1077 results about "Geographic information system" patented technology

The invention relates to the technical field of intelligent agriculture and ecological internet of things, in particular to an ecological irrigation decision dynamic optimization method and related equipment. Comprising the following steps: acquiring multi-source environment data, acquiring a soil profile humidity gradient in real time through a soil humidity sensor array, acquiring future rainfall probability distribution, a temperature change rate and a wind speed predicted value in combination with a weather forecast interface, and synchronously accessing a geographic information system to acquire terrain elevation and crop distribution data. The three technical bottlenecks of model dimension collapse, parameter estimation instability and optimization response lag in a traditional irrigation decision-making system are systematically solved by constructing a space-time coupling analysis framework and a closed-loop optimization mechanism of multi-source heterogeneous data.

The invention provides a cross-modal remote sensing image-text retrieval method based on multistage semantic collaborative matching, which comprises the following steps of: extracting a region of interest by using a semantic segmentation algorithm through an image preprocessing module, segmenting a remote sensing image into a plurality of regions and generating image blocks; respectively extracting global features, regional features and pixel-level features of the image, and carrying out fine-grained coding on key regions such as fine-grained ground feature edges and the like; the text multi-level coding module is used for carrying out three-level feature coding of documents, sentences and words on texts based on a pre-training language model to ensure multi-level understanding of the texts; in the multi-level matching and fusion module, the similarity between the remote sensing image and the text description is calculated through a cross attention mechanism, weighted fusion is carried out on features of all levels, and finally a retrieval score is output. The method not only improves the accuracy and robustness of image-text retrieval, but also can be widely applied to the fields of remote sensing monitoring, environment change recognition, geographic information systems and the like.

The invention relates to the technical field of intelligent water conservancy, and discloses a cross-regional water transfer project intelligent scheduling method and system, and the method comprises the steps: building a digital twin system based on a geographic information system, hydrological monitoring data and a spatial topological structure, and integrating a meteorological evolution prediction model, a basin hydrological response model and a water demand prediction model; predicting a water demand and an adjustable water amount by using a space-time convolutional neural network and a gating circulation unit; establishing a multi-objective optimization model taking water supply benefit, ecological influence and energy consumption cost as optimization objectives; an optimal water transfer scheme is generated through a Markov decision process and multi-agent cooperation; and carrying out robustness evaluation on the scheme and generating an emergency scheduling plan. According to the method, the scheduling efficiency and adaptability of the water transfer project are remarkably improved, and efficient configuration of water resources and quick response under extreme situations are achieved.

The invention discloses an intelligent cable fault accurate positioning and early warning method and system, and the method comprises the steps: collecting the temperature gradient, strain distribution and partial discharge signals of the whole length of a cable in real time through a distributed optical fiber sensing network, and generating a multi-dimensional feature matrix of the operation state of the cable; based on the multi-dimensional feature matrix, outputting a preliminary fault positioning coordinate; generating corrected fault coordinates according to the topological structure data of the cable laying environment and the electromagnetic interference distribution diagram; historical fault data, real-time operation parameters and the corrected fault coordinates are fused, and a fault risk thermodynamic diagram in a future preset duration is output; and based on the fault risk thermodynamic diagram and real-time monitoring data, generating fault first-aid repair information by using a dynamic priority algorithm, synchronously triggering an early warning signal, and visually displaying a fault positioning result and a risk area in a three-dimensional geographic information system. According to the embodiment of the invention, rapid positioning, accurate early warning and intelligent disposal of the cable fault can be realized.

The invention relates to the technical field of geographic information systems, in particular to a GIS-based urban land planning analysis method and system, and aims to construct a multi-scale space-time cube model by integrating remote sensing, historical planning, mobile terminals and social media data, generate standardized urban temporary land data and improve the urban land planning analysis efficiency. Adaptive feature extraction is adopted to identify temporary land, a hierarchical classification system is established, abnormal changes are monitored through a time sequence model, an association diagram of the temporary land and an urban function network is constructed, an interaction relation is analyzed, finally, differentiated urban planning optimization suggestions are proposed, efficient configuration and management of urban land resources are assisted, and through fusion of multi-source data, the urban planning optimization suggestions are optimized. Multi-dimensional cognition of space, time, functions and relations is achieved, and the understanding depth of temporary land is fundamentally improved.

