43 results about "Land based" patented technology

A composite optimization positioning method of a multi-buoy combined land base station is based on an RTK technology, constructs double-difference baselines for a plurality of buoys, and constructs a closed composite optimization solution scheme by using a plurality of baselines, and comprises the following specific steps: (1) baseline construction: obtaining observation data between the plurality of buoys and a land reference station by using the RTK technology, constructing a double-difference base line between every two buoys to obtain a base line resolving result; (2) calculating a closing error; (3) carrying out composite solution; (4) result screening and determination: calculating difference values among multiple groups of combined observation values; eliminating values with difference values exceeding 95% confidence interval of the difference value sequence; calculating an arithmetic average value of multiple groups of observation values of which the difference values are within 95% confidence interval, and taking the arithmetic average value as a final positioning result of the buoy; and (5) selecting a buoy closed ring. The method aims at solving the problem that the ocean buoy positioning result is unreliable and even fails under the complex sea condition, the availability rate of the positioning result can be improved, and the buoy positioning precision can be improved to a certain degree.

The invention relates to an ecological corridor identification method and system based on machine learning. The method comprises: extracting ecological source land based on land utilization data; training a machine learning classification model by using the ecological system service data and the multi-source space impact factors, inputting the multi-source space impact factors into the trained machine learning classification model, predicting ecological resistance values of all space units in the research area, and outputting an ecological resistance surface; and inputting the ecological source land and the ecological resistance surface into an ecological connectivity analysis model based on a circuit theory, simulating an ecological flow process, identifying space channels connected between different ecological source lands according to an ecological flow probability or accumulated resistance, and determining an ecological corridor in the research area. Compared with the prior art, the method has the advantages of improving objectivity and accuracy of an ecological corridor identification result and the like.

The invention discloses a social media data fused urban inefficient land intelligent identification method, which comprises the following steps of: realizing multi-source data space fusion by acquiring a social media geographic marking text, an urban updating policy file, a remote sensing image and basic geographic data; a natural language processing and topic modeling method is used for extracting keywords from the city update text, a topic-feature word mapping table is constructed, a RoBERTa-l arge model and a semantic rule are combined to calculate a text emotion score, and a land use negative emotion map is generated; and constructing a multi-dimensional evaluation system including indexes such as plot ratio and road network density, calculating a composite index by adopting an AMP algorithm, dynamically allocating weights through an entropy weight method, and judging the low-efficiency land. And a white list area is introduced for verification and parameter iterative optimization, and finally, an identification result is visually displayed in WebG IS and AR platforms, so that the accuracy and decision support capability of urban low-efficiency land identification are improved.

The invention discloses a multi-objective optimized urban development boundary land intelligent configuration simulation method, which comprises the following steps: S1, acquiring multi-source original data of a to-be-simulated city, and preprocessing the multi-source original data; s2, based on the preprocessed data, dividing urban land basic units, extracting feature information of each unit, and constructing an urban development boundary configuration basic data set; and S3, building a city development scene generation model of a generative model architecture, and taking the basic data set as input. The invention relates to the technical field of city planning and simulation. According to the multi-objective optimized intelligent configuration simulation method for the urban development boundary land, a generative model and a deep learning technology are adopted, a virtual development boundary scheme is generated according to multi-source data, the virtual development boundary scheme and actual urban land data are compared and analyzed, a deviation value is calculated, model parameters are automatically adjusted, iterative optimization is carried out, and the intelligent configuration simulation method for the urban development boundary land is achieved. And the development scheme gradually tends to be optimal.

