103 results about "Topographic map" patented technology

The invention relates to a southern grassland soil carbon reserve dynamic evaluation method and system fused with remote sensing monitoring, and relates to the technical field of soil carbon reserve evaluation, and the method comprises the steps: drawing a target region topographic map based on multi-source satellite remote sensing data, inputting an initial soil carbon reserve inversion model, and outputting an initial soil carbon reserve distribution diagram and a deterministic thermodynamic diagram; extracting an uncertain area according to a certainty degree threshold value, and configuring and labeling supplementary sampling points according to a division rule; acquiring parameter information of the detection robot, generating a digital twinborn model in combination with the topographic map, configuring a supplementary sampling scheme, and sampling supplementary sampling points to obtain supplementary soil carbon reserve data; and returning the supplemented soil carbon reserve data to the initial soil carbon reserve inversion model, generating a corrected soil carbon reserve distribution diagram and a corrected determinacy thermodynamic diagram, judging that the task is completed when determinacy reaches the upper limit of resource consumption, otherwise, continuing to supplement sampling correction. The problems that traditional soil carbon reserve assessment is inaccurate and low in efficiency are solved.

The invention provides a base station electromagnetic radiation visual monitoring method and device, and the method comprises the steps: determining a three-dimensional topographic map of a monitoring region, carrying out the electromagnetic radiation measurement of an actual geographic position corresponding to a preset collection point on the three-dimensional topographic map, and obtaining the actual measurement data; obtaining beam characteristic parameters of each base station and space coordinate data of the actual geographic position, and calculating predicted electromagnetic radiation data of the actual geographic position according to the electromagnetic radiation prediction model; correcting the model, and calculating electromagnetic radiation data of a target area on the three-dimensional topographic map based on actually measured electromagnetic radiation data and the corrected electromagnetic radiation prediction model; and visually displaying the actually measured electromagnetic radiation data of the preset acquisition point and the electromagnetic radiation data of the target area. Therefore, accurate monitoring and visual display of the electromagnetic radiation of the base station are realized, so that the accuracy and reliability of electromagnetic radiation evaluation are improved, and the overall change rule of the electromagnetic radiation value of each position in the whole monitoring area can be visually observed.

The application discloses a room semantic segmentation method, which comprises the following steps: S1, acquiring a topographic map of a house, detecting door features on the topographic map, and generating a setting area based on the detection positions corresponding to the detected door features; S2, segmenting the setting area to segment out doors from the setting area, and then verifying the segmented doors to determine the shapes and positions of the doors; and S3, based on the shapes and positions of the doors, performing semantic classification on the topographic map, and then generating a topographic map after the semantic classification. The room semantic information of a grid image is recognized and segmented in a deep learning manner, the understanding of a scene semantic by a robot is improved, and different cleaning strategies or other work can be used for different rooms.

The invention relates to the technical field of Beidou inspection data processing, and discloses an automatic inspection data acquisition and space-time association method under Beidou space-time reference. The method comprises the following steps: acquiring historical working condition data of inspection equipment based on nanosecond-level time synchronization and centimeter-level space positioning information of a Beidou system, and constructing a space-time dynamic prediction model; acquiring an equipment sensor measurement value, a moving track point set and a timestamp sequence in real time, and outputting a theoretical inspection value through a model; performing space-time multi-dimensional comparison on the theoretical value and the actual value, analyzing a time accumulation error, a space deviation degree and data flow form consistency, and generating a difference feature tensor; inputting the tensor into a geocoding topological reasoning network, simulating anomaly diffusion and generating an anomaly probability cloud picture in combination with topographic map node attributes and equipment distribution, and delineating an anomaly range; polling parameters are dynamically configured according to the cloud atlas, enhanced collection is started for a high-probability abnormal area, and data credibility inspection is executed on peripheral equipment.

