260 results about "Geomatics" patented technology

The invention provides a particulate matter and ozone source monitoring method and system based on a distributed sensor, and relates to the technical field of pollution treatment. According to the invention, sensor nodes with geographic perception capability are deployed in a monitoring area in a high-density manner, pollutant concentration and meteorological parameters are collected in real time, and data are uploaded to a cloud platform for preprocessing and dynamic calibration; a machine learning model is constructed based on the combined features of the pollutants and the meteorological factors, a driving relation is mined, and pollutant influence factors are extracted; further performing joint modeling on the influence factors and regional emission source data, identifying the coupling strength between pollutants and emission sources by adopting a classification or clustering method, and judging the categories of main sources; backward trajectory simulation, source fingerprint analysis and multi-source regression decomposition are combined to realize pollution path inversion and source contribution rate quantification; and finally, constructing a geographic information visualization platform, displaying a pollution thermodynamic diagram, a contribution change diagram and an evolution path diagram, and providing support for multi-source pollution traceability and scientific management and control.

The invention relates to the technical field of ecological environment monitoring and geographic information, in particular to a coastal wetland soil sample point quality evaluation method and system based on multi-source environmental data. According to the method, remote sensing, climate, terrain, ocean and historical land coverage data are fused, and indexes are extracted and standardized; an environment similarity score (weighted Markov / neighbor weighted Euclidean), a historical consistency score (multi-temporal coverage + transfer penalty) and a source reliability score (metadata integrity + anomaly detection + NDVI-SOC residual) are constructed respectively; comprehensive scores are obtained through self-adaptive weight fusion, A / B / C grades are divided, and a report and a high-quality sample point set are output. The system comprises a data access module, a scoring engine module and a visualization module, and the precision and robustness of soil mapping and carbon storage evaluation can be remarkably improved.

The embodiment of the invention discloses a mineral resource exploration data analysis method and device based on three-dimensional space modeling. The method comprises the steps that back-flushing pushing-covering structure feature information is extracted through structure interface occurrence measurement, lithology combination analysis and structure movement trace recognition and converted into geologic structure feature parameters; stratigraphic age data and lithology distribution information are integrated, and a three-dimensional stratigraphic model is constructed with a stratigraphic superposition relation as a constraint; geophysical data are imported to extract geophysical response characteristics of stratums with different depths, and lithologic boundary correction is combined to obtain deep fracture characteristic parameters; sedimentary system division is carried out on lithofacies paleogeographic information, and deep fracture characteristic parameters are fused to establish a fracture system three-dimensional model; the multi-feature association relationship is identified, the ore body prediction model is established, the spatial data is input to obtain the three-dimensional visual prediction result of the hidden ore body spatial distribution, and the exploration efficiency and accuracy in the deep phosphorite exploration process are improved.

The invention provides a cloud condition adaptive geostationary satellite sea surface temperature inversion method based on deep learning, and relates to the technical field of sea surface temperature inversion, and the method specifically comprises the steps: obtaining geostationary satellite observation data, geographic information data, polar orbit satellite sea surface temperature and cloud products, and analyzing the sea surface temperature and atmospheric background data; performing standardization preprocessing on the obtained stationary satellite observation data; constructing a cloud detection data set; a cloud detection model of deep learning is constructed and trained; constructing a clear sky data set; a clear sky inversion model of deep learning is constructed and trained; constructing a data set for under-cloud inversion model training; constructing an under-cloud inversion model of deep learning and training the under-cloud inversion model; and integrating the cloud detection model, the clear sky inversion model and the under-cloud inversion model, adaptively calling the corresponding model according to a real-time cloud detection result, and generating a final sea surface temperature product. According to the technical scheme, the problem that in the prior art, the accuracy of a reconstructed product on the spatial structure cannot be comprehensively reflected is solved.

