199 results about "Tree species" patented technology

The invention discloses a method for generating an aviation lifelike tree sample and identifying a tree species by using an image diffusion model. The method comprises the following steps: constructing a multi-modal data set; training an image-text comparison model and a Unet denoising network model; outputting predicted noise in the trained Unet denoising network model, and finally generating final image reconstruction which is in semantic alignment with the input text description; the obtained single tree crown images are synthesized; and constructing a YOLOv11 detection model, and training the YOLOv11 detection model by using the synthesized forest image to realize tree species identification. According to the method, language semantics and a diffusion model are combined to generate a vivid tree sample for capturing specific features of species and seasonal phenological changes, and the vivid tree sample is synthesized into a high-fidelity forest image, so that tree species identification in an aerial image is enhanced, and effective crown detection and accurate tree species identification are realized.

The invention relates to the technical field of forestry management, in particular to a forest and grass resource dynamic monitoring system which comprises the steps that a graph attention network is adopted to conduct high-low weight recognition processing on the structure difference value between node pairs, feature vectors are established through the canopy height difference and canopy density difference between adjacent nodes, and the canopy height difference and the canopy density difference between adjacent nodes are obtained; an edge weight scoring system is constructed in the form of segmented statistics and proportion weighting, node edge pairs with high influence relation strength are dynamically screened, ordered aggregation of spatial communication strength is realized, a graph neural network is introduced in a parameter fusion stage to construct a node parameter representation mechanism, and the spatial communication strength is improved. The tree species proportion, the grade of diameter at breast height and the community vertical structure in a regional sample plot are used as input features, unified mapping of node features of each region is completed in multiple rounds of iteration, cross-regional difference analysis is executed on model output in combination with biomass change frequency, parameter items with the difference proportion lower than a set threshold value are replaced with unified expression, and the model output is obtained. And parameter synchronization is realized to realize space nesting and feature integration.

The invention provides an intelligent and rapid pre-examination and diagnosis method and system for tree health, and relates to the technical field of tree management. The method comprises the following steps: constructing a liquid flow database of a standard tree of a target tree species, carrying out model training on an established liquid flow calculation model by utilizing the liquid flow database, then collecting liquid flow data of a to-be-detected target tree in a preset detection time and meteorological and soil information of a growth environment, inputting an optimal liquid flow calculation model, and calculating a theoretical liquid flow value of the target tree, comparing with an actually monitored liquid flow value, calculating a liquid flow deviation degree, grading according to a daily maximum liquid flow deviation degree, and comprehensively evaluating a tree health grade in combination with phenotype information to obtain a diagnosis result; the rapid and intelligent pre-examination diagnosis of the tree health is realized, and the intervention timeliness is improved; and multi-dimensional data fusion is adopted, so that the diagnosis accuracy is improved, and automatic monitoring and real-time early warning are realized.

The invention provides a tree species screening method for high-altitude drought afforestation, an afforestation method and application, and belongs to the technical field of forest tree breeding and cultivation. According to the screening method, five physiological and biochemical indexes of soluble protein, malondialdehyde, proline, peroxidase and soluble sugar in the tree species are measured through a gradient drought stress experiment, and comprehensive scoring is performed by adopting a membership function, so that the drought-resistant tree species are scientifically screened. The tree species such as sophora moorcroftiana, rosa serrulata and amorpha fruticosa screened by the method are applied to afforestation in the high-altitude arid region, and the afforestation survival rate and preservation rate can be remarkably increased. The invention provides a reliable technical scheme for solving the long-term problem that the selection of tree species in the difficult site field lacks scientific basis.

The invention relates to the technical field of power line monitoring, and discloses a tree growth prediction method, system and device based on a multi-temporal point cloud and a growth model, and a medium, and the method comprises the steps: collecting the multi-temporal data of a target region, carrying out the vegetation region recognition and single tree segmentation of a vegetation point cloud, extracting the structural features of each tree, and carrying out the prediction of the growth of each tree; generating a time sequence characteristic data set; constructing a tree growth model, taking the time sequence characteristic data set as model input, introducing a point cloud structure parameter as a dynamic constraint item, and performing parameter optimization on the model to obtain a prediction curve of a multi-dimensional growth index of the tree; and based on the prediction curve of the multi-dimensional growth indexes, performing dynamic geometric reconstruction through original point cloud data, and generating an interactive visual three-dimensional model. According to the method, on the basis of multi-source heterogeneous point cloud data, the single-tree-level growth model can be constructed, the time sequence structure change trend of the single-tree-level growth model is analyzed, and the space error and the time stability of a prediction result are quantified.