The invention discloses a nanogenerator-based self-powered wind power pile seabed scour pit piezoelectric monitoring method, and relates to the technical field of offshore wind power generation pile monitoring, and the method comprises the following core contents: constructing a ''seabed sensor-sea surface signal transfer module-land data processing and early warning system'' integrated architecture; the PVDF piezoelectric unit is used for realizing direct conversion from kinetic energy of ocean fluid to electric energy, synchronously converting the change of the exposed length (corresponding to the scouring depth) of the vertical plate of the sensor into a voltage signal, and transmitting the voltage signal to a land base station after processing to realize real-time monitoring; the sensor takes reinforced fiber / epoxy resin as a carrier and is coated with a plurality of corrosion-resistant coatings, and a double-layer circular array is arranged on a seabed within the range of 1 meter around a wind power pile. By means of the self-energy-supply design, the problems of high maintenance cost and poor reliability caused by the fact that traditional monitoring depends on an external power source are solved, the bottleneck of long-term stable monitoring under the complex marine environment is broken through by combining a high-sensitivity monitoring mechanism and a multi-layer protection structure, the advantages of being convenient and fast to install and controllable in cost are achieved, and technical support is provided for safe operation of a wind power plant.

The present application relates to a kind of hard rock crossing of non-excavation directional drilling based on submarine cable landing construction method, belong to the technical field of optical cable layout, including the following steps: design from high to down and between vertical plane certain angle and the preset trajectory of through hard rock slope surface;Control directional drilling machine along the preset trajectory and drill guide hole;Control the drill rod of directional drilling machine along the preset trajectory and back drag, and finally form guide final hole by expanding the guide hole;Excavation anchoring well of construction operation and the cable trench being communicated with the anchoring well at suitable position, and install anchoring device inside anchoring well;Drag rope of armoured submarine cable is passed from guide final hole to shore.The present application avoids trenching on hard rock, reasonably reduces construction cost, avoids trestle erection on steep slope at the same time, reduces the landscape influence to rock shore reef, avoids the influence of scouring, corrosion to cable structure.

The application provides a kind of based on forest remote sensing data annotation method and system, comprising: obtaining the multi-source remote sensing data of forest land;Multi-source remote sensing data is handled;Optical image features are extracted using improved Mask R-CNN network, multi-modal enhanced feature maps are obtained by compressing and exciting SE module to enhance near-infrared band weight and performing feature fusion;Feature extraction is carried out using 3D convolution network, and multi-level three-dimensional spatial feature map is obtained;The processed data is input into the Transformer model, and the forest growth curve graph is obtained;Initial annotation is carried out based on the feature map and the curve graph, and the initial annotation result is obtained;Small area noise is removed by morphological filtering to the initial annotation result, and the annotation boundary is optimized by combining superpixel segmentation algorithm, to obtain the optimized annotation result;The optimized annotation result is generated into vector annotation file.The multi-dimensional information complement of spectral features, three-dimensional structure features and time sequence dynamic features is realized, and the data availability and reliability are significantly improved.

The invention discloses an information interaction method and device, equipment, a storage medium and a program product, and belongs to the technical field of computers. The method comprises the steps of displaying batch interaction props under the condition that virtual land of a virtual object meets batch interaction conditions; in response to a trigger operation of the batch interaction prop, based on a three-dimensional bounding box of the batch interaction prop and reference information, determining a reference land parcel in the at least two land parcels of the virtual land, the reference information comprising at least one of parameters of the batch interaction prop, a position of a virtual object or a planting state of each land parcel of the virtual land; and displaying the interaction result. The batch interaction prop can directly act on at least two land parcels, so that the interaction efficiency is improved; the virtual land areas of different heights can be covered in the three-dimensional space by using the three-dimensional bounding box of the batch interaction props, land parcel misjudgment caused by topographic relief is avoided, the reference land parcel is determined in combination with the reference information, and the accuracy of determining the reference land parcel is improved.

A computer-implemented method for emission estimation includes collecting top down information including above surface information related to land and collecting bottom up information including below surface information related to the land. Greenhouse gas emissions are estimated for specific parcels of land based in accordance with a parcel size of a first granularity for the top down information and the bottom up information. A geospatial foundation model is fine-tuned using a physics informed loss function that accounts for estimated CO2 through remote sensing and weather and phenological information from soil data, wherein the fine-tuning creates a hyper local model that allocates emissions at a second granularity that has a higher spatial resolution than the first granularity.