The invention relates to the technical field of underground drainage pipeline monitoring and hidden danger analysis, and provides an underground drainage pipeline hidden danger data analysis method based on big data, which comprises the following steps: acquiring data such as flow, water level, pressure and pipeline structure by using a multi-source sensor to form an original monitoring data set; preprocessing the data, extracting time domain, frequency domain and spatial topological features, and constructing a multi-dimensional feature vector; and inputting the feature vectors into a pre-trained hidden danger prediction model, and outputting hidden danger types and position coordinates. And constructing a spatio-temporal data analysis model based on the hidden danger position, generating a spatio-temporal correlation feature matrix, and performing dynamic risk assessment to obtain hidden danger development trend parameters. And the hidden danger information is mapped to a geographic information system, a three-dimensional visual analysis result is generated, and a graded early warning instruction is transmitted to a drainage pipe network operation and maintenance management system through a communication interface. The operation and maintenance management efficiency of the drainage pipeline can be improved, the hidden danger checking cost is reduced, and the safety and reliability of the drainage system are enhanced.

The invention discloses an urban building three-dimensional automatic modeling and visualization method, and belongs to the technical field of building three-dimensional modeling. The method comprises the steps that point cloud data, high-resolution images and geographic information system data of urban buildings are acquired, data cleaning, registration and alignment are carried out, and preliminary building digital representation is formed; accurately segmenting each building, and identifying the contour and main structural features of the building; based on the data integrity and the building complexity, adaptively selecting a proper reconstruction strategy to carry out three-dimensional reconstruction; in the reconstruction process, the geometric structure is analyzed and optimized in real time, and potential topological problems are repaired; automatically generating missing details based on a predefined architectural style library and a component library, and performing material inference and texture mapping; a graph structure is used for representing the relation between the buildings, and the positions and orientations of the buildings are adjusted through a global optimization algorithm; a rendering engine supporting multi-level detail switching is developed, and smooth visualization and interaction of a large-scale city scene are achieved.

The invention discloses a dam seepage stability analysis method based on flood forecasting, and relates to the technical field of hydraulic engineering safety monitoring, comprising the following steps: S1, integrating a flood forecasting system and a seepage monitoring system into a data acquisition layer, and acquiring flood forecasting data and seepage monitoring data by a sensor of the data acquisition layer; s2, performing space-time alignment on the flood forecast data and the seepage monitoring data through a space-time coupling interface of the dynamic fusion layer, and generating a dynamic driving variable of a seepage field boundary condition based on a flood routing model and a geographic information system spatial interpolation technology; through the space-time coupling interface, space-time alignment and dynamic driving variable generation of flood forecast data and seepage monitoring data are achieved, the problem that the real-time flood routing process cannot be reflected due to the fact that the boundary condition is static or lagged in traditional analysis is solved, the seepage field calculation boundary condition can be dynamically updated along with flood forecast, and the real-time flood routing process cannot be reflected. And the timeliness and accuracy of model calculation are improved.

The invention relates to the technical field of geographic information systems, in particular to a map tile data efficient access method and system based on hybrid storage and intelligent layering, and the method comprises the following steps: constructing a multi-level storage architecture, carrying out dynamic heat analysis, carrying out intelligent layering scheduling, preloading and space prediction, and carrying out transmission and access optimization. The method has the beneficial effects that the multi-level storage pool is constructed by combining the advantages of object storage and a distributed file system; adopting a dynamic tile popularity analysis model to realize hot data cache acceleration and cold data hierarchical archiving; and meanwhile, a tile request preloading mechanism is introduced, and an access path is optimized in combination with a spatial locality prediction algorithm. According to the method, the storage cost can be remarkably reduced, the tile request delay is reduced, quick response in a high-concurrency scene is supported, and the method is suitable for application scenes such as Internet map services and smart cities.