The invention discloses a natural secondary forest tree species classification method based on multi-modal data fusion. The method comprises the following steps: S1, building a tree species space-spectrum feature extraction module; s2, building a tree canopy global context sensing fusion module; s3, building a tree perception detail optimization module; s4, building a tree species classification network based on multi-modal data fusion; s5, after the tree species classification network with multi-modal data fusion is built, corresponding hyperspectral and laser radar data sets are used for training and testing; according to the method, the problems of fuzzy crown boundary, difficulty in distinguishing tree species with similar structures and low classification precision caused by difficulty in considering long-distance global dependence modeling and fine-grained local detail reservation when an existing tree species classification technology is used for processing a complex forest stand environment are solved.

The invention discloses a forest fire danger early warning system and method based on meteorological and vegetation data analysis, and relates to the technical field of fire risk prediction and control. According to the forest fire danger early warning system and method based on meteorological and vegetation data analysis, fine grid division is carried out on a target forest area through a high-resolution DEM and a multispectral or hyperspectral image, and vegetation type identification is carried out on each monitoring subunit; calculating a wet-dry cycle index WDI, a monsoon effect index MFI and a dry thunderstorm risk factor DRF by combining hourly wind speed, wind direction, relative humidity, precipitation and vapor pressure difference meteorological data; through extracting canopy height, canopy density, under-forest shrub and grass layer thickness and high VOC tree species coverage rate, fuel continuity coefficient FCI and volatile matter flammability index VEI are calculated, and accurate quantification of continuity and flammability of vertical ladder fuel and horizontal canopy is realized. And a comprehensive fire danger index FFI is constructed and subjected to hierarchical management after judgment, so that the dynamism, the hierarchical property and the pertinence of fire danger early warning are realized, and the forest fire danger prevention and control precision and the patrol resource utilization efficiency are improved.

The invention relates to the technical field of biological fireproof forests, and discloses a design method for a biological fireproof barrier forest belt, which comprises the following steps of: 1, designing a biological fireproof forest belt based on the canopy density of 0.2-0.5 of a broadleaf mixed forest by taking the existing forest stand type as the broadleaf mixed forest, screening suitable fireproof tree species by integrating site conditions, natural environment and hydrothermal conditions of the biological fireproof forest belt of the broadleaf mixed forest; 2, cleaning and soil preparation are conducted on a biological fireproof forest belt to form a hole belt-shaped area, comprehensive complementary planting is conducted on fireproof tree species, the complementary planting density of a broad-leaf mixed forest is 2520 plants per kilometer as tree planting points, the fireproof tree species are planted in the hole belt-shaped area through the tree planting points, and the fireproof tree species are planted in the hole belt-shaped area; after planting, a compound fertilizer is used for topdressing, so that the fireproof tree seeds absorb fertility to accelerate the growth speed.

The present application relates to the technical field of land greening data management, in particular to a land greening system data information management method, comprising: arranging an ecological perception network composed of multiple source sensors in a target administrative region to collect vegetation physiology and soil environment data; carrying out denoising, interpolation preprocessing, standardization and coordinate system conversion in a data processing center to form a standardized basic ecological data set. Based on the data set, an attribute library containing multi-dimensional information such as tree species is constructed with a single plant or a reforestation plot as the smallest management unit, a dynamic three-dimensional green volume voxel model is generated in a geographic information system to reflect the spatial distribution of land greening resources. The model is used to calculate the carbon fixation and oxygen release potential values of different functional divisions, and a planning decision engine is called to generate suggestions for replanting or reforming in low potential value areas. The method effectively improves the data information processing efficiency, calls the planning decision engine to generate land greening implementation suggestions, and quickly and dynamically updates the land greening system data information.

This invention belongs to the field of remote sensing technology and relates to a method for predicting canopy combustible moisture content (CFMC) by combining remote sensing CFMC products and meteorological data. Specifically, through global two-stage sensitivity analysis, key input parameters for different tree species in the MEDFATE model are identified. Using these parameters, a cost function is constructed to measure the error between the CFMC simulated by the MEDFATE ecophysical process model and the CFMC measured in the field, achieving species-based localized correction of MEDFATE. Then, through four-dimensional variational data assimilation technology, the remote sensing CFMC product is combined with the localized MEDFATE. This achieves enhanced CFMC simulation, improving the accuracy of MEDFATE CFMC simulation while also increasing the temporal resolution of remote sensing data and the spatial resolution of the MEDFATE model. With accurate meteorological forecast data, effective daily CFMC prediction of vegetation can be achieved.

