Coastline updating potential evaluation method and device

Abstract

The invention relates to the technical field of marine resource management, and discloses a coastline update potential evaluation method, which comprises the following steps: S10, constructing a coastline type database according to a related standard guide, and judging the type of a coastline to be evaluated based on the coastline type database; s20, constructing an update potential evaluation model according to the coastline type of the to-be-evaluated coastline, wherein the evaluation model comprises a target layer, a criterion layer and an index layer; s30, constructing the updated potential evaluation model into a multi-layer structure model according to an analytic hierarchy process, scoring the evaluation indexes by using a Delphi method to obtain index scores, performing normalization processing on the index scores, and performing consistency check; and S40, obtaining a data set of a to-be-evaluated coastline, inputting the data set into the multi-layer structure model, and outputting a coastline updating potential evaluation result through the multi-layer structure model.

Description

Technical Field

[0001] The present invention relates to the technical field of marine resource management, and particularly to a method and device for evaluating the update potential of a coastline. Background Art

[0002] Evaluating the update potential of a coastline refers to the possibility of transforming, upgrading or redeveloping the existing coastline to improve its utilization efficiency, economic benefits, environmental adaptability and social value. This concept is of great significance in coastal city planning and marine resource management, as it is directly related to the sustainable utilization of the coastline and the development of the regional economy.

[0003] Currently, the research on coastline potential mainly focuses on aspects such as coastline change monitoring, coastline extraction and classification, evaluation of the impact of coastline utilization, and evaluation of the benefits of coastline utilization. The main means used are: evaluating the data of the benefits of coastline utilization. Currently, the evaluation of the benefits or resource quantification mainly focuses on the port coastline. For example, the invention patent of CN202410161961.4 constructs a comprehensive quantitative grade index of port resources for a specific type of coastline, namely the port coastline, from aspects such as the evaluation value of the coastline length, the evaluation value of the coastline water depth, the evaluation value of the formation of the coastline land area, the evaluation value of the industrial support of the coastline, and the evaluation value of the environmental sensitivity of the coastline. This method can only evaluate a specific type of coastline, namely the port coastline in the coastline, and cannot effectively evaluate the coastline potential in multiple dimensions. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to solve the problem that the existing method for evaluating the update potential of a coastline is not comprehensive and cannot perform an adaptability evaluation for multiple types of coastlines.

[0005] To solve the above technical problem, the present invention provides a method for evaluating the update potential of a coastline, and the method includes:

[0006] S10, constructing a coastline type database according to relevant standard guidelines, and judging the coastline type of the coastline to be evaluated based on the coastline type database;

[0007] S20, constructing an update potential evaluation model according to the coastline type of the coastline to be evaluated. The evaluation model includes an objective layer, a criterion layer, and an index layer. The objective layer is the output of the evaluation of the coastline update potential. The criterion layer includes data on the current situation of coastline utilization, data on the planning situation, and data on the supporting degree. The index layer is the coastline evaluation index system;

[0008] S30, constructing the update potential evaluation model into a multi-level structure model according to the analytic hierarchy process, scoring the evaluation indicators by using the Delphi method to obtain index scores, normalizing the index scores and performing a consistency test;

[0009] S40. Obtain the dataset of the coastline to be evaluated and input it into the multi-level structure model. Through the multi-level structure model, output the evaluation result of the coastline renewal potential. The specific steps are as follows:

[0010] S41. Divide several evaluation units according to the dataset of the coastline to be evaluated.

[0011] S42. Based on the linear weighted method and the multi-level structure model, conduct weighted scoring on several of the evaluation units to obtain a scoring value.

[0012] S43. Output the evaluation result of the coastline renewal potential according to the scoring value.

[0013] Furthermore, the criterion layer includes the current situation data of shoreline utilization, the planning situation data, and the supporting degree data.

[0014] Furthermore, the method for determining the shoreline type in S10 is as follows:

[0015] Obtained by referring to relevant standard guidelines and existing research methods for port shorelines.

