78 results about "Diameter at breast height" patented technology

The invention relates to a forest tree diameter at breast height and tree height measurement method based on double-layer unmanned aerial vehicle laser radar point cloud fusion in a complex under-forest environment, and belongs to the technical field of forestry measurement. According to the method, multi-source point cloud registration fusion is carried out based on feature point matching and a weighted fusion algorithm; generating a ground DEM and carrying out point cloud height normalization; carrying out individual tree segmentation by adopting an improved mark control watershed algorithm; constructing a multi-dimensional feature vector for each tree, and calculating each feature; extracting a tree height based on the fused point cloud; an effective point cloud coverage index is introduced to judge the effectiveness of a 1.3 m height point cloud, weighted least square circle fitting is adopted to directly extract the diameter at breast height, and a pre-trained multi-feature fusion gradient lifting model is adopted to estimate the diameter at breast height for a tree with point cloud missing. According to the method, complete stand three-dimensional data is obtained through multi-source point cloud fusion, a multi-dimensional feature system is constructed, a complete mathematical calculation framework is established, and the technical problem that the diameter at breast height cannot be accurately measured due to complex under-forest shrub and grass shielding is effectively solved.

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 discloses a method for estimating overground biomass of a fresh songarus apetalus plant through photography. The method comprises the steps that five-lens oblique photography equipment obtains images of the fresh songarus apetalus plant land in the front view direction and the front, back, left and right directions; based on an improved CatBoost algorithm and the geographic position, the diameter at breast height, the crown breadth and the tree height of each tree, a geographic position weighted tree growth parameter nonlinear mapping model is constructed, and the tree growth parameter nonlinear mapping model is used for obtaining the diameter at breast height according to different geographic positions, the tree heights and the crown breadth; acquiring an image of a to-be-estimated fresh songarus apetala plant field in front view and front, back, left and right directions; the predicted diameter at breast height and the corresponding tree height are obtained from the obtained image, and the above-ground biomass of the fresh songarus apetalus plant of the image is obtained through calculation of the predicted diameter at breast height and the corresponding tree height based on a different-speed growth equation. According to the method, the overground biomass of the fresh songarus apetala plants can be estimated through low-cost and high-efficiency photography.

The invention relates to a high-precision single tree segmentation method based on multi-source point cloud data, and the method comprises the steps: building a high-density point cloud data set through the cooperative collection of an unmanned plane and a knapsack laser radar, carrying out the data preprocessing through the multi-site ICP registration and CSF filtering, carrying out the semantic segmentation based on an Enhanced Tree Instance Net network, and carrying out the segmentation of a single tree. Through feature contribution analysis and dynamic scene adaptive optimization segmentation data, semantic and geometric features are fused to realize individual tree instance segmentation, a physical constraint neural network is introduced to realize multi-parameter collaborative inversion of tree height, diameter at breast height, crown breadth, tree age and the like, it is ensured that the parameters conform to tree growth rules, precision evaluation and calibration are performed through a multi-level index system, and tree growth accuracy is improved. And finally realizing visual expression of a segmentation result and forest stand parameters. According to the method, the individual tree segmentation precision and the growth rule rationality are remarkably improved, and the method is suitable for urban forest carbon sink accurate measurement and intelligent forestry management.

The invention relates to the technical field of forest resource investigation and monitoring, and discloses a natural forest multi-source point cloud registration method and system based on point cloud segmentation optimization, and the method comprises the steps: laying a sample plot, collecting the diameter at breast height, the height and the crown breadth of a single tree, and obtaining the space coordinates of the single tree in combination with RTK; according to the method, unmanned aerial vehicle laser scanning and backpack laser scanning are adopted to collect and preprocess point cloud data of a research area, an ICP algorithm is adopted to align a source point cloud with a target point cloud through rotation and translation, point cloud registration is achieved through a minimization error function, point cloud registration precision and errors are quantified through evaluation indexes, and point cloud registration evaluation is carried out. Therefore, the point cloud registration precision is effectively improved through a segmented registration strategy, limitation caused by single sensor data can be overcome through fusion of BLS and ULS multi-source point cloud data, the extraction precision of tree structure parameters is remarkably improved, and the method is not only suitable for point cloud registration of natural forests, but also suitable for point cloud registration of natural forests. And reliable data support and technical support are provided for forest resource monitoring and ecological protection.