The invention provides an unmanned aerial vehicle intelligent inspection and digital management system for road and bridge facilities. The unmanned aerial vehicle intelligent inspection and digital management system comprises a cloud digital twin platform, distributed edge computing nodes and an unmanned aerial vehicle cluster capable of being dispatched and executed. The cloud digital twin platform is used for constructing and maintaining a high-precision three-dimensional semantic model corresponding to physical road and bridge facilities, and the model fuses geological and geographic information, historical operation and maintenance data and real-time sensor data. Through intelligent collaborative operation and edge real-time data processing of the unmanned aerial vehicle cluster, qualitative leap of inspection efficiency is achieved, labor cost and safety risks are greatly reduced, physical facilities are holographic digitalized, management decisions are made to be based on comprehensive, visual and dynamic visual data, and the inspection efficiency of the unmanned aerial vehicle cluster is improved. According to the method, the accuracy and scientificity of operation and maintenance management are remarkably improved, the evolution trend prediction of the health condition of the facility is realized through deep data mining and simulation analysis, a key basis is provided for accurately formulating a maintenance strategy, and the service life of the facility is effectively prolonged.

The invention relates to the technical field of geographic information data, in particular to an ecological remote sensing data processing system which comprises a remote sensing layer acquisition module, a boundary position checking module, a region coding integration module, a spatial change splicing module and an ecological trend drawing module. According to the method, by accurately matching the geographic identification information and the spatial boundary value, the coverage range and the positioning precision of the ground feature pattern spots are remarkably improved, the time information and the spatial information are effectively integrated, the continuity and the accuracy of the data are enhanced, the boundary resetting technology effectively reduces the errors of the geographic information, and the time-space continuity of the data is improved; the processing efficiency is greatly improved by constructing a continuous layer structure and optimizing a data retrieval process, the fine boundary splicing technology also allows fine tracking of ecological changes, more detailed data support is provided for ecological monitoring, the ability of ecological trend analysis is enhanced, and thus the overall effect and application value of ecological monitoring are improved.

The invention relates to the technical field of geographic information engineering, in particular to a surveying and mapping geographic system based on a remote sensing technology, which is characterized in that a multi-modal remote sensing data acquisition module synchronously acquires satellite remote sensing images, aviation LiDAR point cloud, unmanned aerial vehicle oblique photography and ground Internet of Things sensing data; the data fusion collaboration module carries out geographic coordinate calibration and position coding, and generates a surveying and mapping data set with unified precision in combination with an improved Mamba fusion model; the dynamic terrain high-precision inversion module performs three-dimensional terrain reconstruction, and completes terrain deformation monitoring in combination with an InSAR interference measurement technology and a time sequence analysis algorithm; the real-time error correction module constructs a BP neural network optimized by an ISSA algorithm, and dynamically corrects a terrain three-dimensional model and a terrain deformation result; the intelligent visual application module constructs a digital twinborn simulation model and automatically generates a standardized surveying and mapping result report. Therefore, the problems of weak multi-source data fusion, low terrain inversion precision and the like in the prior art are solved.

The invention relates to an earth surface deformation detection and classification method and system fusing CNN and SBAS-InSAR technologies, and the method comprises the steps: obtaining high-precision deformation data through a small baseline subset and an interference synthesis radar technology (SBAS-InSAR), constructing a CNN classification frame through combining PCA-enhanced optical satellite images, elevation, soil physical parameters, geological landform maps and other multi-source geographic information, and carrying out the detection and classification of the earth surface deformation through the CNN classification frame and the SBAS-InSAR technology. And identification of deformation types such as landslide, settlement and lifting is realized. The process comprises multi-source satellite data acquisition and preprocessing (including InSAR sight velocity decomposition and optical / topographic feature extraction), generation of a preliminary deformation label based on a classification algorithm of a gradient and a deformation velocity threshold, and recognition of a deformation type through a multilayer CNN model. According to the method, the deformation mode is automatically clustered and analyzed in a large-range area, the accuracy and detail performance of deformation type recognition are remarkably improved, the accuracy rate reaches 93%, the method is superior to a traditional method, a stable and extensible tool platform is provided for geological disaster monitoring, and positive risk management of landslide or land subsidence prone areas is assisted.