This invention discloses a method for establishing a high-efficiency leaf regeneration system for aseptic seedlings of Populus tomentosa 'Bofeng No. 3', belonging to the field of agricultural biotechnology. This invention, through 5-AU combined with dark culture treatment, not only induces early leaf differentiation in aseptic seedlings of Populus tomentosa 'Bofeng No. 3', but also significantly increases the number of adventitious buds and the rooting rate. Through chemical treatment and optimized culture conditions, this invention successfully established a high-efficiency plant regeneration system for aseptic leaves of Populus tomentosa 'Bofeng No. 3', laying the foundation for the genetic transformation and gene editing of Populus tomentosa 'Bofeng No. 3', and also providing a reference for the establishment of tissue culture systems for other tree species.

The invention relates to the technical field of distribution line tools, in particular to a tree pruning device for a distribution line and an automatic control method. In the device, a control box is connected below a walking box, a walking mechanism and a first servo motor are arranged in the device, the motor is connected with a rotating plate, and the rotating plate is connected with the control box through an electric telescopic rod to achieve lifting rotation; telescopic cylinders are arranged on the two sides of the control box, two-stage telescopic cylinders in the cylinders are driven by threaded rods driven by a second servo motor and the threaded cylinders to stretch out and draw back, a cutting knife is arranged at the front end, and a multi-data and control module is arranged outside the control box. The control method comprises the following six steps: S1, collecting tree form and cutting knife operation data, and quantifying the correlation degree by using a distance formula; s2, processing the data to improve a normalization formula to extract an adjustment reference; s3, calculating a position and parameter adaptation value by using a composite correlation formula, and counting a trend to obtain pre-processed data; s4, comparing the pruning progress of the same tree species; s5, fusing data output adjustment features such as safety standards; and S6, calculating the fault frequency and the adjustment priority, and outputting an execution instruction to realize safe and automatic trimming.

The invention discloses an unmanned aerial vehicle remote sensing tree species classification method and system fusing a cascade canopy attention mechanism, and the method comprises the steps: obtaining unmanned aerial vehicle RGB image data of a campus scene, carrying out the preprocessing of the data, and obtaining a standardized input image; constructing a classification model fusing the cascaded canopy attention mechanism, wherein the classification model comprises a background suppression module, a fine-grained feature guide module, a channel alignment neck module and a global-local fusion classification head; inputting the standardized input image into a classification model, and obtaining an enhanced canopy image through a background suppression module; inputting the enhanced canopy image into a module carrying fine-grained feature guidance, and extracting fine-grained canopy features; performing channel calibration and feature smoothing on the fine-grained canopy features through a channel alignment neck module to obtain feature mapping of a unified dimension; and fusing the global canopy semantics and the local texture structure in the feature mapping by using a global-local fusion classification head, and outputting a tree species classification result.

The application discloses a prediction method of tree species structure of arbor forest in subtropical areas, and comprises the following steps: 1) dividing the tree species of arbor forest into three categories of pines, firs and broad-leaved trees, and establishing a prediction model according to volume proportion data of each tree species category obtained from fixed sample plots in previous forest resource surveys; 2) taking two-period survey data as modeling data, and fitting parameters by using STATA software; 3) substituting measured data of each sample plot into the prediction model for iterative calculation, obtaining volume proportion values of the future arbor forest in the two-period interval as prediction values; calculating average prediction values of the prediction values of the tree species proportions of all sample plots; and 4) comparing the prediction value of the volume proportion of the broad-leaved trees or the sum of the prediction values of the volume proportions of the pines and firs in the average prediction values of the tree species proportions with a critical value of coniferous and broad-leaved mixed forest, and determining whether artificial intervention needs to be applied in actual forestry management. The application can predict the tree species structure of arbor forest in future years, and has the function of guiding forestry production and operation activities.

The invention relates to the field of plant genetic engineering, and particularly discloses a soapberry SmCYCD3; 2 gene and application thereof. The nucleotide sequence of the gene is shown as SEQ ID NO: 1, and the sequence of the protein coded by the gene is shown as SEQ ID NO: 2. Experiments show that the gene has high specificity expression in female flowers of soapberry. By heterologous overexpression of the gene in arabidopsis thaliana, typical'female promotion and male inhibition 'phenotypes such as pistil elongation, stamen number reduction and shortening, pollen viability reduction and small fruit pods of transgenic plants can be caused. Molecular mechanism studies show that: SmCYCD3; 2, performing functions by up-regulating expression of cell cycle related genes and pistil development genes AtCRC and down-regulating expression of stamen development key genes at the same time; the invention provides a key gene resource and a theoretical basis for directionally regulating and controlling the sex ratio of plant flowers through a molecular breeding means and improving the fruit yield of woody economic tree species.

