies and recycling channel construction were located in the fourth layer of the structural hierarchy model of the carbon emission reduction influencing factors of the furniture supply chain, which were deep influencing factors and had a fundamental impact on the carbon emission reduction of the furniture supply chain.

The furniture supply chain involves many industries, and carbon emission reduction is influenced by more than a single factor. It is necessary to comprehensively consider the carbon emission reduction measures of the supply chain from the perspective of the whole supply chain. It is suggested to start with the deep factors affecting the carbon emission reduction of the furniture supply chain, construct the operation mode of the remanufacturing closed-loop supply chain, optimize the recycling channels of waste furniture, and promote the collaborative emission reduction among the furniture supply chain, build the supply chain carbon reduction coordination contract, introduce new carbon reduction technologies such as block chain, and promote the green and efficient development of the furniture supply chain.