The invention discloses a three-dimensional GIS (geographic information system) system for safety assessment of an urban gas pipeline internet of things. A gas pipe network monitoring and assessment system combining the internet of things, a mobile internet and BIM / GIS information is established. Firstly, an overall framework based on sensing, transmission, knowing and use of the internet of things is established; secondly, a front-end sensing system deployment scheme is established, a database system is built, and index data are collected and stored; thirdly, a gas leakage hazard model is constructed, and possible hazard consequences are evaluated; 4, a pipe network monitoring system application layer module is constructed, and underground space information management, safety analysis, prediction and early warning and an auxiliary decision making module are achieved; and establishing a gas pipe network risk identification module, a basic information checking module, a monitoring and explosion early warning module, a three-dimensional visualization module and an auxiliary decision-making module. The system monitors the operation condition of the gas pipe network in real time, analyzes the operation rule of the gas pipe network, evaluates the risk of the gas pipe network, predicts, early warns and decides in time, changes passive first-aid repair into active protection, and is high in monitoring stability, precision and efficiency.

The invention discloses a method and system for estimating irrigation water consumption and water utilization efficiency, and relates to the technical field of water resource management, and the method comprises the steps: collecting the plant stem flow rate, canopy temperature and soil profile water content data of a target area through a multi-source sensing device, and obtaining a gradient and permeability distribution diagram of a geographic information system; dividing the farmland of the target area into sub-areas with different irrigation priorities based on a soil conductivity mutation point detection algorithm; constructing a dynamic water demand model fused with the plant transpiration hysteresis effect, performing space-time correlation analysis on the stem flow rate data and the soil moisture content gradient, and calculating the real-time water demand intensity of each sub-region; the method comprises the following steps: accessing short-time rainfall prediction data of a meteorological radar, dynamically correcting a future irrigation decision by adopting a sliding time window mechanism, and triggering a gradient delay irrigation instruction when the predicted rainfall amount exceeds an irrigation threshold value; and calculating the actual moisture utilization efficiency based on the inversion data of the moisture content of the irrigated soil and the unmanned aerial vehicle multispectral image.

The invention discloses an intelligent city management information visualization comprehensive management method and system, particularly relates to the technical field of city management, and is used for solving the problem of misalignment of emergency response caused by false association and causal confusion in the prior art. Precise management is realized through multi-modal time sequence data feature alignment, causal chain network dynamic construction and a visual decision mapping technology, firstly, multi-dimensional event features of video monitoring, sensors and text work orders are extracted, a cross-modal association chain is constructed, interference chains are screened out through causal strength evaluation and anti-fact verification, and a visual decision mapping algorithm is established. According to the method, dynamic correction parameters are generated in combination with space-time weights and feedback priorities, finally, a visual guidance scheme is output by fusing a causal chain network and a geographic information system, decision optimization is driven through causal logic, and city event disposal accuracy and cross-department cooperation efficiency are remarkably improved.

The invention discloses a submarine cable fault online diagnosis and positioning method and system based on an optical fiber sensing technology, and relates to the technical field of optical fiber sensing, and the method comprises the steps: obtaining a real-time strain data flow of a submarine cable through a distributed optical fiber strain measurement device; carrying out space-time alignment and abnormal value correction processing on the original data set, and constructing a target data set; coordinate mapping is carried out on the target data set and a geographic information system of a submarine cable laying line, and a fault diagnosis layer with multi-dimensional visualization features is generated; an interactive fault analysis panel is generated on a geographic information system interface, and the deviation ratio between the strain theoretical threshold value and the actual measurement value of each monitoring point in the target data set is calculated; according to the submarine cable fault online diagnosis and positioning method and system based on the optical fiber sensing technology, rapid positioning of fault features is achieved, the fault response efficiency is improved, and long-term stable operation of a submarine communication network is ensured.

