295 results about "Coverage data" patented technology

The invention relates to the technical field of landscape evaluation, and discloses an urban green land landscape evaluation method based on a large model, and the method comprises the steps: carrying out the real-time analysis and standardization processing of a streetscape image, IoT environment data, satellite vegetation coverage data and RTK high-precision positioning information of a target city district, extracting core landscape elements, building cross-scene semantic mapping, and carrying out the calculation of the cross-scene semantic mapping. Transmitting the standardized data to a central database and deploying edge nodes; extracting a multi-dimensional landscape index by adopting an improved semantic segmentation model, dynamically adjusting an index weight in combination with regional features and seasonal changes, and classifying and correcting deviation data by edge nodes; a visual evaluation result is generated based on a cooperative computing architecture and a digital twinborn model, a landscape space to be promoted is identified, and optimization suggestions are generated; and obtaining planner feedback information, updating the model, the weight rule and the suggestion generation strategy, and forming a closed loop iteration mechanism. According to the method, the dynamic and practical evaluation requirements of the current urban green land landscape can be met.

The invention relates to the technical field of intelligent operation inspection of power transmission lines, in particular to an intelligent detection method of a power grid frame and a satellite image processing system.The method comprises the steps that the power grid frame is detected according to collected multi-source monitoring information, information of a plurality of power grid structures is obtained, and a power grid topology model is established; performing connection analysis on the power grid topology model to obtain a power grid topology analysis result, and performing spatial distribution analysis on the power grid frame by collecting coordinate information of the power grid frame and the power grid topology analysis result to obtain power grid coverage data. And performing data visualization on the plurality of pieces of power grid structure information, the power grid topology analysis result and the power grid coverage data to generate a power grid frame detection result. According to the invention, the method effectively solves a problem that the weak edge region is liable to leak detection in the recognition of the power grid frame in a large-range and high-complexity scene, remarkably improves the recognition efficiency and accuracy of the power grid frame, and reduces the cost and time of manual inspection.

Disclosed are a three-dimensional laser point cloud-based method and system for in-depth vegetation management in transmission corridors. The method comprises: collecting multi-source data by means of an unmanned aerial vehicle- and helicopter-mounted multi-sensor system, and preprocessing the multi-source data; using the processed multi-source data to create a digitalized power grid corridor and construct a vegetation management analysis model; on the basis of data analyzed by the vegetation management analysis model and geofencing technology, designing a hazard vegetation clearing-cost-compensation prediction model; and developing a mobile application for analyzing hazard vegetation data flows and the closed-loop management of vegetation management service flows. The described method achieves high-precision and high-coverage data collection, precisely identifies transmission line digital twins and hazard vegetation, standardizes and automates the management of hazard vegetation clearing and related compensation, and develops a mobile application for analyzing hazard vegetation data flows and the closed-loop management of vegetation management service flows, thereby achieving the end-to-end digital and mobile management of vegetation management. The organic combination of steps comprehensively improves the intelligence and efficiency of transmission line vegetation management.

The invention discloses a depth space-time super-resolution mapping method fusing historical high-resolution land coverage data, and the method comprises the steps: constructing a depth space-time super-resolution mapping model structure which is formed by connecting a super-resolution adversarial network SRGAN structure and a MUNet network structure in series; mapping from low-resolution images to high-resolution land coverage category probabilities in combination with super-resolution reconstruction and semantic segmentation is carried out, a historical high-resolution land coverage category map of a target area is used as auxiliary information, and changed categories and unchanged categories are distinguished by comparing category information of the low-resolution images in a historical period and a target period; and a change detection-based sub-pixel category allocation optimization model fusing a historical high-resolution land cover classification map and a predicted high-resolution category probability map is constructed, so that the depth space-time super-resolution mapping of the low-resolution remote sensing image is completed. The method has the advantages of high simulation precision, stability and the like, and is suitable for earth surface information extraction work such as classification, land cover / utilization, change detection and the like when remote sensing images are insufficient.

The invention relates to the technical field of data mining, in particular to a customer behavior analysis method and system based on retail data, and the method comprises the following steps: extracting a numerical set of customer purchase frequency, single consumption amount and shopping duration based on a customer group behavior feature matrix, and calling matrix operation to analyze a multi-feature distribution condition item by item. According to the invention, through extracting the purchase frequency, the consumption amount and the shopping duration in the customer behaviors, combining the analysis of the offset value and the item-by-item comparison of the distribution interval, accurately identifying the abnormal characteristics, and analyzing the offset value in the multi-period frequency change trend, the period characteristics of the behavior change are clearer, and the frequency intersection analysis of the commodity combination purchase behaviors is more accurate. Reconstruction accuracy of feature distribution and hierarchical marking of regional customer coverage data are improved, the assessment ability of regional feature distribution and an offset ratio is refined, and the precision and practicability of the operations in feature distribution capture, multi-period behavior analysis and regional data comparison are improved.

