83 results about "Mountain forest" patented technology

The invention relates to the technical field of intelligent path planning, in particular to an intelligent path planning method and system for hilly and mountain forest machine operation based on satellite remote sensing, and is suitable for intelligent path planning of forestry mechanized operation under complex terrain conditions. Building a multi-dimensional energy consumption prediction model in combination with forest machine parameter data; an initial path is generated by adopting layered progressive path planning, and dynamic adjustment is performed by utilizing real-time environment data so as to adapt to a complex mountain environment; under the scene of multi-machine collaborative operation, the efficiency and safety of the final operation path are ensured through optimization of the adjusted path, the method accurately recognizes the dangerous area, optimizes the passing path, remarkably improves the safety and efficiency of forest machine operation, and is suitable for the complex operation environment of hills and mountains.

The invention provides a forest type remote sensing classification method based on historical sample migration, and belongs to the field of forest monitoring. The method comprises the steps of firstly determining a monitoring area, a historical year and a target year, obtaining corresponding sample points, then obtaining long-time-sequence multi-source remote sensing data of the historical sample points and representing forest growth succession features, then judging whether a forest type is replaced or not, and migrating sample data which is not replaced to the target year; extracting classification features related to remote sensing classification by using the multi-source remote sensing data of the target year; dividing the monitoring area into a plurality of plant regions, and selecting the optimal classification feature of each plant region from the related classification features; finally, based on the optimal classification features and migrated historical forestry field survey sample point data which are not replaced, forest types of all plant regions are classified. According to the invention, the number of samples in the target year is increased, and the accuracy of mountain forest type remote sensing classification under the small sample condition is improved.

The invention discloses a lightweight small target detection method based on improved YOLOv11, and relates to the technical field of artificial intelligence and computer vision. Comprising the following steps: acquiring a mountain forest region image containing a small target, and performing data preprocessing on the mountain forest region image containing the small target to obtain a small target data set; a C3K2 module of the YOLOv11 model is replaced with a CGBlock module, two initial conv modules at the input end of a backbone network are reserved, the other conv modules are replaced with WP modules, an original detection head is replaced with an LDHead detection head, and the improved YOLOv11 model is constructed; inputting a small target data set, continuously iterating to obtain an optimal parameter, and generating a trained improved YOLOv11 model; and small target objects in the mountain forest area are detected. The method has the advantages of being light in structure, high in detection precision and high in complex background adaptability, and is suitable for small target detection tasks in a resource-constrained environment.

The invention provides a fire-fighting virtual prevention simulation system and method for a mountain forest region, and the method comprises the steps: extracting a terrain elevation change trend according to a mountain numerical model, and calculating a spreading path of a fire behavior under different terrain conditions in combination with vegetation density distribution; a meteorological data real-time updating module is adopted to obtain current meteorological conditions and humidity data, and prediction parameters of the fire spreading speed are dynamically adjusted; if the terrain elevation change exceeds a preset threshold value, calculating an acceleration effect of the fire behavior on the steep slope, and correcting a spreading path prediction result; if the vegetation density distribution shows valley characteristics, the chimney effect of the fire behavior in valleys is analyzed, and the fire development situation prediction map is updated; according to the soil type and the geological structure, combustion characteristics of different areas are judged, and a calculation formula of the fire spreading speed is adjusted; and adopting a machine learning algorithm, fusing the terrain elevation, the vegetation density and the meteorological condition data, and generating a prediction result of the fire spreading path.

The invention relates to the technical field of remote sensing biomass detection, in particular to a mountain forest biomass recognition method and system based on high-resolution remote sensing data, and the method comprises the steps: dividing all clusters into a high-gradient shady slope cluster and a low-gradient sunny slope cluster based on the gradient feature value of each pixel; based on the pixel values of all the pixels in each low-gradient sunny slope cluster, screening out feature pixels from each low-gradient sunny slope cluster; and based on a result of fusion of a mean value of pixel values of all pixels in each high-gradient shady slope cluster and a texture feature value, and in combination with a confusion degree of coordinates of all feature pixels in each low-gradient sunny slope cluster, determining biological complexity, and identifying the biomass of the mountain forest region to be identified. According to the method, the problem that the biomass in the mountain forest is misestimated due to interference of topographic factors is solved, and the accuracy of identifying the biomass condition of the mountain forest is improved.

