Wood and its products are widely used in people’s daily life， including furniture manufacturing， interior decoration， construction and other fields. The total annual output value of the wood industry has exceeded 3 trillion yuan， which is an important basic industry of the national economy. However， there are still problems such as low added value of products， weak innovation ability of enterprise， and decentralized production supply chain in the process of wood industry development. Starting towards the new and green departure， incubating new technologies and materials for functional wood manufacturing， and cultivating new productivity in the wood industry are important directions to boost the wood industry development and accumulatively achieve low-carbon transformation. This paper focuses on the frontier development direction of wood science， discusses the important quality productivity of wood industry， and clarifies the importance of scientific and technological innovation for wood industry development. Furthermore， this paper puts forward four directions for the future development of wood science， including the micro in-depth， the macro expansion， the extreme conditions， and the comprehensiveness， and summarizes the newly representative research results， sorts out the development status and trend of the representative wood new products and functional new materials， and lays the foundation for further proposing the development path of new quality productivity in China's wood industry.

Cracks in wood have a non-negligible effect on the propagation characteristics of stress waves. It is significant to investigate the energy change law for the crack depth identification in wood. Pinus sylvestris var. mongholica Litv. wood was used as the specimen in the study， and different numbers of cracks were made on different specimens. The depth of cracks was gradually increased from 0 to 90 mm with an increment of 10 mm each time. Firstly， an acoustic emission （AE） sensor was used to collect the stress wave generated on the surface of the specimen by the pencil lead breaking， and its time-frequency characterization was performed. Secondly， the energy attenuation model of the stress wave in different frequency bands was established based on discrete wavelet analysis. The results showed that， the percentage of AE signals with frequency components of 125 to 250 kHz in the transient wave decreased significantly with increasing crack depth. As the number of cracks increased， the coefficient indicating the attenuation degree in the energy attenuation model after wavelet reconstruction of the AE signal increased from 0.73 to 1.09. In addition， with the increase of crack depth， the energy decay of the wavelet signal with frequency components of 31.25 to 62.5 kHz was obviously slow. And the crack region determined by the energy attenuation model can cover the location of the actual crack.

To expand the application of wood in the field of outdoor reflective materials， a series of calcium carbonate/eucalyptus wood composite materials with different calcium carbonate （CaCO₃） contents were prepared by hot pressing method using the mineralization method of alternating vacuum impregnation of eucalyptus wood with calcium chloride and sodium bicarbonate to mimic the organic/inorganic composite structure of natural pearl layer. The effects of CaCO₃ on the structure and properties of the mineralized materials were investigated through structural characterization and performance tests. The results showed that CaCO₃ could enhance the mechanical properties of the mineralized material， improve its thermal stability and reflective ability to sunlight， and reduce the temperature at which the material was heated by light. When the mineralization time was lower than 3 days， the tensile strength increased with the increase of CaCO₃ content， up to 18.35 MPa， and the fracture process showed multiple fracture； when the mineralization time reached 4 days， the material's reflectance of sunlight reached more than 80 %， which reduced the temperature of the original wood by 10 ℃ compared with the original wood itself. This environmentally friendly material has a certain application potential in the field of outdoor reflective insulation field.

A method for identifying the number of wood cracks based on acoustic emission is proposed for wood crack distances. Firstly， four cracks of 1 mm×9 mm （length×height） are artificially made in sequence on the specimen， and an acousitic emission （AE） signal is generated on one side of the crack by folding the lead， and the sensor is placed on the other side with a signal sampling frequency set to 2 MHz.Then， the number of decomposition layers K and the penalty factor α of the variational modal decomposition （VMD） are determined by the particle swarm algorithm （PSO）， and the original signals are decomposed into the intrinsic mode function （IMF） with different frequencies. tFive groups of signals are then randomly selected for VMD decomposition， and the matrix composed of the decomposed IMFs is subjected to singular value decomposition （SVD） to obtain the corresponding singular value vectors， and then the standard matrix is composed of the five groups of singular value vectors. Finally， from the measured AE signals， the Mahalanobis distance is calculated with the standard matrix， respectively， and the number of cracks is determined based on the principle of minimum discrimination. The results show that the AE signal features can be easily extracted by the PSO-VMD-SVD method and the number of cracks can be discriminated by calculating the Mahalanobis distance， and the correct rate of discrimination is 92%.