The invention discloses a vegetation coverage prediction method and system based on multi-source data fusion, and relates to the technical field of vegetation coverage prediction, and the method comprises the following steps: obtaining historical vegetation coverage data and land utilization type data, and obtaining a matching time sequence of land utilization transformation and vegetation recovery lag; frequency band extraction is carried out on the matching time sequence based on Fourier transform, and the initial change frequency of the matching degree is obtained; performing random disturbance on the initial change frequency of the matching degree based on a preset first constraint condition to obtain a plurality of different matching degree change frequencies; obtaining vegetation coverage degradation influence data and ecological restoration potential data corresponding to different matching degree change frequencies, and constructing an evaluation model; and according to the data output by the evaluation model, the vegetation coverage prediction value of the preset first prediction model is corrected. The problem that the vegetation coverage prediction is inaccurate due to the fact that the relation fluctuation between the land utilization type conversion speed and the vegetation recovery lag degree is not considered is solved.

The invention relates to the field of industrial automation testing, discloses a multifunctional testing tool and method for an EUROMAP interface of an injection molding machine, and achieves the crossing from single function verification to system-level compliance evaluation. A test network is constructed through a controller, and deep compliance verification, coverage data interaction, exception handling and cross-layer response consistency are realized. The test tool integrates the functions of protocol analysis, signal simulation, fault injection and the like, supports dynamic generation of boundary value test scenes and abnormal injection of signal delay, CRC errors and the like, and verifies the time sequence / logic consistency of a protocol instruction and an execution mechanism response through a hardware-level timestamp alignment technology. According to the method, an evaluation report including compliance rating, fault diagnosis and optimization suggestions is automatically generated, the problems of single coverage dimension, insufficient abnormal simulation, cross-layer verification deficiency and the like of a traditional test are solved, the intelligence and standardization level of the injection molding machine interface test is remarkably improved, and the equipment interconnection and intercommunication performance is guaranteed.

The invention discloses an optimal signal selection intelligent network switching management method based on a super SIM multi-network, and relates to the field of intelligent network switching management, and the main scheme is as follows: analyzing and calculating operation state data to obtain a network delay score, a downloading rate score and a network stability score in a current network environment, and carrying out comprehensive analysis to obtain an optimal signal selection score; obtaining a current network state score; judging whether to execute a network switching instruction or not by evaluating the current network state score; the coverage degree data, the network state data and the switching cost data are analyzed and calculated to respectively obtain coverage matching degree indexes, network state indexes and switching cost-benefit ratios of different operators; switching priority indexes of different operators are obtained through comprehensive analysis, the switching priority is determined, and the problem that switching decisions and requirements are disjointed due to the fact that switching is triggered only based on signal strength or a single rate threshold and core indexes such as network delay and stability which affect user experience are not fused is solved.

The invention provides an individual credit risk assessment method, system and device based on federal learning, and belongs to the technical field of data processing. The method comprises the following steps: in response to a credit evaluation request from a credit evaluation node, determining one or more evaluation participation nodes of a credit evaluation object; generating a corresponding local credit evaluation instruction and sending the local credit evaluation instruction to each evaluation participation node; wherein the local credit assessment instruction comprises a desensitization identifier of the credit assessment object. And determining a global credit score of the credit assessment object based on the local credit score fed back by each assessment participation node and the weight set corresponding to the credit assessment request, and sending the global credit score to the credit assessment node. Through the method, the credit assessment coverage data is improved, and the credit assessment is carried out in time, so that the personal credit risk assessment is accurately completed.

The invention discloses an urban block green land planning method and device based on thermal environment big data, and the method comprises the steps: obtaining the thermal environment data, vegetation coverage data and a vegetation database of a target block; constructing a thermal environment map of the target block based on the thermal environment data, and obtaining a thermal environment feature vector of each sub-block according to the thermal environment map; acquiring a microclimate influence value of each vegetation type; performing correlation analysis on the thermal environment feature vector and the microclimate influence value of each sub-block to obtain the microclimate adjustment contribution degree of each vegetation type to each sub-block; and according to the microclimate adjustment contribution degree, determining a target vegetation type to be planted in each sub-block and a planting proportion of each target vegetation type, and obtaining a vegetation configuration scheme of the target block. The microclimate adjusting capability of the urban green land can be improved.