The invention discloses an unmanned aerial vehicle aerial three-dimensional electronic fence construction method and system, and relates to the technical field of unmanned aerial vehicles, and the method comprises the following steps: dividing the region boundary of an electronic fence in a preset geographic range based on a geographic information system and a three-dimensional modeling technology, and calculating the range of the electronic fence; integrating the configured electronic fence to an unmanned aerial vehicle system, establishing a real-time communication and data exchange channel with the unmanned aerial vehicle, and receiving position information and flight state data fed back in the flight process of the unmanned aerial vehicle in real time; and monitoring the flight state of the unmanned aerial vehicle and the area boundary of the electronic fence in real time, and triggering an early warning mechanism when the unmanned aerial vehicle is found to have a boundary crossing behavior. According to the electronic fence system, the size, shape and position of the fence can be automatically adjusted according to the real-time flight state of the unmanned aerial vehicle and the environment change, the dynamic adjustment capability of the electronic fence is directly improved, and it is ensured that the unmanned aerial vehicle can always fly safely in the complex and changeable airspace environment.

The invention discloses a GIS (Gas Insulated Switchgear) tiny defect detection method and system based on X-ray multi-effect fusion, and the method comprises the following steps: firstly, exciting a latent defect in a GIS to generate partial discharge by using an X-ray photoionization effect, detecting a discharge signal by using an ultrahigh frequency method and an ultrasonic method, and after the discharge signal is processed by a noise reduction model, carrying out noise reduction on the discharge signal; and respectively obtaining an ultrahigh-frequency discharge phase spectrogram and an ultrasonic discharge phase spectrogram. Then, the imaging plate is placed on the back face of the GIS, digital DR imaging is carried out through X rays, and an X-ray image is obtained; the ultrahigh frequency discharge phase spectrogram and the ultrasonic discharge phase spectrogram are fused after being denoised, an X-ray image is combined to establish a GIS health state diagnosis model, and reliable defect detection is carried out on the GIS according to the evaluation score of the diagnosis model. According to the method, multiple effects of X-rays are fused, so that smaller GIS latent defects can be found, the detection sensitivity is remarkably improved, and the problem that the traditional method is difficult to identify the tiny latent defects is solved.

The invention relates to the technical field of atmospheric environment monitoring, in particular to an atmospheric pollution source tracking and early warning system based on deep learning, which comprises a multi-source data acquisition layer for acquiring multi-dimensional data of atmospheric pollutant concentration, weather, geography and the like through multi-element equipment such as satellite remote sensing and ground sensors; the data preprocessing layer completes data cleaning by using a statistical method and a machine learning algorithm, and realizes heterogeneous data standardization processing through feature extraction, multi-source integration and space-time alignment, and the deep learning model layer realizes heterogeneous data standardization processing by means of a space-time convolutional neural network, a graph neural network and a long-short term memory network in combination with a space-time attention mechanism. The traceability analysis layer is combined with a back diffusion algorithm and a geographic information system to position a pollution source and generate a thermodynamic diagram. And the early warning decision-making layer sets threshold early warning through transfer learning of the adaptive area, and generates an optimal pollution control scheme based on reinforcement learning.

The invention discloses a livestock epidemic disease early warning method and system based on big data analysis, and the method comprises the steps: generating a preliminary epidemic situation diffusion path through employing the farm distribution and traffic network data of a geographic information system in combination with a space-time propagation model, and carrying out the dynamic adjustment according to the real-time updated data; predicting a high-risk area by adopting a multi-source data fusion early warning model; the strain mutation risk is judged by analyzing the relevance between pathogen genomes and environmental parameters; deploying a deep learning model at an edge computing node, analyzing animal husbandry behaviors and voiceprint data in real time, and evaluating the animal husbandry health state; and integrating mutation risk analysis and animal husbandry health assessment results to generate a comprehensive epidemic situation early warning report. Through multi-dimensional data analysis and edge intelligent calculation, accurate early warning of animal epidemic situations is realized, and a scientific basis is provided for epidemic situation prevention and control.