The invention relates to the technical field of fire source positioning path planning, in particular to an unmanned aerial vehicle fire source point positioning path planning method based on machine learning. Comprising the following steps: firstly, acquiring a suspected fire source estimated position of a mountain forest, and establishing a fire source attraction vector field according to position information and environment information of a suspected fire source area; secondly, generating an accurate initial fire source search path according to influence information in the fire source vector field; in the searching process, a fire source point recognition model is adopted, the model carries out learning from multi-dimensional features according to image information and numerical information, the accuracy of fire source recognition is improved, and the position of a fire source can be adjusted according to a recognition result; and finally, establishing an obstacle repulsion field by using obstacle information of the mountain forest, and combining the obstacle repulsion field with the fire source attraction vector field to form a total influence vector field optimization search path. According to the method, the accuracy of unmanned aerial vehicle fire source point positioning path planning is improved.

The invention discloses a fabricated integrated house (SWP), and belongs to the technical field of fabricated buildings. Comprising a foundation part 01 which is a cast-in-place concrete foundation or a spiral pile foundation and the like; the ground 02 comprises floor bearing plates and the like; 03, a steel structure part; the outer wall comprises an outer facing layer of the outer wall, a wall body of the outer wall and an inner facing layer of the outer wall, or the outer wall is a mortise and tenon structure wall body; doors and windows 08, indoor suspended ceilings 09, metal tiles and the like; the system further comprises an inner partition wall 07 and a roof heat preservation and insulation layer 10. The system can also be of a two-storey or more structure. The invention provides an integral house solution for people who are deficient in concrete or inconvenient to transport in national grassland areas or mountain forest areas of Southeast Asia; the structure is stable, fixed and compact; and factory manufacturing, field installation and construction are convenient, the speed is high, the cost is low, and the cost performance is high. The screw pile foundation is suitable for soil land; the concrete foundation is wide in application range; and the wall body is hollow and is heat-insulated. The system can also be used for building communities in batches.

The invention provides a mountain forest region satellite laser footprint positioning error correction method, which comprises the following steps: acquiring laser echo waveform data of a mountain forest region, and calculating a mountain forest canopy laser real ranging value of each laser footprint; selecting a point near the laser footprint as a laser footprint possible point, and calculating to obtain a satellite-ground integrated laser ranging value of the laser footprint possible point and a ranging residual error between the satellite-ground integrated laser ranging value and a real mountain forest canopy laser ranging value; traversing a plurality of continuous laser footprints, calculating distance measurement residual errors of possible points of the laser footprints, and accumulating the distance measurement residual errors to obtain a distance measurement residual error sum; and iteratively calculating the distance measurement residual sum of the laser footprint possible points, and taking the laser footprint possible point corresponding to the minimum distance measurement residual sum as a correction point, so that correction of the laser footprint positioning error of the mountain forest region can be completed without using high-precision topographic data.

The invention discloses a steep mountainous area forest height inversion method and device fused with rising and falling rail short wave InSAR data, and aims to solve the problems of insufficient observation information and steep mountainous area gradient decoherence during InSAR inversion, and the method comprises the steps: obtaining rising and falling rail short wave InSAR data and sparse LiDAR data, and carrying out the preprocessing; calculating the gradient by using a digital elevation model, and performing terrain effect correction on the effective vertical wave number; determining a lifting rail data overlapping region, and establishing a semi-empirical SINC model for a non-overlapping region to invert the forest height; constructing a double-baseline forest height inversion model considering coherent phase and amplitude at the same time for the overlapped region, determining an optimal model parameter by taking the sparse LiDAR forest height as control, and performing inversion on the forest height; and finally, inlaying forest heights of the overlapping region and the non-overlapping region to form a complete and continuous product. According to the method, high-precision forest height inversion of the steep mountainous area is realized by fusing the ascending and descending rail InSAR data, and the method has good stability and popularization value.

