Resource element evaluation method and system based on space portrait and structure analysis

Abstract

The invention provides a resource element evaluation method and system based on space portrait and structure analysis, and the method comprises the steps: building an evaluation index system; extracting index spatial features of the resource elements; constructing an element space portrait according to the index space features; performing correlation analysis on the resource elements; and comprehensively evaluating the resource elements. According to the resource element evaluation method and system based on space portrait and structure analysis, a multi-dimensional evaluation index system framework and a package evaluation analysis model algorithm are constructed based on technologies of remote sensing interpretation, deep learning, knowledge graph and the like in combination with technical methods of spatial feature extraction, element portrait construction, element association analysis and the like; and a dynamic calculation analysis support is provided for index calculation and report generation of resource element evaluation.

Description

Technical Field

[0001] The invention relates to the technical field of element evaluation, and in particular to a resource element evaluation method and system based on spatial profiling and structural analysis. Background Art

[0002] Traditional resource evaluation methods often focus on single-dimensional data collection and analysis, such as only considering the quantity or quality of resources, while ignoring the spatial distribution characteristics of resources and their structural relationship with the surrounding environment. This results in the evaluation results being unable to fully and accurately reflect the true value and potential advantages of resources, and it is difficult to meet the complex and changing needs of resource management.

[0003] In the existing technology, there is a lack of construction of resource spatial portraits, which cannot intuitively display information such as the distribution, density and concentration of resources in geographical space, which is not conducive to decision makers to quickly understand the overall situation of resources. At the same time, without in-depth structural analysis, it is difficult to reveal the internal connection and interaction mechanism between resource elements, and it is impossible to provide strong support for the optimal allocation and coordinated development of resources. Summary of the invention

[0004] The purpose of the invention is to provide a resource element evaluation method and system based on spatial profiling and structural analysis to solve the problems existing in the existing resource element evaluation methods.

[0005] The present invention provides a resource element evaluation method based on spatial profiling and structural analysis, the method comprising: Establishing an evaluation indicator system; Extract the indicator spatial characteristics of resource elements; Constructing a spatial profile of an element according to the spatial characteristics of the indicator; Conduct correlation analysis on resource elements; Conduct a comprehensive evaluation of the resource elements.

[0006] The above-mentioned resource element evaluation method based on spatial profiling and structural analysis is based on technologies such as remote sensing interpretation, deep learning and knowledge graphs, combined with technical methods such as spatial feature extraction, element profiling, and element correlation analysis. It constructs a multi-dimensional evaluation index system framework and a package of evaluation analysis model algorithms to provide dynamic computing and analysis support for the indicator calculation and report generation of resource element evaluation.

[0007] Furthermore, the method for establishing the evaluation index system includes: Constructing an evaluation indicator framework, which includes economic, social and environmental dimensions; Screen and determine indicators. According to the evaluation indicator framework, clarify the indicator weights of each evaluation object and screen out key evaluation indicators; Design evaluation criteria, set evaluation criteria for each evaluation indicator, and the evaluation criteria include evaluation level, score and threshold.

[0008] Furthermore, the method for extracting the index space characteristics of resource elements includes: Using remote sensing image interpretation methods, identifying and distinguishing different types of resource elements according to spectral characteristics, and extracting spatial distribution characteristics of different resource elements; In combination with a supervised learning algorithm, the patterns and regularities between the spatial distribution characteristics of different resource elements are learned through training samples; The resource elements and the evaluation indicators are bidirectionally mapped, and the evaluation indicators are assigned corresponding geographic space ranges to achieve spatialization and vectorization of the indicators.

[0009] Furthermore, the method for constructing an element space portrait according to the indicator space characteristics includes: Obtaining a resource space image of the resource element; Obtaining an ecological spatial portrait of the resource elements; Obtain a functional spatial portrait of the resource elements.

[0010] Furthermore, for land resources, the element spatial portrait includes resource type, quality, and development potential; for mineral resources and energy resources, the element spatial portrait includes their type, reserve distribution, and component content; for forest ecology, grassland ecology, wetland ecology, and marine ecology, the element spatial portrait includes different ecological functions, animal and plant distribution ranges, and species richness; for residential, industrial, transportation, and public service facilities, the element spatial portrait includes coverage, service radius, and degree of spatial agglomeration.

[0011] Furthermore, the method for performing association analysis on resource elements includes: Analyze the internal structure of the resource elements; Analyzing the spatiotemporal evolution of the resource elements; Conducting correlation analysis between different resource elements; Conduct correlation analysis between the resource elements and the external environment.

