43 results about "Forest management" patented technology

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 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.

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 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.

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.

The utility model relates to the technical field of forest tree measuring equipment, and discloses measuring equipment for forest management and cultivation, which comprises a belt ruler for measuring the diameter at breast height of a forest tree; a crayon is used for marking; the measuring scale comprises a measuring scale rod, scale marks are arranged on the measuring scale rod, a sharp fork is installed at the bottom of the measuring scale rod, and a grab handle is fixedly installed at the top of the measuring scale rod. According to the utility model, the measuring scale rod is adopted to quickly position the measuring position of the diameter at breast height of a tree, and compared with the existing measuring mode of positioning the structure by independently pulling a measuring tape, the measuring scale rod is quicker and more portable, so that the forest tree measuring efficiency is improved, and the measuring scale rod can be used for directly measuring the height of some shorter tree seedlings, so that the practicability is good; meanwhile, when a measurer walks in a forest to measure a tree, the measurer can hold the grab handle with a hand and then is matched with the sharp fork at the bottom of the measuring ruler rod, so that the measuring ruler rod can be used as a mountain climbing crutch to assist the measurer to walk, the device has two purposes, multiple functions are realized, and the practicability is further improved.

A large language model driven forest management data processing method belongs to the cross technical field of forest resource management and artificial intelligence data processing. Multi-source data collection and preprocessing, forest management knowledge graph construction, large language model fine tuning and retrieval enhancement generation, data semantic fusion and understanding, management strategy reasoning: based on the fusion data, management intention and industry knowledge, the large language model automatically reasons to form the management strategy conforming to the forest growth law and the multi-objective balance, management scheme text generation: on the basis of completing the strategy and space matching, the forest management scheme text conforming to the forestry industry specification and management requirement is compiled, human-computer interaction and continuous optimization: through the human-computer interaction interface, the feedback information of the forest management scheme of the forestry workers is collected, and the generated management scheme is systematically evaluated from the forest resource sustainability, ecological function improvement, management target achievement degree, risk controllability and policy compliance.

The application discloses a ginkgo tree species identification and dynamic tree height inversion method based on multi-source data fusion, and belongs to the technical field of forest management, forest resource remote sensing monitoring, tree species identification and stand structure parameter. The application comprises the following steps: S1, data preparation and time phase unification; S2, pre-processing and minimum noise separation and noise reduction of high-resolution five satellite image data; S3, ginkgo identification feature construction; S4, ginkgo classification mapping and thematic mask generation; S5, GEDI sample screening and tree height inversion; and S6, precision evaluation and result output. The application can make high-resolution five hyperspectral data, GEDI L2A tree height samples and SAR structure features work collaboratively in a unified framework, so that the ginkgo tree species identification and dynamic tree height inversion are realized, and the growth and health state of trees can be intuitively monitored.

The utility model discloses a transplanting supporting device based on forest management, which belongs to the technical field of tree supporting and comprises a plurality of side plates, a pair of threaded sleeve plates are fixedly connected to the outer ends of the side plates, supporting legs are hinged to the outer ends of the side plates and positioned between the threaded sleeve plates, and the threaded sleeve plates are fixedly connected to the outer ends of the side plates. The outer ends of the side plates are fixedly connected with supporting rods, the supporting rods are located above the supporting legs, the ends, away from the side plates, of the supporting rods are fixedly connected with baffles, telescopic grooves are formed in the lower ends of the side plates, and extension rods are slidably connected into the telescopic grooves. Meanwhile, a large amount of water in the soil is evaporated through the extension rods, so that the soil is rapidly dried and has enough strength, the loosening of the roots of the trees can be effectively prevented, and the stability of the trees is also improved.

This invention relates to the field of forestry ecological monitoring and data processing, and discloses a monitoring method and system for rainfall redistribution characteristics in moso bamboo forests. It primarily addresses the problem of inaccurate quantitative assessment of the eco-hydrological characteristics of moso bamboo forests due to spatiotemporal misalignment of water quantity and quality data in traditional monitoring. Based on a unified rainfall trigger signal, water quantity and quality data from multiple forest stand comparison plots are collected simultaneously; unique parameters such as bamboo leaf clustering index and bamboo branch inclination angle are extracted to correct the canopy interception model and quantify water retention capacity indicators; machine learning models are used to predict nutrient output flux and non-point source pollution risk; and finally, a comprehensive evaluation index is generated. This invention achieves high-precision analysis of hydrological processes and can automatically generate forest management adjustment strategies, providing quantitative decision support for forestry ecological asset management.

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 discloses a management method for improving the carbon sequestration capacity of Masson pine forests, belonging to the field of Masson pine forest management technology. The method includes steps such as land preparation and clearing, density optimization, mixed planting, formation of multi-layered forests, and post-management. Through the above method, pure Masson pine forests are transformed and managed into multi-layered mixed forests. During this process, fermented fertilizer prepared from pine needle litter is applied to increase the organic matter content of the forest soil, promote good tree growth, increase biomass, and optimize forest stand structure. This, in turn, enhances the carbon sequestration capacity of the tree layer, understory vegetation layer, and soil layer, comprehensively improving the carbon sink capacity of Masson pine forests, which is of great significance for improving the ecological environment.