Method, system, and non-transitory computer readable storage medium are provided for creating a shelf bathymetric map. In some embodiments, a satellite image with a shelf area and related altimeter data for at least a number of points of the shelf area are obtained. The shelf area in the satellite image and depth values for the shelf area from said altimeter data are selected. The selected depth values are associated with points of the shelf area based on geo-coordinates. A training dataset and a testing dataset are created from the associated points. A neural network is trained on the training dataset. The neural network is tested on the testing dataset. Inference of the neural network is adjusted based on testing results. A depth value for each satellite image pixel of the shelf area is predicted by the neural network.

The invention relates to computer aided design, and discloses a Braille printing method and system combined with 3D relief, and the method comprises the steps: carrying out the connection and fusion of a concave-convex topographic map and a multi-level depth map corresponding to each Braille dot matrix, and generating a dual-channel depth map as a printing pattern; controlling the 3D printing system to spray resin on the printing substrate based on the printing pattern read by the light field modulator, and scanning the surface of the resin by laser aiming at the braille dot matrix area to form a concave-convex structure corresponding to the concave-convex topographic map; on the adjacent side of the braille dot matrix area, a multi-wavelength DLP projection system is used for executing layered exposure, the embossment structure represented by the multi-level depth map is projected to the resin layer, and an embossment model is formed; and performing global curing on the whole printed piece based on ultraviolet light to form an integrated finished product of braille alphabets and 3D embossments. The invention further discloses a computer readable storage medium. The method aims at efficiently manufacturing seamless and high-precision multi-layer 3D embossment integrated finished products of braille alphabets and related semantics.

The application provides a method and device for planning an inspection route, electronic equipment and a storage medium. The method comprises the following steps: obtaining a digital orthographic image and a digital elevation model of a target photovoltaic power station area; generating a three-dimensional topographic map of the target photovoltaic power station area according to the digital orthographic image and the digital elevation model; determining a string center position and a string orientation of the photovoltaic string in the three-dimensional topographic map; and planning an inspection route of a camera of a flying machine for the photovoltaic string according to camera parameters of the flying machine and the string center position and the string orientation of the photovoltaic string. The three-dimensional topographic map can be used to more accurately determine the string center position and the string orientation, and then, according to the camera parameters of the flying machine and the string center position and the string orientation of the photovoltaic string, a more accurate inspection route planning result can be obtained, thereby improving the accuracy of the inspection route planning.

The application discloses a PLA composite material and a preparation method and application thereof, and belongs to the field of high polymer materials. The application adds a specific amount of a specific aromatic polycarbodiimide into polylactic acid, and controls the weight average molecular weight, the polydispersity coefficient and the D-lactic acid structural unit content of the obtained PLA resin within a specific range, so that the PLA resin has good wire drawing performance and low yellowness, is suitable for the high-speed 3D printing wire market, and the obtained wire can be used for 3D printing toys, ornaments, medical human simulation organs, artworks, topographic maps, house models and the like.

The invention discloses a debris flow early warning judgment method and system, and belongs to the technical field of hydraulic engineering, and the method comprises the following steps: a, determining the gully bed longitudinal gradient and the area of a drainage basin formation region of potential gully-type debris flow through a topographic map; b, obtaining lithology types of gully-type debris flow, and classifying the lithology types of the gully-type debris flow; c, calculating topographic indexes of gully-type debris flow; d, calculating a rainfall index for inducing gully-type debris flow; e, calculating an early warning discrimination index of the gully-type debris flow; and f, according to the early warning discrimination indexes of the gully-type debris flow, dividing early warning levels of the gully-type debris flow with different lithology. According to the method, a quantitative comprehensive early warning judgment index is constructed, the scientificity and accuracy of judgment of the debris flow starting critical condition are remarkably improved, multi-stage dynamic early warning from extremely low risk to high risk is achieved, and a direct operable technical basis is provided for accurate implementation of graded emergency response and disaster prevention resource allocation.

