56 results about "Forest plantation" patented technology

The invention discloses a method for extracting parameters of a (subtropical) eucalyptus man-made forest based on an unmanned aerial vehicle laser radar. The method comprises the following steps: investigating a sample plot, and measuring and calculating actual forest parameters such as average diameter, average height, sectional area, stand volume and the like; acquiring and preprocessing high-density unmanned aerial vehicle laser radar point cloud data, and extracting three types of feature variables of height, density and vertical structure; deducing a model structural formula on the basis of a stock different-speed growth equation, and screening variables according to rules; constructing a power model by using a regular exhaustion method; the optimal model is screened out through model parameter estimation, inspection, significance analysis and the like. According to the method, the variable synergistic effect is mined through the exhaustion method, the multi-dimensional test system is constructed, and the exclusive model is customized, so that the problems of one-sided variable screening, insufficient model reliability and poor specific forest stand adaptability in the prior art are solved, high-precision estimation of core forest parameters is realized, and the method is suitable for large-scale popularization and application. And scientific and effective technical support is provided for refined management and sustainable operation of eucalyptus man-made forest resources.

The invention discloses an application of a PadPGR5a gene in fast-growing high-quality high-yield poplar breeding, belongs to the technical field of genetic engineering, and particularly relates to the application of the PadPGR5a gene in fast-growing high-quality high-yield poplar breeding, and the nucleotide sequence of the PadPGR5a gene is shown as SEQ ID NO.1. The invention further discloses an application of the PadPGR5a gene in fast-growing high-quality high-yield poplar breeding. Through phenotypic analysis, the plant height of the PadPGR5a gene overexpressed transgenic poplar is obviously increased, the net photosynthetic rate is obviously improved, and the oxidative stress resistance is obviously enhanced. It is shown that the PadPGR5a gene is an important forest fast-growing improved gene resource, and a new excellent transgenic variety can be provided for construction of a fast-growing high-quality high-yield poplar man-made forest by means of a genetic engineering technology.

The invention provides a phoebe bournei needle-broadleaf mixed tending and improving method, and belongs to the technical field of forest cultivation and artificial forest management. Comprising the following steps that (1) phoebe bournei and cunninghamia bournei which are arranged in a spaced mode serve as a unit, a plurality of units are arranged, and phoebe bournei and cunninghamia bournei rows among the units are vertically arranged; (2) digging holes to transplant phoebe bournei seedlings and Chinese fir seedlings, applying a base fertilizer during soil returning, and starting to expand the holes, hilling and apply fertilizer in the second year after transplanting; (3) felling is started in the fourth year of afforestation, phoebe bournei is cultivated with cunninghamia bournei, and wound healing agents are adopted for treatment after the cunninghamia bournei According to the method, the phoebe bournei and the Chinese fir which are arranged in an interlaced mode serve as one unit, multiple units are arranged, so that forest stand arrangement is rationalized through the scheme that the phoebe bournei and the Chinese fir between the units are vertically arranged in a row mode, base fertilizer is accurately applied in the soil returning process, the tending frequency is increased, sanitary cutting is conducted, and tree body management is refined; and the double purposes of rapid growth of phoebe bournei, high-quality dry material cultivation and large-diameter material cultivation of Chinese fir are achieved.

The present application relates to a kind of artificial forest multi-source remote sensing extraction method, belong to the field of remote sensing data detection, comprising: obtaining multi-source remote sensing data and pre-processing, obtain pre-processing multi-source remote sensing data;Respectively obtain training sample and verification sample, according to verification sample screening training sample to obtain first sample set;According to first sample set, respectively train several classifiers to obtain several first classifiers, and first sample set is classified to obtain first classification result;Sample enhancement is carried out to minority classification result in first classification result to obtain second sample set;According to second sample set, respectively train several first classifiers, corresponding to obtain several second classifiers;Through several second classifiers, respectively classify pre-processing multi-source remote sensing data, and the final classification result is obtained by decision fusion to second classification result.The present application is based on multi-source remote sensing data, according to sample enhancement and decision fusion of classification result, improve the recognition ability to minority class sample.