The invention provides a wind power data determination method and device based on geographical constraint attention. The wind power data determination method comprises the steps of obtaining topographic data, surface vegetation coverage data and wind power data; for the wind power data, combining the topographic data and the surface vegetation data, performing feature fusion through an adaptive attention mechanism to obtain a fusion feature containing multi-source information; performing shallow feature extraction, deep feature extraction and image up-sampling on the fusion features in sequence, wherein the deep feature extraction realizes multi-scale feature extraction and geographic constraint fusion through a multi-stage residual fusion module RFSTB, a wind field frequency domain decoupling module CFB and a geographic perception global attention module GAB; verifying the effectiveness of the model by using a peak signal-to-noise ratio (PSNR) and a structural similarity index (SSIM); and performing super-resolution reconstruction on the wind power data based on the trained model to generate wind power data with predetermined precision. The method provides support for fine evaluation and efficient development of wind energy resources in complex terrain areas.

The invention discloses a method for reducing line loss and improving power supply reliability based on the Internet of Things, and the method comprises the steps: carrying out the full-dimension load and line state monitoring: deploying an Internet of Things sensor, constructing an end-to-end monitoring network, and collecting key parameters in real time; a low-delay and wide-coverage data channel is constructed; a layered communication architecture is adopted, and efficient data transmission is realized; the real-time analysis and intelligent decision engine is used for constructing a load-line-equipment three-dimensional data model based on a cloud end and an edge platform, and realizing line loss real-time diagnosis, load prediction, situation awareness and rapid fault positioning; dynamic optimization and self-healing control: based on a data layer analysis result, source-network-load coordinated regulation and control are realized through an Internet of Things terminal, line loss is reduced, and stable power supply is guaranteed; user interaction and global optimization: realizing power grid-user interaction and peak load shifting through a user-side Internet of Things terminal to reduce the pressure of a power system; the system has the advantages of being capable of reducing line loss, guaranteeing power supply reliability, having various functions and being good in comprehensive application effect.

The invention relates to a landscaping coverage rate data statistical method. Comprising the steps of generating independent greening coverage rate data of each layer based on vegetation multi-dimensional stratified analysis of ecological characteristics, and obtaining an overall greening coverage rate through a superposition algorithm; calculating a dynamic coverage rate based on plant spectral characteristics, then calculating a green coverage rate actually participating in an ecological function based on an evaluation result, and adjusting coverage rate data in real time according to a plant health state to obtain the dynamic coverage rate; correcting coverage rate data by analyzing soil humidity and air temperature environmental factors in different time periods based on ecological influence weights of spatial and temporal changes; the ecological functional indexes are associated with the greening coverage rate; according to the method, the vegetation coverage rate and real-time environment data are coupled to construct a statistical model, and then adjusted data are combined with multispectral remote sensing data to form coverage rate evaluation; by introducing an ecological compensation mechanism, the dynamic process of landscaping change is simulated.

The invention relates to the technical field of geological engineering, in particular to a comprehensive evaluation method and system for a mine geological environment, and the method comprises the following steps: collecting mine surface geological data based on a target mine region, collecting vegetation types and vegetation coverage area data, evaluating the occurrence probability of landslide and land subsidence of a plurality of regions of a mine, and obtaining a comprehensive evaluation result; and obtaining a surface risk assessment result. According to the method, the accuracy and the reliability of risk assessment are improved by integrating the surface geological data and the vegetation coverage data and combining meteorological information and topographic analysis, the judgment for geological stability is enhanced by combining fixed-point assessment and stratigraphic analysis, so that early warning for a hidden danger area is more timely and specific, and the risk assessment accuracy and the risk assessment reliability are improved. By monitoring surface deformation in real time and combining long-term data analysis, a more dynamic and continuous geological environment change trend is provided, mining strategies and disaster prevention and reduction measures can be adjusted in time, and the environmental influence of mining activities is reduced.