The invention provides a risk identification method and device for a fan impeller to sweep obstacles, electronic equipment and a storage medium. The risk identification method comprises the following steps: constructing a simulated topographic map for simulating the topographic condition after the construction of the wind power plant is completed based on an actually measured topographic map of the wind power plant and the construction information of each machine site; inputting the wind parameter information of each machine position point and the set information of the fan to be installed at each machine position point into a fan load simulation model to obtain the tower top displacement information after each fan is installed and operated; taking the terrain point with the risk to be identified around each machine location point as a target terrain point, and determining the minimum distance from the hub center of the target fan to the obstacle at the target terrain point based on the tower top displacement information of the target fan to be installed at the machine location point, the height of the obstacle at the target terrain point and the simulated topographic map; and if the difference value between the minimum distance and the radius of the impeller is smaller than a preset threshold value, it is determined that the target fan has the risk that the impeller sweeps the obstacle at the target terrain point.

This application discloses a method, apparatus, device, and storage medium for heterogeneous topographic map reconstruction based on spatial indexing and multidimensional ray detection, relating to the field of geographic information system processing technology. The method includes: emitting scanning rays within the geographic range corresponding to the target mapping area and obtaining their intersections with vector boundaries; classifying the target mapping area based on the intersections and scanning rays to identify boundary depressions and cavity edges; extracting background elevation points from a preset background topographic map library based on the identified boundary depressions and cavity edges; constructing a constrained Delaunay triangulation network and then smoothing it to obtain the target topographic file. This solves the problem of not being able to automatically identify irregular boundaries and cavities during stitching, which leads to elevation faults. It achieves automatic identification of the mapping area boundary morphology and accurate positioning of the elevation points to be filled without manual intervention.

The present application provides a kind of topographic map unlabelled area segmentation method based on deep learning, including collecting and segmenting topographic map grid, obtain multi-source tensor topographic map;Design backbone network, output the feature representation of multi-source tensor topographic map;Build geographic semantic library, increase the geographic semantic understanding of topographic map, generate semantic weight;Design main segmentation network, carry out initial segmentation prediction;Quantify the prediction uncertainty of main segmentation network, output initial segmentation result by the way of multiple iterations;For initial segmentation result, pixel connected domain detection, terrain constraint and spatial consistency improvement are carried out, and coherent segmentation result is obtained;Again, coherent segmentation result is visualized as heat map and spatial explainability layer.The present application can handle complex landform and spatial heterogeneous situation, make topographic map unlabelled area segmentation more accurate, intelligent and efficient, restore unlabelled area real landform, significantly optimize boundary and spatial distribution, promote the intelligent upgrading of geographic information system.

The application relates to a fusion remote sensing monitoring southern grassland soil carbon storage dynamic evaluation method and system, and relates to the technical field of soil carbon storage evaluation, and comprises the following steps: drawing a target region topographic map based on multi-source satellite remote sensing data, inputting an initial soil carbon storage inversion model, and outputting an initial soil carbon storage distribution map and a deterministic thermal map; extracting an uncertain region according to a certainty threshold, configuring a supplementary sampling point according to a division rule and marking; obtaining probe robot parameter information, generating a digital twin model in combination with the topographic map, configuring a supplementary sampling scheme, sampling the supplementary sampling point, and obtaining supplementary soil carbon storage data; returning the supplementary soil carbon storage data to the initial soil carbon storage inversion model, generating a corrected soil carbon storage distribution map and a corrected deterministic thermal map, determining that a task is completed when the certainty is up to standard or reaches a resource consumption upper limit, and otherwise, the task is continuously corrected by supplement sampling. The application solves the problems of inaccurate and low-efficiency traditional soil carbon storage evaluation.

The invention relates to the technical field of house safety detection, and discloses a characterization key parameter-based house safety assessment method, which comprises the steps of determining house information of a to-be-assessed house according to image information, landform information and a three-dimensional topographic map; performing safety grade evaluation on the indexes corresponding to the house information to obtain a plurality of index grades; determining weights corresponding to the indexes based on an importance degree evaluation matrix among the house information, and performing weighted summation on index rating according to the weights to generate a safety level score of the to-be-evaluated house; and evaluating the to-be-evaluated house according to the security level score. Specific house information is rated, and then the house safety level is comprehensively rated according to the importance degree of various kinds of house information, so that the safety comprehensive level of the house is obtained. The scientificity and the consistency of the evaluation result are remarkably improved, and a reliable decision basis is provided for maintenance, management and risk early warning of the house.

