20 results about "Geographic database" patented technology

The invention discloses an unregistered geographical name discovery and spatial position reasoning method and a related device, and relates to the technical field of geographic information, and the method comprises the steps: constructing a geographical name space-time derivation relation knowledge graph based on an open source geographic database; inputting the target place name text data into a sequence labeling model to obtain a labeling result, and extracting candidate derived place names based on the labeling result; performing general name segmentation on the candidate derived geographical names to obtain potential basic geographical names, and judging whether the potential basic geographical names meet preset association conditions or not based on a geographical name space-time derivation relationship knowledge graph; if yes, eliminating potential basic place names; if not, determining the potential basic place name as an unlogged place name; and determining the spatial position of the unregistered place name according to the general name of the unregistered place name and the place name space-time derivation relationship knowledge graph. According to the invention, the automation degree of unregistered place name discovery and spatial position reasoning can be improved.

The invention discloses a GIS-based city planning data automatic checking method and system and a medium, and relates to the technical field of data processing, and the method comprises the steps: constructing a current situation data graph layer and a planning data graph layer based on a GIS platform, and carrying out the spatial indexing of the current situation data graph layer and the planning data graph layer, and obtaining a city planning database; importing a checking base map, and superposing the urban planning database into the checking base map through a GIS platform for layer registration to generate a checking data set; an automatic checking tool set is loaded to carry out automatic checking analysis on the checking data set, and a checking analysis result is generated and comprises a chart file; and carrying out sequence storage on the chart file according to a geographic database, and carrying out automatic checking on the city planning database according to the stored information. The technical problems of low manual checking efficiency and insufficient accuracy in the prior art are solved, and the technical effect of improving the checking efficiency and accuracy is achieved.

The invention discloses a geographic data collection method and system based on machine learning, and relates to the field of geographic data collection, and the method comprises the steps: obtaining a historical collection record set of a target geographic region, carrying out the statistics of the historical collection record set, and obtaining the collection frequency distribution of different sub-regions in the target geographic region; according to the acquisition frequency distribution, identifying a historical low-coverage sub-region of which the acquisition frequency is lower than a first threshold value; generating a deviation correction guiding factor for each candidate acquisition position based on the spatial distribution characteristics of the historical low-coverage sub-region and the associated geographic element change characteristics; and in response to a current acquisition task request, gaining a prediction score according to the deviation correction guiding factor and information of a candidate acquisition position obtained from a pre-trained geographic element change prediction model. According to the method, a deviation correction mechanism is introduced, information acquisition efficiency and space coverage balance are cooperatively optimized in path planning, historical acquisition deviation is improved, and comprehensiveness and long-term application value of a geographic database are improved.

A personnel positioning system and method for a large underground cavern complex based on a 5G communication network is disclosed. The system includes: a 5G communication network module transmitting the unique NR-PCI code and antenna deployment information of each base station to a GIS information system module; the GIS information system module providing an indoor geographic database containing the binding relationship between NR-PCI codes and geographic locations to a positioning engine module; the positioning engine module calculating the location of the user equipment based on the measurement data, NR-PCI codes, and GIS geographic information reported by the user equipment, and sending the positioning result to a data management server module; the data management server module storing the positioning result, personnel trajectory, and system configuration data, and supporting access by upper-layer applications; and the user equipment accessing the 5G network, collecting positioning measurements such as reference signal received power, signal arrival time, and signal arrival angle, and uploading the data to the positioning engine module to report its own location. This system addresses the problems of insufficient positioning accuracy, reliance on additional base stations, and poor adaptability in existing technologies.

A method may include retrieving, from a geographic database, geographic information of a geographic area, segmenting the geographic area into one or more regions, executing a buildability algorithm using as input the geographic information to determine buildable portions of the one or more regions, executing a PV array placement algorithm using as input a total area of the buildable portions of the one or more regions to determine a baseline PV capacity for the one or more regions, executing the PV array placement algorithm using as input the buildable portions of the one or more regions to determine an actual PV capacity for the one or more regions, and generating a data structure to associate the one or more regions with a respective ratio of the baseline PV capacity to the actual PV capacity for each of the one or more regions.

