84 results about "Forest plantation" patented technology

The invention provides a method and device for evaluating the stability of a soil slope in a man-made forest area and electronic equipment, and relates to the technical field of slope protection. In the method, a multi-field coupling numerical model not only considers a hydrological effect and a mechanical effect, but also considers the comprehensive effect of the hydrological effect and the mechanical effect; and the comprehensive influence of the artificial forest on the slope stability under the real environment load can be accurately quantified and verified.

The invention relates to the technical field of image processing, and discloses a man-made forest remote sensing image segmentation method, electronic equipment and a computer readable storage medium, the method introduces MMF, performs joint modeling on vegetation indexes such as NDVI, EVI and the like and RGB images so as to improve the ability of a model to distinguish a man-made forest from other ground features, and introduces KAN-HGC so as to improve the efficiency of the model to distinguish the man-made forest from other ground features. A graph structure is adaptively constructed by combining a space structure and feature similarity, so that the recognition capability of the model on a boundary region is improved, and GIGA is introduced, and key region features are enhanced through multi-dimensional attention, so that background interference is effectively inhibited, and the recognition accuracy of the model in a complex scene is improved; besides, an FReSCO optimizer is provided, a boundary enhancement and spectrum adjustment mechanism is introduced in training, and the adaptability and cross-scene generalization ability of the model to spectrum differences are improved.

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 present application provides a method for extracting short-time-span growth of eucalyptus plantations based on UAV data, and relates to the field of forest resource investigation and forestry quantitative remote sensing research. The method comprises the following steps: field investigation and UAV data collection are carried out on selected eucalyptus plantation sample plots; DEM and monthly DOM and DSM of the sample plot are obtained, and monthly CHM is obtained by subtracting monthly DSM from DEM; a training set is divided from a data set composed of 12-month CHM, each tree crown on the CHM is labeled to obtain a labeled training set, and single tree segmentation is carried out by using the training set data and deep learning algorithm to obtain a monthly single tree segmentation vector diagram; single tree height, single tree crown and DOM spectral reflectance index of the sample plot are extracted; a single tree volume inversion model of the sample plot is constructed; single tree volume of eucalyptus plantations of the sample plot is extracted every month, and the sum is obtained to obtain stand volume, so as to realize short-time-span growth extraction of single tree and stand of eucalyptus plantations.

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 device and a method for measuring the canopy interception of a tropical man-made forest. The measuring device comprises an in-forest rainfall measuring device, an out-forest rainfall measuring device and a trunk flow measuring device. The measurement method comprises the steps of equipment deployment, calculation of penetration rainfall and calculation of canopy interception. According to the method, the rainfall outside the forest, the penetration rainfall and the trunk flow data are obtained, the crown interception data can be obtained through simple calculation, and the tropical artificial forest water source conservation capability is conveniently researched; the in-forest rainfall measuring device has the advantages that sundries accumulated in the rain gauge and shelters at the opening of the rain gauge can be automatically cleaned, the accuracy of the measuring process is ensured, and the in-forest rainfall measuring device can be suitable for tropical artificial forests in rainstorm and typhoon weather and with many litters, tropical artificial forests in the repairing process and the like; the corrected value is adopted to replace abandoned penetrating rainfall data, the problem of inaccurate measurement caused by a shielding object at the opening of the rain gauge can be corrected, and the measurement precision is greatly improved.

The invention relates to the technical field of seedling cultivation, in particular to a pinus massoniana artificial forest seedling cultivation device which comprises a peripheral cylinder, an inner surrounding sleeve is arranged in the peripheral cylinder, an annular filling area is formed between the inner surrounding sleeve and the peripheral cylinder, a stress clamping part is arranged on a hanging piece, and the stress clamping part is connected with the inner surrounding sleeve. The stress clamping part is bent upwards and then clamped at the top end of the outer surrounding sleeve, a radial expansion part is arranged on the inner surrounding sleeve, a flexible bending part is arranged at the position, close to the stress clamping part, of the hanging piece, the inner surrounding sleeve is expanded in the radial direction through the radial expansion part, and the stress clamping part and the flexible bending part serve as core buffering elements. Mechanical stress transmitted by expansion of the inner encircling sleeve or external acting force can be effectively absorbed and buffered, the risk that the stem epidermis is scratched or crushed in the growth and device operation process is remarkably reduced, the device is composed of an inner layer main part and an outer layer main part, seedling soil lifting can be achieved through the simple hand lifting function, the structure is simple, and operation is convenient.

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 present application provides a method for retrieving the age of eucalyptus plantations based on time series satellite images, which belongs to the technical field of forest resource investigation and quantitative remote sensing of forestry. The method can more quickly and accurately obtain the age data of eucalyptus plantations, making up for the shortcomings of traditional methods for obtaining the age of eucalyptus plantations, such as time-consuming, labor-intensive, high cost, and long data acquisition period. The use of long time series remote sensing image vegetation index before and after eucalyptus felling for age retrieval can make up for the shortcomings of the relationship between age and remote sensing spectral reflection to establish an age retrieval model to retrieve the age, and realize the accurate extraction of time series age. By using a spatio-temporal fusion algorithm to spatio-temporally fuse high spatial resolution satellite remote sensing images and low spatial resolution satellite remote sensing images, the missing image data that cannot be used due to cloud and rain in a month is reconstructed, a complete time series image is constructed, and the age of eucalyptus plantations is accurately retrieved to the monthly scale.