The invention discloses a forest stock calculation method based on three-dimensional point cloud data and a neural network, and the method comprises the steps: carrying out the preprocessing of point cloud data, including point cloud denoising, filtering and normalization, and removing the redundant data, such as the surrounding ground feature environment and non-ground points, except for single tree information; a mark control watershed algorithm based on morphological filtering is adopted to mark a crown center point, individual tree segmentation is achieved, and individual tree parameters such as individual tree diameter at breast height, tree height and crown breadth are extracted; a neural network volume inversion model is established, the model takes the individual tree parameters as an input layer and the forest volume as an output layer, and an optimization algorithm is adopted to optimize the training process; and estimating the forest stock by using the stock inversion model, inputting the diameter at breast height, the tree height and the crown breadth in the sample plot checking data into the model, and outputting a forest stock estimation result.

The invention discloses a forest tree DBH (diameter at breast height) inversion method based on a multispectral remote sensing image, which relates to the technical field of remote sensing information inversion, and comprises the following steps of: performing radiometric calibration and geometric correction processing on original multispectral observation data, generating a standardized multispectral data set, and performing single tree identification and canopy segmentation processing to obtain a tree DBH (diameter at breast height); generating single-plant tree crown image data; combining the illumination direction features with the red-edge wave band and the near-infrared wave band, performing multi-scale feature analysis and fusion processing, and outputting canopy feature data; performing nonlinear processing and illumination correction on the canopy feature data to generate breast diameter prediction data; and carrying out space mapping and visual mapping processing on the diameter at breast height prediction data to generate a diameter at breast height distribution diagram result, carrying out precision evaluation and quality inspection processing, and outputting a forest tree diameter at breast height inversion result. The stability, the precision and the environmental adaptability of the breast diameter inversion are improved, and high-reliability technical support is provided for forest structure monitoring and resource evaluation.

Embodiments of the present description provide a carbon sink assessment method and apparatus for a target forest region. The method comprises: on the basis of laser echo signals collected for a target forest region, predicting a first tree feature of the target forest region, wherein the first tree feature is used for indicating tree heights at sampling points in the target forest region; on the basis of optical images collected by a camera for a plurality of sampling areas in the target forest region, determining a second tree feature corresponding to each of the plurality of sampling areas, wherein the second tree feature is used for indicating the number, species, and diameter at breast height of trees included in the corresponding sampling area; on the basis of the first tree feature and the second tree feature corresponding to each of the plurality of sampling areas, predicting a first aboveground biomass of the target forest region; and on the basis of the first aboveground biomass, predicting a carbon sink stock of the target forest region.

The invention discloses a method and a system for automatically measuring the diameter at breast height of a forest based on a millimeter-wave radar network, particularly relates to the technical field of radar signal processing and target detection, and is used for solving the problem of inaccurate forest identification and diameter at breast height measurement caused by false point clouds generated by multiple signal reflections of the existing millimeter-wave radar in a complex forest environment. An initial three-dimensional point cloud is obtained by deploying a millimeter wave radar network, and potential trunk points and suspected false points are identified; suspected points which are gathered around tree trunk anomalies are screened out, and multi-view observation angle information of the suspected points is obtained through network multi-node observation geometry; fitting the optimal spatial position of each point and calculating an observation residual error; and finally, screening and eliminating geometrically inconsistent false points according to residual distribution, and realizing accurate identification and breast diameter extraction of the forest based on the purified point cloud. Interference of multipath reflection false point clouds is effectively suppressed, and reliability and precision of automatic breast diameter measurement of a millimeter wave radar network in a dense forest region are improved.

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 utility model relates to the technical field of forestry investigation, and discloses a tree breast diameter measuring device for forestry investigation, which comprises a long rod, a box body is arranged at the upper end of the long rod, a cog belt is arranged in the box body, two belt wheels are symmetrically arranged in the cog belt, the two belt wheels are both rotatably arranged in the box body, and the cog belt is arranged in the box body. Two buckles are arranged on the toothed belt, the two buckles and the two belt wheels are arranged at intervals, one side of each buckle is fixedly connected with a sliding block, the sliding blocks are arranged on a sliding way in the box body in a sliding mode, the two sliding blocks are each provided with a clamping rod, one belt wheel is connected with a motor, and the other belt wheel is connected with a clamping rod. On the basis that the diameter at breast height of a trunk at a lower position can be conveniently measured, the front end of the long rod is lifted to the trunk at a higher position, the two clamping rods are close to each other until the trunk is clamped, the diameter at breast height of the tree is obtained through the distance between the two clamping rods, the diameter at breast height of the trunk at the higher position can be conveniently measured, and the application range of the measuring device is expanded.