The application relates to the technical field of pest and disease identification, in particular to a dynamic early warning and prevention and control system based on forestry pest and disease identification, which obtains crown layer leaf attribute data of target forest area tree species and excitation source physical characteristic parameters of a patrol unmanned aerial vehicle, determines aerodynamic pressure required for turning over of the crown layer leaves according to the leaf attribute data, determines aerodynamic excitation control parameters in combination with the excitation source physical characteristic parameters and a final parameter mapping model, controls the unmanned aerial vehicle to force the leaves to turn over by using a downward airflow to obtain leaf back image data, and adaptively corrects the control parameters according to an effective leaf back exposure rate; image recognition is performed on the leaf back image data to obtain pest and disease characteristic data, and a leaf stiffness index is calculated through time domain analysis; pest and disease severity is generated according to the pest and disease characteristic data and the leaf stiffness index, and a graded early warning is performed; the application can effectively obtain leaf back image information, and realizes early and accurate identification and dynamic early warning of pests and diseases.

The utility model relates to the technical field of tree species collection, and discloses a forest tree species collection device which comprises a rectangular plate, L-shaped rubber plates are arranged at the corners of the rectangular plate, and idler wheels are arranged on the L-shaped rubber plates. A vertical plate is arranged at one end of the rectangular plate, and soft bags are connected to the rectangular plate, the L-shaped rubber plate and the vertical plate. A feeding hole matched with the soft bag is formed in the vertical plate; a discharging barrel is arranged at one end, far away from the feeding hole, of the soft bag; the end, close to the vertical plate, of the soft bag is movably provided with a dragging rod capable of dragging the device to move. Compared with the prior art, the forest tree planting rack has the advantages of being convenient to move in a forest and capable of containing tree species.

The invention discloses a method for extracting tree information in a power transmission line channel based on multi-source remote sensing data, and relates to the technical field of remote sensing data processing, and the method comprises the following steps: screening a tree distribution space based on the spectral characteristics of a target region, and inputting image data with the tree distribution space as a constraint into an improved D-UNet model; a convolution attention branch in the improved D-UNet model is used to generate an attention feature map; extracting global and local context features by improving parallel multi-scale pooling branches in a D-UNet model; performing weighted fusion on the context features by using the attention feature map to generate context enhanced features, and outputting a tree species classification result after decoding; and generating comprehensive tree information in combination with the tree species classification result and the tree geometric height obtained based on the target area point cloud. The method is used for solving the problem that the refined hidden danger evaluation requirement is difficult to meet due to low tree identification precision in the prior art.

The invention belongs to the technical field of ecological restoration, and particularly relates to a standardized mangrove forest ecological restoration system after a typhoon disaster. According to the method, the disaster degrees of the mangrove forest damaged by the typhoon are divided into severe disasters, moderate disasters and mild disasters on the basis of remote sensing images and field investigation; for severe disasters, lodging forest classification cleaning operation and landform restoration are implemented, big seedlings are selected for field planting in combination with tidal flat elevation, and reconstruction of a standardized mangrove forest ecological system is formed; in allusion to moderate disasters, pruning and complementary planting operation based on forest gaps are carried out, and the recovery efficiency of the primary forest stand is improved; for mild disasters, the forest stand canopy density is dynamically monitored by adopting an unmanned aerial vehicle, and corresponding grade intervention is adopted, so that accurate restoration is realized. According to the method, indigenous tree species are adapted based on the tidal flat environment and salinity, differential remediation operation is adopted, collaborative reconstruction of the mangrove forest ecological system structure and the coast protection function is achieved, and a standardized operation system breaks through limitation of traditional remediation.

The utility model relates to the field of garden planting, especially garden greening engineering is used planting equipment. Including support and connecting structure, the upper end fixed connection of support has a plurality of connecting frames, the one end fixed connection of connecting frame is away from support has hydraulic pressure rod, the output of hydraulic pressure rod installs the connecting piece, the inside fixed installation of connecting piece has servo motor, the lower extreme of servo motor is provided with drill bit, the drill bit is connected with support and servo motor by connecting structure, and the output of servo motor is equipped with connecting structure, the connecting structure includes the card piece, the card piece is fixedly connected with the output of servo motor, the inside fixed connection of support has two link rods. The utility model provides a kind of planting equipment for garden greening engineering, drill bit can be directly replaced quickly, satisfy the direct demand of a variety of tree species, greatly improve the applicability of the equipment.

