92 results about "Forest management" patented technology

A forest point cloud reconstruction method and system based on combination of a handheld radar and an unmanned aerial vehicle, relating to the technical field of remote sensing. The method comprises: on the basis of an unmanned aerial vehicle and a handheld radar device, using a multi-band radar sensor to perform forest terrain and vegetation information acquisition to generate original radar data. The use of the multi-band radar sensor improves the data acquisition accuracy and the coverage range, so that forest terrain and vegetation information is recorded more comprehensively and accurately; a generative adversarial network improves the data quality, and reduces the noise, thereby ensuring the accuracy of subsequent analysis; a convolutional neural network and a random forest algorithm are combined to improve the accuracy of vegetation classification and terrain feature recognition; the generation of comprehensive environmental feature data integrates multidimensional environmental parameters, providing richer information for in-depth analysis; a three-dimensional point cloud model visually displays a forest structure; and time series analysis and a long short-term memory network improve the accuracy of forest change trend prediction, and provide decision support for forest management strategies.

The invention discloses a full-reactor-core parallel fluid-solid coupling simulation method and system. The system comprises a global collaborative coupling simulation scheduling module, a hierarchical index forest management module, a high-performance parallel solver module and an intelligent parameter transmission module. Wherein the global collaborative coupling simulation scheduling module is used for being responsible for overall process control, time stepping, solver scheduling, convergence judgment and inter-module communication triggering; the hierarchical index forest management module is used for being responsible for distributed parallel construction and efficient dynamic updating of CLGIF and providing rapid geometric query service; the high-performance parallel solver module is used for embedding or tightly integrating numerical solvers of fluid and solid physical fields and applying a dynamic parallel multi-solver optimization module to maximize the calculation performance and expansibility of the high-performance parallel solver module; and the intelligent parameter transmission module is used for executing physical quantity exchange on a fluid-solid interface, the core of the intelligent parameter transmission module is a GME-driven region sensing RBF mapping engine, and the transmission precision and efficiency are ensured.

The invention discloses a forest quality evaluation method based on big data analysis, and relates to the field of forest quality evaluation, and the forest quality evaluation method based on big data analysis comprises a data acquisition analysis module, a rating index selection module, a research analysis module, a forest quality evaluation index module and a result analysis module. According to the method, analysis can be carried out through big data, and a complex forest evaluation problem can be refined into a plurality of factors at different levels, so that comprehensive and systematic evaluation of forest quality is realized, forest conditions can be mastered more accurately, powerful support can be provided for forest operation and management, and the method is worthy of popularization and application. Meanwhile, accurate data of all forest parks can be obtained, the forest quality is estimated, a scientific forest management strategy is made, sustainable utilization of forest resources is promoted, a scientific and reasonable forest quality evaluation system is constructed, and the basis of the accurate improvement effect of the forest quality can be measured.

The invention relates to the technical field of forestry investigation, and discloses a forestry investigation system for carbon sink forest management, which comprises a data acquisition module, a data processing module, a data integration module, a model construction and analysis module, a decision and early warning module, an output module and an implementation monitoring module. Through multi-dimensional index investigation, information can be obtained from multiple levels of an ecological system, the carbon cycle process and ecological functions of the carbon sink forest are comprehensively known, more comprehensive data support is provided for scientific management, in addition, more variables influencing carbon sink are introduced, so that the model better conforms to the actual situation, the accuracy and generalization ability of the model are enhanced, and the method is suitable for popularization and application. According to the method, carbon reserve changes of the carbon sink forest under different conditions can be better predicted, finally, effect prediction of multiple management schemes is provided for managers through scene simulation and model analysis, scientific and reasonable management decision making is assisted, and meanwhile, an early warning mechanism can find potential risks in time and guarantee stable development of the carbon sink forest.

The invention discloses a forest management data processing method driven by a large language model, and belongs to the technical field of forest resource management and artificial intelligence data processing crossing. The method comprises the steps of multi-source data acquisition and preprocessing, forest management knowledge graph construction, large language model fine adjustment and retrieval enhancement generation, data semantic fusion and understanding and management strategy reasoning, wherein the large language model performs automatic reasoning based on fused data, management intention and industry knowledge to form a management strategy conforming to a forest growth law and multi-target balance; operation plan text generation: on the basis of completing strategy and space matching, compiling a forest operation plan text meeting forestry industry specifications and management requirements, and man-machine interaction and continuous optimization: collecting feedback information of forestry workers on forest operation plans through a man-machine interaction interface, and systematic evaluation is carried out on the generated operation scheme from forest resource sustainability, ecological function improvement, operation goal achievement degree, risk controllability and policy compliance.