The invention provides a power grid cable temperature monitoring and alarming method, device and equipment and a storage medium. The method comprises the following steps: acquiring cable outer sheath temperature data through a temperature sensor and acquiring cable current load data and health condition indexes; calculating the temperature of the conductor according to the temperature data of the outer sheath, the current load data and the environmental parameter data by using a superposition principle calculation model based on time attenuation coefficient correction; according to the cable health condition index, calculating a grading early warning threshold value, and comparing the conductor temperature with the threshold value to determine an early warning grade; and when the early warning level reaches a preset condition, matching the sheath temperature data with a template in an abnormal mode library, identifying an abnormal reason through multiple algorithms, and generating a disposal suggestion in combination with geographic information system data. According to the invention, the conductor temperature can be quickly and accurately calculated, the early warning threshold value is dynamically adjusted, the abnormal reason is intelligently identified, and the accuracy and effectiveness of cable temperature monitoring and early warning are greatly improved.

The invention provides a carbon neutralization evaluation method for an ecological park, and the method comprises the steps: obtaining the basic data of various carbon assets in the ecological park, and the basic data comprises the natural ecological system carbon sink capability and human activity carbon emission intensity data; according to the carbon asset basic data, a time sequence analysis method is adopted to carry out modeling on the change trend of the carbon sink capacity and the carbon emission intensity, and a change trend model is obtained; modeling the spatial distribution of the carbon reserves and the carbon flux by utilizing a geographic information system technology and combining a change trend model to obtain a spatial distribution model; key variables are extracted from the spatial distribution model, and the effects of different factors on the carbon assets are quantified by adopting a multiple regression analysis method; acquiring carbon asset monitoring data, evaluating data quality, and if an abnormal value exists, performing correction by adopting a data cleaning algorithm; and according to the corrected carbon asset data, adopting a random forest model to predict the carbon sink capacity and the carbon emission intensity, and generating a dynamic evaluation result.

The invention relates to the technical field of electric power management and control, and discloses an electric power BIM type data GIS discount classification method and system, and the method comprises the following steps: 1, constructing an electric power industry exclusive classification system and semantic mapping, and building a three-stage classification frame based on a GIS and an electric power industry standard; 2, unifying a space coordinate reference and a topological relation, and verifying topological consistency between components and between the components and topography and roads through a GIS (Geographic Information System) tool; 3, multi-scale classification and dynamic LOD model generation are carried out, and LOD model details are automatically switched according to a GIS scale; 4, performing data format conversion and intelligent lightweight processing, performing lossless compression on key components, and performing simplified compression on secondary components; and step 5, performing classification verification and dynamic updating mechanism, and comparing whether BIM and GIS base map position classification is correct or not, thereby realizing data synchronization. According to a dynamic classification framework and an intelligent lightweight strategy in the power industry, the BIM model efficiently adapts to the spatial analysis requirement of the GIS, and the data fusion and application efficiency is improved.

The invention relates to the technical field of geological disaster monitoring, and discloses a point-like landslide and debris flow potential degree adaptive monitoring and early warning method. According to the method, a dot matrix monitoring equipment array is arranged, and displacement data and environmental parameters of multiple monitoring points are collected; analyzing the displacement data timestamp through a timeline analysis module, generating a dynamic timeline, and marking geological event nodes; a geographic information system is combined to carry out spatial mapping on displacement data, and environmental parameters are fused to obtain a preliminary potential degree evaluation result. The pattern recognition engine classifies displacement speed and deformation characteristics in the preliminary result to generate a deformation characteristic spectrum with a space-time label; calculating a dynamic potential degree evaluation map according to the multi-factor weighted evaluation model; and adjusting an early warning threshold according to a user instruction, generating a personalized early warning rule set, and scanning the atlas to output a multi-stage early warning response scheme. On the basis of an early warning feedback iteration updating model and an engine, monitoring data are newly added to trigger and re-analyze in real time, a related scheme is updated in a linkage mode, and different scene requirements are met.