The invention discloses a camellia oleifera forest intelligent management method and system, a camellia oleifera planting mechanized intelligent management and agricultural machine remote monitoring management system and a storage medium, and belongs to the technical field of agricultural production management. The method comprises the following steps: acquiring current soil parameters; obtaining current crop growth data, and predicting the root depth of the current crop according to the current crop growth data; according to the current crop growth data and preset soil standard humidity data, the current soil required humidity is obtained; and obtaining a soil irrigation strategy according to the current required soil humidity, the current soil humidity and the root depth of the current crop. The system can accurately adapt to water demand differences of different growth stages and different growth vigor of camellia oleifera, effectively avoids poor crop growth vigor and yield reduction caused by insufficient water supply in traditional irrigation, remarkably improves the water resource utilization rate, reduces the irrigation cost, and promotes intelligence and refinement of camellia oleifera forest management.

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.

The invention provides a tree measurement method and device, electronic equipment and a storage medium, and is suitable for the technical field of tree measurement. The method comprises the following steps: acquiring three-dimensional point cloud data; the three-dimensional point cloud data is used for representing a forest scene, and the point cloud data carries coordinate information; performing single-tree segmentation on the three-dimensional point cloud data, and determining a point cloud model and coordinate information of each tree; based on the point cloud model of each tree, measuring each tree to obtain tree structure parameters of each tree; and generating a tree database corresponding to the forest scene based on the coordinate information and the tree structure parameters of each tree. According to the embodiment of the invention, the structured tree database including the detailed information of the single tree can be automatically generated according to the three-dimensional point cloud data, the tree measurement time is shortened, the tree measurement accuracy is improved, large-scale measurement can be realized, and the expandability in large-scale forest management or ecological research is improved.

The invention discloses an unmanned aerial vehicle-based forestry pest monitoring and prevention system, which comprises an unmanned aerial vehicle carrying module, an unmanned aerial vehicle mounting module, a forest management system terminal and a networking data terminal, and is characterized in that the unmanned aerial vehicle carrying module is used for receiving an instruction sent by the forest management system terminal and completing starting, stopping and navigation of an unmanned aerial vehicle; the unmanned aerial vehicle mounting module collects image data and sends the image data to the forest management system terminal, the unmanned aerial vehicle mounting module is used for mounting different types of pest control objects, the forest management system terminal is used for receiving the image data, processing the image data and uploading the processed image data to the networking data terminal, and the networking data terminal is used for comparing the image data with a database. And the types and the coping methods of the pests are judged and returned to the forest management system terminal. According to the invention, the efficiency of the forestry pest monitoring and prevention process is improved, forest trees with different heights can be monitored, the pests are identified through the Internet database, the prevention method is accurately obtained, and the workload of forest farm workers is reduced.

The invention discloses a bamboo forest management and automatic acquisition system, which belongs to the field of bamboo acquisition, acquires the size and the shape of a bamboo forest from the air through a map information acquisition device, and is used for directly positioning the position of a bamboo information acquisition device positioned inside a forest farm outside the forest farm. The situation that after entering a forest farm, the bamboo information collector is blocked by the forest farm, and consequently signals are blocked is avoided; the bamboo information collector carries out fixed inspection tour in the forest farm every day, changes of the bamboos in the forest farm every day are rapidly iterated, two parts of three-dimensional data are generated, and then prediction information of the bamboos is followed in real time through an intelligent algorithm; at the moment, the required bamboo type is input into the operation terminal, the acquisition module is used for acquisition, and the transportation module is used for transporting the acquired bamboo out of the bamboo forest.

The invention discloses a coastal saline-alkali land artificial forest management and protection and carbon sequestration and sink increase method and system based on unmanned aerial vehicle remote sensing. The method comprises the steps of obtaining an image of a coastal saline-alkali land artificial forest area, reconstructing a three-dimensional point cloud and generating DSM, DEM and CHM models; constructing a Mask R-CNN model, performing instance segmentation on the image, and generating a crown breadth area spatial interpolation graph; according to the crown breadth area spatial interpolation graph, identifying the heterogeneous stripe inlaying characteristics of the coastal saline-alkali soil, positioning a crown breadth abnormally low-value region as a soil stress key region, and adopting a targeted scheme for precise management and protection; establishing a biomass estimation model, calculating forest aboveground biomass and carbon sink, and evaluating the contribution of accurate management and protection to artificial forest carbon sequestration and carbon sink increase; according to the method, low-cost and high-efficiency accurate management and protection and carbon sink estimation are realized by optimizing the consumption-level camera carried by the unmanned aerial vehicle and utilizing artificial intelligence technologies such as deep learning and machine learning, and an economic and effective technical scheme is provided for making a man-made forest in the coastal saline-alkali land.