A mobile agricultural machine receives a topographic map indicative of topographic characteristics of a worksite, wherein the topographic characteristics are based on data collected at or prior to a first time and receiving supplemental data indicative of characteristics relative to the worksite, the supplemental data collected after the first time. A topographic confidence output is generated which is indicative of a confidence level in the topographic characteristics of the worksite as indicated by the topographic map, based on the topographic map and the supplemental data. In some examples, an action signal is generated to control an action based on the topographic confidence output.

The invention relates to the technical field of image recognition and block chain evidence storage, and discloses a block chain management system for plastic batch traceability and performance prediction. The invention aims to solve the problems that the identity label of the bulk plastic raw material is easy to lose and the traditional detection is lagged and the trust is lost. According to the method, a plastic unit microscopic image is obtained through multi-angle dark field imaging, and a standardized morphology graph is generated through self-adaptive segmentation; extracting texture features to generate a unique digital fingerprint, identifying microdefects and deducing a performance prediction score; and finally, recording the encrypted fingerprint and score to the block chain. According to the method, the unique identity label is established for the bulk material based on the microscopic visual features, non-destructive real-time performance pre-judgment is realized, the non-tampering property of traceability and quality data is ensured by utilizing the block chain, and a credible closed-loop management mechanism is constructed.

This provides an improved and simplified solution for manufacturing aesthetically pleasing dials, including three-dimensional decorations. [Solution] A method relating to a method for manufacturing a watch dial including a visible surface having a small surface area, wherein the surface includes a three-dimensional representation of a landscape, in particular a topographic map of a landscape, the method comprising: step 20 manufacturing a dial blank including a top surface having a three-dimensional structure relating to a three-dimensional representation of a landscape, the step comprising a substep 22 generating topographic data for constructing a three-dimensional structure on the top surface; step 29 processing the surface of the three-dimensional structure on the top surface of the blank, during which at least one visual feature of the surface is modified so as to obtain a three-dimensional representation; and step 35 finishing the blank to obtain a dial.

The application relates to a kind of artificial intelligence-based dam-break scene unmanned aerial vehicle monitoring method and system.The method comprises: obtaining hydrological data, meteorological data, satellite image data and topographic map data, and inputting into monitoring area identification artificial intelligence model, generating target monitoring area risk level information and target monitoring area detection range information;Based on target monitoring area risk level information and target monitoring area detection range information, the number of unmanned aerial vehicle and the preset route of each unmanned aerial vehicle are allocated;Control each unmanned aerial vehicle to fly along the corresponding preset route, obtain the target monitoring data of each unmanned aerial vehicle;The target monitoring data of each unmanned aerial vehicle is input into dam-break scene analysis artificial intelligence model, and dam-break scene analysis result is generated.The method can realize the efficiency, accuracy and real-time of dam-break monitoring through multi-source data driving, dynamic task allocation and artificial intelligence model optimization.

The application provides a full-automatic optometry topographic chart instrument, comprising an imaging system and a control processing system, the imaging system comprises an imaging assembly, an illumination device and a shooting device, the light exit side of the illumination device is provided with a projection objective, the light exit side of the projection objective is provided with a digital micromirror device or a transmission type calibration plate with a projection pattern, and the projection pattern is used for assisting qualitative and quantitative analysis of the refractive degree of the human eye; the control processing system comprises a data processing module for receiving fundus images and calculating a generated topographic chart and an output display module for displaying the topographic chart. The application also provides an optometry method using the full-automatic optometry topographic chart instrument. The full-automatic optometry topographic chart instrument and the optometry method provided by the application have simple equipment structure, low cost, complete detection parameters, and can obtain the ametropia condition of the human eye through the change of the projection pattern characteristics, and then obtain the optometry topographic chart through image processing.