The invention belongs to the field of remote sensing technology and environment monitoring, and particularly relates to a three gorges reservoir area ground surface settlement monitoring method, system and device based on multi-source remote sensing data, and the method comprises the steps: obtaining a plurality of single-view complex images and corresponding image surface coverage data in a period of time, and carrying out the preprocessing of the image data; carrying out SBAS-InSAR processing on the preprocessed image data, wherein the SBAS-InSAR processing comprises carrying out interference, inversion and geocoding processing on the image; fusing the coded data by adopting a multi-source remote sensing data fusion technology; inputting the fused image into a pre-trained machine learning model to obtain a three gorges reservoir area ground surface settlement monitoring result; by introducing multi-source remote sensing data fusion and an advanced machine learning model, the problems of single data source, difference in temporal-spatial resolution, poor model adaptability and the like in the prior art are solved, and the precision, the stability and the robustness of ground surface settlement monitoring and evaluation are remarkably improved.

The invention relates to the technical field of bridge detection and data processing, in particular to a bridge appearance detection method and system based on cooperation of an unmanned aerial vehicle and a workstation. The technical problems are as follows: the modern bridge detection technology is complex in bridge environment, most of the existing unmanned aerial vehicle detection schemes depend on manual control flight, the flight difficulty is high, and high-definition pictures are difficult to shoot, so that a large amount of rework is caused; according to the technical scheme, the bridge appearance detection system based on cooperation of the unmanned aerial vehicle and the work station comprises an unmanned aerial vehicle platform and a ground work station; real-time data acquisition is performed on the bridge and the surrounding environment thereof through the unmanned aerial vehicle, a bridge digital map is produced by integrating a multi-sensor fusion technology and a three-dimensional modeling and deep learning technology, and a fine acquisition path is planned; and automatic, high-precision and high-coverage data acquisition of the bridge appearance in a complex environment is completed, so that the precision and efficiency of disease detection are greatly improved.

The invention discloses an SAR (Synthetic Aperture Radar) image overlay detection method, device and equipment and a storage medium. The method comprises the following steps: acquiring SAR time sequence image data, external DEM (Digital Elevation Model) data and external earth surface classification coverage data of a current detection area; obtaining a region amplitude diagram of the current detection region according to the SAR time sequence image data, and carrying out normalization processing on the region amplitude diagram; obtaining a corresponding interferometric phase diagram according to the SAR time sequence image data, and calculating a coherence coefficient; performing normalization processing on the external DEM data, performing wave band splicing on the normalized region amplitude diagram, interference phase diagram and coherence coefficient, and the normalized external DEM data and external earth surface classification coverage data to generate a corresponding data block, and inputting the data block into a preset overlay identification model, and obtaining an overlay identification result of the current detection area. The SAR overlay recognition method can improve the overlay recognition precision of the SAR.

The invention relates to the technical field of electronic design automation, in particular to a coverage rate-based index database management method, coverage rate-based index database management equipment and a storage medium. Meanwhile, extracting design level information in the coverage rate database to establish an index database consisting of a plurality of index tables; when the visual query window initiates a query request, the index database queries the identifier of the target object according to the query request, and processes and updates the target window of the coverage rate visual system according to the identifier in the coverage rate data structure, so that the search efficiency is greatly improved, and the search time is shortened. And the purpose of real-time searching is achieved.

The invention discloses a cloud management and intelligent distribution method for classroom teaching resources, and relates to the technical field of cloud computing software. The classroom teaching resource cloud management and intelligent distribution method comprises the steps that S1, multi-source teaching resource data and auxiliary distribution data are acquired and preprocessed, and a knowledge content database is constructed; s2, performing semantic fusion analysis through text semantic association, structural consistency and professional term coverage data; s3, carrying out dependency evaluation by fusing pre-association, knowledge co-occurrence, sequence association and semantic fusion data; s4, performing resource adaptability distribution analysis through the maximum knowledge dependence value in combination with the learning state data and the historical feedback data; and S5, evaluating the teaching resource quality by collecting classroom feedback, teacher evaluation and resource use data, and implementing content optimization. The problems of semantic distortion, path breakage, distribution mismatching and resource updating inconsistency in the teaching resource data fusion and intelligent resource distribution process are solved.

The invention belongs to the field of software testing and defect detection, focuses on reliability verification of a physical simulation engine, is suitable for scenes depending on physical simulation, such as robot simulation, automatic driving testing, unmanned aerial vehicle control, education and scientific research, and particularly relates to a variation-based physical simulation engine defect detection method. Potential defects of core modules of collision detection, mechanical calculation, dynamics and the like are efficiently found through a variation test method. According to the method, a feature library is constructed through static library API analysis and AST / IR code analysis, test code expansion is performed by utilizing a large model, a test driver adaptive to a specific data type is generated, a physical semantic constraint mutation seed is combined, a test is executed through libFuzzer, defect and coverage rate data are analyzed, a use case selection strategy is optimized, and the test efficiency is improved. Defects of core modules such as collision detection and dynamic solution are efficiently detected, and the test pertinence and efficiency are improved.