The invention discloses a tree growth amount three-dimensional form intelligent generation system and method based on multi-dimensional data, and relates to the technical field of plant three-dimensional modeling and forestry information. Tree height, diameter at breast height, ground diameter, multi-year climate and east-south-west-north four-direction annual ring spacing data are collected through the data input module, and after the data are processed through the data processing module, radial annual ring width data and historical environment data are combined through the growth inversion and fusion module. A spatial historical growth difference coefficient matrix is calculated through inversion of a spatial growth inversion model, after a three-dimensional morphology generation module receives the matrix, a final growth difference coefficient is generated in combination with a species inherent morphology parameter matrix, and a parametric modeling engine is driven to generate three-dimensional models of branches, leaf clusters and root systems in a differentiated mode. The result output module outputs a parameterized three-dimensional model; the problems that traditional tree three-dimensional modeling neglects orientation growth difference and is weak in environment relevance are solved, and differentiation tree three-dimensional form intelligent generation is achieved.

The utility model belongs to a tree diameter at breast height and height surveying device, and particularly relates to the technical field of tree surveying, which comprises a machine body, a height measuring assembly is arranged on the outer top surface and the left end of the machine body, a diameter at breast height measuring assembly is arranged on the left end of the outer bottom surface of the machine body, and a grip is fixedly arranged on the right end of the outer bottom surface of the machine body. A square plate is fixedly connected to the outer bottom face of the grip, a clamping and fixing assembly is arranged on the outer wall of the left side of the square plate, a rope can be wound around and attached to a tree by a circle through the arranged positioning square cylinder and then is connected with a rope head in a clamped mode, then the rope is prevented from being automatically recycled, and therefore the situation that the rope head needs to be continuously pulled is avoided; and the workload of a user is reduced.

The invention discloses a larch single tree segmentation and phenotype extraction method based on unmanned aerial vehicle multi-source remote sensing, and relates to the technical field of forestry remote sensing. The method comprises the following steps: firstly, synchronously acquiring visible light, a multispectral image and laser radar point cloud data through an unmanned aerial vehicle; then, a dynamic sparse gating multi-modal feature fusion network is constructed, key features of different data sources can be adaptively focused for effective fusion, and accurate larch individual tree instance segmentation is achieved; and finally, automatically extracting phenotype parameters such as tree height, crown breadth, canopy area and diameter at breast height based on a segmentation result. According to the method, multi-source data fusion, individual tree segmentation and phenotype extraction are integrally completed through an end-to-end deep learning model, the problem of accurate segmentation of larch individual trees in a complex scene is solved, and the efficiency and precision of forestry investigation are remarkably improved.

This invention belongs to the field of geographic information technology, specifically relating to a non-destructive estimation method for standing timber volume based on LiDAR. The method includes: acquiring three-dimensional information of a portion of sample trees to obtain point cloud data; manually measuring a portion of the sample trees after pruning to obtain manual measurement parameters; preprocessing the point cloud data; calculating the volume of the base segment of the sample trees based on the preprocessed point cloud data; calculating shape parameters based on the manual measurement parameters; calculating the volume of the upper segment of the sample trees using the BCTEM model based on the shape parameters and point cloud data; calculating the sum of the base segment volume and the upper segment volume as the standing timber volume of the sample trees; calculating the tree height and diameter at breast height (DBH) of the sample trees; constructing a standing timber volume equation based on the standing timber volume, DBH, and tree height of the sample trees; and using the standing timber volume equation to achieve non-destructive estimation of the standing timber volume of trees similar to the sample trees. This invention solves the problem of inaccurate or impossible trunk measurement due to canopy shading and has good application prospects.

This invention relates to the field of forestry technology and discloses a method for regulating the cultivation of *Machilus chinensis* in forest gap microenvironments. The method includes: constructing a digital twin of *Machilus chinensis* plants by fusing lidar point cloud data, multispectral time-series data, and soil microenvironment parameters; calculating a comprehensive competition index based on three dimensions: light shading, nutrient competition, and spatial expansion potential; generating a graded thinning priority sequence by combining forest gap boundary characteristics and target retention density; and outputting a structured instruction set containing geographic coordinates, diameter at breast height (DBH) grade, and felling order. This invention achieves quantitative, precise, and traceable thinning operations, improving the growth efficiency and resource utilization level of *Machilus chinensis*.