The invention discloses a GIS-based cross-section diagram real-time synchronous display method and system, and relates to the technical field of geological modeling, and the method comprises the steps: importing multi-source heterogeneous geographic data, carrying out the standardized preprocessing, and generating a geographic information data set in a unified format; carrying out multi-dimensional feature extraction on the geographic information data set by adopting a feature level fusion algorithm, and constructing a multi-dimensional geographic feature model fusing geological structure, terrain elevation and earth surface coverage information; performing data optimization by adopting a spatial interpolation algorithm based on the multi-dimensional geographic feature model to generate a continuous geographic surface model; and performing parallel contour tracking and topological sorting on the discrete section line segment set, and generating a user-defined section diagram supporting interactive parameter adjustment in real time. According to the method, the multi-dimensional geographic feature model is constructed through the feature level fusion algorithm, semantic level association of the geologic structure, the terrain elevation and the earth surface coverage information is realized, the problem of pixel level fusion is solved, and the data space consistency error is reduced.

The invention provides a submarine topography and land elevation matching method based on multi-source data fusion, and belongs to the technical field of geographic information technology and ocean engineering cross fusion. Seamless splicing of sea and land topographies is realized through multi-source data preprocessing, topographic feature correlation extraction, dynamic compensation matching and adaptive weight fusion; according to the method, the problems of data heterogeneity, dynamic environment adaptability and insufficient feature association can be solved, the matching precision can reach + / -3cm, the processing efficiency is also improved, and the method is suitable for coastal zone modeling, ocean engineering and other scenes.

The invention discloses a unified rainfall downscaling method based on a multi-stream analysis diffusion model, and the method comprises the steps: collecting the meteorological data of a target region, including low-resolution rainfall data and preset auxiliary variable data, generating a low-resolution rainfall field, and calculating the rainfall deviation between a high-resolution real rainfall field and the low-resolution rainfall field; based on preset auxiliary variable data, combining the low-resolution rainfall data to form multi-modal condition input; constructing a precipitation downscaling model which takes the analysis diffusion model as a framework and is combined with a mixed attention U-shaped network, and predicting precipitation deviation; and training the rainfall downscaling model, performing reasoning by adopting the rainfall downscaling model, inputting meteorological data of the target area, outputting predicted rainfall deviation, and superposing the predicted rainfall deviation to the low-resolution rainfall field to obtain super-resolution rainfall. According to the method, multi-source meteorological and geographic information is effectively fused, high-fidelity and high-resolution rainfall data is generated, the generalization ability is high, and the calculation efficiency is high.

The invention relates to the technical field of channel monitoring and underwater topography analysis, in particular to a multi-beam sounding data driven underwater topography profile extraction method and device and a medium, and the method comprises the steps: obtaining channel region multi-beam sounding original data, carrying out the standardized preprocessing, and outputting a sounding data set; performing spatial interpolation and vectorization processing on the sounding data set to generate channel geological data, and issuing the channel geological data as a similar three-dimensional channel bottom graph through a geographic information service platform; generating a profile path, and generating interpolation points according to a preset interval; constructing a spatial index structure based on the sounding data set, and establishing an adjacent sounding point retrieval channel for each interpolation point; and in allusion to the same profile path, acquiring multiple periods of sounding data, calculating water depth difference, and dynamically and visually displaying an abnormal movement phenomenon by using a broken line graph. According to the method, efficient extraction, dynamic comparison and automatic early warning of the multi-period sounding data can be realized, and the analysis efficiency and accuracy of the channel topographic change are remarkably improved.

The invention provides a geographic information surveying and mapping data intelligent analysis method and system, and relates to the technical field of surveying and mapping data analysis, and the method comprises the steps: determining a to-be-analyzed region, and obtaining geographic information surveying and mapping data; gridding the to-be-analyzed region to form a plurality of spatial positions, constructing a time sequence, and extracting multi-dimensional trend feature vectors in different time windows based on the time sequence; for each spatial position, screening to obtain a final candidate neighborhood; screening to obtain an effective neighborhood according to the multi-dimensional trend feature vector; performing interpolation processing on the time sequence of the target spatial position based on the effective neighborhood to obtain a complete time sequence of each spatial position; and performing spatio-temporal change mode analysis on the complete time sequence, identifying a spatio-temporal evolution rule and generating a spatio-temporal change analysis report. According to the method, accurate identification and intelligent analysis of the spatial-temporal evolution law of the geographic surveying and mapping data can be realized, and an interpretable analysis result with geographic significance is provided.