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 present application belongs to the field of saline-alkali soil improvement and carbon sequestration, and provides a method for improving carbon sequestration and stability of Tamarix chinensis artificial forest in coastal heavy saline-alkali soil. The method is characterized by the following steps: crushing and throwing litter and branches into the field, applying acetic acid to promote decomposition, supplementing soil nutrient and carbon pools, cutting roots and spraying treatment liquid to the cut roots to increase root exudates and secretion capacity, and promoting carbon sequestration and stability in the soil. Through the above measures, the carbon sequestration and stability capacity of Tamarix forest land is improved by more than 32%, and the treatment measures for Tamarix forest land are proposed to increase soil carbon storage and maintain carbon pool, which has multiple effects such as rapid carbon sequestration and soil fertilization, and has important application value for improving the carbon sink function of coastal saline-alkali soil ecosystem.

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 discloses an irrigation system and method for a pinus sylvestris man-made forest, and relates to the technical field of irrigation systems, the irrigation system comprises a controller and a water delivery module, the outlet end of the water delivery module is connected with a plurality of irrigation modules in parallel, and the inlet end of each irrigation module is provided with an electromagnetic valve; the irrigation system further comprises a plurality of temperature monitoring modules, a plurality of runoff monitoring modules and a plurality of humidity monitoring modules. The temperature monitoring modules, the runoff monitoring module and the humidity monitoring module are electrically connected with the controller. A plurality of standard evaluation models can be generated according to historical parameters, and comparison soil humidity parameters are generated for each planting area according to each actual runoff parameter, each actual environment temperature parameter and each standard evaluation model; and finally, comparing each comparison soil humidity parameter with each actual soil humidity parameter, and respectively generating an irrigation control instruction for each pinus sylvestris. The irrigation instruction is generated after the water content of the area where the plants are located is independently analyzed and judged, and therefore precise irrigation is achieved.

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 provides a larch man-made forest status index distribution estimation method based on an aviation laser radar digital canopy height model, and the method can quickly extract forest stand dominant height and forest age information of a 20-meter grid scale through directly utilizing the canopy height model generated by aviation LiDAR and the existing forest facies diagram data. By combining layered random sampling and guiding curve fitting, automatic generation of the forest farm-level high-spatial-resolution status index distribution map is realized, field labor and time costs are greatly saved, destructive sampling is avoided, spatial resolution and estimation precision are improved, requirements on point cloud density and an algorithm are reduced, data processing is simpler and more convenient, and the method is suitable for popularization and application. And the method is more suitable for large-range business operation. The status index distribution diagram can accurately reflect the subtle difference of the quality of the site in the forest, provides direct and reliable technical support for the selection of afforestation land parcels, the grading of the quality of the site and the formulation of management measures in the directional cultivation of large-diameter materials of larch, and has good application prospects and popularization values.

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.

The invention discloses an ecological prevention and control method for trunk borers of betula alnoides in an artificial forest of betula alnoides. According to the method, when a betula alnoides artificial forest is built, melia azedarach and betula alnoides are mixed and planted in a dotted uniform configuration mode. Volatile active substances released by leaves, flowers and fruits of melia azedarach cooperate with toosendanin diffused by carriers such as pollen and tiny tissue debris of melia azedarach to form a biological barrier which can effectively interfere with olfaction localization, growth and development and reproduction behaviors of the parapsilotona in forest air, so that ecological prevention and control of the parapsilotona in the betula alnoides artificial forest are realized. The whole planting density of the betula alnoides artificial forest is 111-167 plants per mu, 101-162 plants of the betula alnoides are planted per mu, 5-10 plants of the melia azedarach are planted per mu, and the maximum ecological prevention and control effect is achieved with the minimum number of the melia azedarach plants. The method can effectively control the damage of trunk borers of Betula alnoides in the artificial forest, reduces the use of pesticides, reduces the prevention and control cost, improves the wood quality, and promotes the sustainable operation of forest stands.

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.

The invention relates to the technical field of man-made forest sustainable operation and forestry carbon sink management decision optimization, and discloses a man-made forest operation decision method and system based on a carbon sink and economic synergistic effect, which constructs an operation decision model with strong adaptability by combining national forest resource continuous checking data and site index grading. And target weight, market price and intermediate cutting strength are introduced as key decision variables, global optimization is realized by adopting a simulated annealing algorithm, a traditional mode taking wood benefits as a core is broken through, a carbon increment and sink net present value and a wood net present value are brought into a unified optimization system, and cooperation of ecological value and economic benefit is realized. According to the method, collaborative optimization of carbon benefits and economic benefits is effectively realized, and a systematic and generalizable technical path and theoretical support are provided for man-made forest carbon sink operation, carbon asset development and marketization forestry policies.