The invention discloses a flood detention area emergency evacuation early warning method based on environmental perception and intelligent analysis, and relates to the technical field of flood control and disaster mitigation, and the method comprises the steps: collecting the original data of a flood detention area site, and forming a monitoring array; a monitoring array is divided into a plurality of monitoring units according to geographic grids, a rainfall permeation model is established according to rainfall data and soil humidity data, a surface runoff field is constructed in combination with terrain elevation data, and the confluence direction of the runoff field is calibrated through water level data; based on a rainfall penetration model and a surface runoff field, generating a flood detention area inundation evolution sequence, segmenting into an inundation grade map according to a time step length, planning a flood detention area emergency evacuation path, matching with a road network in a geographic information system, generating an optimal evacuation path, and issuing graded early warning information to an early warning area. And sending a withdrawal instruction to residents in the flood detention area through the emergency broadcasting system. According to the invention, by establishing a partition early warning mechanism and a differential early warning strategy, accurate delivery and efficient transmission of early warning information are realized.

The invention relates to the technical field of environmental pollutant detection, in particular to a straw open-air incineration pollutant emission quantitative method based on multi-source data fusion, which comprises the following steps: based on air pollutant monitoring data, calling a sensor network to obtain PM2.5, CO and NOX concentrations, analyzing fire point heat radiation intensity, collecting meteorological data, and calculating the concentration of PM2.5, CO and NOX; and obtaining a pollution source data set by combining the time sequence change of the fire points and the meteorological parameters. By integrating an environment monitoring sensor, satellite remote sensing and ground meteorological data, the comprehensiveness and accuracy of pollution source monitoring are improved, the combination of fire point intensity and pollutant concentration time sequence data is optimized, the evaluation of fire point and pollution hot spot areas and the comprehensive analysis of wind directions and meteorological conditions are optimized, the accuracy of a pollutant diffusion model is improved, and the pollution source diffusion efficiency is improved. The pollutant release amount is dynamically adjusted, and the diffusion model is corrected by using a geographic information system, so that the scientificity of pollution prediction and emission intensity evaluation is enhanced, and more accurate pollution prevention and control decision support is provided.

The invention relates to the technical field of distributed data processing, in particular to a hydraulic engineering distributed flood prevention prediction system and method.The system comprises a real-time monitoring module for calculating the mean value and variance of data of a water level sensor every five minutes, and an anomaly detection module for comparing the mean value difference with a threshold value, recognizing a sudden change point and sending the sudden change point to a cloud server; the window adjustment module adjusts the collection frequency according to the abnormal result, the trend analysis module predicts the flood trend by applying moving average and exponential smoothing, and the early warning generation module evaluates the water level and generates an early warning signal. According to the method, the mean value and the variance of the water level monitoring data are calculated in real time and compared with the threshold values, so that the recognition capability of the abrupt change point is improved, the data collection frequency and the window size are adjusted according to the anomaly detection result, the adaptability and efficiency of data collection are enhanced, and the water level trend is predicted through the moving average and exponential smoothing technology; and in combination with a geographic information system, the affected area is accurately evaluated, so that the early warning accuracy and the decision support effectiveness are remarkably improved.

The invention discloses an ecological protection and restoration planning method and system, and the method comprises the steps: obtaining ecological multi-source data of a target region, and carrying out the spatial registration and format standardization processing through a geographic information system; constructing a three-dimensional ecological background model, and fusing the ecological multi-source data to generate a gridding geographic unit; performing dynamic coupling analysis on the ecological multi-source data by adopting a convolutional neural network, identifying an ecological degradation hot spot region, and outputting a spatial probability distribution diagram; and based on the spatial probability distribution of the ecological degradation hot spot region and the ecological background model, generating a multi-level ecological restoration scheme through a self-organizing feature mapping neural network, and outputting a visual planning map. According to the scheme disclosed by the invention, the accuracy and efficiency of ecological assessment are improved, the economic cost of ecological protection and restoration in the region is reduced, the benefit is improved, a better expected effect can be obtained through tests, and the method has a good popularization prospect.