The invention discloses an unmanned aerial vehicle detection and directional interference system based on an artificial intelligence technology, which belongs to the technical field of unmanned aerial vehicle detection interference and comprises a data acquisition module, an unmanned aerial vehicle identification module, a geographic information correction module, a trajectory prediction module and a directional interference module. The data acquisition module is used for acquiring geographic information data of a target area based on a geographic information system, comprises a radar, an acoustic sensor and a radio frequency spectrum detection sensor, and is used for acquiring feature data of a moving object in the target area; and the unmanned aerial vehicle identification module obtains feature data of a moving object in the target area based on the data acquisition module. According to the unmanned aerial vehicle detection and directional interference system based on the artificial intelligence technology, the obstacle in the target area is identified, the personalized behavior of the unmanned aerial vehicle is analyzed, the trajectory prediction and interference strategy of the unmanned aerial vehicle is optimized in combination with topographic features, and the trajectory prediction precision and the directional interference effect are improved.

The invention discloses a geographic space entity vectorization method and a geographic space entity vectorization system based on multi-modal fusion and metric learning, which are used for solving the problems that the traditional geographic information representation is single and multi-source data cannot be effectively fused. The method comprises the following steps: firstly, carrying out multi-modal feature extraction on text and coordinate information of a geographic space entity; then, through a neural network model with an independent coding stream and a deep fusion layer, intelligently fusing the multi-modal features and projecting the multi-modal features to a unified embedded vector space; and finally, optimizing the model by adopting a metric learning normal form through a hybrid triple sampling strategy combining semantic and spatial constraints. The invention also provides a system for realizing the method. The system comprises a feature engineering module, a training set generation module, a model training module and a reasoning application module. The system can automatically complete the whole process from data preprocessing, model training to vectorization reasoning. Compared with the prior art, the method has the advantages that the embedded vector with high semantic distinction degree and accurate spatial perception capability can be generated, and the computability and intelligence of geographic spatial data are effectively improved.

The invention discloses a GIS-based arid and semi-arid region farmland irrigation priority dynamic evaluation and zoning method, system, device and medium, and belongs to the technical field of farmland irrigation priority evaluation and zoning, and the method comprises the steps: collecting various types of remote sensing satellite data of a to-be-irrigated region; performing pretreatment; identifying the boundary and range of the to-be-irrigated area, and extracting a remote sensing image of the to-be-irrigated area; based on the remote sensing image of the to-be-irrigated area and the basic geographic information, parameter calculation is carried out, and normalization processing is carried out; performing superposition calculation on each normalized parameter according to a set weight to obtain an irrigation priority index; partitioning the to-be-irrigated area based on the irrigation priority index to generate an irrigation priority map; and judging whether agricultural irrigation management requirements are met or not according to preset conditions. According to the method, temperature vegetation drought indexes, normalized moisture indexes, water resource accessibility and crop economic value parameters are coupled; the irrigation priority index weight can be automatically adjusted according to a season strategy.

The invention discloses a GeoJSON-oriented geospatial analysis execution method and system, and relates to the technical field of geographic information science and artificial intelligence. One embodiment of the method comprises the following steps: acquiring a GeoJSON file to be processed; acquiring a natural language task instruction input by a user, performing semantic understanding on the task instruction by using a first language model, extracting an operation target and a constraint condition, and generating an overall task; disassembling the whole task into a plurality of logically ordered sub-tasks to form a sub-task sequence; calling a function library API or generating a script code, executing the subtask, and generating a subtask result; continuously receiving and evaluating the generated sub-task results, and updating the sub-tasks which are not executed completely according to the evaluation result of the sub-task results until all the sub-tasks are completed; and integrating the subtask results to generate an output result. In this way, efficient, reliable and controllable automated geospatial analysis driven by natural languages is achieved.