The invention discloses a load management operation method for comprehensive energy optimal configuration, and relates to the technical field of energy management, and the method comprises the following specific steps: microclimate partition division: carrying out the comprehensive field exploration of a target region, collecting the landform, building layout and vegetation coverage data, analyzing the influence of each factor on the microclimate formation, and carrying out the calculation of the microclimate; according to the method, a partition division basis is determined according to the difference between airflow and heat caused by topographic relief, the influence of a building on sunlight and ventilation and local microclimate characteristics of vegetation construction, and a linkage model comprehensively considering the relationship among a microclimate partition state, a building adjustment behavior and an energy load is established; the complex relation among microclimate parameter changes, building adjustment action changes and energy load changes is accurately reflected, meanwhile, according to state changes after building adjustment, the energy management system can dynamically optimize an energy configuration scheme, unnecessary energy transmission and conversion links are reduced, and the energy utilization rate is improved. And deep optimization configuration of comprehensive energy of the whole area from generation, transportation to use is realized.

The invention discloses an incremental code coverage rate acquisition device based on a Java bytecode dynamic instrumentation technology, and relates to the technical field of software testing and quality control. Comprising a code difference analysis module, a byte code instrumentation module, a coverage rate data acquisition module, a coverage rate data integration module, a coverage rate report generation module and a test trigger and threshold control module, and a syntax tree structure of incremental codes is generated based on a Java syntax analysis tool, so that line level analysis of code differences is realized. According to the method, incremental codes are accurately analyzed through Git and JavaParser, coverage rate data are collected through dynamic instrumentation, a unified report is generated in combination with path analysis, missing scenes are marked in a highlighted mode, and the test efficiency and the code quality control capacity are improved.

The invention relates to the field of ecological environment monitoring, and discloses a vegetation coverage spatio-temporal change analysis method, which comprises the following steps of: firstly, preprocessing remote sensing image data of a research area, including radiometric calibration, atmospheric correction and image splicing and cutting; then calculating a vegetation index value based on the normalized vegetation index, and extracting a vegetation coverage through a pixel bipartite model; and performing difference calculation on the vegetation coverage data in different periods, analyzing spatial and temporal change characteristics of vegetation coverage, and generating a vegetation coverage grading map and a change distribution map. According to the method, the spatial distribution and dynamic change trend of vegetation coverage can be accurately reflected, the defect that a traditional vegetation monitoring method is sensitive to soil background and atmosphere interference is overcome, the method has the advantages of being high in precision, wide in applicability and high in dynamic monitoring capacity, and a scientific basis is provided for formulation and effect evaluation of regional ecological protection measures.

The invention discloses a continuous casting adjustment method and system for crystallizer assembly simulation, and relates to the technical field of continuous casting process optimizing.The method comprises the steps that networking data collection is conducted according to equipment ID and molten steel component information of a crystallizer assembly, and continuous casting historical data are obtained; performing working condition expansion on the continuous casting historical data to obtain continuous casting coverage data; establishing an initial finite element model; calibrating boundary conditions to obtain a continuous casting finite element model; clustering analysis is carried out, and a continuous casting optimization difference starting point is positioned; parallel local iteration optimization is started, and a continuous casting multi-target equilibrium solution set is obtained; and performing global iteration optimization to obtain the continuous casting adjustment control reference. The technical problem that in the prior art, the blank shell uniformity and thickness are difficult to accurately control in the continuous casting process, and consequently the continuous casting quality is unstable is solved, and the technical effects that the blank shell uniformity and thickness are indirectly optimized and controlled in the continuous casting process, and the continuous casting quality is improved are achieved.

The invention provides a satellite observation data restoration method and device based on generation of a collaborative adversarial network, and relates to the technical field of data restoration, and the method comprises the steps: extracting a cloud coverage sub-region and a cloud-free sub-region from a target region, and carrying out the cloud coverage sub-region and the cloud-free sub-region based on respective corresponding current satellite observation data subsets; performing space-time registration and radiation correction on the historical satellite observation data subset corresponding to the cloud coverage sub-region under the condition of no cloud coverage to obtain a corrected historical satellite observation data set corresponding to the target region; and performing progressive cooperative training on the generated cooperative adversarial network by using the current satellite observation data set of the target area and the corrected historical satellite observation data set. According to the method, the problems of poor cloud coverage data missing repair effect and insufficient physical consistency in a traditional method can be relieved.