The present invention provides an ecosystem service optimization assessment method based on mountain micro-geomorphological feature analysis, comprising: performing topographic and geomorphological division on a mountainous area, performing micro-geomorphological type division on the mountainous area based on a Geomorphons method, and obtaining mountain location information; obtaining a mountain forest type based on the mountain location information; based on the mountain forest type, obtaining a coefficient of variation of a vegetation index of a ratio value and a tree layer biomass of each mountain forest type area according to multispectral unmanned aerial vehicle image acquisition and processing and tree layer investigation; using the coefficient of variation of the vegetation index of a ratio value and the tree layer biomass of each mountain forest type area to respectively correct an InVEST model habitat suitability parameter and a carbon density value, and obtaining an optimal InVEST model; and using the optimal InVEST model to obtain an optimization assessment result of an ecosystem service. The present invention solves the problem of low accuracy of ecosystem service assessment in mountainous areas in the prior art.

The invention discloses a mountain forest global intelligent fire monitoring and automatic disposal system. The system comprises a rainwater collection and water polo fire extinguishing unit, a wind-solar complementary power supply and robot dog battery replacement unit, a multi-sensor monitoring unit, an unmanned aerial vehicle disposal unit and an intelligent control center. The system is based on theoretical design and engineering planning, rainwater is collected and filled into a specially-made rubber water ball, and accurate throwing fire extinguishing of the unmanned aerial vehicle is achieved; wind-solar power generation and robot dog autonomous power conversion design is adopted, so that the power supply continuity of the system is ensured; through the multi-level multi-sensor fusion design, low false alarm and rapid identification of the fire behavior are realized; and a three-level fire disposal strategy is designed, and automatic disposal and manual remote takeover are supported. The water storage tank is of a heat preservation heating structure, and annual stable operation is achieved. The system is suitable for fire prevention of large-area mountain forests, realizes water source self-sufficiency, autonomous power supply, intelligent monitoring, automatic fire extinguishing and autonomous operation and maintenance in principle, and remarkably improves the early-stage handling capacity of mountain forest fires.

The invention belongs to the technical field of forest fire monitoring and early warning, and relates to a mountain forest farm fire prevention monitoring system which comprises an environment monitoring module and a video monitoring module, the environment monitoring module comprises a sensor and a data acquisition unit, and the video monitoring module comprises a high-resolution camera and a processing module. The environment monitoring module and the video monitoring module are connected to the data transmission module, and the data transmission module is connected to the early warning response module. According to the invention, the forest environment change can be monitored in real time, the fire risk can be automatically identified, and the early warning information can be timely sent out, so that the scientificity and effectiveness of fire prevention and control are improved, and the monitoring, early warning and response capabilities of forest fire are improved to protect the ecological environment and human property safety.

The invention provides a method for correcting satellite laser footprint positioning errors in mountainous forest areas, comprising: acquiring laser echo waveform data of the mountainous forest area, calculating the true laser ranging value of the mountainous forest canopy of each laser footprint; selecting points near the laser footprint as possible laser footprint points, calculating the satellite-ground integrated laser ranging value of the possible laser footprint points, and the ranging residuals between the satellite-ground integrated laser ranging value and the true laser ranging value of the mountainous forest canopy; traversing a number of continuous laser footprints, calculating the ranging residuals of the possible laser footprint points and accumulating them to obtain the ranging residual sum; iteratively calculating the ranging residual sum of the possible laser footprint points, and taking the possible laser footprint points corresponding to the minimum ranging residual sum as correction points, so as to complete the correction of the laser footprint positioning errors in the mountainous forest area without using high-precision terrain data.

The invention relates to the technical field of biodiversity research, and discloses a mountain tree species diversity remote sensing estimation method, which comprises the following steps: acquiring mountain tree species distribution data, acquiring a mountain remote sensing image, preprocessing the data, and calculating a tree species diversity index according to tree species distribution. Calculating the correlation between the spectral heterogeneity index and the tree species diversity index, constructing a mountain tree species diversity remote sensing mapping model according to the influence factor calculated by the spectral heterogeneity index, extracting the optimal parameter of mountain tree species diversity remote sensing estimation, and making a tree species diversity index spatial distribution map according to the spectral heterogeneity index to realize tree species diversity estimation. A terrain correction mechanism is introduced into the spectral heterogeneity index constructed by the method, the stability and reliability of the spectral heterogeneity index are improved, spectral response of the model to different tree species is improved after a weighted distance construction mechanism between pixels is combined, and the method is suitable for mountain forest areas with obvious topographic relief and has good application prospects. And multi-source input of multi-sensor remote sensing images is supported.