The invention discloses a virtual role memory extraction and application system and method based on geographic position triggering, and relates to the technical field of artificial intelligence and geographic information processing. The system comprises a mobile client and a cloud server, the client collects multi-modal data and triggers retrieval through an H3 index, and a cloud constructs a space-time memory bank to achieve hybrid storage and retrieval. According to the method, a smooth trajectory is obtained through multi-sensor fusion positioning, geo-fence pre-filtering is carried out based on an H3 index, an S-T-S model is adopted for sorting memory, and memory is adaptively updated after a context-related reply is generated through LLM. According to the method, time-space-semantic integrated memory management is realized, the problems of context dislocation, low retrieval efficiency, insufficient virtual-real fusion precision and the like of an existing system are solved, a virtual character has anthropomorphic geographical environment perception and memory wake-up capability, and interaction immersion and real-time performance are improved.

The invention relates to the technical field of geographic information measurement, in particular to a landform surveying method and system for territorial space planning, and the method comprises the steps: 1, carrying out the fusion preprocessing of multi-source data; 2, constructing a planning constraint dynamic rule base; 3, space-time constraint coupling analysis: taking the digital elevation model as a reference, and correcting the space offset of the land cover map through a thin-plate spline function; comparing the planning threshold value with the current landform parameter in real time, and marking a conflict coordinate set of gradient overrun or settlement overspeed; 4, intelligently segmenting the landform units; and 5, planning suitability output: setting a dynamic buffer distance according to the fault activity grade and the rock-soil body type, and generating an early warning layer when a town unit exists in a buffer area. According to the method, remote sensing images, laser radar point clouds and geological survey data are fused, space-time dislocation among various data sources is eliminated, and the precision of space analysis is improved.

The invention relates to the technical field of surveying and mapping and geographic information, and discloses a metal mine area terrain updating method based on a laser radar. The method comprises the following steps: fusing a satellite SAR remote sensing image, an unmanned aerial vehicle orthoimage and a mining area production operation plan, and constructing a topographic change probability grid model; based on the model, identifying a high-probability change area and generating a target laser radar scanning task; and the unmanned aerial vehicle platform executes high-precision scanning, denoising, registration and ground point extraction are performed after point cloud data are obtained, and the three-dimensional digital terrain reference model is locally updated. The system comprises a multi-source data acquisition module, a probability modeling module, a dynamic task planning module, a laser scanning execution module and a model updating module. Through on-demand accurate scanning and closed-loop automatic updating, the terrain monitoring efficiency, accuracy and timeliness are improved, and resource consumption is reduced.

The invention relates to the field of geographic surveying and mapping equipment, and discloses a geographic information surveying and mapping device which comprises a cruise trolley, a base is fixedly installed at the top end of the cruise trolley, a base is movably installed in the base, and a rotating disc is movably installed in the middle of the top end of the base. Supporting columns are fixedly mounted at the four corners of the top end of the rotating disc, the top ends of the supporting columns are fixedly mounted at the four corners of the bottom end of a mounting frame correspondingly, movable blocks are movably mounted on the two sides of the top of the mounting frame correspondingly, shells are fixedly mounted at the top ends of the movable blocks correspondingly, and short shafts are movably mounted on the upper sides of the inner side ends of the shells correspondingly; l-shaped clamping plates are fixedly mounted at the inner side ends of the short shafts correspondingly, and anti-skid lines are arranged at the inner side ends of the L-shaped clamping plates correspondingly. A detection instrument can be conveniently fixed, the instrument is driven by the motor to rotate longitudinally and transversely to expand the surveying and mapping range, the damping function is achieved, automatic surveying and mapping can be achieved according to a preset route, structural design is reasonable, and surveying and mapping efficiency, accuracy and stability are improved.

The invention relates to the field of surveying and mapping devices, in particular to a geographic information acquisition surveying and mapping device which comprises a device body, a lifting mechanism is arranged on the device body, a spiral drill rod is arranged on the lifting mechanism, and a transmission mechanism used for rotation of the spiral drill rod is arranged between the lifting mechanism and the spiral drill rod. And a sample pushing mechanism for reducing upward extrusion of the soil sample is arranged between the interior of the spiral drill rod and the transmission mechanism. According to the geographic information acquisition surveying and mapping device, the spiral drill rod, the transmission mechanism, the sample pushing mechanism and other components are arranged, and when the spiral drill rod descends and rotates through the lifting mechanism and the transmission mechanism, arc-shaped pushing teeth move upwards in an intermittent mode and slightly deflect by a certain angle, so that when soil is lifted by means of blade grooves, the soil is lifted; according to the spiral drill rod, the spiral blades are arranged, soil in the grooves of the spiral blades is pushed, excessive extrusion of the spiral drill rod on the soil in the soil drilling process can be reduced, disturbance on the soil is reduced, and the accuracy of follow-up laboratory analysis is further improved.