[0016] Furthermore, the coastline evaluation index system is constructed by integrating the coastline renewal condition and demand data, the current situation data of shoreline utilization, the shoreline utilization benefit data, the shoreline ownership situation data, the planning situation data, and the supporting improvement degree data.

[0017] Furthermore, the specific steps for constructing the multi-level structure model in S30 are as follows:

[0018] S31. Establish a hierarchical structure model according to the target layer, the criterion layer, and the index layer.

[0019] S32. Gradually construct a judgment matrix according to the criterion layer and the index layer.

[0020] S33. Establish an expert scoring database and use the weighted average method to summarize the judgments of the expert scoring database for the evaluation indicators, and generate several final judgment matrices.

[0021] S34. Conduct normalization processing on each of the final judgment matrices, calculate the weights of each level, and calculate the quantization values of each evaluation indicator in the final judgment matrix.

[0022] Furthermore, the method includes:

[0023] For the evaluation indicators that can be directly standardized, conduct negative normalization processing on the quantization values of the evaluation indicators.

[0024] Furthermore, the method also includes:

[0025] Propose an update strategy based on the evaluation results of the coastline update potential.

[0026] Furthermore, the method for dividing several evaluation units in S41 is as follows:

[0027] Divide according to the remote sensing image data and the surveyed shoreline types, in accordance with the shoreline type, terrain features, and development and utilization conditions. The length of a single shoreline evaluation unit is greater than 100m.

[0028] According to another aspect of the present invention, there is provided a coastline update potential evaluation device. When using the coastline update potential evaluation device for evaluation, it includes the coastline update potential evaluation method described above in the claims.

[0029] Furthermore, the device includes:

[0030] A shoreline classification unit, which is used to determine the shoreline type of the shoreline to be evaluated;

[0031] A model construction unit, which is used to construct an update potential evaluation model according to the shoreline type of the shoreline to be evaluated. The evaluation model includes a target layer, a criterion layer, and an index layer. The target layer is the output of the shoreline update potential evaluation. The criterion layer includes shoreline utilization status data, planning situation data, and supporting degree data. The index layer is the shoreline evaluation index system;

[0032] A model processing unit, which is used to construct the update potential evaluation model into a multi-level structure model according to the analytic hierarchy process, score the evaluation indexes using the Delphi method to obtain index scores, normalize the index scores, and perform a consistency test;

[0033] An output unit, which is used to obtain the data set of the shoreline to be evaluated and input it into the multi-level structure model to obtain the evaluation results of the coastline update potential;

[0034] Among them, the output unit further includes:

[0035] An evaluation unit division module, which is used to divide several evaluation units according to the data set of the shoreline to be evaluated;

[0036] A weighted score calculation module, which is used to perform weighted scoring on several evaluation units based on the linear weighted method and the multi-level structure model to obtain a score value;

[0037] An evaluation result output module, which is used to output the evaluation results of the coastline update potential according to the score value.

[0038] Compared with the prior art, the beneficial effects of the method for evaluating the coastline update potential in the embodiments of the present invention are as follows:

[0039] By clarifying the coastline type of the coastline to be evaluated and constructing a dedicated update potential evaluation model based on this type, this targeted approach enables the evaluation model to fit the actual situation of various coastlines, improving the accuracy of the coastline update potential evaluation; the adaptability evaluation method of the present invention can fully consider the coastline differences, formulate evaluation indicators and weights that meet the actual development needs of different coastline types, improving the accuracy of the coastline update potential evaluation; the present invention constructs an update potential evaluation model including a target layer, a criterion layer, and an index layer, which has hierarchy and systematicness compared with the single or simple evaluation system in the prior art; the present invention performs weighted scoring on the evaluation units through the linear weighting method and the multi-level structure model, fully considering the importance of each evaluation indicator in the evaluation, highlighting the influence of key factors on the coastline update potential through reasonable weight allocation, so that the scoring results can more accurately reflect the actual potential of the coastline. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flowchart of the method for evaluating the coastline update potential provided by the embodiments of the present invention;