An approach for traffic incident verification involves receiving a traffic message channel (TMC) message indicating a traffic incident. The TMC message indicates an extent of the traffic incident in a road graph using TMC location code(s) / offset(s). The approach also involves matching the TMC location code(s) / offset(s) to a first set of map road link(s) and offset(s) of a geographic database, determining sensor data collected from vehicle(s) travelling within the road graph. The sensor data indicates the extent as location point(s) of topology segment(s) (TSs) and TS offset(s), matching the location point(s) of the TS(s) and TS offset(s) to a second set of map road link(s) and offset(s) of the geographic database, determining an intersection set between the first and second sets, and initiating a confirmation of the traffic incident reported in the TMC message based on the sensor data of the location point(s) of the TSs in the intersection set.

The invention relates to the technical field of underground pipeline data conversion, in particular to an underground pipeline full-process multivariate database automatic conversion method and system, and the method comprises the following steps: S1, converting data in a field collection database into data in an interior processing database; s2, converting data in the interior work processing database into data in a file geographic database; and S3, converting the data in the interior work processing database into the data in the result table. The underground pipeline full-process multi-source database automatic conversion method provided by the invention has the beneficial effects that the problems that indoor and outdoor data formats and fields are inconsistent, and the efficiency of a traditional conversion mode is low are solved. An automatic conversion framework from DB to MDB to GDB to an achievement table is constructed by integrating three modules of field operation-interior operation conversion, interior operation-GIS conversion and achievement table generation.

The invention relates to a system and a method for simulating travel patterns in a metropolitan area to assess the suitability of electric vehicle infrastructure. The method includes, in particular: a step (S01) of obtaining a set of routes for a given period within the metropolitan area, using a geographic database (DGeoA) and at least one simulation parameter (ParSSim), yielding a set of routes (EDS); a step (S03) of obtaining, from the set of routes (EDS) of said at least one simulation parameter (ParSSim), at least one representative data point of the suitability (DrAIR) between an electric vehicle charging infrastructure (DiBH, DiBA, SCP) and an electric vehicle adoption parameter (AdVE) for the execution of routes from the set of routes (EDS). Abstract figure: Fig. 1

The application discloses a method and related device for discovering unregistered place names and reasoning spatial positions, and relates to the technical field of geographic information. The method comprises the following steps: constructing a place name space-time derivation relationship knowledge graph based on an open source geographic database; inputting target place name text data into a sequence labeling model to obtain a labeling result, and extracting candidate derived place names based on the labeling result; performing common name segmentation on the candidate derived place names to obtain potential basic place names, and judging whether the potential basic place names meet preset association conditions based on the place name space-time derivation relationship knowledge graph; if yes, the potential basic place names are excluded; if no, the potential basic place names are determined as unregistered place names; and determining the spatial positions of the unregistered place names according to the common names of the unregistered place names and the place name space-time derivation relationship knowledge graph. The application can improve the automation degree of discovering unregistered place names and reasoning spatial positions.

The invention discloses a WFS-based power distribution network geographic data synchronization method and system, and the method comprises the steps: carrying out the initialization processing of the power distribution network geographic data in a process that a power distribution network automatic system deploys a power distribution network map module, and obtaining the equipment graphic element name information from a power distribution network single line diagram file, associating the primitive name information with all power distribution network object geographic data stored in a relation model library, and then synchronizing to a geographic database; after the distribution network map module is deployed and operates normally, establishing a change monitoring mechanism for the distribution network object model data; when the change of the object data of the power distribution network in the relation model library is monitored, extracting change information corresponding to the change data, and writing the change information into the geographic database through WFS service to complete the synchronous updating of the geographic data of the power distribution network; according to the invention, multi-system integration difficulty can be reduced, and efficient operation of a power distribution network automation system is facilitated.