[0012] Further, spatial autocorrelation, hot spot analysis, and spatial clustering are used to identify the spatial structure and pattern of the resource elements; Using trend analysis and cycle analysis, through the interpolation of multi-time point monitoring data, study and identify the spatiotemporal dynamic changes of the resource elements; Through correlation impact analysis, the associations between different resource elements are explored to discover the causal relationships, dependencies, and interactions between different resource elements; Through the interaction and influence between resource space, ecological space and functional space, the correlation between all resource elements and the correlation analysis results of the whole cycle changes are analyzed.

[0013] Furthermore, the method for comprehensively evaluating the resource elements includes: Establish model algorithms, combine spatial portraits and correlation analysis results, establish evaluation models for various resource elements, and form a set of model algorithm libraries; The evaluation results are analyzed by simulating and predicting based on the model algorithm library, comprehensively evaluating the resource elements, and assessing the performance and changes of the resource elements under different conditions.

[0014] The evaluation results are displayed by combining the indicator system and weight assignment method to calculate the comprehensive evaluation score of the resource elements and form a corresponding evaluation report.

[0015] The present invention also provides a resource element evaluation system based on spatial profiling and structural analysis, the system comprising: System establishment module, used to establish an evaluation indicator system; Feature extraction module, used to extract the indicator space features of resource elements; An element space portrait construction module is used to construct an element space portrait according to the indicator space characteristics; Relationship analysis module, used to conduct relationship analysis on resource elements; A comprehensive evaluation module is used to conduct a comprehensive evaluation of the resource elements.

[0016] Furthermore, the system establishment module includes: Evaluation indicator framework construction module, used to construct the evaluation indicator framework; Indicator screening and determination module, used for screening and determining indicators; Evaluation criteria design module, used to design evaluation criteria. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart of a resource element evaluation method based on spatial profiling and structural analysis in the first embodiment of the invention; Figure 2 This is a module diagram of the resource element evaluation system based on spatial profiling and structural analysis in the second embodiment of the invention.

[0018] The following specific implementation manner will further illustrate the invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0019] In order to facilitate understanding of the invention, the invention will be described more fully below with reference to the relevant drawings. Several embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the invention more thorough and comprehensive.

[0020] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the invention belongs. The terms used in the specification of the invention herein are only for the purpose of describing specific embodiments and are not intended to limit the invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0022] See also Figure 1 The present invention provides a resource element evaluation method based on spatial profiling and structural analysis, the method comprising steps S01 and S05: Step S01, establishing an evaluation index system; Step S02, extracting the index space characteristics of resource elements; Step S03, constructing an element space portrait according to the indicator space characteristics; Step S04, performing correlation analysis on resource elements; Step S06, comprehensively evaluating the resource elements.

[0023] The above-mentioned resource element evaluation method based on spatial profiling and structural analysis is based on technologies such as remote sensing interpretation, deep learning and knowledge graphs, combined with technical methods such as spatial feature extraction, element profiling, and element correlation analysis. It constructs a multi-dimensional evaluation index system framework and a package of evaluation analysis model algorithms to provide dynamic computing and analysis support for the indicator calculation and report generation of resource element evaluation.

[0024] In one embodiment of the present invention, the method for establishing an evaluation index system includes: constructing an evaluation index framework, wherein the index framework includes economic dimension, social dimension and environmental dimension; screening and determining indicators, and clarifying the indicator weights of each evaluation object and screening out key evaluation indicators according to the evaluation index framework; designing evaluation criteria, and setting evaluation criteria for each evaluation indicator, wherein the evaluation criteria include evaluation levels, scores and thresholds. It should be noted that the evaluation index framework is constructed from three dimensions: economy, society and environment. The economic dimension mainly considers the contribution of resources to economic development, such as the economic benefits of resources, the driving role of industries, etc.; the social dimension focuses on the impact of resources on social development, including employment opportunities, social welfare and other aspects; the environmental dimension focuses on the impact of resource development and utilization on the ecological environment, such as ecological protection, environmental pollution and other factors. By comprehensively considering these three dimensions, the comprehensiveness and scientificity of the evaluation index framework are ensured. Screening and determining indicators: Based on the constructed evaluation index framework, scientific methods are used to clarify the weights of each indicator for different evaluation objects. For example, we can use multi-criteria decision-making methods such as analytic hierarchy process and Delphi method, combined with expert opinions and actual data, to rank the importance of each indicator and screen out the indicators that have a key impact on the evaluation object. These indicators should be representative, operational and quantifiable, and can accurately reflect the characteristics and attributes of resource elements. Design evaluation criteria: set clear evaluation criteria for each selected evaluation indicator, including evaluation level, score and threshold. The evaluation level can be divided into different levels according to actual conditions, such as excellent, good, medium, poor, etc.; the score is assigned to each level for quantitative evaluation; the threshold is used to define the boundaries between different levels to ensure the objectivity and fairness of the evaluation criteria.