The invention provides a satellite remote sensing high-temperature heat wave risk early warning method, device and equipment and a medium. The method comprises the following steps: acquiring satellite remote sensing data, numerical mode forecast data, cloud coverage data and land utilization type analysis data corresponding to a research area; according to a model dynamic allocation mechanism, dynamically allocating a corresponding high-temperature heat wave risk early-warning model for each grid in the research area according to the cloud coverage data, and determining a high-temperature heat wave early-warning result corresponding to each grid based on satellite remote sensing data and numerical mode forecasting data through the high-temperature heat wave risk early-warning model corresponding to each grid; and determining a susceptibility weight corresponding to each grid according to the land utilization type analysis data, and determining a high-temperature heat wave risk level corresponding to each grid in combination with the high-temperature heat wave early warning result corresponding to each grid. According to the method, the high-temperature heat wave prediction precision can be remarkably improved, and meanwhile risk early warning is more regional and targeted.

The invention provides an automobile electronic control unit fuzzy testing method based on partial code coverage rate feedback and a computer, and belongs to the technical field of automobile electronic control unit code testing. The computer performs static analysis on source codes of the automobile electronic control unit, identifies inevitable execution blocks and conditional execution blocks, performs selective instrumentation on the conditional execution blocks, and inserts coverage rate recording instructions of the conditional execution blocks. And the computer source code is loaded into the automobile electronic control unit, and a test input signal is generated through the fuzzy test engine and is injected into the automobile electronic control unit. In the process of executing the program by the automobile electronic control unit, recording the coverage condition of the condition execution block to a bitmap in the memory; the computer reads the coverage rate data of the condition execution block through the debugger every time a complete execution cycle is completed; and the fuzzy test engine adjusts the input generation strategy according to the coverage rate data feedback of the condition execution block and tests again. According to the method, the automobile electronic control unit source code fuzzy test coverage condition is efficiently collected.

The invention discloses an automobile interior and exterior decoration product size measurement method based on automatic scanning, and belongs to the field of automobile part detection, and the method comprises the following steps: carrying out the non-contact comprehensive scanning of an automobile interior and exterior decoration product through a 3D automatic scanner, and obtaining high-precision point cloud data; preprocessing the point cloud data, including denoising, splicing and three-dimensional reconstruction, and generating a product digital model corresponding to the real object; performing automatic alignment and size comparison on the product digital model and a preset CAD design model, and calculating a deviation error of each feature size; and performing automatic qualification judgment on the deviation error based on a preset tolerance standard, and generating a detection report containing an error analysis result and a judgment conclusion. According to the automobile interior and exterior decoration product size measurement method based on automatic scanning, full-coverage data acquisition can be completed in a short time through 3D automatic scanning, the measurement efficiency is improved, the dependence on the experience of measurement personnel is reduced, and high-precision measurement of the size of the automobile interior decoration product is realized.

The invention provides a method for improving urban green land biological source emission based on a high-resolution global mode, and provides a technical scheme for optimizing a biological source emission list by using high-resolution land coverage data aiming at the problem of urban green land emission deficiency in a current numerical model. The technologies comprise a weak supervision global land coverage mapping method, spectral information of images can be fused, and features extracted by a visual large model are used for drawing high-resolution land coverage images; the vegetation function type matching method is used for converting the high-resolution land coverage data into vegetation function types; and preparing a high-resolution numerical mode input file, converting the file into an input format suitable for a high-resolution earth system mode, carrying out numerical simulation, and estimating global biological source emission, especially urban green space emission.

A method for delineating an ore body of deep-sea polymetallic nodules based on coverage data includes steps as follows. Ore body data of the deep-sea polymetallic nodules is obtained, the ore body data includes: mining site production scale parameters, mining system parameters, and ore body geological characteristic parameters. A boundary coverage rate and a cumulative weighted average coverage rate are calculated based on the mining site production scale parameters, the mining system parameters, and the ore body geological characteristic parameters. The ore body is delineated, based on the boundary coverage and the cumulative weighted average coverage, through a principle of ore body boundary range delineation to obtain an ore body range. The method delineates ore body of nodule with proper geological continuity based on abundance data. It can be directly applied to deep-sea polymetallic nodule mining, solving the problems existing in the delineation of ore body of deep-sea polymetallic nodule.