The invention discloses an image data acquisition method and device based on an unattended intelligent airport, and relates to the technical field of image data processing.The method comprises the steps that forest image data are acquired based on the unattended intelligent airport, the unattended intelligent airport selects a forest area meeting preset mountain forest conditions, and the selected forest area is selected as a forest area; the unattended intelligent airport is used for taking off, landing and parking a predetermined type of unmanned aerial vehicle, and the predetermined mountain forest conditions comprise that the height fall of a mountain land is greater than a preset fall threshold value, the forest vegetation coverage rate is higher than a preset coverage rate threshold value, and the number of roads in a forest is lower than a preset number threshold value; and analyzing the preprocessed forest image data by adopting a pre-trained machine learning model, identifying a forest resource state, and displaying the forest resource state on a terminal screen. The technical problems that image resource analysis is difficult to carry out on an unattended intelligent airport system in a severe environment and the operation efficiency is low in the prior art are solved.

1. Name of the designed product: sofa (mountain forest). 2. Use of the designed product: sofa for sitting when resting. 3. Design points of the designed product: in shape. 4. Picture or photo best indicating the design points: perspective view.

The application relates to the technical field of remote sensing biomass detection, in particular to a mountain forest biomass recognition method and system based on high-resolution remote sensing data.The method comprises the following steps: based on the slope characteristic value of each pixel, all clustering clusters are divided into high-slope shady slope clusters and low-slope sunny slope clusters; based on the pixel value of all pixels in each low-slope sunny slope cluster, feature pixels are screened out from each low-slope sunny slope cluster; based on the fusion result of the pixel value mean value and the texture characteristic value of all pixels in each high-slope shady slope cluster, and in combination with the confusion degree of the coordinates of all feature pixels in each low-slope sunny slope cluster, the biological complexity is determined, and the biomass of a to-be-recognized mountain forest region is recognized. The application solves the problem that the biomass in the mountain forest is wrongly estimated due to the interference of terrain factors, and improves the accuracy of the recognition of the biomass condition of the mountain forest.

The invention discloses a rare earth mining area illegal mining unmanned aerial vehicle remote sensing intelligent detection method fusing multi-scale convolution and an attention mechanism. According to the method, YOLO11m is used as a baseline network framework, a multi-scale convolution attention enhancement module is embedded in the feature connection position of a backbone network and a neck network of the YOLO11m, and the multi-scale convolution attention enhancement module is formed by cascading a channel attention module, a space attention module and a multi-scale convolution residual block module. Complementary collaboration is formed among semantic channel enhancement, spatial region focusing and multi-scale context modeling through a progressive enhancement link, so that the detection rate and the positioning stability of a suspected illegal mining target under the complex mountain forest region condition are improved.

The application relates to the technical field of environmental protection, in particular to a forest desertification treatment method, which comprises the following steps: firstly, preparing a planting layer; then, transporting the planting layer to a desertification area; then, filling nutrient soil in the planting layer; then, planting plants in the nutrient soil; then, laying the planting layer on the surface of a stone wall; then, fixing the planting layer; then, watering the surface of the planting layer; and finally, spraying sticky mud on the surface of the planting layer. The planting layer is laid and fixed on the surface of the stone wall, and plants are planted in planting cavities in the planting layer, so that the influence of the slope gradient of the stone wall on the planting of the plants can be ignored, green plants can be effectively covered on steep stone walls, especially on huge stone blocks forming cliffs in mountain forests, and the desertification treatment effect of the mountain forests is improved.

The utility model discloses a small fire pump which comprises a pump shell, a dynamic impeller and a power output shaft are arranged in the pump shell, a pump outer cover is arranged on the front side wall of the pump shell, the circumferential face of the power output shaft is fixedly connected with the dynamic impeller, and the rear side wall of the power output shaft penetrates through the pump shell and is rotationally connected with the pump shell. A static impeller is arranged on the rear side wall of the pump outer cover, a sealing groove is formed in the rear side wall of the pump outer cover, and the pump shell, the dynamic impeller and the pump outer cover are all formed by casting aluminum parts in a finish machining mode. By means of the structure, the water supply device can adapt to various kinds of power, has the advantages of being small in size, easy to carry, light in weight, low in oil consumption, low in work, efficient, capable of achieving multiple purposes and multiple matching in one machine and easy and convenient to install, is lower in economic cost, is suitable for being widely popularized in the fields of grassland emergency fire fighting water supply, mountain forest fire fighting, agricultural irrigation and the like, and has great market popularization value.