The invention discloses a construction method, a construction system, a recognition method and a recognition system for a fine tree species recognition model, belongs to the field of forest management and ecological protection, and solves the problems that the overall contribution of the whole group of time sequence features to model performance cannot be comprehensively examined, and due to the resolution limitation of remote sensing images and the randomness of forest species distribution space and quantity, the model performance cannot be comprehensively examined in the prior art. And the performance of the remote sensing tree species classification model is obviously reduced. The method comprises the steps of 1, constructing a high-dimensional multi-source feature data set; 2, performing feature optimization based on the high-dimensional multi-source feature data set to obtain an optimal classification feature set; 3, collecting actual measurement sample data, and constructing a deep learning sample library in combination with the optimal classification feature set; and step 4, presetting a fine tree species identification model, and inputting the deep learning sample library to train the preset fine tree species identification model to obtain the fine tree species identification model. The method is used for obtaining the accurate and newest tree species distribution map.

The invention discloses an image processing and measuring method and system based on unmanned aerial vehicle radar and oblique photography, relates to the technical field of oblique photography image measurement, and is used for solving the problem that the accuracy of region division and anomaly detection results is reduced. The method comprises the following steps: calculating a vegetation change gradient in combination with a radar echo amplitude to generate vegetation distribution characteristics; extracting an under-forest ground and generating uniform extrapolation points; arranging a clinometer to obtain an elevation and a coordinate; calculating a local slope and a crown fluctuation amplitude; according to the method, the area vegetation coverage state is evaluated, abnormal areas are screened, extrapolation ground points of the abnormal areas are marked and output, high-precision exploration of the forest area is achieved, terrain complexity and vegetation distribution characteristics are accurately reflected, reliable data support is provided for forest management and terrain analysis, and exploration efficiency and precision are improved.

The invention provides a forest fire analysis method and system based on satellite remote sensing, and the method comprises the steps: obtaining continuously collected thermal infrared, near infrared and visible light dimension satellite remote sensing image sequences of a target forest region, and executing time sequence correlation modeling to generate a time sequence correlation feature set; inputting the set into a pre-trained forest fire dynamic analysis model, and extracting a forest fire suspected region feature set; based on a preset forest fire spatio-temporal evolution rule library, executing multi-condition constraint verification on the suspected region features to obtain a confirmed region feature set; generating forest fire real-time state description information and spreading trend prediction description information according to the confirmed region features; and finally generating a forest fire prevention and control instruction containing the regional coordinate chain and sending the instruction to the target forest management and protection terminal. According to the invention, through multi-dimensional time sequence association, dynamic model analysis and time-space rule verification, accurate identification and dynamic prediction of forest fire are realized.

The invention discloses a forest stand tree species identification method and system based on multi-source remote sensing data fusion, and the method comprises the following steps: obtaining data which comprises forest land remote sensing image data and ground data; carrying out preprocessing on the obtained data; a dual-path CBAM-UNet network model is constructed; inputting the preprocessed data into the double-path CBAM-UNet network model to carry out tree species classification prediction and obtain a tree species classification chart; performing image splicing on the tree species classification map to obtain a tree species classification grid map; the system comprises a data acquisition module, a data preprocessing module, a prediction module and an image processing module. According to the forest stand tree species identification method and system based on multi-source remote sensing data fusion provided by the invention, multi-scale feature capture and feature fusion of multi-source heterogeneous data can be realized through the constructed dual-path CBAM-UNet network model, high-precision identification can be performed on forest stand tree species under complex links, and high-quality data can be provided for forest management.

The present invention provides a method and system for optimizing stand mixed planting based on tree cluster units, which relates to the technical field of forest management. The method provided by the present invention includes: obtaining the information of tree planting points of arbors in the surveyed forest and selecting multiple tree cluster units, investigating the stand indexes of the tree cluster units and constructing a tree species database; constructing an association model between the stand indexes and each pair of relative traits, and obtaining the optimal mixed ratio of each pair of relative traits under the optimal stand indexes; obtaining the geographical information of the to-be-planted plot and randomly selecting to-be-planted points; based on the optimal mixed ratio of each pair of relative traits, performing trait assignment on the to-be-planted points and then matching arbor tree species for tree species mixed planting. The present invention can directly guide the construction of artificial mixed forests from scratch in the to-be-planted plots, which is beneficial to improving the efficiency and replicability of forest management.