The application relates to a desert artificial forest space configuration method and device based on water resource carrying capacity, equipment and medium. The method comprises the following steps: collecting environmental data of a target desert area; dividing the target area into multiple regional partitions based on the environmental data; calculating a water resource carrying capacity index of each regional partition according to a preset water resource carrying capacity evaluation index; for each regional partition, combining the environmental data and the water resource carrying capacity index, and screening suitable artificial forest tree types by simulating an ecological hydrological process under a preset stand structure configuration; based on the artificial forest tree types, combining the environmental data and the water resource carrying capacity index to determine a planting density, and matching the tree types and the density to generate an artificial forest regional configuration scheme; and integrating all the regional configuration schemes to form a desert artificial forest space configuration scheme. The method can realize scientific space layout of the desert artificial forest, optimize water resource carrying capacity matching degree, and improve afforestation survival rate and ecological restoration effect.

The invention discloses a man-made forest stand structure and function integrated monitoring system and method based on multi-source data fusion in the technical field of man-made forest monitoring, and the system comprises a movable ground monitoring box, one side of which is provided with a gap groove for accommodating single trees; the unmanned aerial vehicle is used for carrying out multi-view observation on a single tree crown; the two parking platforms are symmetrically distributed on the ground monitoring box, located on the two sides of the notch groove and used for allowing the unmanned aerial vehicle to take off and land, and the unmanned aerial vehicle takes off from one parking platform and flies around the single tree along a preset flight path in the vertical plane so as to collect stand structure data of the bottom, the top and the side of the crown of the single tree. According to the system, multi-source data acquisition is achieved through the unmanned aerial vehicle and the ground monitoring assembly, the parking platform and the ground monitoring assembly are driven to synchronously and accurately rotate through the orientation conversion mechanism, unmanned aerial vehicle multi-path canopy collection and ground circumferential all-dimensional measurement are achieved, and the integrity of canopy structure data and the three-dimensional reconstruction precision are remarkably improved.

This invention relates to the field of forestry remote sensing monitoring technology and discloses a leaf SPAD prediction method based on UAV multispectral imaging. The method involves acquiring images of the target forest area through low-altitude multispectral aerial photography using a UAV, and extracting spectral data based on the locations of measured ground sampling points. Enhanced feature engineering is applied to the data to construct a multi-source feature set including original bands, basic vegetation indices, red-edge vegetation indices, and texture features. An early fusion strategy is used to construct a high-dimensional fusion feature vector, which is then input into an ensemble learning regression model based on ExtraTrees for training and prediction. Finally, a spatial distribution map of leaf SPAD values ​​in the forest area is generated. This invention effectively overcomes the shortcomings of conventional multispectral imaging, such as limited band size and saturation. By fusing the red-edge index and the ensemble learning algorithm, it significantly improves the accuracy and robustness of SPAD inversion, providing an effective technical means for precise management and rapid nutrient diagnosis of plantations.

This invention discloses a method and system for identifying planted and natural forests based on multi-source remote sensing and spatiotemporal joint optimization, belonging to the fields of remote sensing image processing, earth observation, and dynamic monitoring of forest ecology. Addressing the problems of high label noise and disordered temporal logic in existing technologies, this invention obtains high-purity training samples through multi-stage iterative purification by fusing CCDC mutation history and deep semantic features; obtains pixel-level confidence through independent initial classification by geographic partitioning; constructs an HMM model integrating ecological prior constraints and dynamic adaptive emission probabilities for Viterbi decoding; and performs constrained spatial restoration with cross-dimensional temporal security checks. This invention effectively suppresses temporal pseudo-variables and salt-and-pepper noise, achieving high-resolution thematic mapping year by year with no temporal logical contradictions and regular spatial patches, suitable for fine-grained forest classification and compliance monitoring of zero-deforestation laws in tropical and subtropical regions.

The present application belongs to the poplar plantation technical field, and particularly relates to a poplar plantation structure optimization and sustainable management method and system. The method comprises the following steps: S1, constructing a growth model of poplar, and dividing the poplar into three stages of a juvenile stage, a middle-aged stage and a near-mature stage according to the growth model; S2, collecting site factor data; S3, dividing the research area into multiple site grade areas, and configuring differentiated growth parameters, rotation periods and felling intensities for the site grade areas; S4, building a multi-objective linear programming model, and the objective function covers maximization of total wood yield, minimization of management cost and maximization of ecological benefit; S5, linearly fitting the juvenile stage, the middle-aged stage and the near-mature stage to obtain the corresponding linear equations of the stages, embedding the linear equations of S2 into the multi-objective linear programming model as constraint conditions, and clearly defining the forest age range of each stage; and S6, solving the multi-objective linear programming model to obtain optimal felling area, rotation period and felling intensity parameters.