High-quality and efficient wood cutting processes are of significant importance for improving the utilization rate of wood resources and enhancing the quality of wooden products. Currently， the commonly used steel 65Mn for woodworking circular saw blades has issues with subpar mechanical properties such as hardness and tensile strength. To address this， nickel was added to modify the 65Mn steel. The Ni-modified 65Mn steel was prepared through steps including raw material smelting， casting test bars， forging processing， and heat treatment. Microhardness， impact toughness， and tensile strength tests were conducted on the 65Mn steel before and after modification. Additionally， the organizational differences of 65Mn steel before and after modification were analyzed using Metallographic microscopes and Scanning Electron Microscopes （SEM）. The results of the study indicated that， 1） after adding Ni elements， the tempered structure of 65Mn steel changed from tempered troostite to a mixture of quenched martensite and tempered martensite， and when the mass fraction of Ni reached 0.9%， residual austenite appeared. 2） Under the same heat treatment conditions， the effect of Ni elements on the hardness and tensile strength of the material showed a trend of first increasing and then decreasing， with the impact toughness being lower than that of unmodified 65Mn steel. The hardness and tensile strength of the 65Mn steel with a mass fraction of 0.7% Ni were optimal， increasing by 10.18% and 35.40%， respectively compared to unmodified 65Mn steel （at room temperature）. This research findings provides new ideas and methods for the subsequent improvement of woodworking circular saw blade steels and is expected to promote further development in the wood processing tools industry.

This paper aims to compare the differences of burning properties of 12 typical tree species in Xiaoxing’anling，and to provide reference for the selection and allocation of fireproof forest tree species. In the study， the 12 kinds of shrubs in the Xiaoxing’anling region of Heilongjiang Province are taken as the main research subjects， with their stems， branches， and leaves measured separately for the combustibility indicators. The hierarchical analysis method （AHP） is then applied to construct a hierarchical model of the combustibility of shrub plants， determining the weights of each index of combustibility， calculating the combustibility values of different parts of the shrub， and confirming the weight ratio of each part of the shrub in combination with expert scoring methods to arrive at the combustibility ranking of 12 kinds of shrub. It has been revealed by the research results that： in terms of the whole plant， Rosa davurica has the strongest combustibility， while Lonicera japonica has the weakest. Compared the combustibility of the stem， the most easily ignited is Sambucus williamsii and the hardest to ignite is Lonicera japonica. Compared the branch combustibility， the most easily ignited is Sambucus williamsii and the hardest to ignite is Lonicera japonica. Compared the combustibility of leaves， those of Acanthopanax senticosus are most easily ignited and those of Tamarix ramosissima are the hardest to be ignited. The results can provide a theoretical basis for the shrub′s combustibility and a support for predicting forest fire behavior， and combustible materials management.

Because the planting mode of Eucalyptus robusta plantation is basically a single mode of multi-generation continuous planting， many ecological problems are caused. Therefore， ensuring that artificial E. robusta forests can achieve long-term and stable sustainable management has become a hot issue in the cultivation technology of artificial E. robusta forests. In order to achieve this goal， adopting appropriate tree species configuring and moderate canopy density is an effective way to adjust the stand structure and enhance the soil quality. In this study， six E. robusta pure forest plots were selected from the West Coast Forestry Farm in Foshan City， China， to study the effects of two species configuration modes （A is 5 species of Theaceae， B is 5 species of Theaceae and 2 deciduous broad-leaved tree species） and three E. robusta canopy density （Y1 is 0%， Y2 is 15%， and Y3 is 30%） on the soil physical and chemical properties， enzyme activities， and soil stoichiometric ratios. Among the different tree species configuration mode， the soil capillary water holding capacity， soil capillary porosity and soil void ratio of three soil layers （0-20， 20-40， 40-60 cm） and the total nitrogen N∶P， catalase activity and urease activity of 0-20 cm soil layer in Y3 plot of mode B were significantly higher than those in Y3 plot of mode A （P<0.05）. In different canopy density， the total phosphorus， available phosphorous， available potassium， catalase and urease activity of the three soil layers in the Y3 plot of the A model were significantly higher than those in the Y1 plot （P<0.05）， and the soil organic carbon， total nitrogen， alkali-hydrolyzable nitrogen， available phosphorous， catalase activity and N∶P of the three soil layers in the Y3 plot of the B model were significantly higher than those in the Y1 plot （P<0.05）. In conclusion， the appropriate tree species configuration mode and canopy density are beneficial to the improvement of soil nutrients and enzyme activities， and the pattern of Theaceae tree species and deciduous broad-leaved tree species under 30% E. robusta canopy density has a good prospect of application in the transformation of South China.