The invention relates to the technical field of forest vegetation monitoring, in particular to a forest vegetation parameter real-time monitoring method based on unmanned aerial vehicle images, which comprises the following steps: starting an unmanned aerial vehicle, carrying out real-time image acquisition on a predetermined forest area through a camera, carrying out continuous image capture, synchronously calibrating the camera and setting matched differentiated illumination and depth-of-field conditions; and generating forest image acquisition data. According to the method, the chlorophyll concentration and the leaf area index can be accurately measured through analysis of different color wavelength reflectance, the understanding and tracking precision of the vegetation physiological state is improved, long-term vegetation changes can be carefully monitored through time sequence analysis, the prediction capacity of forest ecological behaviors is enhanced, and the method is suitable for popularization and application. Drought response and pest and disease damage signs are monitored in real time, the timeliness and accuracy of health state evaluation are enhanced, the real-time performance and continuity of data are ensured by dynamically updating a forest vegetation database, and the dynamic monitoring and decision support capacity of forest management is remarkably improved.

The invention provides a high-resolution forest ecological safety evaluation method, which comprises the following steps: S1, acquiring and preprocessing multi-source high-resolution spatial data; three criterion layers are systematically calculated: 1) sensitivity, including preparation of a climate sensitivity index for quantifying the response intensity of vegetation to climate fluctuation and preparation of a human footprint response index for quantifying the response intensity of vegetation to a plurality of human footprint subclass indexes; 2) exposure degree, wherein a standardized extreme climate exposure index and a human footprint index are integrated; and 3) toughness: evaluating the recovery capability of the forest ecosystem by adopting a first-order time sequence autocorrelation coefficient based on a critical deceleration theory. According to the method, the weight of each index is determined by adopting a subjective and objective weighting method, and a refined forest ecological safety index spatial distribution diagram is generated through a comprehensive evaluation model, so that refined, dynamic and objective evaluation of forest ecological safety is realized, and scientific decision and support are provided for accurate forest management and risk early warning.

The invention discloses a forest management method for improving quality and efficiency of a fir man-made forest, application and the fir man-made forest, and the forest management method for improving quality and efficiency of the fir man-made forest comprises the following steps: cutting off part of forests in the fir man-made forest to enable the retention density of the existing forest stand to be 100-1050 plants / hm < 2 >; precious and indigenous tree species are planted in forest stand gaps in a complementary mode, and the complementary plant number is 300 plants / hm < 2 > to 1260 plants / hm < 2 >; the complementary planting tree species are at least three of phoebe bournei, sweetgum, schima superba, camphor tree, cyclobalanopsis glauca, taxus chinensis var mairei, gingko, schima superba, mangnolia officinalis, melia azedarach and sapium discolor. According to the method, quality improvement / operation transformation measures such as stand density adjustment and tree species configuration regulation are carried out on the fir man-made forests in different age groups, precious and indigenous tree species are selected according to local conditions for complementary planting, different-age, multi-layer and mixed stand is cultivated, precious wood is stored, and the operation purpose of quality improvement and efficiency improvement of the fir man-made forests is achieved.

The invention provides a forest insect pest prediction method and system and a readable storage medium, and relates to the technical field of forest insect pest prediction.The forest is divided into a plurality of grids, main forest tree types, forest tree characteristics, soil characteristics and meteorological data of each grid are collected, and scientific assessment and management of insect pest risks are achieved. The method mainly comprises the following steps: firstly, carrying out characteristic parameter acquisition on grids, and carrying out similar grid group division based on soil characteristics; secondly, constructing an insect pest prediction model through a random forest algorithm, training by utilizing insect pest data of a sample grid, and predicting insect pest severity levels of other grids; and finally, analyzing the pest severity level change of each grid at the current and historical moments, generating an alarm index, and sending out a corresponding alarm signal according to a preset threshold value. According to the method, the environmental suitability index and the forest vulnerability index are combined, the insect attack grade is determined by adopting the expert scoring method, and the insect attack risk can be effectively monitored and early warned, so that a scientific basis is provided for forest management.