The application discloses a plantation remote sensing image segmentation and recognition method and system, relates to the technical field of remote sensing image processing, and comprises the following steps: acquiring multi-temporal remote sensing images and laser radar point cloud data and registering, extracting stand height information and crown structure information, using the crown structure information to constrain and reconstruct spectral characteristics to obtain structure spectral coupling characteristics; calculating spectral differences and texture changes, combining stand height time series changes to construct stand state evolution characteristics; fusing to obtain fusion characteristics; constructing a double-channel semantic segmentation model to train and perform pixel-level joint classification to obtain an initial classification result; based on the crown structure information, a matching constraint rule is established to modify the initial classification result to obtain a final classification result, and high-precision recognition of degraded forest land tree species is realized.

The invention discloses a man-made forest ecological function monitoring method based on meteorology and hydrology, and relates to the technical field of forestry ecological monitoring, and the method comprises the steps: obtaining the soil penetration resistance time sequence data of different soil layers of a target man-made forest area, calculating the soil physical structure toughness index of the soil maintenance pore structure and the compaction resistance through combining with soil auxiliary parameters, and calculating the soil physical structure toughness index; analyzing the historical evolution trend; collecting short-term meteorological data and long-term climate change data of the target artificial forest area, coupling the short-term meteorological data and the long-term climate change data with the soil physical structure toughness index, and establishing a meteorological-hydrological-soil structure coupling process model; quantitatively evaluating the water source conservation capability, the soil erosion risk and the climate adaptability of the artificial forest area in the target artificial forest area, and simulating the future evolution trajectory of the soil physical structure and the ecological function of the target artificial forest area by taking different climate scenes and management intervention scenes in the future as compensation factors; meteorological and hydrological dynamic monitoring and early warning of the ecological function of the artificial forest are realized. According to the invention, the accuracy of ecological function evolution prediction is improved.

The invention relates to a desert man-made forest space configuration method and device based on water resource bearing capacity, equipment and a medium. The method comprises the following steps: acquiring environmental data of a target desert area; dividing the target area into a plurality of area partitions based on the environment data; according to a preset water resource bearing capacity evaluation index, calculating a water resource bearing capacity index of each region subarea; aiming at each region subarea, combining the environment data and the water resource bearing capacity index, and screening suitable artificial forest tree types by simulating an ecological hydrological process under preset forest stand structure configuration; determining the planting density based on the tree type of the man-made forest in combination with the environmental data and the water resource bearing capacity index, and matching the tree type and density to generate a man-made forest region configuration scheme; and integrating the configuration schemes of the regions to form a desert man-made forest space configuration scheme. By adopting the method, scientific spatial layout of the desert man-made forest can be realized, the matching degree of water resource bearing capacity is optimized, and the afforestation survival rate and the ecological restoration effect are improved.

The invention relates to the technical field of seedling cultivation, in particular to a man-made forest soil nutrient monitoring sensor which comprises a sensor body, the outer side of the sensor body is sleeved with a guide pipe, and the sensing end of the sensor body can extend out of the guide pipe; the outer wall of the non-induction end of the sensor body is fixedly connected with a sliding sleeve, the outer wall of the sliding sleeve is fixedly connected with a sliding seat, the sliding seat penetrates through the linear sliding groove and extends to the radial outer side of the guide pipe, and an inclined extrusion part is formed at the outer end of the sliding seat; the inclined surface of the inclined extrusion part downwards and obliquely extends towards the non-sensing end of the sensor body; a hole is formed in soil in advance through the drill bushing, a clean and stable deep detection space is provided for detection, the sensing end of the sensor does not participate in deep hole prefabrication, the sensing end extends out to achieve deep soil detection only when the sensing end reaches the detection space at the bottom of the formed hole, and the service life is prolonged.