The invention provides a geographic JSON data generation method and device, equipment, a medium and a program product, and relates to the technical field of artificial intelligence. The method comprises the steps that geographic semantic keywords are obtained, and the geographic semantic keywords are used for representing the query intention of a user in a geographic space; converting the geographic semantic keywords to obtain a target space range; space objects in the target space range are screened, a candidate space data list related to the target space is obtained, and the candidate space data list comprises identifiers corresponding to one or more candidate space objects; extracting position information and attribute information corresponding to each candidate spatial object in the candidate spatial data list, and constructing a geographic information cue word; and inputting the geographic information cue word and a preset GeoJSON format template into a pre-constructed large language model, and outputting GeoJSON data. According to the method and the device, the GeoJSON data generation efficiency can be improved, and meanwhile, the labor cost involved in the process is reduced.

The invention relates to the technical field of geographic surveying and mapping, in particular to a geographic information surveying and mapping data anomaly detection method based on data analysis, which comprises the following steps: collecting and integrating multi-source geographic information data, and eliminating error and interference information through data cleaning; mining a spatial position relationship, a time sequence change rule and attribute characteristics in the data; determining space, time and time-space combined anomaly types and judgment standards in geographic information data, and constructing a space neighborhood LOF algorithm model to realize accurate detection and identification of abnormal data; and the model performance is optimized by adjusting algorithm parameters. The geographic information surveying and mapping data anomaly detection method based on data analysis supports multi-source data fusion processing of GPS, remote sensing images, laser radar point cloud, total station data and the like, realizes space, time and space-time associated multi-dimensional feature deep mining, constructs an anomaly detection model based on density, and optimizes model parameters. And the model precision is verified and evaluated in real time.

The invention provides a geographic information surveying and mapping data processing method and system, and the method comprises the steps: obtaining terrain superpixels, carrying out the segmentation operation of the terrain superpixels, obtaining terrain superpixel blocks, carrying out the pulse frequency coding operation of the terrain superpixel blocks, obtaining a pulse frequency sequence, and carrying out the pulse delay coding operation of the terrain superpixel blocks. The method comprises the steps of obtaining a pulse frequency sequence, obtaining a pulse delay sequence, adjusting pulse density through terrain superpixels, obtaining pulse density, carrying out feature integration on the pulse frequency sequence, the pulse delay sequence and the pulse density, and obtaining a structured feature tensor. The method comprises the following steps: obtaining original point cloud data, carrying out position calibration on the original point cloud data through equipment movement track data, carrying out feature extraction on original point cloud according to a structured feature tensor, obtaining a terrain block map with a classification label, and improving the accuracy of geographic information surveying and mapping data while ensuring terrain continuity.

The invention discloses a limited view field cross-view-angle geographic positioning method based on view enhancement contrast learning, and belongs to the technical field of computer vision, deep learning and geographic information. The method comprises the following steps: executing view enhancement operation on an original panoramic ground view and a panoramic satellite view to generate a multi-view sample set; extracting each view feature embedding vector through a feature encoder sharing the weight; constructing a composite optimization target based on an InfoNCE loss function, and optimizing a total loss function through bidirectional cross-view-field contrast learning and in-view-field contrast learning to obtain an optimized feature encoder; and inputting a new limited field-of-view ground query image into the optimized encoder to extract features, performing similarity comparison with the satellite image feature library, and determining a geographic position. According to the method, the difference between the field of view and the viewpoint is reduced through active view enhancement, the feature robustness is enhanced through multi-target contrast learning, the positioning challenge caused by the limited field of view and unknown direction is effectively solved, the positioning precision and robustness are remarkably improved, and the method is suitable for multiple fields such as automatic driving and robot navigation.