[0025] Taking land resource evaluation as an example, in the economic dimension, the economic benefits of land are considered, such as indicators such as land output rate and land appreciation potential; in the social dimension, the driving effect of land on employment and the fairness of land use are concerned; in the environmental dimension, the ecological protection function of land and the degree of land pollution are considered. Through comprehensive consideration of these indicators, a comprehensive land resource evaluation indicator framework is constructed.

[0026] It should be noted that the analytic hierarchy process is used to determine the weight of each indicator. First, the land resource evaluation problem is decomposed into the target layer (comprehensive evaluation of land resources), the criterion layer (economic, social, and environmental dimensions) and the indicator layer (specific evaluation indicators). Then, experts in related fields are invited to score the relative importance of each indicator and construct a judgment matrix. By calculating the eigenvector and eigenvalue of the judgment matrix, the weight vector of each indicator is obtained, and a consistency test is performed to ensure the rationality of the weight. After screening and determination, the key indicators of land resource evaluation are finally obtained, such as land output rate, employment driving coefficient, ecological protection index, etc.

[0027] In the specific implementation process, specific evaluation standards can be set for each evaluation indicator. For example, for the land output rate indicator, according to the land use status and economic development level of different regions, the evaluation level is divided into five levels: high, relatively high, medium, relatively low, and low. The corresponding scores are 80-100 points, 60-80 points, 40-60 points, 20-40 points, and 0-20 points, and the thresholds are 80, 60, 40, and 20, respectively. Through clear evaluation standards, the evaluation results are comparable and objective.

[0028] In one embodiment of the present invention, the method for extracting the index space characteristics of resource elements includes: Using remote sensing image interpretation methods, different types of resource elements are identified and distinguished according to spectral features, and spatial distribution features of different resource elements are extracted. For example, through spectral analysis of satellite remote sensing images, different types of land resources such as cultivated land, forest land, grassland, etc., as well as their distribution range and boundaries in geographic space can be accurately identified. Combined with supervised learning algorithms, the patterns and laws between the spatial distribution features of different resource elements are learned through training samples. The supervised learning algorithm can establish a model to predict the features of unknown data based on known sample data. In resource element evaluation, through learning training samples, the algorithm can automatically identify the typical patterns and features of the spatial distribution of resource elements, and improve the accuracy and efficiency of extracting spatial features of resource elements. The resource elements and the evaluation indicators are bidirectionally mapped, and the evaluation indicators are given corresponding geographic spatial ranges to achieve spatialization and vectorization of indicators. This means combining traditional abstract evaluation indicators with specific geographic spatial locations so that evaluation indicators can be intuitively displayed and analyzed in geographic space. For example, the quality indicators of land resources are corresponding to the specific plot locations, and the spatial distribution of land of different quality levels can be intuitively seen through geographic information system (GIS) technology.

[0029] It should be noted that in this application, the supervised learning algorithm can be: collect historical data and field survey data of the land resources in the area as training samples. Use the support vector machine (SVM) algorithm for training to learn the patterns and laws between the spatial distribution characteristics of different land resource types. The trained SVM model can classify and predict new remote sensing image data to improve the accuracy and efficiency of land resource type identification.

[0030] In one embodiment of the present invention, the method for constructing an element space portrait according to the indicator space feature includes: Obtaining a resource space image of the resource element; Obtaining an ecological spatial portrait of the resource elements; Obtain a functional spatial portrait of the resource elements.

[0031] Specifically, based on the extracted spatial characteristics of resource elements, GIS technology and visualization tools are used to draw visualization images of the distribution, quantity, quality and other information of resource elements in geographic space to form a resource space portrait. Resource space portrait can intuitively display the spatial distribution pattern of resource elements and help decision makers quickly understand the overall status of resources. In view of the impact of resource elements on the ecological environment, analyze and extract the spatial characteristics of relevant ecological indicators, such as ecological functions and biodiversity, to construct an ecological space portrait. Ecological space portrait can reflect the degree and scope of the impact of resource development and utilization on the ecological environment, and provide an important basis for ecological protection and sustainable development. Considering the functional attributes of resource elements, such as residence, industry, transportation, public service facilities and other functions, extract the corresponding indicator space characteristics and construct a functional space portrait. Functional space portrait can show the role and influence of resource elements in different functional fields, which helps to optimize the functional layout and configuration of resources.