This invention discloses a method and system for inverting the nutrient content of eucalyptus canopy leaves based on multi-feature fusion, belonging to the field of UAV remote sensing and forestry information technology. The method includes: acquiring and preprocessing multispectral image data from a UAV; extracting vegetation index features and texture features of the eucalyptus canopy; filtering the fused features based on mutual information to construct a multi-feature fusion dataset; constructing an inversion model for the nitrogen, phosphorus, and potassium content of eucalyptus leaves using a random forest regression algorithm; and verifying and optimizing the accuracy of the inversion model. This invention effectively compensates for the information gaps of single features by fusing spectral and spatial structure information, significantly improving the inversion accuracy of eucalyptus canopy leaf nutrient content, and providing reliable technical support for precise nutrient management of eucalyptus plantations.

The invention belongs to the technical field of statistical methods, and particularly relates to a method for cultivating large-diameter wood of a red pine cone and wood dual-purpose forest based on dynamic density regulation and control. The method comprises the following steps: firstly, dividing a Korean pine cultivation period into three stages, namely a young forest, a middle-age forest and a near-matured forest, and determining a differentiated cultivation target of each stage; secondly, a pre-stored density regulation and control model is established and applied, and the model defines the maximum forest stand density and the suitable operation density range corresponding to different growth indexes; then, obtaining a current growth index through forest stand survey, and querying the model to determine whether intermediate cutting is needed or not and determine a target density range; and finally, performing intermediate cutting based on a query result, wherein the intermediate cutting takes the principle of cutting inferior and keeping superior, and protecting the solidity potential. According to the method, through dynamic and quantitative density management, the contradiction between large-diameter wood production and cones high yield in Korean pine cultivation is effectively solved, wood and fruit abundance is achieved, and the comprehensive economic benefits and sustainable operation level of Korean pine artificial forests are remarkably improved.

The invention relates to the field of agriculture, and more particularly to a novel next-generation environmentally-friendly organic mineral fertilizer containing structured zeolite, an amino acid component, water, phosphoric acid, cobalt nitrate, iron nitrate, carbamide and / or ammonium nitrate. Said fertilizer can be used for all types of agricultural crops, fruit and berry trees and bushes, decorative plants and forest plantations and is suitable for plants grown in open ground or under cover, the fertilizer enabling a significant increase in crop yield and improving the properties (physical, chemical, biological) of the soil and having an overall positive effect on the soil-plant system.

The application discloses a forest stand structure optimization method based on the relationship between forest density and carbon fixation rate, relates to the technical field of forest management, and comprises the following steps: S1, performing sample plot investigation; S2, determining the forest stand structure and annual average carbon fixation amount of each sample plot, and calculating the carbon fixation rate under the current forest stand structure; S3, determining the quantile regression relationship between the breast height cross-sectional area and the carbon fixation rate; S4, determining the proportion of a kind of tree species and two kinds of tree species in the forest stand structure in different sample plots, and determining the relationship between the forest stand structure and the carbon fixation rate; and S5, selecting at least one target area in each sample plot to perform logging under preset logging conditions, and forming an artificial forest window, so that the breast height cross-sectional area reaches the critical density. The method is used for guiding forest management activities and improving the carbon fixation and sink capacity of forests.

This invention relates to the field of puffball propagation technology in Yunnan and discloses a management system for promoting puffball propagation in Yunnan Pinus kesina plantations. The system includes a data acquisition module, a stand structure assessment module, a growth assessment module, and a propagation management module. The stand structure assessment module constructs the stand structure coefficient of the corresponding block of Pinus kesina plantation by reading the environmental data of the current Pinus kesina plantation, and simultaneously transmits the constructed stand structure coefficient to the propagation management module. This system simultaneously collects data on the aboveground stand environment and the underground soil environment, as well as all key parameters related to the host and symbiotic fungi. Through a forest block correction unit, it integrates sky visibility, litter conditions, and the dispersion of Pinus kesina diameter at breast height, ensuring the visualization and quantification of parameters during the cultivation of Yunnan puffball. It also promptly reminds planting staff to adjust the stand structure and correct growth deviations in puffball, improving seedling survival rate, stand stability, puffball yield, and quality.