The invention relates to a landslide identification method and device. The method comprises the following steps: acquiring a remote sensing image and basic geographic data of an area after a landslide disaster occurs, and fusing the remote sensing image and the basic geographic data through spatial registration to obtain a fusion data set with unified spatial reference; the basic geographic data at least comprises a topographic map and a geological map; extracting a landslide influence factor from the fused data set, and constructing a landslide sample data set based on the landslide influence factor and the spectral band of the remote sensing image; constructing a network model fused with a feature extraction module, a gridding attention mechanism module, a feature fusion module and a prediction module; based on the landslide sample data set, training and optimizing the network model to obtain a trained network model; and inputting the test image into the trained network model, and outputting the contour of the area in which the landslide is estimated to occur in the test image. By adopting the method, high-precision identification and boundary segmentation of the landslide mass in a complex terrain environment can be realized.

The invention relates to the technical field of map generation, in particular to a topographic map intelligent labeling and generating method based on a knowledge graph, and the method comprises the steps: obtaining data in real time; constructing a knowledge graph; generating a to-be-labeled element; carrying out preliminary annotation integration; carrying out low-confidence correction; dynamically updating the annotation; generating a primary topographic map; adjusting the historical duration; and generating a final plate. According to the method, a knowledge graph structure is introduced, spatial geometry, texture and spectral features of image data are fused with semantic features in text terrain description information, a feature vector library and hierarchical attribute relationship is constructed, and a labeling confidence calculation and dynamic updating mechanism is introduced in a labeling stage; and the spatial distribution and feature difference degree of the low-confidence region is corrected, so that the problems of inaccurate terrain change capture and limited labeling precision caused by single data source processing, static knowledge representation and insufficient utilization of multi-temporal data are effectively solved.

This invention discloses a system and method for identifying low back pain based on a combined electromyography (EMG) and muscle oxygenation (MOO) array. The system includes: a data generation module for generating EMG and MOO topographic maps based on EMG and MOO information from the lower back; a feature processing module for extracting features from the EMG and MOO topographic maps to obtain EMG and MOO topographic map feature data, wherein the EMG and MOO topographic map feature data are morphological features of areas of high activity; and an analysis and diagnosis module for inputting the EMG and MOO topographic map feature data into a trained neural network model to obtain a low back pain category identification result. This invention improves the objectivity and accuracy of low back pain detection and classification, thereby improving the treatment and rehabilitation effects of low back pain.

Embodiments of the present application disclose a water accumulation depth identification method and device, electronic equipment and a readable storage medium. The method comprises: collecting a water accumulation image of a road, and extracting a water accumulation edge contour of a water accumulation region in the water accumulation image; collecting point cloud data of the road, and obtaining a contour line topographic map in the same perspective as the water accumulation image based on the point cloud data, wherein the contour line topographic map is a map representing ground undulation and height conditions using contour lines; superimposing the contour line topographic map and the water accumulation image, and identifying water accumulation depth of the road in the water accumulation edge contour based on the superimposed image. Through the present application, the technical problem that water accumulation depth cannot be identified due to lack of a scale or reference object in the related art is solved, and the technical effect that water accumulation depth of the road can be accurately identified without a scale or reference object is achieved.

The invention provides a distribution network field survey path planning method based on a near-end strategy optimization PPO, and relates to the technical field of unmanned aerial vehicle path planning. A surveying area coordinate and a topographic map are input into an unmanned aerial vehicle, an unmanned aerial vehicle deployment point is initialized, and an environment state including a position coordinate, a target distance, a recognition certainty degree and a recognized target index is constructed; the environment state is input into a pre-trained PPO model, the model adopts a parallel action network structure, a discrete action network outputs a device identification instruction, a continuous action network outputs a flight speed vector, and a reviewer network evaluates a state value; and a comprehensive reward function is designed, and the unmanned aerial vehicle is guided to efficiently complete a survey task while avoiding repeated recognition. According to the invention, through cooperative processing of discrete identification decision and continuous flight control, the intelligent level and operation efficiency of distribution network exploration are significantly improved.