[0032] In one embodiment of the present invention, the resource space portrait is mainly for land resources, and the element space portrait includes resource type, quality, and development potential. For mineral resources and energy resources, the element space portrait includes their type, reserve distribution, and component content. The ecological space portrait is mainly for forest ecology, grassland ecology, wetland ecology, and marine ecology, and the element space portrait includes different ecological functions, animal and plant distribution ranges, and species richness. The functional space portrait is mainly for residence, industry, transportation, and public service facilities, and the element space portrait includes coverage, service radius, and spatial agglomeration degree.

[0033] In one embodiment of the present invention, the method for performing association analysis on resource elements includes: Analyze the internal structure of the resource elements; specifically, analyze the internal structure of the resource elements in detail to understand the characteristics, proportions and relationships of each component. For example, for mineral resources, analyzing the internal structure characteristics such as ore composition and grade distribution will help to gain a deeper understanding of the quality and development potential of the resources.

[0034] Analyze the temporal and spatial evolution of the resource elements; specifically, through multi-point monitoring data, use trend analysis, cycle analysis and other methods to study the dynamic change laws of resource elements in time and space. For example, observe the change trend of land resource utilization types over time, as well as the cyclical characteristics of land resource utilization in different regions, to provide a basis for the rational planning and sustainable utilization of resources.

[0035] Conduct correlation analysis between different resource elements; specifically, use methods such as correlation impact analysis to explore the internal correlation between different resource elements and discover the causal relationship, dependency and interaction between them. For example, analyze the interdependence between land resources and water resources, and the impact of mineral resource development on the surrounding ecological environment, to provide guidance for the comprehensive management and coordinated development of resources.

[0036] Conduct correlation analysis between the resource elements and the external environment. Specifically, consider the interaction and impact between resource elements and the external environment, and comprehensively evaluate the status and role of resource elements in the entire system through correlation analysis between resource space, ecological space and functional space. For example, analyze the impact of resource development on the surrounding social and economic environment and ecological environment, as well as the feedback effect of external environmental factors on resource elements, to provide comprehensive decision-making support for the sustainable development of resources.

[0037] In one embodiment of the present invention, spatial autocorrelation, hot spot analysis, and spatial clustering are used to identify the spatial structure and pattern of the resource elements; trend analysis and cycle analysis are used to study and identify the spatiotemporal dynamic changes of the resource elements through interpolation of multi-time point monitoring data; correlation impact analysis is used to explore the associations between different resource elements, and to discover the causal relationships, dependencies, and interactions between different resource elements; and the associations between all resource elements and the results of the association analysis of full-cycle changes are analyzed through the interactions and influences between resource space, ecological space, and functional space.

[0038] In one embodiment of the present invention, the method for comprehensively evaluating the resource elements includes: Establish a model algorithm, combine the spatial portrait and correlation analysis results, establish evaluation models for various types of resource elements, and form a set of model algorithm library; the evaluation model can adopt a variety of methods, such as hierarchical analysis method, fuzzy comprehensive evaluation method, grey correlation analysis method, etc., and select appropriate models for comprehensive evaluation based on the characteristics of resource elements and evaluation needs.

[0039] Evaluation result analysis: simulate and predict based on the model algorithm library, conduct a comprehensive evaluation of the resource elements, and assess the performance and changes of the resource elements under different conditions. Through in-depth analysis of the evaluation results, understand the advantages and disadvantages of resource elements, and provide targeted suggestions for the optimal allocation and management of resources.

[0040] Evaluation results display, combined with the index system and weight assignment method, calculate the comprehensive evaluation score of the resource elements and form a corresponding evaluation report. The evaluation report should include the basic information of the resource elements, the evaluation index system, the analysis of the evaluation results and related suggestions and measures, and show the evaluation of the resource elements to decision makers in an intuitive and clear way.

[0041] See also Figure 2 The embodiment of the present invention further provides a resource element evaluation system based on spatial profiling and structural analysis, the system comprising: The system establishment module 10 is used to establish an evaluation index system; specifically, the system establishment module is responsible for establishing an evaluation index system, including an evaluation index framework construction module, an index screening and determination module, and an evaluation standard design module. The evaluation index framework construction module is used to construct an evaluation index framework covering the three dimensions of economy, society and environment; the index screening and determination module selects key evaluation indicators according to the evaluation index framework and clarifies the weight of each indicator; the evaluation standard design module sets evaluation standards for each evaluation indicator.