The invention discloses a multi-source remote sensing forest biomass estimation method and system for high-precision inversion, and relates to the technical field of forest biomass estimation, and the method comprises the steps: obtaining multi-source remote sensing data of a target artificial forest region; performing pretreatment; constructing a multi-dimensional feature vector based on the preprocessed multi-source remote sensing data, wherein the multi-dimensional feature vector comprises a spectral feature, a texture feature, a radar scattering feature and a forest three-dimensional structure feature; inputting the multi-dimensional feature vectors into an auto-encoder model, and performing nonlinear dimension reduction on high-dimensional features by an encoding layer to obtain low-dimensional deep feature representation; constructing an optimization model taking the above-ground biomass inversion error as a target function, and performing collaborative global optimization by adopting a simulated annealing algorithm to obtain an optimal feature combination and an optimal model parameter; an XGBoost above-ground biomass inversion model is constructed, and the inversion model is trained by using actually measured sample above-ground biomass data; and spatial continuous estimation of the above-ground biomass is realized. According to the method, the biomass inversion precision under the complex artificial forest condition is remarkably improved.

This application relates to the field of image processing technology, specifically to a method for constructing a digital canopy height model (CHM) of plantations based on high-precision point cloud data. The method includes: selecting local RGB images corresponding to point cloud data points based on the registration results of the 3D point cloud and RGB images of the plantation area; setting an initial large-size grid and adaptively adjusting the initial grid size by combining the spatial characteristics of the point cloud within the grid and the corresponding local image features; extracting a seed terrain skeleton from the point cloud data; constructing an adaptive stiffness based on the current plantation environment characteristics using the seed terrain skeleton; optimizing the CSF algorithm; classifying the point cloud data using the improved CSF algorithm; and finally constructing a CHM model by combining ground point cloud data and non-ground point cloud data. The purpose of this application is to solve the problem of local distortion in UAV point cloud data caused by the sparse distribution of ground points in high-canopy-density plantations, thereby improving the accuracy of CHM construction.

The application provides a mountainous Chinese fir large-diameter timber "ecological forestation" cultivation method and belongs to the technical field of forestry. The mountainous Chinese fir large-diameter timber "ecological forestation" cultivation method of the application is to transform a Chinese fir degraded artificial forest or a Chinese fir simple artificial forest and comprises the following steps: felling and removing stakes, ecological grass control, forest land design, deep ploughing and making mounds, forest belt making Chinese fir, forest belt grass control, mound protection and fertilization, ecological maintenance and shelter felling for cultivating large-diameter timber. The mountainous Chinese fir large-diameter timber "ecological forestation" cultivation method of the application implements new quality productivity of "ecological forestation" with ecological priority, about 2 / 3 of the forest land is not cultivated to maintain the original ecology, the biodiversity of the forest land is protected, and about 1 / 3 of the forest land is used for establishing a forestation belt for cultivating Chinese fir large-diameter timber. The application can promote the fast growth of Chinese fir, achieve the large-diameter timber standard, and simultaneously consider the high efficiency and sustainable management of the forest land.

The application provides a plantation thinning device and relates to the technical field of tree felling, which comprises a load remote control vehicle, a climbing mechanism, a multistage grabbing mechanism, a cutting mechanism and a remote controller. The load remote control vehicle is provided with a docking portion, and the climbing mechanism is detachably connected with the docking portion. The multistage grabbing mechanism is arranged on the climbing mechanism. The cutting mechanism is arranged on the climbing mechanism. The load remote control vehicle is provided with a controller, and the controller is in communication connection with the load remote control vehicle, the climbing mechanism, the multistage grabbing mechanism and the cutting mechanism. The load remote control vehicle is used for carrying and moving in the plantation, so that the damage to the undergrowth structure in the moving process is reduced. The target tree is gradually cut and decomposed through the cooperation of the climbing mechanism, the multistage grabbing mechanism and the cutting mechanism, and the trunk and branches after cutting and decomposition are stably placed on the ground, so that the damage to the nearby reserved wood and undergrowth caused by the whole tree falling is avoided, and high-quality thinning of the plantation is realized.

The invention relates to a method for optimizing productivity of a man-made Chinese fir forest under multi-factor cooperative driving. The method comprises the following steps: firstly, regularly collecting soil samples at different forest age stages, and comprehensively measuring physicochemical indexes, microbial community structures and enzyme activity to realize dynamic diagnosis of soil environment quality and accurate identification of limiting factors; based on the diagnosis result, the interaction relationship among soil nutrients, microorganisms and enzyme activity is analyzed, and a multi-factor cooperative regulation strategy including nutrient precise management, microbial agent inoculation and biological activator use is formulated; directional optimization is implemented by means of organic and inorganic fertilizer combined application, pH and humidity adjustment and the like, and soil properties and forest growth indexes are continuously monitored in the execution process; and finally, dynamically adjusting a management strategy according to a multi-dimensional evaluation result, constructing a synergistic effect model by using a structural equation model or a machine learning algorithm, quantifying the contribution degree of each factor, and realizing iterative optimization of the strategy.

