156 results about "Geomatics" patented technology

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 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 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 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 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 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.

The application discloses a petrochemical field precise space-time information processing and service system based on Beidou. The application is based on a petrochemical Beidou ground enhancement network of the Beidou navigation satellite system, relies on a petrochemical special network to collect satellite observation data, deploys a set of precise space-time information processing and service system of China Petrochemical in a petrochemical intelligent cloud, and provides independent controllable real-time centimeter-level positioning navigation and geographic information collection services in a plurality of high-precision positioning and navigation work scene applications such as long-distance pipeline inspection, dangerous chemical vehicle monitoring, industrial control system time service, oil and gas pipeline safety monitoring, geographic information data collection and geological disaster prevention monitoring.

The invention discloses an oblique photography geographic information surveying and mapping unmanned aerial vehicle which structurally comprises a protection device, a support, a supporting device, propellers and a vehicle body, the support installed on the vehicle body is connected with the supporting device, the propellers arranged at the upper end of the supporting device are matched with the vehicle body for flight surveying and mapping, and the protection device is installed at the bottom of the vehicle body. The instruction receiver in the unmanned aerial vehicle body transmits an instruction, the instruction receiver receives the instruction and then transmits the instruction to the processor, the processor synchronously starts the motor to drive the propeller to rotate, the device lifts off, the flight direction of the unmanned aerial vehicle is controlled through the transmitted instruction, and data is transmitted to the processor for processing through cooperation of the camera. When the machine body lands on the ground after surveying and mapping are completed, the base can directly make contact with the ground, then the base transmits landing impact force to the buffer assembly in the connecting cylinder, the buffer assembly is matched with the connecting cylinder to disperse the impact force, and the landing impact force directly acting on the machine body is effectively reduced.

A kind of geotechnical engineering application analysis system based on BIM and GIS combination, it is related to geographic information technology field, it is characterized in that the system includes: data integration module, model fine presentation module, evaluation analysis module and attribute data modeling module, each module is sequentially connected, data integration module carries out integrated display to the various data of multi-source heterogeneous;Evaluation analysis module carries out evaluation analysis to pile foundation model according to the spatial position and attribute information of pile foundation model layer and engineering geology model layer in three-dimensional scene;Attribute data modeling module carries out modeling to the attribute field of geotechnical investigation design information model according to modeling parameter, and modeling result is rendered and exported in three-dimensional scene.Optical advantage: system realizes to "BIM+GIS" integrated technology as foundation, to multi-source heterogeneous data visualized integration, quantification analysis, collaborative application as goal, forms set above, ground, underground geotechnical engineering multi-source data three-dimensional visualized integrated display.

1. The name of the design product: geographical position search graphical user interface of electronic equipment. 2. The use of the design product: for an electronic equipment. 3. The design points of the design product: the interface content and layout of the graphical user interface. 4. The picture or photo that best indicates the design points: interface change state diagram. 5. The use of the graphical user interface: the interface is the geographical position search interface of the multimodal transport path planning decision engine platform software, the main view is the main interface of the software, after inputting "Wenchang Street, Harbin City" in the search bar on the upper left side of the main view and clicking the "magnifying glass" button, the interface change state diagram is entered, the interface is displayed in a three-dimensional mode, so that the user can intuitively understand the geographical information. 6. Other circumstances that need to be explained: the map content in the interface is only for display and is not within the protection scope of the design.

The application discloses a kind of spatiotemporal continuous land surface water body generation methods based on multi-source geospatial data, belong to remote sensing information processing and geographic information technical field.The method includes: obtaining the multi-source geospatial data related to water body distribution, including climate, hydrology and topographic data;It is spatiotemporal resolution and coordinate system, constructs pixel level characteristic variable;Based on existing water body data constructs training sample library;Using random forest or gradient boosting tree and other machine learning methods trains water body distribution reconstruction model;The model is applied to historical or missing time node, and water body distribution prediction result is generated every time phase;Finally form long time sequence, spatially continuous, resolution consistent land surface water body grid data set.The application can effectively fill in remote sensing data missing, improve the spatiotemporal continuity and consistency of water body data, suitable for wide range, long time sequence water body dynamic monitoring and analysis.

The invention relates to the field of remote sensing satellite observation task planning, in particular to a remote sensing satellite hotspot target observation method and system based on meteorological elements, which are used for carrying out priority division and analysis on tasks according to the conditions of importance degree, emergency degree, observation time window and the like of hotspot targets, determining hotspot target observation tasks, and carrying out real-time observation on the hotspot targets. And obtaining a corresponding geographic information data set. On the basis, simulation calculation of the satellite transit area is carried out in sequence, and a spatio-temporal data set of the hotspot observation target in the satellite transit process is generated. And in combination with CMA-GFS data, carrying out space-time screening on observable targets, determining hotspot targets with clear sky observation conditions, and forming a selected space-time data set. And finally, the whole process operation from satellite observation task planning, platform attitude maneuver and instrument pointing calculation to observation guidance generation and instruction uploading execution, and observation state tracking and effect evaluation is completed, invalid observation caused by cloudy and foggy weather is reduced, and the satellite observation efficiency is improved.