The invention provides a high-yield tetraacetyl phytosphingosine strain and application thereof, and belongs to the technical field of biology. Wild Wickerhamomyces ciferrii RK01 which is separated from rotten wood in a mountain forest in Yunnan China for the first time is used as an original strain, ascospores are generated by the original strain, so that a haploid strain with better tetra-acetyl phytosphingosine (TAPS) production performance is obtained through separation, and a mutant strain W. ciferrii CG223 with high yield of TAPS is obtained by performing multiple rounds of ARTP iterative mutagenesis on the haploid strain. The strain can produce 4.02 g / LTAPS after being cultured for 72 hours under a batch shake-flask culture condition, which is 11.82 times that of a wild strain, and can produce 47.3 g / LTAPS after being cultured for 96 hours in a 20L fermentation tank, so that the yield of TAPS is remarkably increased, and large-scale production of TAPS is facilitated.

The application discloses a forest leaf area index inversion acquisition method and system based on data fusion. The acquisition method comprises the following steps: performing cloud removal processing and cutting on remote sensing image data of a research area to obtain a segmented image; based on land cover data, obtaining forest pixels in each segmented image, and performing spatial aggregation matching with resolution to obtain aggregated remote sensing images; extracting a vegetation index from the segmented image; obtaining forest canopy height data of the research area; taking reflectivity values of different bands in the aggregated remote sensing images, the vegetation index, the forest canopy height data and a sun sensor related parameter as inputs, and taking the forest leaf area index as output to construct a forest leaf area index fusion prediction model, and obtaining a prediction result. The LAI distribution result obtained by the application has more spatial details, is more suitable for mountain forest ecosystems with large spatial heterogeneity, and can accurately and rapidly monitor mountain vegetation parameters.

The invention provides a fire monitoring method, which comprises the steps of performing data acquisition on a mountain forest fire scene through data acquisition equipment, performing scanning for flame color distribution and contour shape, and generating an initial fire feature matrix in combination with dynamic features of motion track fluctuation and regional heat accumulation; after the fire risk distribution map is obtained, adjusting key parameters in the fire feature vector by adopting a solution concentration proportioning technology and simulating the influence of a chemical environment stability test on the smoke diffusion rate, and obtaining the optimized fire state description; and according to the dynamic boundary of the fire area, fusing boundary heat flow analysis and solvent evaporation rate logic, analyzing the change trend of the smoke concentration gradient in the fire area, and generating the fire diffusion prediction sequence.

The present application relates to the technical field of mountain forest fertilization, and discloses a mountain forest tree energy-saving and environment-friendly slow-release fertilizer device, which comprises an enclosing cylinder, the enclosing cylinder is provided with an enclosing cavity, the enclosing cavity is provided with a swing ring plate, the swing ring plate is provided with an outer circumferential ring and an inner circumferential ring, the inner circumferential ring surrounds a tree base and is elastically connected with the tree base, and the outer circumferential ring surrounds the enclosing cavity in a circumferential direction and is elastically connected with the inner side wall of the enclosing cavity; the bottom of the swing ring plate is arranged in a suspended manner, the swing ring plate is provided with a storage cavity for placing fertilizer, and a plurality of fertilizer application holes are arranged in the swing ring plate; the top opening of the enclosing cavity is provided with a floating ring plate, the floating ring plate is annular, the outer side of the floating ring plate is provided with a floating outer circumferential ring, and the inner side of the floating ring plate is provided with a floating inner circumferential ring; the floating outer circumferential ring is elastically connected with the top of the enclosing cylinder, and the floating inner circumferential ring is elastically connected with the tree base; the floating ring plate is provided with a water cavity which is concave downward, and a plurality of water permeable holes are arranged in the floating ring plate; a plurality of support strips are arranged at the bottom opening of the enclosing cavity, and the inner ends of the support strips are fixedly connected with the tree base.