[0041] Figure 2 is another flowchart of the method for evaluating the coastline update potential provided by the embodiments of the present invention;

[0042] Figure 3 is a schematic diagram of the device for evaluating the coastline update potential provided by the embodiments of the present invention;

[0043] In the figure, 10 is the coastline classification unit; 20 is the model construction unit; 30 is the model processing unit; 40 is the output unit; 41 is the evaluation unit division module; 42 is the weighted scoring calculation module; 43 is the weighted scoring calculation module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] The following describes exemplary embodiments of the present invention with reference to the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0045] As Figure 1-2 shown, in an alternative embodiment of the present invention, the method for evaluating the coastline update potential includes:

[0046] S10. Construct a shoreline type database according to relevant standard guidelines, and determine the shoreline type of the shoreline to be evaluated based on the shoreline type database;

[0047] S20. Construct an update potential evaluation model according to the shoreline type of the shoreline to be evaluated. The evaluation model includes an objective layer, a criterion layer, and an index layer. The objective layer is the output of the shoreline update potential evaluation. The criterion layer includes shoreline utilization status data, planning situation data, and supporting degree data. The index layer is the shoreline evaluation index system;

[0048] S30. Construct the update potential evaluation model into a multi-level structure model according to the analytic hierarchy process (AHP). Use the Delphi method to score the evaluation indicators to obtain index scores, normalize the index scores, and conduct a consistency test;

[0049] S40. Obtain the dataset of the shoreline to be evaluated and input it into the multi-level structure model. Through the multi-level structure model, output the evaluation result of the shoreline update potential. The specific steps are as follows:

[0050] S41. Divide the dataset of the shoreline to be evaluated into several evaluation units;

[0051] S42. Conduct weighted scoring on the several evaluation units based on the linear weighted method and the multi-level structure model to obtain a score value;

[0052] S43. Output the evaluation result of the shoreline update potential according to the score value.

[0053] Among them, the shoreline type refers to different types divided according to factors such as the natural characteristics and development and utilization status of the shoreline; the update potential evaluation model refers to a structured model used to evaluate the update potential of the shoreline, including an objective layer, a criterion layer, and an index layer. The objective layer clarifies the output direction of the evaluation, the criterion layer determines the main aspects of the evaluation, and the index layer details specific evaluation indicators. The analytic hierarchy process (AHP) refers to a decision-making analysis method that decomposes complex problems into multiple levels and determines the relative importance of elements at each level through pairwise comparisons. In the present invention, it is used to construct a multi-level structure model and determine the weights of each evaluation indicator.

[0054] Specifically, a specific embodiment is further described in combination with Table 1-9:

[0055] Using the ARCGIS platform, based on the idea of overall land and sea planning, combined with existing standards and specifications and practical experience, integrating coastline update conditions and demand data, a coastline update potential evaluation index system is constructed from five aspects: current shoreline utilization data, shoreline utilization benefit data, shoreline ownership data, planning data, and supporting improvement degree data. The analytic hierarchy process and the Delphi method are combined to assign weights to the evaluation indicators, thus forming a complete set of evaluation methods for coastline update potential. The steps are as follows:

[0056] Step 1: Refer to relevant standard guidelines and existing research methods for port shorelines to determine the types of artificial shorelines to be evaluated;

[0057] Referring to the "Technical Regulations for National Shoreline Survey and Revision", the utilization types of artificial shorelines include fishery shorelines, industrial shorelines, transportation shorelines, tourism and entertainment shorelines, land reclamation project shorelines, special shorelines, and other utilization types. Considering the domestic coastline utilization situation, the current shoreline utilization mainly includes fishery shorelines, industrial shorelines, transportation shorelines, and tourism and entertainment shorelines. Therefore, the research objects of this invention are defined as fishery shorelines, industrial shorelines, transportation shorelines, and tourism and entertainment shorelines.