The invention discloses a two-dimensional vector geographic database defect detection method and a computer readable storage medium, and belongs to the field of electric digital data processing. In order to reduce the risk of missing detection of the defect of the two-dimensional vector geographic database, the defect detection method comprises the following steps: a screening module receives an inspection batch and determines the total number of samples and the submission number; calculating a quality risk index, and obtaining geometric center coordinates to form a first coordinate sequence; generating a random number, constructing a second coordinate sequence, and taking a corresponding sample unit and a quality risk index; generating a random number, comparing the random number with a quality risk index, and determining to repeatedly select samples or add the samples into an inspection set; descending the inspection set according to the quality risk index and detecting by using an automatic tool; and the judgment module refuses to receive the inspection batch if the judgment module is unqualified. The method is applied to the field of databases, and has the advantages of low database defect omission ratio and high detection result reliability.

The invention relates to a system that enables accurate and reliable calculation of risk scores for immovable properties (20) subject to insurance policies (10) by using geographical database–based analyses The system operates in an integrated manner with a location determination module (30) for identifying the location of the property, a geographical database (40) and an environmental proximity analysis module (50) for analyzing historical loss and natural disaster risks, a cumul calculation module (60) for evaluating regional risk accumulation, and a user interface (90) for visualizing the analysis results. The user (K) initiates the risk analysis process by entering details such as the activity type, construction type, and floor information of the property. The resulting risk scores calculated by the risk score calculation module (80), together with cumul assessments, enable accurate pricing of insurance policies (10). By improving analytical precision and optimizing operational costs, the system contributes to the financial sustainability of insurance companies. This innovative structure provides a fast and reliable solution for the insurance sector.

A pressure change is detected based on pressure measurement data from a barometric pressure sensor of a computing device. A 2D location of the computing device is determined. An altitude change of the computing device is determined using the pressure change. A cumulative altitude offset value is determined by adding the altitude change to a previous cumulative altitude offset value. A terrain-based altitude of the computing device is determined based on the 2D location and terrain data from a geodatabase. An altitude of the computing device is determined based on the terrain-based altitude and the cumulative altitude offset value.

A method for generating a map display for natural disaster monitoring includes collecting sensor data from a geographic area and assigning sensor data to one of a plurality of pixels. The collected data is preprocessed to remove unreliable or irrelevant data and then each pixel value is georeferenced to a location on the globe. The georeferenced data is aggregated according to location and time of collection and is assigned a quality score. The scored and georeferenced pixels are then aggregated into a map representing the best collected data for a geographic area during a period of time. The temporally aggregated map is then output for further use. A system for mapping a natural disaster includes airborne and ground sensors for collecting data over a geographic area, a ground control station, a geographic database, a weather database, a processor, and a remote server. The sensors include infrared, thermal, and camera sensors.

The invention relates to the technical field of radar remote sensing, and discloses an MIMO-SAR (Multiple Input Multiple Output-Synthetic Aperture Radar) system based on an MIMO-SAR architecture. A data acquisition module of the system acquires multi-channel signal data streams in radar transmitting and receiving stages; the feature stripping module is used for implementing feature stripping processing on the data stream, and separating a signal partition identifier of imaging processing; the geographic information processing module calls real-time positioning information and generates a corresponding geographic partition contour in combination with a geographic database; the association matching module associates and matches the signal partition identifier and the geographic partition contour, generates an initial mapping table, and screens out a high-priority core partition set; the collaborative analysis module calculates a collaborative degree index, generates a signal optimization combination sequence, performs data consistency auditing on a geographic partition contour, and finds out difference points of radar observation data; and the strategy generation module corrects the mapping link, derives an imaging target list and an imaging scheduling sequence by using the corrected mapping link, and constructs an imaging strategy library.