This utility model discloses a novel tree diameter at breast height (DBH) measuring device, comprising a first arc-shaped clamping rod and a second arc-shaped clamping rod. One end of the first arc-shaped clamping rod is a first measuring head, and the other end is a first grip handle. One end of the second arc-shaped clamping rod is a second measuring head, and the other end is a second grip handle. The first and second arc-shaped clamping rods are hinged together by a hinge structure. An elastic contact head is provided on one side of both the first and second measuring heads. A locking component is provided on the hinge structure. This utility model offers high measurement efficiency, accurate measurement results, and simple operation.

The invention discloses a method for transforming and felling a low-efficiency forest, which relates to the field of forest cultivation and comprises the following steps of felling operation, stump treatment, fallen wood treatment and tending management. The felling operation is carried out innovatively by adopting at least one combination mode of a global felling method, a canopy felling method, a lower felling method, a crown diameter felling method and a target diameter-at-breast-height felling method according to forest stand characteristics and operation targets. The cutting strength adopts diameter at breast height; the cutting cycle is set according to the tree age, the wind damage risk, the tree growth height and the forest stand canopy density difference and is carried out in the tree dormancy period. According to the low-efficiency forest transformation felling method, through combined application of multiple targeted felling modes, accurate regulation and control of a forest stand structure are achieved; by adopting the diameter at breast height cutting strength index, the operation design process is simplified, and the operability is improved; measures such as pile cutting treatment and fallen timber on-site scientific stacking are combined, and multiple targets of water and soil conservation, soil fertility maintenance and ecological restoration are effectively considered.

The utility model relates to the technical field of plant measurement, in particular to a portable arbor DBH (diameter at breast height) tester placing component, which comprises a placing frame and a fixed plate, a placing groove is arranged on the surface of the placing frame, a rotating rod is movably connected to the inner side of the placing groove, a movable plate is sleeved on the outer surface of the fixed plate, and the rotating rod is movably connected with the movable plate. The surface of the movable plate is connected with an abutting rod through threads, and the surface of the placing frame is connected with a supporting plate in a penetrating mode. Under the connection of the fixing plate and the placing groove, the connecting use performance between the fixing plate and the placing frame is achieved, separation use is not needed, the rotating connection between the fixing plate and the placing frame does not affect the normal measuring use of the fixing plate, the placing frame cannot be lost, and under the elastic sliding connection of the sleeve and the rotating rod, the fixing plate and the placing frame can be fixed conveniently. And the sleeve and the connecting rod are connected in a sleeving manner, so that the fixing plate can be conveniently disassembled and assembled in the placing groove, and the use performance and effect are improved.

The utility model relates to the technical field of standing tree measuring equipment, in particular to a tree diameter at breast height measuring device, which comprises a diameter at breast height ruler for measuring the diameter at breast height of a trunk and a length-variable fixing device for fixing the diameter at breast height ruler, and a fixing rod is detachably connected below the fixing device. One end of the fixing device is fixedly provided with an accommodating box for accommodating the DBH ruler; one end of the DBH ruler extends out of the accommodating box and is fixedly connected with one end, far away from the accommodating box, of the fixing device; the fixing device can be connected end to end around a trunk to be measured through length change. Compared with the prior art, the fixing device capable of driving the DBH ruler to surround the trunk by one circle is arranged, so that the technical problems that an existing tree DBH measuring device is troublesome to use and the labor intensity of operators is increased on the premise that the DBH numerical value is accurately measured are solved.

The application relates to a forest tree annual growth data remote measurement method based on image recognition, which comprises the following steps: a multispectral image recognition device is controlled by a positioning algorithm to be aligned to a measured tree, and the current coordinates of the measured tree are recorded; the images of multiple spectrums of the measured tree are acquired; the multiple spectrums are recorded at the same time and have time point information; pixel cutting is performed on the multispectral images, the image edge feature mismatch area is removed, and a multispectral image set with completely coincided features is obtained; image normalization calculation is performed, and a normalized image is regenerated according to the normalization calculation result; the pixel numbers of tree height H, crown width A and diameter at breast height C are acquired, and the actual values of the tree height H, the crown width A and the diameter at breast height C are calculated; the RGB feature information of tree leaves is acquired, the specific growth cycle T of the measured tree is determined, and the annual growth data of the measured tree is acquired to obtain a growth model Phi of the measured tree; and data generation comprises the tree height H, the crown width A, the diameter at breast height C and the growth cycle T.