[0058] Step 2: Construct an evaluation model for the update potential of artificial shorelines, and construct an evaluation index system for the update potential of shorelines from three aspects: shoreline status, planning, and supporting degree;

[0059] Referring to the artificial shoreline quality evaluation factors in the "Technical Specification for Shoreline Quality Evaluation", combined with the land urban renewal method and management practice, an evaluation index system for the update potential of shorelines is constructed from three aspects: shoreline status, planning, and supporting degree. Referring to the analytic hierarchy process, a multi-level analysis structure model is established.

[0060] Among them, the first layer is the target layer, which is the evaluation of the update potential of shorelines.

[0061] The second layer is the criterion layer, including current shoreline utilization data, planning data, and supporting degree data.

[0062] The third layer is the index layer, including thirteen indicators.

[0063] Among them, the current status of the shoreline mainly evaluates the current situation of shoreline utilization, shoreline utilization efficiency, and ownership situation. The current situation of shoreline utilization is characterized by two indicators: the situation of shoreline utilization and the input intensity per unit shoreline. The shoreline utilization efficiency mainly evaluates the benefit of shoreline use and is characterized by two indicators: the output intensity per unit shoreline and the abundance of shoreline resources. Among them, the output intensity per unit shoreline is calculated according to different utilization types of fishery shoreline, industrial shoreline, transportation shoreline, and tourism and entertainment shoreline. The fishery shoreline is characterized by the fishing intensity per unit shoreline, the industrial shoreline is characterized by the tax intensity per unit shoreline, the transportation shoreline is characterized by the port throughput per unit shoreline, and the tourism and entertainment shoreline is characterized by the number of tourists received per unit shoreline. In terms of the abundance of shoreline resource utilization, the fishery shoreline is assigned values according to the fishing port level gradient, the industrial shoreline is assigned values according to the gradient of the water demand of the adjacent port industry type, the transportation shoreline is divided according to the port capacity utilization rate, and the tourism and entertainment shoreline is assigned values according to the accessibility of the hydrophilic space and the degree of sea enclosure behavior; the ownership situation mainly evaluates the ownership and illegal situation, and is characterized by two indicators: the degree of completion of procedures and the illegal situation;

[0064] The data of the planning situation mainly evaluates the data of the overall land use planning and the special coastal zone planning, and is characterized by three indicators: the data of the sea use space planning on the seaward side of the shoreline, the compliance of the coastal building setback line on the landward side of the shoreline, and the occupation of the marine control line;

[0065] The data of the supporting degree mainly considers the feasibility of the update and is characterized by four indicators: the improvement degree of the sea use supporting facilities, the development and utilization level of the rear land area, the traffic accessibility, and the facility maintenance degree.

[0066] Step 3: Model processing and normalization test. According to the analytic hierarchy process, a multi-level structure model is formed, the Delphi method is used to score the indicators, and finally the results are normalized and consistency tested.

[0067] First, establish a classification hierarchy structure, and apply the analytic hierarchy process to establish a hierarchical model, as shown in Table 1.

[0068] Table 1 Classification hierarchy structure

[0069]

[0070]

[0071] Secondly, construct the judgment matrix. According to the importance scale, construct the pairwise comparison judgment matrix A as shown in Equation 1. Construct the judgment matrix layer by layer according to the criterion layer and the index layer. Invite 8 experts and scholars in related fields such as urban and rural planning, ecology, oceanography, land resource management, environmental science, agricultural remote sensing, and physical geography for scientific evaluation. Use the weighted average method for processing to judge the importance degree of each evaluation index. Assign values from 1 to 9 to the relative importance degree according to the Saaty scale table to form the judgment matrix, and use the weighted average method for processing to obtain the quantization value of each index in the judgment matrix. The judgment matrix is presented in tabular form.