The invention provides a multi-modal contrast learning data set construction method, device and equipment for a remote sensing image, and the method comprises the steps: carrying out the superposition analysis of a target remote sensing image and vector data in a plurality of open-source geographic databases, and obtaining a plurality of vector regions in the target remote sensing image; generating an initial text description result corresponding to each vector region according to the plurality of vector regions and a semantic understanding result of the target remote sensing image; generating a comprehensive text description result according to the initial text description results corresponding to all the vector regions; and finally generating a target remote sensing image text data pair. According to the method, vector data information in a plurality of open source geographic databases and a semantic understanding result of a target remote sensing image are fused, the position information in the existing open source geographic database is fully utilized, the information of the remote sensing image is mined, more accurate semantic analysis of the remote sensing image is realized, and the semantic understanding accuracy of the remote sensing image is improved. And abundant and accurate image text data pairs are provided for subsequent multi-modal contrast learning tasks.

A pressure change is detected based on pressure measurement data from a barometric pressure sensor of a computing device. A 2D location of the computing device is determined. An altitude change of the computing device is determined using the pressure change. A cumulative altitude offset value is determined by adding the altitude change to a previous cumulative altitude offset value. A terrain-based altitude of the computing device is determined based on the 2D location and terrain data from a geodatabase. An altitude of the computing device is determined based on the terrain-based altitude and the cumulative altitude offset value.

The invention relates to the technical field of geographic information databases, in particular to a cloud management method for automatic driving map data, which comprises the following steps of: dividing map data into a static basic layer, a quasi-dynamic layer and a high-dynamic layer, extracting a road network and a topological structure of the static basic layer, and traffic rules and road speed limits of the quasi-dynamic layer, basic attributes of all the automatic driving road sections are combined, and a space-time hierarchical geographic database is established. The map data is divided hierarchically and processed, so that the updating efficiency and real-time performance of the automatic driving map data are effectively improved, and road section basic attributes are formed by combining a road network structure in the static basic layer data and traffic rules and road speed limits in the quasi-dynamic layer data. And a space-time hierarchical geographic database is established according to the basic attributes of the road sections, so that high association of space information and traffic rules is realized, data redundancy is reduced, and the accuracy and processing speed of data calling are improved.

The present application relates to the technical field of geographic information database, specifically to a cloud management method of automatic driving map data, comprising the following steps: dividing map data into static basic layer, quasi-dynamic layer and high dynamic layer, extracting road network and topological structure of the static basic layer, and traffic rules and road speed limit of the quasi-dynamic layer, combining into the basic attribute of each automatic driving section, and establishing a space-time layered geographic database. The present application effectively improves the updating efficiency and real-time performance of automatic driving map data by hierarchical division and processing of map data, uses the road network structure in the static basic layer data and the traffic rules and road speed limit in the quasi-dynamic layer data to combine to form the section basic attribute, and establishes a space-time layered geographic database according to the section basic attribute, realizes high correlation between spatial information and traffic rules, reduces data redundancy, and improves the accuracy and processing speed of data calling.

The application discloses a prior knowledge-based training sample selection method for Doppler post-STAP, which comprises the following steps: mapping each information point in a geographic database in a radar beam irradiation range to a corresponding distance unit; re-dividing the information points mapped to the distance unit according to a Doppler frequency, indexing into a corresponding distance-Doppler unit, and forming a normalized vector of each distance-Doppler unit according to a landform type; constructing a weighted normalized vector of each distance-Doppler unit, calculating the Euclidean distance between a training unit and a normalized vector of a to-be-detected distance-Doppler unit, and selecting the first L samples with the smallest distance as uniform training samples; performing power difference correction on the selected uniform training samples; estimating a clutter noise covariance matrix based on the corrected uniform training samples, and calculating a space-time filtering weight vector. The application also provides a corresponding prior knowledge-based training sample selection device for Doppler post-STAP.