The invention relates to the field of polluted land parcel restoration and treatment, and particularly discloses a solid waste cleaning effect evaluation method which comprises the following steps: S1, acquiring excavation boundary control point coordinate data and land parcel basic information of a to-be-evaluated land parcel; s2, for each evaluation unit, taking the excavation boundary control point as a core sampling point, setting an auxiliary sampling point, and determining a sampling scheme; s3, at each sampling point, collecting a soil sample in a stratified sampling manner, and performing pretreatment to obtain a to-be-detected sample; s4, performing solid waste residue and soil particle composition uniformity detection on the to-be-detected sample; s5, setting an evaluation threshold value standard, and comparing a detection result with a threshold value to judge the cleaning qualification of each evaluation unit; and S6, summarizing judgment results of all evaluation units, integrally evaluating the land parcel cleaning effect and outputting a secondary cleaning suggestion scheme. The method is easy and convenient to operate and accurate in judgment, the solid waste cleaning effect can be objectively and accurately judged, the evaluation efficiency is improved, and practicability and generalizability are high.

Navigation filters / estimators are coupled with coordinated multi-agent batch navigation to facilitate “Synthetic Aperture” capabilities for improved GPS-denied or degraded navigation. The modified single-agent navigation filter continues to estimate platform (Airborne, water based and / or land based autonomous vehicles) position, velocity, and attitude in a global reference frame in the standard way, but now simultaneously outputs “delta-poses” (effectively a low rate odometry) with accurate covariances. The delta-poses are then used in complementary multi-platform navigation algorithms which provides accurate relative pose between cooperating platforms. The relative position knowledge allows the modified global filter to ingest the other platforms navigation-aiding measurements directly.

The invention relates to the technical field of greenbelt management and maintenance, in particular to a greenbelt intelligent management and maintenance system based on cloud computing, which comprises a cloud multi-source integration module, a time sequence disturbance analysis module, a disturbance chain association module, a disease trend identification module and a management and maintenance regulation and control linkage module. And judging the online state of the sensing equipment and the plot numbering accuracy. According to the method, a cloud-oriented data integration system is constructed, multi-source environment parameters and spatial attributes are collected into a dynamic data structure, global association and time sequence connection of information among land parcels are achieved, data are automatically sorted through a cloud platform to form a parameter evolution link, multi-level feature criteria such as coverage, time sequence and trend are established for monitoring objects, and the monitoring efficiency is improved. Abnormal evolution performance of a disease state is directly fed back to a management and maintenance regulation and control process through linkage judgment, and system output regulation and control configuration is generated according to a real-time state, so that the consistency of risk research and judgment and the pertinence of a regulation and control decision are improved.

1. The name of the design product: land floating wind power generation device. 2. The use of the design product: wind power generation. 3. The design points of the design product: the shape of the product. 4. The picture or photo that best indicates the design points of the design: perspective view.

The invention relates to the technical field of machine learning, in particular to an urban green land NDVI prediction method and system based on machine learning, and the method comprises the steps: obtaining the multi-dimensional state data of a target green land; based on the multi-dimensional state data, constructing a vegetation ecological process prediction network corresponding to the target green land; the vegetation ecological process prediction network at least comprises a photosynthesis prediction sub-network, a respiration consumption prediction sub-network and a stress suppression prediction sub-network; and performing NDVI prediction on the target green land based on the vegetation ecological process prediction network to obtain an NDVI prediction value, thereby realizing NDVI prediction based on the ecological process, and improving reliability and interpretability of NDVI prediction.