The invention relates to the technical field of ecological restoration, in particular to an ecological restoration method for a marsh wetland patrol road slope. Experiments show that compared with other tree species (salix procumbens), the survival rate of the salix procumbens in the marsh wetland patrol road side slope is higher, and the salix procumbens has a more excellent slope fixing effect. Furthermore, the length and the thickness of the willow branches are optimized and adjusted, the willow branches with the proper diameter at breast height and the proper length are finally selected for cuttage, the survival rate is remarkably increased, and the slope fixing effect is remarkably improved. Water and soil loss can be effectively reduced, stable vegetation coverage can be formed in a short time, and reliable technical support is provided for ecological restoration of marsh wetland patrol road slopes.

The invention discloses a tree species identification method based on multi-modal spectrum and texture features of a wood cross section. The method comprises the following steps: acquiring hyperspectral image data of the wood cross section; constructing a comprehensive similarity matrix based on a plurality of spectrum similarity indexes, and selecting a representative wave band subset from the hyperspectral image data by adopting a multi-strategy wave band screening mechanism; performing multi-scale wavelet fusion on the representative wave band subset to generate a single-channel fusion image with consistent spatial resolution, and extracting points of interest and spectral features thereof from the single-channel fusion image; generating a gray-scale base map based on the hyperspectral image data, extracting various complementary texture feature maps from the gray-scale base map, and screening out significant points of interest from the various texture feature maps; and fusing the spectral features and the texture features, constructing feature vectors for representing wood tree species, and inputting the feature vectors to a classification model to complete tree species identification. According to the invention, rapid, accurate and intelligent identification of wood tree species can be realized.

The invention discloses a method for researching the influence of phosphorus tailing blending and water and fertilizer regulation on ecological restoration tree species growth and soil microenvironment, and relates to the technical field of mining area ecological restoration and solid waste resource utilization. Complete combination design is carried out through a pot experiment; then measuring tree species growth indexes, biomass, soil physicochemical properties and microbial community structures; finally, analyzing an interaction mechanism of the phosphate tailings, the water fertilizer and the microorganisms by using variance analysis and redundancy analysis; the system provided by the invention evaluates the feasibility of the phosphate tailings as an improved matrix, defines the optimal mixing ratio and water-fertilizer ratio adapted to different tree species, and reveals the mechanism of'phosphate tailings-water-fertilizer-microorganism 'synergistic drive vegetation recovery. And a scientific basis and a technical support are provided for high-value utilization and accurate regulation and control of the phosphate tailings in ecological restoration of a mining area.

The invention provides an urban wind speed monitoring and assimilation method and system based on tree swing features. The system comprises an image acquisition module, an image processing and feature extraction module, a model training and storage module, a wind speed inversion module, a data assimilation module and a data storage and visualization module. Comprising the following steps: deploying a camera in a target area; collecting a tree image sequence by using a camera; extracting swing characteristic parameters of different tree species based on the tree image sequence; constructing swing-wind speed mapping models of different tree species based on the swing characteristic parameters of different tree species and tree attributes; inverting urban wind speed distribution based on the swing-wind speed mapping model; and assimilating the wind speed distribution into an urban wind field mode. The method has the advantages that urban-scale refined wind speed monitoring is achieved through existing camera resources, the spatial-temporal resolution of wind speed data is improved, and powerful support is provided for urban meteorological service, disaster prevention and reduction and the like.

The invention discloses a lumbering-free live tree stump-carried edible and medicinal mushroom method, and belongs to the technical field of edible and medicinal mushroom cultivation. The method comprises the steps of tree seed selection, tree stump pretreatment, inoculation opening formation, special wood-rotting fungus liquid seed preparation, two-time inoculation and covering, cultivation management, mushroom bud cultivation and harvesting and drying processing. The method comprises the following steps: selecting trees suitable for cut-log cultivation, forming a three-shaped inoculation opening in the base part of a tree stump, sequentially inoculating special wood-rotting fungus liquid seeds and target edible and medicinal fungus liquid seeds, realizing symbiosis of hyphae and live trees through fallen leaf covering and moisturizing and ecological management, and harvesting mature sporocarps 24-28 months later, and drying and processing the mature sporocarps. Long-term fruiting can be achieved through one-time inoculation, the yield is stable, operation is easy and convenient, the production cost is low, produced edible and medicinal fungus products are safe and high in quality, the method is suitable for large-scale popularization in mountainous areas and orchards and forest lands, and the industrial ecological benefits and economic benefits are remarkably improved.