The invention provides a forest stand mixing optimization method and optimization system based on tree cluster units, and relates to the technical field of forest management. The method provided by the invention comprises the following steps: acquiring arbor planting point information in an investigation forest, selecting a plurality of tree cluster units, investigating forest stand indexes of the tree cluster units, and constructing a tree species database; constructing a correlation model of the forest stand index and each pair of relative traits, and obtaining the optimal mixing ratio of each pair of relative traits under the optimal forest stand index; obtaining geographic information of a to-be-planted land parcel and randomly selecting to-be-planted points; and carrying out character assignment on the to-be-planted points based on the optimal mixing ratio of each pair of relative characters, and then matching arbor tree species to carry out tree species mixing. The method can directly guide the construction of artificial mixed forests from zero to existing in the to-be-planted land parcels, and facilitates the improvement of the forest management efficiency and replicability.

The invention discloses an operation mode suitability evaluation method based on forest carbon sequestration and sink increase, and relates to the technical field of ecological protection and forest operation, and the method comprises the following steps: calculating basic dynamic light transmittance according to satellite multispectral data and soil microbial biomass carbon data of a target forest region; constructing a light inhibition compensation mechanism, and correcting soil microbial biomass carbon data through the mechanism so as to adjust a calculation result of the basic dynamic light transmittance; determining a soil animal disturbance coefficient and calculating an ecological elasticity index; and dynamically adjusting an intermediate cutting intensity value according to the index deviation proportion and generating a staged intermediate cutting scheme. According to the method, the ecological elasticity index is calculated by measuring the key ecological indexes before and after interference in real time, the original intermediate cutting strength is dynamically adjusted according to the comparison relation between the ecological elasticity index and the preset elasticity threshold value, the correction value is formed, the operation intervention strength is accurately matched with the instant bearing capacity of an ecological system, and ecological degradation caused by excessive intervention is avoided.

The invention belongs to the field of forestry, and discloses an octagonal forest management and low-change process carbon emission accounting method, and the method comprises the following steps for different forest stand octagonal forest management modes: determining a target range, a function unit and a system boundary; collecting a data list; constructing a life cycle list; modeling a carbon footprint; sensitivity analysis and data quality analysis; the method aims at providing an accurate and efficient carbon emission accounting system so as to promote sustainable operation of the illicium verum forest and protection of the ecological environment.

The present invention provides a method for estimating forest aboveground biomass by combining multi-source remote sensing data and an integrated model, relating to the field of forest management technology. The method comprises: obtaining airborne LiDAR data, high-resolution orthophotos, and multi-source remote sensing data of a predetermined sample plot; using the high-resolution orthophotos as an aid, obtaining the forest aboveground biomass of the predetermined sample plot based on the airborne LiDAR data; performing feature optimization on the multi-source remote sensing data to obtain an optimal combination of remote sensing feature variables; constructing and stacking multiple models based on the optimal combination of remote sensing feature variables and the forest aboveground biomass of the predetermined sample plot using an extreme gradient boosting algorithm, an adaptive boosting algorithm, a random forest algorithm, and a gradient boosting decision tree algorithm; determining the model with the highest accuracy among all the models and using it to estimate the forest aboveground biomass of the predetermined study area to obtain an estimated result. The present invention solves the problem of low accuracy in forest biomass estimation in the prior art.

The invention discloses a forest stand attribute analysis method and system based on unmanned aerial vehicle remote sensing data feedback, and relates to the technical field of data processing, and the method comprises the steps: obtaining to-be-analyzed forest region data, querying the historical route data of an unmanned aerial vehicle based on position data, and determining remote sensing data collection equipment information and corresponding multi-source environment information; determining a forest stand attribute influence first sub-value of the to-be-analyzed forest; constructing an attribute analysis space coordinate system, determining to-be-analyzed remote sensing data corresponding to the coordinate points, and obtaining a to-be-analyzed forest stand attribute influence second sub-value; analyzing the remote sensing data to obtain a forest stand attribute index matrix; and based on the matrix and the to-be-analyzed forest stand attribute influence second sub-value, obtaining a forest stand attribute standard matrix and drawing up a forest management strategy. The system comprises an acquisition module and an unmanned aerial vehicle data and environment information association module. According to the method, systematic integration of multi-source data is realized, the forest stand attribute analysis precision is improved, and a scientific basis is provided for forest management.