The application discloses a long-distance land planning geographic information surveying and collecting system based on network interaction, which comprises a unmanned aerial vehicle, and four supporting rods are symmetrically arranged on the outer part of the unmanned aerial vehicle. The long-distance land planning geographic information surveying and collecting system based on network interaction is characterized in that the second protection strip, the third protection strip and the fixed first protection strip are driven by a transmission mechanism to be linked and unfolded, and jointly form a spherical protection layer, which can protect the unmanned aerial vehicle from all directions, effectively resist the collision of obstacles such as trees, buildings and high-voltage lines in complex terrains, and realize compact folding through reverse driving of a servo motor, so that the whole is in a flat annular structure after folding, which can effectively reduce the flight resistance of the unmanned aerial vehicle and the winding risk with obstacles, and meet the demand of flexible shuttle in complex terrains, so that the overall protection is provided while the work efficiency is ensured.

The invention provides a modeling method and system applied to ecological system carbon library monitoring under influence of water-power engineering, and the method comprises the steps: obtaining a drainage basin geographic information data set and a water-power engineering operation data set, and carrying out the water flow dynamic feature analysis of the drainage basin geographic information data set and the water-power engineering operation data set; the method comprises the following steps: obtaining a watershed water flow dynamic feature vector set, deducing soil physicochemical property offset and vegetation community structure variation according to the watershed water flow dynamic feature vector set, coupling the soil physicochemical property offset and the vegetation community structure variation to carry out carbon cycle process digital quantitative modeling, and generating a carbon reservoir reserve change sequence. And constructing an ecological system carbon library monitoring model under the influence of the hydropower engineering based on the carbon library reserve change sequence. According to the method, the accuracy of water-power engineering ecosystem carbon sink effect evaluation and prediction is effectively improved, and a more reliable basis is provided for related decisions.

The invention relates to the technical field of geographic information, and discloses a soil heavy metal high-precision prediction method fusing optimal scale screening and spatial layering. The method aims at solving the problems that a traditional global model is insufficient in prediction precision and unclear in mechanism interpretation in spatial heterogeneity regions such as a plain urban and rural ecotone. According to the technical scheme, the method comprises the steps that firstly, a system collects multi-source environment variables and constructs a multi-scale buffer area candidate variable set, the optimal action scale of each variable is screened out in combination with soil sample data screened through geochemical background values, and an optimal scale variable set is formed; then, driving mode space layering is carried out on the research area through unsupervised clustering based on the variable set, and the heterogeneous area is divided into a plurality of relatively homogeneous sub-areas; and finally, constructing an independent random forest model for each sub-region for prediction and fusion mapping. According to the method, the precision and mechanism interpretation capability of soil heavy metal space prediction are remarkably improved, and a reliable basis can be provided for soil environment risk management and control.

The invention discloses a method, a system and equipment for calculating the area of a newly-added water body in a mountainous area and a medium. The method adopted by the invention comprises the following steps: acquiring a specific time period, a geographic range and other parameters, loading a satellite data set of a cloud geographic information processing platform, screening to obtain a screened satellite data set, and processing by adopting a dual-polarization water body index, an optimal segmentation threshold and a digital elevation model in sequence to obtain a data set; obtaining a water body region extraction result and specifying a data output format to obtain water body region export data in a specific time period; and obtaining water body region change information corresponding to the previous and later time periods according to the previous and later time periods, the geographic range and other parameters, and performing vector conversion and area summation to obtain the newly-added water body area of the mountainous area. The method provides a scientific basis for river water body extraction, water body change comparison in different areas and area attention of newly added reservoirs or increased water bodies, and lays a foundation for subsequent icing monitoring.

The invention relates to a travel flow scale conversion method and system cooperating with multivariate data spatial-temporal characteristics, belongs to the technical field of geographic information processing, and solves the problem that the converted flow is different from the actual flow in the prior art. The method comprises the following steps: acquiring mobile phone signaling data and collaborative data; obtaining a user moving track sequence; determining dominant plot features of each base station cell based on the collaborative data; constructing a collaborative feature coefficient of each plot feature in each time period based on the dominant plot features and the user movement track sequence; based on the collaborative feature coefficient of each land parcel feature in each time period and the spatial distribution feature of each land parcel feature in each base station cell, constructing a space-time adjustment coefficient of flow distribution to each target scale unit by each base station cell in each time period; and mapping the travel flow to the target scale units based on the space-time adjustment coefficient of the flow allocated to each target scale unit by each base station cell in each time period. And accurate travel flow scale conversion is realized.