Taking the typical frozen soil area of Da Xing'an Ling Huzhong as example， the spatial distibution law of soil carbon storage in the suface layer （0-15， 15-30 cm） was studied. Through field investigation， sampling and indoor anlysis， the reflectance of seven bands based on Landsat 8 OLI images was modeled using the Random Forest （RF） algorithm to analyze the spatial distribution of surface soil organic carbon in the permafrost region of the Da Xing′an Ling. The highest correlation variable was selected among 13 remote sensing variables， and six environmental variables of altitude， ARVI， VIGreen， EVI， OSAVI， NDVI were identified as the highest correlation variables and could be used as independent variables. The results showed that with a leaf value of 5 and a tree value of 900， the training and test sets of the prediction model were closest， indicating that the model stability was the best at this time. The fitting accuracy of training set R ² of 0-15，15-30 cm soil layer was 0.23 and 0.43， the fitting accuracy of test set R ² was 0.35 and 0.24. Using this parameter to predict the spatial distribution characteristics of soil carbon stock in the surface layer （0-15， 15-30 cm）， 0-15 cm and 15-30 cm average soil carbon density was 7.40 kg/m² and 14.80 kg/m²， respectively. The distribution of soil carbon content in 0-15 cm soil layer gradually increased from north to south， and there was no significant difference in soil carbon distribution in 15-30 cm soil layer， but slightly higher in the south than in the north.

Studying the spatial-temporal evolution and driving factors of forest vegetation in the three parallel rivers region can provide data support for building the ecological safety barrier and promoting the social and economic development in Southwest China. The spatial-temporal evolution pattern of forest vegetation in the three parallel rivers region was explored by geospatial analysis， and the evaluation index system was constructed from the two dimensions of ‘natural-social economy’. And 14 specific evaluation indexes （elevation， slope and annual precipitation， etc.） were selected to measure the driving force of the area change of each vegetation type in the study area. The results were as follows， 1） there were three types of forest vegetation in the study area： evergreen broad-leaved forest， deciduous broad-leaved forest and evergreen needle-leaved forest， among which evergreen needle-leaved forest accounted for more than 84% of the forest vegetation. 2） There were three change track of stablility， mutation and fluctuation， among which the stablility type accounted for 80.35% of the changing area. The spatial distribution of “cold-hot spots” in evergreen broad-leaved forest and deciduous broad-leaved forest was similar， and the “cold-hot spots” in evergreen needle-leaved forest showed a trend of cold spots surrounding hot spots. 3） The factor detection showed that the influence of each factor on evergreen broad-leaved forest was greater than others， and the explanation strength for evergreen needle-leaved forest was small. The spatial distribution of forest vegetation in the three parallel rivers region has obvious spatial heterogeneity， and the interaction effect of elevation and other factors on forest vegetation in the study area is significantly stronger than that of single factor detection.

Dioryctria is a kind of pest that seriously harms conifer species and seriously affects the health and growth of conifer trees. The larvae of Dioryctria feed on the leaves of coniferous trees and build nests in coniferous trees. Gradually， they destroy the leaf tissues， causing the needles to turn yellow and eventually leading to the withering of the trees. In addition， larvae may also erode the bark of trees， resulting in bark flaking and trunk exposure， leaving trees vulnerable to other pests， germs and natural elements， increasing the vulnerability of trees and reducing their viability. In order to assist the ground treatment of trees eaten by Dioryctria， the YOLOv8s target detection algorithm was adopted to realize the detection and recognition of the trees eaten by Dioryctria. By using C2f-GAM and dynamic detection head to build a model （YOLOv8-DM）， the detection ability of YOLOv8s against Dioryctria moth trees was improved. The experimental results showed that YOLOv8-DM could effectively identify Dioryctria moth trees with an average accuracy of 84.8%. Compared with other target detection algorithms， YOLOv8-DM has higher average precision.

In order to solve the problem that the target detection algorithm is prone to leakage detection and insufficient detection accuracy in pedestrian detection in forest areas， a forest pedestrian target detection algorithm based on improved YOLOv8 is proposed. The C2f_DWRSeg module is used to replace the C2f module， and the number of initial convolutional channels is expanded so that the network can extract multi-scale features more efficiently. A reconstructed detector head is proposed to increase the complexity of the convolution layer during training， and a single branch structure is used in inference， so as to enrich the feature representation of the network and maintain efficient inference speed； add CGA， the convolution attention mechanism module， before feature fusion， to reduce the amount of calculation； use the Focaler-ShapeIoU loss function to replace the CIoU loss function to make up for the shortcomings of the boundary box regression method and further improve the detection ability. Experimental results show that compared with benchmark model， the improved algorithm mAP50 has increased by 2%， mAP50-95 has increased by 2.4%， and FPS has increased by 4.33%. It proves that the improved algorithm can be better applied to the task of pedestrian detection in forest areas.