This invention proposes a spatial mapping method and system for new bamboo shoot yield based on satellite-UAV fusion. Addressing the problem of remote sensing observation gaps caused by the underground growth of bamboo shoots, this invention constructs a multi-scale fusion framework of "satellite identification of potential high-yield areas + UAV inversion of old bamboo density." First, a new bamboo yield prediction model is constructed using old bamboo density and topographic factors as variables through ground-based sample plot surveys. Second, indices such as NDVI and LSWI are calculated using time-series imagery, and a decision tree model is used to identify potential new bamboo germination areas in high-yield bamboo forests. Then, based on high-resolution UAV imagery, a region growing algorithm is used to extract individual old bamboo plants and invert the spatial distribution of old bamboo density. Finally, using the potential areas as masks, old bamboo density and topographic factors are substituted to generate a spatial distribution map of new bamboo yield. This invention enables large-area, low-cost, and high-precision mapping of new bamboo shoot yield, providing core technical support for precise bamboo forest management.

The invention discloses a supporting device for forest tree pest and disease damage data acquisition, and relates to the technical field of agriculture and forestry, and the supporting device is characterized by comprising a telescopic rod, a fixing plate is arranged on the telescopic rod, an insect pest trapping and killing mechanism is arranged on the fixing plate, and an insect pest data acquisition mechanism is arranged on the insect pest trapping and killing mechanism; a supporting mechanism is arranged at the bottom of the telescopic rod, a clamping mechanism is arranged on the telescopic rod, and the clamping mechanism is clamped on a forest tree and used for improving the stability of the device. The system can adapt to different tree heights, trunk diameters and complex woodland terrains, is matched with solar power supply, realizes stable field long-term operation, can accurately identify plant diseases and insect pests, predicts trends through fusion of meteorological and forest basic data, scientific analysis and an ARIMA model, triggers graded early warning and pushes prevention and treatment suggestions, and has good application prospects. Large-scale and refined forest management requirements are met, a scientific basis is provided for disease and pest control decisions, and the accuracy and efficiency of forest management and protection are improved.

The invention discloses a forest land intelligent pesticide application and soil treatment integrated robot based on a crawler platform, and belongs to the field of agriculture and forestry plant protection machinery. The device comprises a platform rack, a crawler walking mechanism, a lifting mechanism, a bucket, a stirring mechanism and a spraying mechanism, the crawler walking mechanism is installed at the bottom of the platform rack, the bucket is installed on the platform rack through the lifting mechanism, the stirring mechanism can be arranged at the bottom of the bucket, and the spraying mechanism is arranged on the platform rack. The three core problems that existing forest land management equipment is single in function, low in intelligent level and poor in terrain adaptability are solved. Specifically, through the integrated design, the limitation that traditional equipment can only independently complete pesticide application or soil loosening operation is overcome; an autonomous navigation and intelligent decision-making system is introduced, so that the mode of relying on manpower and extensive operation is changed; and through the innovative chassis and the lifting mechanism, precise, stable and efficient operation in the complex rugged forest land is achieved, and therefore the operation efficiency, safety and economical efficiency are remarkably improved.

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 invention discloses a land measurement device for land and forest land management, and belongs to the technical field of land measurement, the land measurement device for land and forest land management comprises an unmanned aerial vehicle and a laser radar, the laser radar is fixedly arranged at the bottom of the unmanned aerial vehicle, and the laser radar comprises a host, a side panel and a radar head, the main engine is fixedly arranged at the bottom of the unmanned aerial vehicle, the side panel is fixedly arranged at the bottom of the main engine, the radar head is arranged on the side wall of the side panel, and a rainproof cover is arranged on the side panel and located outside the radar head; two rotating rings are arranged on the side wall of the rainproof cover, a connecting rod is arranged between the two rotating rings, a scraper is arranged on the side wall of the side, facing the rainproof cover, of the connecting rod, and the scraper abuts against the side wall of the rainproof cover. According to the invention, the rain cover is arranged outside the laser radar, and the wind generated in the flight process of the unmanned aerial vehicle is used for cleaning the raindrops outside the rain cover, so that the influence of the raindrops on the measurement process of the laser radar is effectively reduced.

The invention discloses a small sample hyperspectral image classification method and device based on fuzzy contrast graph convolution. The method comprises the following steps: determining membership information, fuzzy node initial feature vectors and similarity of each initial graph node corresponding to each fuzzy cluster based on a hyperspectral image; generating a fusion weight, a fusion feature and a target feature according to convolution features output by convolution of different layers of fuzzy images; performing linear transformation operation and probability distribution operation on the target features in sequence to obtain the probability that the corresponding initialized graph node belongs to each category; and performing argmax operation on the probability to obtain a category index corresponding to the hyperspectral image. The uncertainty of pixels is effectively processed through fuzzy learning, interference of neighborhood pixels is weakened, the uncertainty between the pixels is better processed, and meanwhile richer and more expressive feature representation is obtained. The method has higher classification effect and robustness, and plays an important role in multiple fields of mineral exploration, environment monitoring, forest management, precision agriculture and the like.