The invention discloses a power distribution network fault differentiation operation and maintenance first-aid repair decision recommendation method, system and device based on a knowledge graph and a medium, and belongs to the technical field of operation and maintenance recommendation, and the method comprises the steps: obtaining the real-time monitoring data of a power distribution network, and constructing a fault feature data set; based on the fault feature data set, combining with a power distribution network knowledge graph to identify a historical fault entity; extracting a corresponding operation and maintenance first-aid repair strategy from the historical fault entity, presetting an evaluation index, and calculating a strategy effect score; evaluating a fault processing priority; and sorting the candidate first-aid repair strategies according to the strategy effect score and the fault processing priority, and screening and outputting a target operation and maintenance strategy suitable for the current fault and matters needing attention of the target operation and maintenance strategy. According to the method, the geographic information system is used for positioning the fault, the distance between the fault and the first-aid repair personnel is evaluated, the processing priority is determined in combination with the emergency degree of the fault, resource allocation is effectively optimized, and response efficiency is improved.

The invention relates to the technical field of image retrieval, in particular to an image retrieval method based on big data mining, which comprises the following steps: collecting images and metadata, screening metadata fields, determining a candidate image set and obtaining a metadata screening result, according to the method, in the image retrieval process, image metadata screening, geographic information clustering, visual feature fusion, index construction and matching strategy optimization are combined, and the retrieval accuracy and response efficiency are improved. In the metadata screening link, data is screened by using information such as time, places and equipment types, so that interference of irrelevant data is reduced, and a candidate image set is more targeted. Geographic information and timestamps are combined for classification, and clustering analysis is performed by utilizing a geographic information system, so that spatial distribution information plays a greater role in a retrieval process, and a more accurate result can be obtained for query of a specific region.

The invention discloses a multi-field sensing fusion deep sea geological environment dynamic monitoring system and an application method. The system comprises a buoy measuring platform, a multi-beam sounding system, a high-precision marine gravimeter, an external camera, a GPS, a data acquisition and transmission control unit and a power supply system. By designing a modularized and integrated multi-sensor buoy platform, various sensors are fused and integrated. A plurality of sensors are connected to the data acquisition control terminal, the steps of sensor calibration, data synchronization and clock calibration, correction and compensation, data acquisition, real-time processing, fine post-processing, data transmission and the like are completed, and multi-sensor collaborative operation is realized, so that submarine topography and ocean gravity data of a deep sea ditch area are synchronously acquired in real time; and thus, diving erosion information experienced by the area can be accurately monitored. The method can provide important support for submarine topography and landform detection and application and marine geographic information system construction, and has application value in the aspects of geological disaster early warning, resource development and the like.

The invention provides an automatic plant identification method and system based on a neural network model, and relates to the technical field of intelligent agriculture, and the method comprises the steps: inputting a composite feature map into a compressed and optimized lightweight convolutional neural network model, and outputting a plant type identification result and a confidence value in real time; dynamically binding a plant type identification result with a geographic information system (GIS) coordinate, generating an endangered plant space distribution thermodynamic diagram and triggering a real-time alarm; images are automatically collected and marked based on newly-added plant sample positions marked in the spatial distribution thermodynamic diagram, and weight parameters of the lightweight convolutional neural network model are periodically updated. The plant identification and protection capability is comprehensively improved through the links of data acquisition diversification and standardization, image processing high efficiency and scientificity, feature extraction and identification accuracy, endangered plant protection and dynamic monitoring, model continuous optimization and adaptability and the like.

The invention discloses an urban live-action three-dimensional modeling method based on multi-source geographic information coupling, and relates to the technical field of geographic information systems and three-dimensional modeling. The method comprises the steps of 1, data acquisition; 2, data preprocessing; 3, performing three-dimensional modeling; 4, optimizing the model; step 5, applying and displaying; according to the urban live-action three-dimensional modeling method based on multi-source geographic information coupling, feature information of terrains, buildings and traffic facilities can be extracted more accurately, so that the model is kept consistent with an actual object in the aspects of shape, size and the like, and therefore, the accuracy of the model is improved; according to the method, elevation information and reflection intensity data of the earth surface can be captured, the texture image of the building can be more real through the three-dimensional contour extraction and texture mapping technology, the visual quality and detail performance of the model are enhanced, and through application of the virtual reality technology, the construction efficiency is improved. And the user can appreciate beautiful scenery and tourism resources of the city at home.