To address the issue that traditional semi-supervised self-training classification methods can lead to dataset confusion， affecting the accuracy of subsequent small-sample tree species classification， an EW-EL（entropy weight and ensemble learning） semi-supervised small-sample tree species classification method is proposed based on the entropy weight method（EW） and ensemble learning（EL）. EW-EL introduces the concept of EL into the theoretical framework of traditional semi-supervised self-training classification methods， using the entropy weight method as a foundational theory. It calculates the information entropy based on the F1 score of base classifiers in the current training cycle as a weight factor. Then， design the weights according to the idea that the larger the information entropy， the more unstabel the base classifier will be. This will make the classification probabilities of the ensemble classifier more concentrated and reduce the bias of the ensemble classifier. The findings demonstrate that， in contrast to conventional semi-supervised self-training techniques， EW-EL can efficiently balance data distribution， producing more precise pseudo-label sample categories for recently added data. With a recall of 0.96 and a Kappa coefficient of 0.97， the overall accuracy（OA） of the EW-EL method for small-sample tree species classification is 0.97. All three indicators are superior to supervised classification， conventional semi-supervised self-training techniques， and semi-supervised self-training techniques built using conventional EL mechanisms. In particular， the EW-EL approach outperforms semi-supervised self-training techniques that incorporate a soft voting mechanism in terms of OA and recall by 1%. Furthermore， in the chosen test area， the tree species map produced with EW-EL in combination with basic linear iterative clustering reached 94% accuracy. Moreover， extra analyses show that EW-EL can integrate several classifiers to provide better small-sample tree species classification results， which makes it more appropriate for relevant departments in forestry resource statistics under low-cost circumstances.

To improve the accuracy of non-destructive estimation of volume of trees with complex trunk shapes， this study uses terrestrial laser scanning （TLS） point cloud data and developes a taper-binary volume equation based on the optimal taper model for plantation Mongolian oak. The study was conducted in a Mongolian oak plantation located at the Urban Forestry Demonstration Base in Harbin. Complete point cloud data were collected via TLS， and tree trunk structural parameters were extracted after processes such as clipping， elevation normalization， filtering， individual tree segmentation， and leaf-branch separation. Based on the trunk shape characteristics of Mongolian oak， six taper equation models were tested （Biging（1984）， Amidon（1984）， Meng Xianyu（1982）， Kozak（2004）-Ⅱ， Zeng Weisheng et al.（1997）， Max and Burkhart（1976））， and the best-fitting model was selected through nonlinear regression to construct the taper-binary volume equation. Results showed that the accuracy of individual tree identification was 95.22%， with the coefficient of determination （R²） for extracted tree height and diameter at breast height （DBH） being 0.97 and 0.98， respectively， when compared to field measurements. The optimal taper model achieved an R² of 0.99 and a root mean square error （RMSE） of 0.38 cm. Residual analysis of the Mongolian oak taper-binary volume equation from this study with the existing volume equation showed the reliability of its estimation results. It can provide important technical support for estimating the volume of trees with complex trunk shapes using TLS point cloud data.

Based on the large-span asymmetric small-spacing tunnel project of Pingnan Road in Longgang District of Shenzhen， the internal force changes of tunnel lining are analyzed through on-site monitoring results. A finite element model is established to compare the arch settlement， the stability of the middle rock pillar and the lining stress of the tunnel under different construction sequences. The results show that， the side arch waist and arch foot near the middle rock pillar are the structural instability points during the construction of large span asymmetric small spacing tunnel， and reinforcement treatment is needed in the construction. Compared with the large section first， when the small section of the tunnel is first， the arch settlement， lining bending moment and axial force of the large and small sections are reduced by up to 16.1%， 10.6% and 12.5%， respectively， and the stability of the middle rock pillar is improved. The horizontal stress and vertical displacement are reduced by up to 16.7% and 28.3%， respectively， which is beneficial to the overall safety of the structure. Combined with the comparative analysis of field monitoring data and numerical results， the maximum errors of axial force and bending moment are controlled within 12.5% and 16.5%， respectively. The overall trend of numerical results is basically consistent with the field monitoring results， which verifies the accuracy and feasibility of the calculation model. Therefore， it is reasonable to follow the principle of ‘small section first， large section backward， and backward hole far away from the middle rock pillar area first’ in the construction of large span asymmetric small spacing tunnel.