To provide an information processing system that supports mountain forest operation management.SOLUTION: An information processing system includes: an operation method estimation unit that, with a mountain forest image taken of a mountain forest of a management object as an input, using a trained model to determine the operation method for the mountain forest, estimates the operation method of the mountain forest of the management object; a geographic information acquisition unit that acquires geographic information related to the mountain forest of the management object; a processing unit that inputs a prompt, which includes the estimated operation method for the mountain forest, the acquired geographic information, and an instruction to perform specific processing such as creation of a report related to the mountain forest, creation of an operation plan for the mountain forest, or answering to a user question, into a sentence generation model that generates a sentence according to an input sentence, and acquires a result of the specific processing using an output of the sentence generation mode; and an output unit that outputs the result of the specific processing.SELECTED DRAWING: Figure 15

This invention relates to an automated monitoring method for the dynamic changes of plant diversity in mountainous forest areas, comprising: constructing a three-dimensional model of the target mountainous area and deploying a sensor network; collecting microclimate data and soil characteristic data to determine a spatial distribution matrix; acquiring historical plant distribution data of the target mountainous area, mapping it to the spatial distribution matrix to construct a comprehensive distribution map of environmental factors, and determining a correlation model between plant distribution and environmental factors; acquiring real-time satellite remote sensing image data of the target mountainous area, using the correlation model to analyze the characteristics of changes in plant cover and plant diversity distribution, and locating several key plant distribution areas; identifying plant species and counting their numbers in the key plant distribution areas, updating the comprehensive distribution map of environmental factors, and completing the automated monitoring of the dynamic changes of plant diversity in the target mountainous area. This invention integrates multi-source environmental data to achieve automated analysis of plant diversity distribution.

The utility model discloses a multifunctional alpenstock which comprises an ejector rod, the top of the ejector rod is fixedly connected with a grip, and a compass is arranged in the middle of the top end of the grip. The alpenstock is diversified in function and is of an integrated structure, and the compass is arranged, so that a climber is prevented from getting lost in a mountain forest; a mobile phone of a climber can be charged by arranging the power bank; media music is played through the Bluetooth sound equipment, so that a climber feels comfortable in body and mind; by arranging the angle-adjustable lamp body, illumination can be provided for climbers at night; the mountaineering stick is supported on the ground by rotating the support plate, a mobile phone is placed in the universal mobile phone clamp and can be placed in a posture, mountaineering shooting is carried out through the mobile phone, the lifting mechanism is arranged, the length of the mountaineering stick can be adjusted, and the mountaineering stick can be conveniently used by climbers of different heights; and the damping rod, the buffer pad and the spring are matched for use, so that buffering and damping are achieved.

The invention provides a self-circulation drinking water supply station for a mountain stream environment, which is characterized in that an integrated controller carries out cooperative management of power generation, energy storage and water treatment and supply, and comprises an integrated house, a horizontal shaft type wind driven generator, an inclined-jet type vertical hydraulic generator, a built-in toilet, an integrated working bar counter, an instant heating hanging type water dispenser and a glass door. Island operation of equipment is met through wind power and water power resources in a mountain stream, self-circulation utilization of mountain stream water is achieved by combining with built-in water treatment corollary equipment, and the problem of high-quality drinking water and beverage water resource supply of an original mountain forest is solved; and meanwhile, due to an integrated modular factory product structure, the application scene is greatly improved, the construction standard is reduced, and the system can adapt to most scenic spot scenes.

The invention relates to the technical field of polygonatum sibiricum planting, in particular to an under-forest polygonatum sibiricum ecological planting device and method in a karst stony mountainous area. According to the technical scheme, the sealwort planting device comprises a planting and transporting assembly, and a planting distance adjusting assembly used for adjusting the sealwort planting range is installed on one side of the planting and transporting assembly. According to the invention, the control unit controls the seedling storage pipe to release or close the polygonatum sibiricum seedlings in the four seedling transport pipes, and the planting spacing of the polygonatum sibiricum seedlings is adjusted according to the regional state of the karst rocky mountain forest, so that the planting spacing is well adjusted according to environmental factors; compared with traditional small and medium-sized planting equipment which needs to frequently change positions for planting polygonatum sibiricum, the equipment has higher efficiency and smaller size.

1. Name of the Design Product: Dual-purpose Brooch and Pendant (Mountain Forest Little Fox). 2. Use of the Design Product: Jewelry for wearing. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Key Points: Perspective View 1.