The invention discloses an intelligent algorithm for evaluating a target land price based on a market land price. The intelligent algorithm comprises the following steps: 1) acquiring target land parcel data; 2) based on the target land parcel data, using a GIS tool to delimit a peripheral area range of the target land parcel, and screening out similar land similar to the target land parcel in use, property and planning index from the determined peripheral area range; 3) calculating the average unit price of the same kind of land; 4) adjusting the average unit price based on land use, planning indexes and position advantages; and 5) based on the adjusted average unit price and the area of the target land parcel, obtaining the land price of the target land parcel, and performing visualization. According to the method, the economic value and potential value of the land are quantified in combination with multi-source data, and the influence of policy adjustment and market fluctuation on the land value is tracked in real time; and a scientific basis is provided for time sequence planning of land collection, storage, transfer and development.

The invention discloses a method and a system for accurately identifying a irrigated land based on space-time two-dimensional feature fusion, and belongs to the technical field of remote sensing image processing and agricultural information. The method comprises the following steps: acquiring multi-source data of a target area, wherein the multi-source data comprises a remote sensing image sequence, surface water source spatial distribution data, underground water irrigation facility spatial distribution data and cultivated land pattern spot data; spatial analysis is carried out based on water source and irrigation facility data, and an irrigation condition spatial distribution diagram is generated through Euclidean distance calculation and nuclear density analysis; extracting a time sequence vegetation index of the cultivated land pattern spot data in a moisture sensitive phenological period based on the remote sensing image sequence, and calculating a stability index; constructing a deep learning model fusing the spatial semantic segmentation network and the time sequence analysis network, and performing model training by taking the spatial distribution map and the stability index as fusion input features; and identifying and outputting a irrigated land distribution map by using the trained model. The invention further discloses a corresponding system, electronic equipment and a storage medium. According to the invention, through time-space two-dimensional feature fusion, the precision of irrigated land identification is effectively improved, and the limitation of a single-dimensional method is solved.

This invention relates to a model buffer and capture device for land-based vertical catapult tests. The device, used to capture a model, includes a damping system and a capture system. The damping system absorbs energy and buffers during the capture process. The capture system, mounted on the damping system, includes a capture support with a buffer net at its top and a gripper system below the net for clamping and securing the model. A photoelectric proximity switch is also mounted on the capture support; when the switch detects an object passing through, it sends an electrical signal to control the gripper system. A launch tube, vertically positioned below the capture system, launches the model. This invention enables capture in vertical land-based catapult tests, allowing for safe, damage-free, and efficient model recovery after launch, thus improving test efficiency. The buffer system significantly reduces the load on the grippers during model capture, enhancing the overall system reliability.

This application provides a method, apparatus, system, device, medium, and product for controlling the landing of a drone, relating to the field of drone control technology. The method includes: acquiring image data from a visual marker tag, radio frequency data transmitted by multiple radio frequency tags (RFID tags) affixed to the visual marker tag, and environmental data of the drone; determining target control parameters based on the image data, RFID data, and environmental data; and controlling the drone to land based on the target control parameters. This application uses RFID tags affixed to the visual marker tag. These RFID tags are unaffected by lighting conditions, enabling accurate drone positioning even in low-light conditions or when the visual marker tag is partially obscured. Furthermore, utilizing multimodal data to determine the parameters for controlling the drone improves the accuracy of the control parameters compared to a single sensor or tagging system, thereby enhancing landing accuracy.

The invention relates to the technical field of ecological funeral and interment and forestry carbon sink, in particular to a bone ash land bearing capacity assessment method and system based on tree species and intelligent monitoring. According to the method, a bone ash tolerance database of different tree species is established, a bone ash acid-base adjusting technology, a single-tree multi-position bone ash bearing capacity calculation model and a carbonized bamboo tube container degradation control system are combined, and a soil sensor network, a property right type associated tree sharing platform and a three-dimensional cadastre model carbon sink management system are integrated; and a complete intelligent tree burial solution is formed. According to the system, the bone ash bearing capacity is dynamically evaluated by monitoring soil parameter changes in real time, healthy growth of trees is guaranteed, and meanwhile accurate carbon sink metering and ecological value conversion are achieved.