The invention discloses a power meteorological prediction error analysis method based on power transmission line attribute weighting. The method comprises the following steps: acquiring geographic information data and voltage class attribute data of a power transmission line in a target area; obtaining meteorological grid point prediction data and live data in the same historical time period and the same geographical range; for each meteorological grid point, calculating a spatial distance weight, a voltage grade weight and a tower density weight of the meteorological grid point relative to each adjacent power transmission line, calculating a comprehensive weight coefficient of the meteorological grid point, and forming a weight coefficient matrix; calculating an error value between the predicted data and the live data on each meteorological grid point; and weighting the error value of each meteorological grid point by using the weight coefficient matrix, and calculating to obtain a weighted region error index reflecting the prediction precision of the surrounding weather of the power transmission line. According to the method, a meteorological prediction error evaluation system oriented to the safety of the power system is constructed by integrating the weight coefficients, and a scientific basis can be provided for site selection of the micro-meteorological device.

The application discloses a power transmission and transformation engineering geographic information basic data processing system based on multi-mode data fusion, comprising: a power grid multi-mode data acquisition module, a multi-source geographic data receiving module, an ICP registration calculation module, a quality perception fusion module, a topological graph modeling module and a geographic data processing module. The system obtains data such as buildings, terrains, bridges, power lines and towers through the power grid multi-mode data acquisition module, and obtains data such as unmanned aerial vehicle aerial images and laser radars through the multi-source geographic data receiving module; the ICP registration calculation module calibrates multi-source geographic data to improve coordinate consistency; the quality perception fusion module adjusts weight according to data reliability to improve fusion accuracy; the topological graph modeling module constructs device node correlation based on fused data to improve model comprehensiveness; and the geographic data processing module integrates data and topological parameters to generate comprehensive data sets. The system improves data integrity and provides reliable data support for power transmission and transformation engineering survey and design and later operation and maintenance.

The invention relates to the technical field of weather radar networking, in particular to a multiband networking weather radar reflectivity factor puzzle fusion method and system, and the method comprises the following steps: extracting an observation overlapping region of an S-band weather radar network and an X-band weather radar network, and generating mask data containing geographic information; on the basis of the mask data, generating puzzle data on an equal-altitude surface with different S-band weather radar reflectivity factors; based on the mask data, generating jigsaw data on an equal-altitude surface with different X-band weather radar reflectivity factors; and based on a fusion algorithm, fusing the reflectivity factor puzzle data of the S wave band and the X wave band. According to the invention, the networking observation data of the S-band and X-band weather radars are subjected to jigsaw and fusion processing to be processed into a new data product, the collaborative observation result of the S-band and X-band networking weather radars and the low-altitude blind compensation effect can be visually presented, and a data product support is provided for a meteorological department to monitor and early warn weather with strong disastrous conditions.

The invention belongs to the technical field of meteorological remote sensing and geographic information, and particularly relates to a mountain air temperature long-time-sequence high-resolution estimation method based on multi-source satellite remote sensing, which comprises the following steps: acquiring multi-source satellite surface temperature product data, meteorological station observation data and multi-dimensional auxiliary factor data; based on different observation scenes of the multi-source satellite surface temperature product data, an air temperature estimation model is constructed, the air temperature estimation model is constructed based on a random forest regression model, and the multi-dimensional auxiliary factor data is input of the air temperature estimation model; training the air temperature estimation model by using the meteorological station observation data to generate a plurality of sets of air temperature estimation initial value products; according to the deviation of each set of air temperature estimation initial value product relative to the meteorological station observation data, carrying out weighted fusion on the plurality of sets of air temperature estimation initial value products to generate fused air temperature data; and carrying out space-time continuous interpolation filling on a gap existing in the fused air temperature data to obtain a space-time continuous mountain air temperature data set.

The application discloses a fixed-wing flight device landing control method and device, the method comprises the following steps: collecting the geographical information of the runway to construct a data calibration difference table; obtaining the first height difference of the flight device relative to the take-off point determined by each height sensor according to the take-off data and the data calibration difference table; obtaining the second height difference of the flight device relative to the estimated landing point determined by each height sensor based on the height difference between the estimated landing point and the take-off point; selecting the second height difference of a single height sensor as a height source for landing control according to the landing field difference until the flight device lands. The application solves the problem that the existing landing technology is difficult to realize safe and accurate landing control under complex runway conditions, reduces the hardware cost, avoids environmental interference and measurement error caused by additional equipment, and is an economical, efficient and safe solution.

The invention discloses a landslide susceptibility evaluation method and system based on an optimized non-landslide sample selection strategy, and belongs to the field of geological disaster risk analysis. The method aims at solving the technical problem that the evaluation precision of the landslide susceptibility is not high due to unreasonable selection of traditional non-landslide samples. According to the technical scheme, the method comprises the steps that multi-source geographic information data and historical landslide data of a research area are collected and processed in a unified mode; extracting evaluation factors and constructing a susceptibility evaluation index system; performing susceptibility pre-partitioning based on an information quantity value method, and selecting a non-landslide sample in a low-susceptibility region; combining the landslide sample with the primarily selected non-landslide sample, eliminating a noise sample by adopting density-based spatial clustering analysis, and supplementing and generating a balanced optimized sample set by utilizing a synthetic minority oversampling technology; and inputting the optimized sample set into a support vector machine model for training and susceptibility evaluation drawing. By optimizing the sample selection strategy, the sample quality and the accuracy of the model evaluation result are improved.