[0042] The feature extraction module 20 is used to extract the index spatial features of resource elements; specifically, the feature extraction module is mainly used to extract the index spatial features of resource elements. This module uses remote sensing image interpretation methods to identify and distinguish the types of different resource elements and extract their spatial distribution features; combines supervised learning algorithms to learn the patterns and laws between spatial distribution features; realizes the two-way mapping between resource elements and evaluation indicators, and spatializes and vectorizes the evaluation indicators.

[0043] The element space portrait construction module 30 is used to construct the element space portrait according to the index space characteristics; specifically, the element space portrait construction module constructs the spatial portrait of the resource element according to the extracted index space characteristics, including obtaining the resource space portrait, ecological space portrait and functional space portrait. Through these spatial portraits, the distribution, ecological function and functional attributes of the resource element in the geographical space are intuitively displayed.

[0044] The association analysis module 40 is used to perform association analysis on resource elements. Specifically, the association analysis module performs association analysis on resource elements, including the internal structure composition, spatiotemporal evolution, and association analysis between different resource elements and the external environment. The spatial structure and pattern of resource elements are identified by using spatial autocorrelation, hot spot analysis, spatial clustering and other methods; the spatiotemporal dynamic changes of resource elements are studied by trend analysis and cycle analysis; the association between different resource elements is explored by using correlation impact analysis; and the interaction and impact between resource space, ecological space and functional space are analyzed.

[0045] The comprehensive evaluation module 50 is used to conduct a comprehensive evaluation of the resource elements; specifically, the comprehensive evaluation module conducts a comprehensive evaluation of the resource elements, including establishing a model algorithm, analyzing the evaluation results, and displaying the evaluation results. A model algorithm library is established, and the resource elements are simulated and predicted in combination with the spatial image and the results of the association analysis; the comprehensive evaluation score is calculated according to the indicator system and the weight assignment method, and an evaluation report is formed to provide decision support for the development, utilization, and management of resources.

[0046] The present invention constructs an evaluation index system from the three dimensions of economy, society and environment, comprehensively considers various attributes and influencing factors of resource elements, and avoids the one-sidedness of traditional evaluation methods. At the same time, by constructing resource space portraits, ecological space portraits and functional space portraits, and conducting in-depth analysis of the internal structure, spatiotemporal evolution, mutual correlation and relationship with the external environment of resource elements, a comprehensive evaluation of resource elements is achieved, which can more accurately reflect the true value and potential advantages of resources.

[0047] Visualization: Use GIS technology and visualization tools to construct a spatial portrait of resource elements, and display abstract resource information in the form of intuitive maps, charts, etc., so that decision makers can quickly and clearly understand the spatial distribution pattern, ecological functions and functional attributes of resources, thereby improving the scientific nature and efficiency of decision-making.

[0048] In-depth analysis: Through structural analysis and correlation analysis of resource elements, the inherent connections and interaction mechanisms between resource elements are deeply explored, revealing the structural characteristics and evolution laws of the resource system. This helps decision makers better understand the complexity of the resource system, formulate more scientific and reasonable resource development, utilization and management strategies, and achieve optimal allocation and coordinated development of resources.

[0049] Intelligence: The evaluation system of the present invention integrates a variety of advanced technologies and algorithms, such as remote sensing image interpretation, supervised learning algorithms, spatial analysis methods, etc., to achieve automation and intelligence in the processes of data processing, feature extraction, evaluation and analysis. This not only improves the efficiency and accuracy of the evaluation work, but also reduces the interference of human factors, ensuring the reliability and objectivity of the evaluation results.

[0050] Adaptability: The evaluation method and system of the present invention have strong adaptability and can flexibly adjust the evaluation index system, model algorithm and evaluation criteria according to different types of resource elements, evaluation purposes and actual needs. At the same time, the system can effectively integrate and utilize multi-source heterogeneous data, adapt to the requirements of different data formats and sources, and provide a wider range of application scenarios for resource element evaluation.

[0051] The above-mentioned embodiments only express several implementation methods of the invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the inventive concept, and these all belong to the protection scope of the invention. Therefore, the protection scope of the invention patent shall be based on the attached claims.