The invention discloses a broad-leaved mixed forest operation prediction method based on time sequence per-tree data, which comprises the steps of collecting and preprocessing time sequence data, calculating a basic growth potential through basic growth potential quantification logic integrated with an attention mechanism, performing competition-microenvironment interaction correction in combination with per-tree scale data and microenvironment data, and predicting a broad-leaved mixed forest operation prediction result. And introducing biological interaction data and operation measure parameters to construct feedback optimization logic, outputting a final growth prediction value, generating an individual operation scheme, and dynamically adjusting through closed-loop iteration. The method solves the core problem of disjunction of prediction and operation in the prior art, realizes precise prediction and individualized operation of growth of the broad-leaved mixed forest, and adapts to forest growth dynamics and environmental changes.

The utility model provides a kind of push type forest mature seed collecting device, it is related to forest management technical field, and it includes: collector support, the collector support outer welding has push handle, the rotatable joint of two supporting rods between the collector support has center supporting rod, the seed collection ring is movably connected on the center supporting rod, the inside of the seed collection ring is fixedly connected with ring body centering plate by ring body connecting rod, different width elastic gasket can be installed between two adjacent seed collection rings by selection, so as to change the gap between two seed collection rings of collecting device in normal state, when the size of seed collected is larger, the gap between two seed collection rings is adjusted to increase, avoid the small volume sundries in cage interior in the process of collection, for small volume seed, the gap between two seed collection rings can be appropriately reduced, avoid large volume sundries in cage by gap in the process of collection, improve the application range of seed collecting device, reduce the entry of impurity in the process of collection.

The application discloses a low-efficiency forest reconstruction management method, and belongs to the technical field of low-efficiency forest management. The reconstruction management method comprises the steps of forest regulation, density regulation, mixed forest cultivation and post-period management and protection. The forest density is adjusted by forest regulation and thinning, and the health condition is improved, so that suitable habitat conditions are created for the growth of trees. Then, suitable native trees and shrubs are selected for mixed cultivation, and a mixed forest with complex structure and rich species is formed, so that the forest regeneration capacity is improved, the low-efficiency forest is positively succeeded, and the forest ecological benefits are improved. In the process, a composite regulation fertilizer is prepared and applied. The composite regulation fertilizer can help the seedlings to safely pass the slow growth period, promote root growth, adsorb the migrated nutrients in the surrounding soil and fix the nutrients at the root system of the seedlings, improve the competition ability of the seedlings for the soil nutrients in the forest, efficiently utilize the soil nutrients in the forest, ensure the good growth of the seedlings and effectively improve the afforestation benefits.

The invention belongs to the technical field of ecological monitoring and forest management, and discloses a tree photosynthetic yield and radial growth dynamic response monitoring and time-delay analysis method which comprises the following steps: performing high-resolution dynamic monitoring on radial growth of a sample tree through a micro-tree core technology, collecting a micro-tree core sample, and determining dynamic change of cambium cells; constructing a photosynthetic productivity model, and calculating the daily photosynthetic yield; carrying out normalization processing on radial growth and photosynthetic yield data, fitting a dynamic relationship between the radial growth and the photosynthetic yield by utilizing linear and nonlinear equations, and analyzing and discussing the instantaneity or hysteresis influence of the photosynthetic yield on the radial growth in combination with a time sequence; and judging the response relationship between the photosynthetic yield and the radial growth by adjusting the correlation parameters and the dynamic change trend of the fitting model. According to the method, the research precision and efficiency are remarkably improved, and an important technical support is provided for dynamic research and management of a forest ecosystem.

Achieve greater efficiency and sophistication in forest management operations. [Solution] A program to be executed by a computer having a processor, which causes the processor to perform the following steps: acquiring status information indicating the state of the forest at a specified time from multiple information sources; organizing the acquired status information in chronological order using identification information that uniquely identifies specific areas within the forest geographically as a common key, and storing it in a database as historical information; analyzing time-series changes in the satellite data included in the historical information, and extracting areas of change where vegetation in the forest has changed; and comparing the extracted changed areas with ground record data included in the historical information, and calculating the priority of visiting the forest for on-site inspection based on whether or not there is ground record data corresponding to the changed areas.