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 South China artificial broadleaf mixed forest management decision-making method. The method comprises the following steps: constructing a sample plot initial forest stand database containing spatial information; calculating the important value of each tree species of the sample plot according to the initial forest stand database of the sample plot so as to determine the target tree species of the sample plot; performing spatial structure parameter calculation on the trees in the sample plot, performing optimization, and then analyzing and checking the spatial relevance between the target tree species and the associated tree species by adopting a bivariate point pattern; and providing an optimal operation decision scheme for adjusting tree species composition and spatial configuration through structure optimization simulation by combining a forest space structure and a spatial correlation result and combining a stand current situation and a set operation target. According to the method, spatial structure parameter analysis and point pattern analysis are combined, large-diameter timber cultivation for the target tree is focused on, the inter-species spatial relevance between the target tree species and the associated tree species in the stand is comprehensively considered, and therefore a scientific basis is provided for stand spatial structure optimization of an existing artificial broad-leaved mixed forest.

The application discloses a kind of forest stand boundary extraction method and system, the method includes the following steps: obtaining data, including forest remote sensing image data and ground data;The data obtained is preprocessed;Double-path CBAM-UNet network model is constructed;The data after pre-processing is input into double-path CBAM-UNet network model to carry out tree species classification prediction and obtain tree species classification chart;Image mosaic is carried out to tree species classification chart to obtain tree species classification grid chart;Vectorization processing and vector boundary optimization are carried out to tree species classification grid chart to extract forest stand boundary and generate forest stand boundary vector chart.The forest stand boundary extraction method provided in the application can realize multi-scale feature capture and feature fusion of multi-source heterogeneous data through the double-path CBAM-UNet network model constructed, can solve the problem of automatic extraction of forest stand boundary according to high-precision identification of forest stand tree species under complex forest conditions, and provide high-quality data for forest management.

The application provides a forest fire analysis method and system based on satellite remote sensing, acquires a continuous acquisition thermal infrared, near infrared and visible light dimension satellite remote sensing image sequence of a target forest area, performs time sequence correlation modeling to generate a time sequence correlation feature set; inputs the set into a pre-trained forest fire dynamic analysis model to extract a forest fire suspected area feature set; based on a pre-set forest fire space-time evolution rule library, performs multi-condition constraint verification on the suspected area features to obtain a confirmed area feature set; generates forest fire real-time state description information and spread trend prediction description information according to the confirmed area features; finally generates forest fire prevention and control instructions containing area coordinate chains and sends them to a target forest management terminal. The application realizes accurate identification and dynamic prediction of forest fires through multi-dimensional time sequence correlation, dynamic model analysis and space-time rule verification.

The invention relates to the technical field of ecological restoration and forest management, and discloses a vegetation restoration method based on microhabitat regulation and mixed management collaboration, comprising the following steps: S1, determining a restoration target area for a degraded ecosystem of an ecologically fragile area; s2, establishing a dynamic model containing microhabitat, indigenous tree species and functional microbial flora configuration; and S3, inputting the microhabitat basic data obtained in the step S1 into the dynamic model in the step S2. By establishing dynamic association of the microhabitat, the tree species and the microorganisms, three-dimensional synergistic remediation of the microhabitat, the tree species and the microorganisms is achieved, the limitation of single microhabitat regulation or independent mixed operation can be effectively avoided, microhabitat regulation provides a suitable environment for tree species growth and microorganism activity, and a community structure constructed by mixed operation provides carbon source support for the microorganisms; the microorganisms back feed the growth of plants by improving the physicochemical properties of the soil to form a mutually promoted restoration closed loop, so that the self-restoration capability and the restoration persistence of a degraded ecological system are remarkably improved.

The invention discloses a method for interplanting phoebe zhennan in a pure masson pine forest to cultivate a mixed forest, and belongs to the technical field of masson pine forest management. Large-size phoebe zhennan container seedlings are cultivated and transplanted, a root cluster dispersing agent is prepared and applied during transplanting, the dispersing agent can effectively disperse root clusters and promote root systems to extend into soil, and therefore the soil quality is improved; the method solves the problem that the growth condition is reduced due to limited nutrient and moisture absorption after transplanting caused by root system winding and seedling raising container obstruction of large-sized nanmu container seedlings, ensures the survival rate and good growth condition of the large-sized nanmu container seedlings cultivated in the masson pine forest, and can effectively improve the management benefit of the masson pine forest. The method disclosed by the invention has a good application prospect in operation and transformation of the pure masson pine forest.

To provide appropriate support for forest management. [Solution] The information processing device includes a receiving unit, a prediction unit, and an output control unit. The receiving unit receives a designation of a range for a forest displayed on map information. The prediction unit predicts output information for the forest included in the range based on statistical information generated from forest information about the forest. The output control unit controls the output information to be output to the user.