Claims

1. A resource element evaluation method based on spatial profiling and structural analysis, characterized in that: The method comprises: Establishing an evaluation indicator system; Extract the indicator spatial characteristics of resource elements; Constructing a spatial profile of an element according to the spatial characteristics of the indicator; Conduct correlation analysis on resource elements; Conduct a comprehensive evaluation of the resource elements.

2. The resource element evaluation method based on spatial profiling and structural analysis according to claim 1 is characterized in that: The method for establishing the evaluation index system comprises: Constructing an evaluation indicator framework, which includes economic, social and environmental dimensions; Screen and determine indicators. According to the evaluation indicator framework, clarify the indicator weights of each evaluation object and screen out key evaluation indicators; Design evaluation criteria, set evaluation criteria for each evaluation indicator, and the evaluation criteria include evaluation level, score and threshold.

3. The resource element evaluation method based on spatial profiling and structural analysis according to claim 2 is characterized in that: The method for extracting the index spatial characteristics of resource elements includes: Using remote sensing image interpretation methods, identifying and distinguishing different types of resource elements according to spectral characteristics, and extracting spatial distribution characteristics of different resource elements; In combination with a supervised learning algorithm, the patterns and regularities between the spatial distribution characteristics of different resource elements are learned through training samples; The resource elements and the evaluation indicators are bidirectionally mapped, and the evaluation indicators are assigned corresponding geographic space ranges to achieve spatialization and vectorization of the indicators.

4. The resource element evaluation method based on spatial profiling and structural analysis according to claim 1 is characterized in that: The method for constructing an element space portrait according to the indicator space feature comprises: Obtaining a resource space image of the resource element; Obtaining an ecological spatial portrait of the resource elements; Obtain a functional spatial portrait of the resource elements.

5. The resource element evaluation method based on spatial profiling and structural analysis according to claim 4 is characterized in that: For land resources, the element spatial portrait includes resource type, quality, and development potential. For mineral resources and energy resources, the element spatial portrait includes their type, reserve distribution, and component content. For forest ecology, grassland ecology, wetland ecology, and marine ecology, the element spatial portrait includes different ecological functions, animal and plant distribution ranges, and species richness. For residential, industrial, transportation, and public service facilities, the element spatial portrait includes coverage, service radius, and degree of spatial agglomeration.

6. The resource element evaluation method based on spatial profiling and structural analysis according to claim 1 is characterized in that: The method for performing association analysis on resource elements comprises: Analyze the internal structure of the resource elements; Analyzing the spatiotemporal evolution of the resource elements; Conducting correlation analysis between different resource elements; Conduct correlation analysis between the resource elements and the external environment.

7. The resource element evaluation method based on spatial profiling and structural analysis according to claim 6 is characterized in that: Using spatial autocorrelation, hot spot analysis, and spatial clustering to identify the spatial structure and pattern of the resource elements; Using trend analysis and cycle analysis, through the interpolation of multi-time point monitoring data, study and identify the spatiotemporal dynamic changes of the resource elements; Through correlation impact analysis, the associations between different resource elements are explored to discover the causal relationships, dependencies, and interactions between different resource elements; Through the interaction and influence between resource space, ecological space and functional space, the correlation between all resource elements and the correlation analysis results of the whole cycle changes are analyzed.

8. The resource element evaluation method based on spatial profiling and structural analysis according to claim 6 is characterized in that: The method for comprehensively evaluating the resource elements comprises: Establish model algorithms, combine spatial portraits and correlation analysis results, establish evaluation models for various resource elements, and form a set of model algorithm libraries; Analysis of evaluation results: simulation and prediction based on the model algorithm library, comprehensive evaluation of the resource elements, and assessment of the performance and changes of the resource elements under different conditions; The evaluation results are displayed by combining the indicator system and weight assignment method to calculate the comprehensive evaluation score of the resource elements and form a corresponding evaluation report.

9. A resource element evaluation system based on spatial profiling and structural analysis, characterized in that: The system comprises: System establishment module, used to establish an evaluation indicator system; Feature extraction module, used to extract the indicator space features of resource elements; An element space portrait construction module is used to construct an element space portrait according to the indicator space characteristics; Relationship analysis module, used to conduct relationship analysis on resource elements; A comprehensive evaluation module is used to conduct a comprehensive evaluation of the resource elements.

10. The resource element evaluation system based on spatial image and structural analysis according to claim 9 is characterized in that: The system establishment module includes: Evaluation indicator framework construction module, used to construct the evaluation indicator framework; Indicator screening and determination module, used for screening and determining indicators; Evaluation criteria design module, used to design evaluation criteria.

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