This application provides a method and apparatus for inverting the leaf area index (LAI) of a forest. The method first acquires information about the tree height and the total attenuation coefficient of each component in the forest to electromagnetic waves. The total attenuation coefficient includes the attenuation coefficients of leaves and branches. Then, based on the tree height and the total attenuation coefficients of each component, the product of the total attenuation coefficients is calculated. Finally, the LAI is inverted using the relationship between the product of the total attenuation coefficients and the LAI. This method utilizes the attenuation characteristics of the forest to electromagnetic waves to invert the LAI. Since the attenuation of electromagnetic waves is not affected by tree species, region, complex meteorological conditions, or the chosen mathematical model, it can more accurately reflect the attenuation of electromagnetic waves by the leaf area. Therefore, the accuracy of the LAI inversion using this method is higher.

This application discloses a fire early warning method based on multidimensional forest health status analysis, belonging to the field of forest fire prevention technology. The method includes: acquiring multidimensional observable data for each assessment unit in a target forest area; inputting the multidimensional observable data into a pre-constructed hybrid prediction model, outputting a comprehensive flammability risk index for each assessment unit within a specified future time period, and generating a visualized spatiotemporal distribution map on a GIS map; wherein the hybrid prediction model calculates the flammability probability of each tree species using a single-tree physical mechanism model, obtains a stand risk index using a spatial weighted aggregation algorithm, outputs a landscape-level probability through a landscape-level risk prediction network, and performs weighted fusion of three sources of uncertainty based on traditional empirical paths; and issuing early warning information based on the spatiotemporal distribution map. This application combines physical mechanisms with transfer learning to achieve rapid adaptation with few samples and accurate prediction at multiple scales, providing reliable decision support for forest fire prevention.

The invention discloses a phoebe bournei stem in-vitro rapid propagation method, and relates to the technical field of forest tree tissue culture.The phoebe bournei semi-wood branch is used as an explant, two reagents are used for double-effect sterilization, and a sterile material is rapidly and efficiently obtained; plant growth regulators with different component combinations and concentrations are added for systematic research on axillary bud induction culture, adventitious bud subculture multiplication culture and rooting culture, and browning prevention and control and strong seedling culture tests are further carried out aiming at the browning phenomenon of phoebe bournei cluster buds in the adventitious bud subculture multiplication culture process; according to the method, effective measures for preventing phoebe bournei subculture browning and a method for improving seedling quality are screened, a phoebe bournei stem in-vitro rapid propagation technical system is successfully constructed, a reliable method is provided for phoebe bournei precious resource preservation and large-scale propagation, and a technical reference is provided for in-vitro culture research of other phoebe tree species.

A method for producing printed wood veneer sheets comprises capturing high-resolution digital images of source wood veneer using polarized lighting and a digital camera with a polarizing filter; digitally processing and aligning the images to create a seamless composite image with enhanced color and grain detail; and printing the composite image directly onto a natural wood veneer substrate using a large-format UV flatbed printer with UV-curable inks. The method enables replication of rare, endangered, or extinct wood species on sustainable substrates while preserving the tactile qualities of natural wood and achieving superior visual fidelity. The printed veneer sheets may be used in furniture, cabinetry, architectural millwork, and other applications.

The present application relates to a kind of tree species identification method based on spectral orthogonal transformation and multivariate filtering, comprising the following steps: S1, the high spatial resolution remote sensing image of forest area is collected, and pretreatment is carried out;S2, preliminary interpretation is carried out to the image after pretreatment, and tree species sample is obtained in combination with field investigation, tree species sample is marked on the image after pretreatment, and is divided into training sample and verification sample;S3, the spectral band of remote sensing image is orthogonally transformed, and a set of two two orthogonal feature layers are generated;S4, multivariate filtering processing is carried out to the layer after orthogonal transformation, and filter feature is extracted, and hybrid feature set is constructed;S5, based on hybrid feature set, tree species is identified using machine learning classification method, and classification result and precision statistics are output.The present application reduces the correlation between layers by orthogonal transformation of multispectral data, then highlights the difference of tree species by four filters of texture, low-pass, median and enhanced Lee, to promote the identification of tree species.