The system according to this embodiment aims to quickly derive buildable plans based on land information and to evaluate the economic value of the land. [Solution] The system according to the embodiment comprises a reception unit, an analysis unit, and an evaluation unit. The reception unit receives land information. The analysis unit analyzes the land information received by the reception unit and derives a buildable plan considering legal regulations. The evaluation unit evaluates the economic value of the land based on the building plan derived by the analysis unit.

The present application belongs to the technical field of remote sensing application, and relates to a photovoltaic land vegetation detection method and system based on remote sensing data. The method comprises the following steps: collecting basic attribute data of a target photovoltaic power station, synchronously acquiring multi-source remote sensing data covering the target photovoltaic land; data preprocessing; extracting a photovoltaic panel array mask, dividing the target photovoltaic land into multiple functional subareas; constructing a photovoltaic land vegetation detection model; constructing a time series prediction model to obtain vegetation growth prediction results; matching vegetation treatment strategies to generate a vegetation control operation and maintenance scheme for the target photovoltaic land. The present application designs an interference elimination processing flow for the photovoltaic scene, improves the vegetation detection accuracy, constructs a PV-VegNet vegetation detection deep learning model with multi-feature fusion, realizes multi-dimensional detection, improves the vegetation detection accuracy, realizes future vegetation growth prediction, realizes early risk prediction in combination with a hierarchical early warning mechanism, and improves the safety control capability of the photovoltaic power station.

The application relates to a soil moisture inversion method based on low-altitude unmanned aerial vehicle remote sensing information. The method comprises the following steps: acquiring real-time state data of a monitoring target land; analyzing the characteristics of the monitoring target land based on the real-time state data to obtain soil observation characteristics; predicting the state of the monitoring target land based on a preset soil initial state vector and a preset soil environment database to obtain predicted soil state characteristics and a predicted gradient value corresponding to the predicted soil state characteristics; quantifying the difference between the predicted soil state characteristics and the soil observation characteristics to obtain an observation difference value, and obtaining a real-time soil moisture content value based on the observation difference value, the predicted gradient value and a soil moisture initial component. The method can improve the soil moisture prediction accuracy.

A kind of fire-burned trace land quick identification extraction method based on time sequence remote sensing vegetation index belongs to the cross field of electronic information technology and resource and environment technology, including the following steps: step one, obtains and pre-processes historical and latest remote sensing image, calculates spectrum index sensitive to fire-burn and constructs time sequence curve;Step two, extracts historical synchronous data, carries out trend fitting using non-parametric Theil-Sens method, obtains the prediction model of each pixel;Step three, calculates the residual between the actual value and predicted value of spectrum index of latest image and previous effective image, and further calculates residual change amount;Step four, carries out threshold binaryzation processing to the residual change amount image of each spectrum index, takes intersection to multi-index binary result and fuses iteration with historical monitoring result, finally determines the range of fire-burned trace land.The present application significantly improves the timeliness and accuracy of fire-burned trace land identification, and can provide effective technical support for forest fire prevention, ecological assessment and emergency management.

The application belongs to the technical field of unmanned aerial vehicle landing on a ship, and discloses a rotary-wing unmanned aerial vehicle autonomous dynamic landing method and related device; wherein the rotary-wing unmanned aerial vehicle autonomous dynamic landing method comprises the following steps: obtaining a ship-aircraft relative rough pose after the rotary-wing unmanned aerial vehicle enters a landing state sequence; constructing a ship-aircraft relative pose and a relative speed credible state estimator based on the ship-aircraft relative rough pose; generating a landing-allowable score curve and obtaining a candidate available landing time window containing a main window and an alternative window based on the credible state estimator and ship movement information; and generating an executable space-time trajectory for guiding the rotary-wing unmanned aerial vehicle to land based on the candidate available landing time window. The technical scheme disclosed by the application is a kind of all-weather autonomous landing scheme for dynamic ships, and solves the technical problem that the rotary-wing unmanned aerial vehicle cannot be safely, stably and autonomously landed and recovered under the conditions of arbitrary navigation of a ship, high sea conditions and low visibility environment.