[0072]

[0073] Table 2 Criterion Layer Judgment Matrix

[0074] Criterion layer Current utilization status B1 Planning situation B2 Supporting degree data B3 Current utilization status B1 1 3 5 Planning situation B2 0.33 1 1.67 Degree of supporting perfection data B3 0.2 0.60 1

[0075] Table 3 Index Layer B1 Judgment Matrix

[0076]

[0077] Table 4 Index Layer B2 Judgment Matrix

[0078]

[0079] Table 5 Index Layer B3 Judgment Matrix

[0080]

[0081] Next, normalize the results and conduct a consistency test to obtain the weights of each index. Use spss software to calculate the maximum eigenvalue and the random consistency RI value of the judgment matrix of each level of influencing factors for the coastline renewal potential evaluation. The calculation results are shown in the table, and all pass the consistency test.

[0082] Table 6 Consistency Test Table

[0083] Weight vector Maximum eigenvalue Random consistency RI value W(A-B) 2.997 0.520 W(B1) 5.995 1.260 W(B2) 3.004 0.52 W(B3) 4.158 0.89

[0084] The consistency test is passed, and the final weight results are shown in Table 7.

[0085] Table 7 Weight Result Table

[0086]

[0087] Step 4: Determine the quantization standard of the potential evaluation index.

[0088] For the indicators that can be directly standardized, such as the input intensity per unit shoreline and the output intensity per unit shoreline, directly perform negative standardization on the data results. The negative index standardization calculation method is as follows:

[0089] Negative index: Ei = (Pmax - Pi) / (Pmax - Pmin) * 5

[0090] For indicators that are difficult to quantify, such as utilization status, planning data, ownership status, and supporting degree data, combined with the characteristics of the coastline, the non - quantitative indicators are quantified in the form of gradient scores, and the processing standards for quantifying indicator factors are established. See Table 1 for details.

[0091] Table 8 Quantification Standards for Evaluation Indicators of Artificial Shoreline Renewal Potential

[0092]

[0093]

[0094] Step 5: Construction and acquisition of the basic evaluation dataset

[0095] First, download the coastline image data of the study area from the Geospatial Data Cloud. Try to select remote sensing image data with a time range from March to October, cloud cover less than 5%, and good image quality. Second, collect the artificial shoreline data from the latest published coastline resurvey results or the latest coastline survey results. The coastline types and development and utilization types are classified according to the "Technical Specifications for Coastline Survey (DB37 / T 3588 - 2019)". The land survey, utilization status, and supporting degree data of the shoreline are obtained from relevant competent departments, statistical yearbooks, and sea - related plans. The shoreline planning data is collected from the planning department.

[0096] Second, construct the basic evaluation dataset, quantitatively process the data obtained from data collection and on - site investigation, and after processing, use digital processing methods to form vector data. The vector data adopts the shapefile format or the filegeodatabase format, and the data is checked through topology.

[0097] Step 6: Division of coastline evaluation units

[0098] Combined with remote sensing image data and the surveyed shoreline types, divide the basic evaluation units according to shoreline types, terrain features, and development and utilization conditions. The length is generally not less than 100m.

[0099] Step 7: Use the linear weighted method to score the coastline renewal potential, grade the score of the coastline renewal potential, and propose renewal strategies.

[0100] First, based on the evaluation units, use the linear weighted method to score the unit renewal potential

[0101]

[0102] Among them, Fj represents the shore segment update potential score of the j-th shore segment, n represents the total number of factors, Ci represents the index score of the i-th factor, and Li represents the weight of the i-th factor.

[0103] Secondly, based on the potential score, the potential is classified and graded according to the classification standard of the artificial shoreline update potential level. The potential score is 0-2 points, and the shoreline update potential level is low potential, and the update orientation is mainly to maintain the status quo; the potential score is 2-3 points, and the shoreline update potential level is medium potential, and the update orientation is mainly to moderately improve; the potential score is 3-5 points, and the shoreline update potential level is high potential, and the update orientation is mainly to gradually guide; the potential score is 4-5 points, and the shoreline update potential level is high potential, and the update orientation is mainly to gradually guide, and the update orientation is mainly to give priority to updating.