In order to lessen the environmental issues caused by the accumulation of titanium gypsum and to also alleviate the current situation of road material shortage， titanium gypsum and silane coupling agent-treated titanium gypsum were used to partially or completely replace limestone mineral powder. Additionally， the effects of titanium gypsum and modified titanium gypsum on the conventional and rheological properties of asphalt mastic were investigated. First， a laser particle size meter and a scanning electron microscope were used to examine the micro-morphology and particle size distribution of titanium gypsum， modified titanium gypsum， and limestone mineral powder. Subsequently， asphalt mortar containing varying amounts of titanium gypsum and modified titanium gypsum dosage was prepared. The asphalt mortar's three main indicators （penetration， ductility， and softening point）， as well as its high temperature and low temperature rheological performances， fatigue resistance， were tested using conventional testing methods， temperature scanning test， frequency scanning test， multiple stress creep recovery test （MSCR）， linear amplitude scanning test （LAS）， and bending beam rheological test （BBR）. The findings indicated that： titanium gypsum and modified titanium gypsum had a wider particle size range and a rougher surface. The addition of titanium gypsum and modified titanium gypsum decreased the asphalt mortar's ductility， penetration， unrecoverable creep flexibility （Jnr）， fatigue life （N _f）， creep rate （m） and phase angle （δ）， while the softening point， complex modulus （G*）， resilience （R） and stiffness modulus （S） were increased. In other words， performance at high temperatures was enhanced while low temperatures and weariness were decreased. The low-temperature performance was decreased and the high-temperature performance and elastic recovery indexes of modified titanium gypsum outperformed those of titanium gypsum at the same temperature. The determination of the viability of utilizing titanium gypsum in the creation of asphalt mixtures provides a path forward for the resource's exploitation.

In order to realize the high-value and large-scale utilization of metallurgical solid waste materials， the soil curing agent was synergistically prepared by using metallurgical solid waste materials （blast furnace slag， fly ash， calcium carbide slag and gypsum）， and the effects of different solid waste materials on the mechanical properties of the cured soil were investigated by orthogonal ratio optimization experiments and the optimal parameter formulations were obtained. The mechanical properties （unconfined compressive strength， splitting strength， delayed molding） and weathering properties （water stability， freeze-thaw cycle） of the solidified soil with solid waste-based curing agent （SWC） were systematically studied and compared with PO 42.5 silicate cement （OPC）. The results showed that： calcium carbide slag played an important role in the curing agent system， and the appropriate gypsum dosage had a positive effect on the strength growth； the strength of cured soil increased with the increase of SWC dosage and the age of curing， and the 7 day unconfined compressive strength of the cured soil at 4% dosage was more than 1 MPa， and the splitting strength was basically comparable to that of the OPC cured soil； the SWC cured soil showed a longer allowable delay in construction， and there was no trend of decreasing strength within 12 h after mixing； the water stability coefficient was more than 90% when the dosage was more than 5%， and the anti-freezing coefficient under the same dosage was increased by 3%-5% compared with that of cement， so it had good water stability and anti-freezing property； X-ray Diffraction （XRD） and Scanning Electron Microscope （SEM） analyses showed that SWC cured soils generate expansionary hydration products， calcite alumina （AFt） and hydrated calcium silicate （C-S-H）， during the hydration process， and that calcite crystals played a significant role in improving the cleavage strength of cured soils and increasing the resistance to cracking and deformation.

In tunnel engineering， ensuring the safety of the lining structure is crucial， with internal force analysis and safety assessment being key components. This study analyzed the structural internal forces through numerical simulations and on-site monitoring measurements， calculating the safety factors at critical locations. Given the existence of modeling and measurement errors， this paper introduced a probabilistic model to quantify the uncertainty in estimating safety factors， and normalizes the reconstruction errors of axial forces and bending moments to comprehensively evaluate the suitability of measurement points. Taking a tunnel in Anhui as an example， the study comprehensively analyzed the impact of factors such as the rock pressure sharing ratio， the horizontal rock pressure coefficient， and measurement noise on the estimation of safety factors. The estimated safety factors generally followed a normal distribution trend， with larger fluctuations at the mid-arch and arch shoulder positions. Aiming to reduce estimation uncertainties and biases in the reconstruction of internal force information， measurement points were arranged in accordance with on-site working conditions. Long-term monitoring data indicated that the internal forces in the secondary lining structure fluctuated significantly due to various factors at the initial stage of casting and stabilized after 100 days， ensuring an adequate safety reserve for the structure. This research can provide references for the statistical analysis of safety factors and sensor placement in tunnel lining structures.