The application discloses a method for determining the age of natural forest stand, comprising the following steps: selecting the reserved wood with multi-period measured diameter at breast height to calculate the average diameter at breast height of the forest stand, dividing the forest stand site class according to the annual growth rate of the diameter at breast height of the forest stand, constructing a statistical model between the average diameter at breast height of the forest stand and the corresponding investigation time interval based on a theoretical growth equation, introducing a density variable to reflect the characteristics of the forest stand, constructing a site class dummy variable to reflect the site influence, and adopting a starting point constraint to transform the model form; reversely calculating the age calculation formula of the natural forest stand from the diameter growth model, determining the site class of the sample site, and estimating the age of the natural forest stand according to the initial diameter at breast height and parameters. The application provides a simple method for estimating the age of the natural forest stand by combining the multi-period diameter data of the reserved wood with the density condition of the forest stand and the site difference, effectively improves the investigation efficiency and estimation accuracy, and meets the demand of the forestry production and scientific research on the age data of the natural forest stand.

The invention relates to a method for calculating diameter at breast height by establishing a curve model of a trunk shape below a tree chest height, which comprises the following steps of: S1, selecting an investigation area in which trees of the same type are distributed in a concentrated manner, randomly selecting a plurality of trees of the same type in the investigation area as sample trees, and measuring the sample trees to obtain an original measurement data set; s2, selecting a plurality of models and a plurality of fitting software; s3, preprocessing the original measurement data set; s4, substituting the preprocessed data into a plurality of models, performing trunk shape curve fitting, finally obtaining a plurality of fitting models, and calculating fitting errors according to test indexes; s5, analyzing and checking each fitting model according to the fitting error, and screening out an optimal model; and S6, performing trunk analysis on the sample wood according to the optimal model. According to the method, the volume of the felling wood can be accurately calculated by accurately measuring the diameter at breast height of multiple parts below the breast height of the sample wood and screening the optimal model in combination with multi-model fitting and scientific examination by taking the Chinese fir in the Fushan City as an example.

This invention belongs to the field of forest resource monitoring and growth prediction technology, specifically involving a tree species strategy grouping and forest growth prediction method based on morphological traits. The method includes the following steps: acquiring individual-level monitoring data from sample plots; preprocessing the data to construct growth response variables, and transforming and standardizing the diameter at breast height (DBH) and competition index terms; constructing a species-level morphological trait table, standardizing the morphological traits, and generating morphological representations; clustering tree species based on morphological representations to form tree species strategy groups, and backfilling these strategy groups into individual-level samples to construct a training dataset; establishing a hierarchical growth prediction model based on the training dataset, and setting tree species random effects; when the target tree species is not present in the training dataset, determining the strategy group label based on its morphological representation, and outputting the growth prediction result solely based on the model's fixed effects. This invention is applicable to the monitoring and prediction analysis of multi-species natural forest growth and has good market application prospects.

The invention provides a tree biomass calculation method and system. The method comprises the steps of obtaining a database file selected by a user and tree parameters input by the user; wherein the database file is created and stored in advance according to a data file selected by a user; the tree parameters at least comprise diameter at breast height, tree height and tree species; extracting a biomass model and calculation parameters corresponding to the tree species from the database file; inputting the diameter at breast height, the tree height and the calculation parameters into a biomass model for calculation, and judging whether an abnormal condition exists in the calculation process or not; if an abnormal condition exists in the calculation process, processing the abnormal condition to obtain a calculation result; and if no abnormal condition exists in the calculation process, obtaining a calculation result. Therefore, the efficiency of biomass measurement and calculation is effectively improved through database management and an automatic calculation technology.

This application relates to a method and system for detecting the diameter at breast height (DBH) of individual trees in forests based on the organic fusion of multi-source sensors, belonging to the field of forestry remote sensing technology. It performs terrain filtering, orthorectification, and independent tree instance segmentation on airborne lidar point cloud data and multispectral satellite imagery, respectively. Then, through local semantic topology graph construction and cross-modal graph matching, object-level identity binding is achieved to obtain a set of homologous binding pairs for individual trees. Subsequently, a Gaussian weight field for the tree canopy is constructed using the 3D point cloud spatial density distribution of the bound trees. A pixel-by-pixel probabilistic soft-assignment weighting is performed on the multispectral image object blocks to generate a soft-fusion feature vector for individual trees. Finally, this feature vector is input into a regression model constrained by the forest allometric growth law for DBH detection. This application effectively suppresses edge noise pollution caused by spatiotemporal misalignment of multi-source data through object-level flexible anchoring and probabilistic feature fusion, improving the accuracy and robustness of DBH detection in complex forest areas.