[0104] Table 9 Classification standard of artificial shoreline update potential level

[0105] Potential score Potential grading Update orientation 0 - 2 points Low potential Maintain the current situation 2 - 3 points Medium potential Moderate improvement 3 - 4 points High potential Gradual guidance 4 - 5 points Extremely high potential Priority update

[0106] In the embodiment of the present invention, the present invention constructs a special update potential evaluation model according to the shoreline type by clarifying the shoreline type of the shoreline to be evaluated. This targeted method enables the evaluation model to fit the actual situation of various shorelines and improves the accuracy of the shoreline update potential evaluation; the adaptability evaluation method of the present invention can fully consider the shoreline differences, formulate evaluation indicators and weights that meet the actual development needs for different shoreline types, and improve the accuracy of the shoreline update potential evaluation; the present invention constructs an update potential evaluation model including a target layer, a criterion layer and an index layer, which has hierarchy and systematicness compared with the single or simple evaluation system in the prior art; the present invention uses the linear weighted method and the multi-level structure model to perform weighted scoring on the evaluation unit, fully considering the importance of each evaluation index in the evaluation, and highlighting the influence of key factors on the shoreline update potential by reasonably allocating weights, so that the scoring result can more accurately reflect the actual potential of the shoreline.

[0107] In an alternative embodiment of the present invention, the criterion layer includes shoreline utilization status data, planning situation data, and supporting degree data.

[0108] Among them, the current status of shoreline utilization data reflects the actual development and utilization of the current coastline, covering the degree, method and efficiency of development and utilization. For example, the proportion of the length of the developed and utilized coastline to the total length of the coastline directly reflects the degree of use of the coastline. For example, if the total length of a certain section of coastline is 10 kilometers, of which the length of the coastline that has been developed and utilized for ports, docks, aquaculture and other purposes is 6 kilometers, then the utilization rate of this section of coastline is 60%. The current status of shoreline utilization data is an important basis for evaluating the potential for coastline renewal. By analyzing the utilization rate and development intensity of the coastline, it can be determined whether there is room for further development of the coastline. Examining the diversity of shoreline utilization methods helps to find out whether the functional layout of the coastline is reasonable and whether there is the possibility of optimization and adjustment, thereby providing direction for shoreline renewal.

[0109] Among them, planning compliance refers to the degree of fit between the current status of the development and utilization of the coastline and relevant plans (such as marine functional zoning, urban planning, port planning, etc.), ensuring that the development activities of the coastline are carried out within the framework of legality and compliance. The supporting degree data reflects the improvement of infrastructure and public services around the coastline, including transportation, water and electricity, communications, environmental protection facilities and other aspects.

[0110] In the embodiment of the present invention, the three elements of the shoreline utilization status data, planning situation data, and supporting degree data in the criterion layer are interrelated and influence each other, and together constitute the core framework of the shoreline renewal potential evaluation. The shoreline utilization status data provides a realistic basis for the evaluation, reflecting the current level of development and utilization of the shoreline and the existing problems; the planning situation data ensures that the shoreline development activities are carried out on a legal and compliant track, and guides the shoreline to develop in a scientific and reasonable direction; the supporting degree data provides the necessary guarantee and support for the development and utilization of the shoreline, affecting the development efficiency and sustainable development capacity of the shoreline. By comprehensively considering these three factors, the renewal potential of the coastline can be comprehensively and systematically evaluated.

[0111] In an optional embodiment of the present invention, the specific steps of constructing the multi-level structure model in S30 are:

[0112] S31, establishing a hierarchical structure model according to the target layer, the criterion layer, and the indicator layer;

[0113] S32, constructing a judgment matrix step by step according to the criterion layer and the indicator layer;

[0114] S33, establishing an expert scoring database and using a weighted average method to summarize the expert scoring database's judgments on the evaluation indicators to generate a number of final judgment matrices;

[0115] S34, normalizing each of the final judgment matrices, calculating the weight of each level and calculating the quantitative value of each evaluation index in the final judgment matrix.