The invention discloses a hydraulic safety estimation method and device based on tree morphological structure parameters, a medium and a product, and relates to the technical field of ecology and forest management, and the method comprises the steps: obtaining to-be-measured tree data; the to-be-measured tree data comprises tree height, branch height and diameter at breast height; calculating a morphological structure index of the to-be-measured tree data according to a formula; wherein I represents a morphological structure index, H represents a tree height, CBH represents an under-branch height, and DBH represents a diameter at breast height; and substituting the morphological structure index into an empirical model to obtain a hydraulic safety index of the to-be-tested tree data. The quantitative relation between the tree morphological structure and the hydraulic vulnerability is disclosed for the first time, compared with the prior art, the method does not need experimental instruments, the hydraulic characteristics can be estimated only through conventional forestry measurement data, and a scientific basis is provided for artificial forest pruning, density regulation and control and drought resistance management.

The invention discloses a monitoring and regulation system for restoration of a caragana microphylla artificial forest in a high and cold sand area, and relates to the technical field of artificial forest monitoring, the system comprises a monitoring module, a control analysis module and an execution module; the monitoring module is used for acquiring a plurality of underground ecological indexes of a measured area of the caragana microphylla artificial forest; the control analysis module is used for judging a system state based on the plurality of underground ecological indexes and a plurality of preset recovery stage thresholds, and generating a regulation and control instruction based on the system state; the execution module is used for executing the regulation and control instruction. According to the invention, in-situ, real-time and continuous monitoring of key physicochemical and biological indexes of forest underground soil can be realized.

The invention discloses a knowledge graph construction and service system for artificial larch forest land quality evaluation. The system is composed of a mode layer, a data layer and a knowledge service module. The mode layer and the data layer realize interaction through a bidirectional constraint verification mechanism, cooperatively complete construction of a knowledge graph and provide data support for the knowledge service module; the model layer is based on industry standards, resource systems and expert knowledge to construct a larch site quality evaluation ontology framework, the entity class takes evaluation indexes and site factors as a core top class, and the semantic relationship covers relationships such as hierarchical structures and causal effects. The invention relates to the crossing field of forestry science and information technology. According to the system, term unification and format standardization of multi-source heterogeneous data are achieved through the semantic alignment module, the consistency of 1424 entity nodes and 3152 semantic relationships in the knowledge graph is ensured, and the problems that traditional multi-source data are difficult to integrate and prone to conflicts are solved.

The application provides a method and device for evaluating the stability of soil slopes in artificial forest areas and electronic equipment, and relates to the technical field of slope protection. In the method, a multi-field coupling numerical model not only considers hydrological effects, mechanical effects, but also considers the comprehensive effects of the two, and can accurately quantify and verify the comprehensive influence of artificial forests on the stability of slopes under real environmental loads.

The invention provides a method for realizing rapid core material formation of dalbergia odorifera by utilizing a physical stress effect, the method is based on a device for realizing rapid core material formation of dalbergia odorifera by utilizing the physical stress effect, and the rapid core material formation device comprises a physical stress unit, a temperature change regulation and control unit and an intelligent control unit; according to the rapid core material forming method, rapid core material forming of dalbergia odorifera is achieved through the physical stress effect, core material cambium cells are induced to be directionally differentiated through composite physical-temperature change stress, the natural process of tens of years is shortened to 3-5 years, and the economic benefits of a man-made forest are remarkably improved; stress intensity and duration are accurately regulated and controlled, wood cracking or decaying caused by excessive damage is avoided, and the core material density and aroma components are basically consistent with those of traditional natural formation; a pure physical means (without chemical agents) is adopted, vibration and temperature change parameters conform to the physiological tolerance range of trees, and ecological balance is not damaged; through real-time feedback of a sensor and automatic optimization of a processing strategy, the method is suitable for dalbergia odorifera individuals of different tree ages and diameters at breast height, and the generalization performance is high.