The invention relates to the technical field of geographic multi-dimensional data management, and provides a rasterized geographic information construction method based on Gaussian projection, which comprises the following steps: carrying out zoning projection processing on the earth surface, and converting a geodetic coordinate system into a rectangular plane coordinate system by adopting Gaussian-Kruger projection; further dividing the projection zone into a plurality of longitude and latitude zones, and distributing a unique identifier EarthID for each longitude and latitude zone; in each latitude and longitude zone, taking the central point as a reference, and calculating the offset Axoffset and Ayoffset of the grid in the latitude and longitude directions; the position of each grid is uniquely determined according to the EarthID, the Axoffset and the Ayoffset; grid coordinates are converted into geodetic coordinates through an inverse calculation method, and visual display of the grids on the map is achieved. According to the method, the problems of unified expression, efficient management and flexible application of the multi-scale geographic space data are effectively solved, and powerful technical support is provided for space-time big data analysis in the fields of smart cities, traffic planning, emergency command and the like.

The present invention discloses a geographic information collection and mapping device and a mapping method, which relate to the technical field of mapping device technology. The device comprises a level and a telescopic ruler, wherein a top fixed ruler is provided at the upper end of the telescopic ruler, and an auxiliary mechanism is provided on the upper surface of the top fixed ruler. The auxiliary mechanism comprises a drone assembly and a marking assembly. The drone assembly comprises a fuselage component, and the fuselage component comprises: a bottom hanging plate, a fixed notch is provided at the center of the bottom hanging plate, an auxiliary fixed slot matched with the fixed notch is provided at the upper end of the top fixed ruler, and the marking assembly comprises: an auxiliary laser light, the auxiliary laser light is located on one side of the bottom surface of the bottom hanging plate, and a small camera matched with the auxiliary laser light is provided on the upper surface of a support plate body located on the front of the drone. In this solution, by providing the auxiliary mechanism, the equipment can break through geographical restrictions, expand the mapping scope, and comprehensively improve the efficiency, accuracy and adaptability of geographic information collection and mapping.

The invention belongs to the technical field of hazardous chemical substance transportation safety monitoring, and provides a hazardous chemical substance transportation monitoring system based on visual image processing. The data acquisition module is used for acquiring multi-dimensional data including GIS (Geographic Information System) geographic information, hazardous chemical substance transportation task data, spectral visual data of hazardous chemical substance transportation vehicles and environmental meteorological data of hazardous chemical substance transportation routes; the multi-dimensional data processing module is used for performing modeling analysis and risk assessment on the multi-dimensional data based on the configured edge computing unit and the cloud platform to obtain a risk assessment result; and the self-adaptive early warning module is used for implementing safety monitoring and early warning of dangerous chemical transportation based on the risk assessment result. According to the invention, the multi-dimensional data acquisition module, the processing module, the self-adaptive early warning module and the like are adopted for cooperative work, so that comprehensive and accurate monitoring of the whole transportation process of the hazardous chemical substances is realized.

The invention relates to a marking device for geographic information acquisition, which comprises a first rod body and a second rod body which are separately arranged, the first rod body is provided with a heating assembly, and the second rod body is provided with a lighting assembly; the first rod body and the second rod body are in butt joint up and down, a power connection assembly is arranged at the butt joint position, a conductive assembly is arranged on the first rod body, and the conductive assembly is electrically connected with the heating assembly and the power connection assembly; the second rod body is provided with a power supply assembly and a circuit board, and the circuit board is electrically connected with the lighting assembly and the power connection assembly. By arranging the heating assembly, a heat source can be provided, so that effective and accurate reference can be provided in combination with the infrared surveying and mapping device, and application of the infrared surveying and mapping device during surveying and mapping at night is greatly facilitated. And the illumination assembly can provide illumination, so that the operation in the night scene is facilitated. And through the arrangement of the power connection assembly, the conductive assembly and the power supply assembly, the circuit board can be combined to supply power to the heating assembly and the lighting assembly, and normal heating and lighting are guaranteed.