The present application relates to a kind of based on high-precision position sensing surveying and mapping method, device, equipment and storage medium, comprising the following steps, utilize high-precision GNSS receiver to collect the position signal of surveying and mapping area target survey point, obtain survey point coordinate and associate time stamp, form with time tag coordinate;Calibration coordinate is obtained by threshold screening and correction processing, and adjacent survey point spacing data is accounted;Calibration coordinate is combined with survey point spacing data, and the basic geographic three-dimensional base map obtained is grid division and feature point matching, and regional grid chart is generated;Based on regional grid chart, calculate terrain undulation, obtain grid elevation difference;Finally, combined with grid elevation difference, basic geographic three-dimensional base map is implemented texture filling and boundary optimization, complete the fine expression of topographic feature, output high-precision surveying and mapping image, solve how to improve the anti-interference ability of survey point data, and realize the technical problem of the automation, fine reconstruction from discrete coordinate to high-fidelity three-dimensional topographic map.

This invention relates to the field of data processing technology, and in particular to a method, apparatus, and storage medium for multi-source alarm data fusion processing in industrial parks. The method includes: constructing a risk propagation network map of the target industrial park based on a topographic map of the park, and setting node vulnerability indices for each risk source; extracting primary events within a monitoring period based on normalized alarm data from each risk source, and extracting diffusion characteristics for each primary event within the monitoring period; performing correlation analysis on the primary events within the monitoring period based on the risk propagation network map of the target industrial park, and constructing a risk causal graph based on the analysis results; correcting the risk causal graph based on real-time environmental data; calculating the cumulative risk value based on the corrected risk causal graph, and generating a multi-level early warning scheme. This invention effectively improves the efficiency of alarm data processing in chemical industrial parks.

The invention discloses a technical method for quickly evaluating the dam break submerging risk of a silt dam, which comprises the following steps of: extracting a dam control drainage basin area, a dam crest elevation and a current water level-reservoir capacity curve of the silt dam according to a current topographic map, and determining the position of a downstream residential area of the silt dam; determining the amount of water contained in the reservoir area during dam break of the silt dam, the corresponding frequency of dam break of the silt dam and the water depth in front of the dam before dam break; according to the dam front water depth before dam break, the maximum flow at the dam site during dam break is calculated; calculating the maximum flow of the residential area; calculating the submerging water level h1 of the residential area; calculating the submerging water depth of the residential area according to the submerging water level of the residential area; and calculating the submerging risk degree of the downstream residential area caused by dam break. According to the method, the judgment efficiency of the outburst risk of the silt dam under the extreme rainfall condition is improved, the required data is simple, the calculation method is simple and convenient, and the method is suitable for risk assessment of engineering facilities such as silt dams which are large in quantity and lack of engineering data.

The application provides a photovoltaic support erection construction simulation method, comprising the following steps: obtaining erection target position information, searching target position terrain information based on the erection target position information; displaying a target position simulation topographic map in a visual interface based on the target position terrain information; obtaining bored pile preset position information selected in the target position simulation topographic map, and obtaining photovoltaic support selection information, generating a corresponding photovoltaic support erection effect schematic model in the target position simulation topographic map based on the bored pile preset position information and the photovoltaic support selection information; performing feasibility analysis based on the target position terrain information, the bored pile preset position information and the photovoltaic support selection information, and outputting a photovoltaic support erection construction simulation analysis report based on the feasibility analysis result. The application can improve the early work efficiency of photovoltaic support erection construction.

The application discloses a shallow sea heavy mineral sand mine resource exploration method and related equipment, and the method comprises the following steps: obtaining pre-research data of a target shallow sea area, predicting an exploration scheme based on the pre-research data, and arranging a bottom seismograph in the target shallow sea area based on the exploration scheme; collecting passive source micro-motion data by using the bottom seismograph, and extracting original data from the passive source micro-motion data based on a preset data quality standard; constructing a horizontal and vertical spectral ratio curve based on the original data, performing frequency spectrum separation on the horizontal and vertical spectral ratio curve, and obtaining a low-frequency curve of a bedrock resonance peak; constructing a palaeotopographic map through bedrock surface depth inversion based on the low-frequency curve; obtaining a regional geological model of the target shallow sea area, superimposing and analyzing the palaeotopographic map and the regional geological model, and obtaining an evaluation result of heavy sand mine resource potential. The application can effectively improve the exploration directivity and the accuracy of resource potential evaluation by identifying the change of ore-controlling landforms, and can be widely applied to the technical field of data processing.