This invention discloses an intelligent classification system for alpine grassland vegetation and bare land based on multi-band remote sensing image collaboration, relating to the fields of remote sensing information processing and ecological environment monitoring technology. It includes a multi-source data acquisition module, an ice crystal suspected area generation module, a reflection anomaly identification module, an interference dynamic modeling module, and a dynamic classification correction module. The multi-source data acquisition module acquires remote sensing image data over multiple time periods and simultaneously records the location of shady slopes and frost signs, generating an observation data list for alpine regions. This invention achieves temporal correspondence between red and near-infrared bands through multi-time period, multi-band, and meteorological parameter acquisition, dynamically identifying and eliminating ice crystal interference. Combined with shady slope and frost feature screening and threshold temporal redistribution, along with backlighting patrols, shading patrols, and polarization adjustments, it achieves adaptive correction of classification results, improving the accuracy and stability of alpine grassland surface identification.

The utility model relates to the technical field of high-altitude wind power generation, in particular to a land-based high-altitude wind power generation umbrella ladder releasing device. According to the land-based high-altitude wind power generation umbrella ladder releasing device, by arranging the base, the guide rails and the umbrella beams, it can be guaranteed that all umbrella units in an umbrella ladder are inversely hung on all the umbrella beams respectively before releasing, buckles on all the umbrella beams can lock mooring ropes at the tails of all the umbrella units, and meanwhile it can be guaranteed that in the releasing process, all the umbrella units are not prone to falling off. When the umbrella ladder flies, the umbrella beam corresponding to the current umbrella unit moves downwards along the guide rail, and the ring buckle corresponding to the current umbrella unit is opened to avoid the space for releasing the next section of umbrella unit, so that the automatic releasing of the umbrella ladder can be realized, and the safety of workers can be guaranteed.

This invention relates to the field of image recognition technology, specifically to a method for identifying urban and rural planning land use based on remote sensing imagery. This invention effectively integrates visual, geometric, and topological information, performing radiometric calibration and orthorectification on the acquired optical remote sensing images and metadata. Primarily targeting high-resolution optical remote sensing images, this invention separates complementary spatial-frequency domain texture representations through frequency domain transformation and depth feature extraction techniques to address the feature confusion caused by similar appearances but differences in microstructure among ground features. Utilizing morphological reconstruction operations and projection geometric constraints, through the detection and correlation analysis of shadow areas, it recovers the object-level mask and pseudo-3D height geometric attributes of buildings from monocular images, overcoming the limitations of traditional 2D images in perceiving vertical physical features. Based on scene adjacency graphs, it performs topological modeling and contextual information aggregation on the spatial distribution relationships between ground features, achieving refined classification and identification of building functional attributes.

The invention relates to the field of land planning management, in particular to a land index management system and method based on differentiated territorial space use control, and the method comprises the steps: obtaining land use control partition data and land attribute data, and evaluating the land use control sensitivity; construction attribute data and adjacent space environment data are obtained, and overflow hazard assessment of the construction land candidate position is executed; constructing a purpose control-overflow hazard coupling weight matrix based on the land purpose control sensitivity and the overflow hazard evaluation result, and evaluating the spatial coupling influence of each construction land candidate position; performing developability judgment on each candidate construction land based on a spatial coupling influence evaluation result, and evaluating the development suitability of each construction land candidate position; and generating a construction land selection suggestion based on the development suitability evaluation result. According to the method, the scientificity and the reliability of the development site selection decision of the construction land are improved by quantifying the coupling influence of the use control sensitivity and the overflow hazard degree.