The invention provides a forest individual tree parameter automatic extraction method based on point cloud and deep learning, and the method is used for the extraction of the diameter at breast height and position data of a forest individual tree. The method comprises the following steps: S1, data acquisition and preprocessing; s2, multi-height-layer point cloud slicing is carried out; s3, performing point cloud slice imaging and anti-truncation enhancement processing; s4, marking the diameter at breast height and training the model; s5, preliminarily detecting the diameter at breast height, resolving the position and cutting off and removing; s6, multi-height-layer data fusion, false detection elimination and modeling sample identification are carried out; and S7, constructing a DBH (diameter at breast height) prediction model. S8, detecting and complementing the diameter at breast height data; s9, single tree segmentation and tree height extraction are carried out; according to the invention, image boundary truncation interference can be effectively overcome, and efficient, automatic and high-precision extraction of stumpage diameter at breast height and position data is realized.

The invention discloses a method for automatically measuring the diameter at breast height of a tree based on depth vision, and relates to the technical field of forest resource monitoring, and the method is characterized in that a depth imaging device is used for synchronously collecting RGB-D data streams; carrying out median filtering noise reduction processing on the depth map, and carrying out bounding box labeling and data amplification on the RGB image; carrying out feature extraction and trunk region detection on the RGB image by adopting a lightweight convolutional neural network comprising a dynamic channel attention module; dynamically positioning a chest height section based on camera pose parameters, and extracting a trunk boundary point set by using depth continuity constraint; and mapping the boundary point set to a three-dimensional space to calculate the tree diameter at breast height. According to the invention, the automatic measurement of the diameter at breast height of the tree is realized, the measurement time of a single tree is shortened to 10-15 seconds from traditional manual 2-3 minutes, compared with laser radar measurement equipment, the cost is lower, the size is smaller, the environmental adaptability is higher, and an efficient and economic solution is provided for large-scale forest resource investigation.

The utility model belongs to the field of plant breast diameter measurement, and particularly relates to a plant breast diameter measurement statistical device which comprises a positioning shell, a storage mechanism is arranged on one side of the positioning shell, a fixed guiding rule is fixedly connected to the surface of the positioning shell, and a toothed plate is fixedly installed in an inner cavity of the positioning shell. A positioning frame is arranged in an inner cavity of the positioning shell, and the surface of the positioning frame makes contact with the inner wall of the positioning shell. By arranging the storage mechanism, a worker can conveniently carry recording paper for counting the diameter at breast height of a plant, so that the portability of measurement and counting is improved, by arranging the positioning mechanism and shifting two conical clamping plates to move reversely, a positioning shell can be fixed to the surface of the plant, and thus the stability of measuring the diameter at breast height of the plant is improved; the problem that errors exist in measurement results due to the fact that a traditional device for measuring the diameter at breast height is usually a manual hand-held measuring tool for measuring the diameter at breast height of a plant and the manual hand-held mode is poor in stability is solved.

The invention relates to the technical field of image data processing, and discloses a rubber tree bark slice panorama generation method, which comprises the following steps of: taking a proper bark sample from a diameter at breast height of a rubber tree; the method comprises the following steps: fixing a sample, dehydrating, performing latex denaturation and dyeing, dehydrating and transparentizing, permeating wax and embedding, slicing, dewaxing, dyeing, slicing and dehydrating, and transparentizing and sealing; a common optical microscope is matched with a 4 * objective lens to carry out image acquisition, equidistant shooting is carried out along a Z-shaped path of rubber tree barks, the overlapping area of adjacent images is larger than or equal to 25%, and the resolution of a single image is larger than or equal to 4088 * 3072 pixels. Through an extremely simple technical route of Z-shaped full-coverage shooting and general image splicing software, the dependence on an expensive automatic microscopic platform is eliminated, and the equipment investment and the operation and maintenance cost are greatly reduced. Under the condition that hardware does not need to be transformed, a high-resolution and seamlessly spliced bark panorama can be generated, the shooting and processing flow is remarkably accelerated, and a breast duct array and a ray structure are kept complete and continuous.