[0116] Specifically, in S33, experts in related fields, such as marine planning experts, port engineering experts, environmental assessment experts, etc., are invited to form an expert team. Each expert scores the relative importance of the indicators in the judgment matrix according to their professional knowledge and experience, establishes an expert scoring database, records the scoring results of each expert, and uses the weighted average method to determine the weight of each expert according to factors such as the authority and experience of the expert. The expert scores are summarized to generate several final judgment matrices. Considering the opinions of multiple experts comprehensively reduces the influence of the subjective judgment of a single expert, improves the accuracy and reliability of the judgment matrix, and the weighted average method can fully reflect the important role of different experts in the evaluation, making the evaluation result more scientific.

[0117] Specifically, in S34, normalization processing: normalize each column of the final judgment matrix, that is, divide each element in the column by the sum of the elements in the column so that the sum of each column of elements is 1. Calculate the weight: average each row element of the normalized judgment matrix to obtain the weight of the corresponding indicator in that row. For example, if a row has three elements, which are 0.3, 0.4, and 0.3 after normalization, then the weight of the corresponding indicator in that row is (0.3 + 0. + 0.3) / 3 = 0.33.

[0118] In the embodiment of the present invention, based on the constructed multi-level structure model, the complex shoreline update potential evaluation problem can be decomposed into multiple levels. By quantifying the relative importance between indicators, the weights and quantization values of each indicator are calculated, making the evaluation result more accurate; at the same time, the model has strong flexibility and adaptability and can be adjusted and optimized according to different shoreline types and evaluation requirements.

[0119] In an alternative embodiment of the present invention, the method includes:

[0120] For the evaluation indicators that can be directly standardized, perform negative normalization processing on the quantization values of the evaluation indicators.

[0121] Specifically, for indicators such as unit shoreline input intensity and unit shoreline output intensity that can directly obtain data results, a negative normalization processing method is adopted. Negative indicators mean that the smaller the indicator value, the better. For example, the lower the unit shoreline input intensity, the higher the resource utilization efficiency may be; if the unit shoreline output intensity is considered from a negative perspective (such as the output intensity of certain pollutants), the smaller its value, the smaller the environmental pressure. The calculation method for normalizing negative indicators is as follows:

[0122] Negative indicator: E i = (Pmax - Pi) / (Pmax - Pmin)*5

[0123] For difficult-to-quantify indicators such as utilization situation, planning situation data, ownership situation, and supporting degree data, combined with the characteristics of the coastline, the non-quantifiable indicators are quantified in the form of gradient scores, and a processing standard for quantifying indicator factors is established.

[0124] In an alternative embodiment of the present invention, the method further includes:

[0125] Propose an update strategy based on the evaluation result of the coastline update potential.

[0126] Specifically, differential strategies are formulated for different potential levels. For example, for the coastline with high update potential, large-scale and comprehensive development and utilization can be given priority. For instance, if a certain section of the coastline has good conditions for port construction, superior geographical location, and complete surrounding supporting facilities, a modern port logistics park can be planned and constructed. Combining advanced port facilities and an efficient logistics management system can improve the cargo handling capacity and transportation efficiency, and build it into a regional logistics hub. For the coastline with medium potential, partial transformation and optimization can be carried out. For example, upgrade and transform the existing fishing port, improve the port's infrastructure and operating conditions, and enhance the sheltering capacity of the fishing port and the fishing production efficiency. At the same time, combined with the characteristics of the fishing port, develop industries such as fishery entertainment and seafood processing to promote the diversified development of the fishing port economy. For the coastline with low update potential, ecological protection should be the main focus. For example, delimit the ecological protection red line, strictly restrict development and construction activities. Strengthen the monitoring and protection of the coastline ecosystem to maintain ecological balance. A nature reserve or a marine park can be established to protect rare and endangered species and the marine ecological environment.

[0127] In an alternative embodiment of the present invention, the method of dividing several evaluation units in S41 is:

[0128] Divide according to the remote sensing image data and the surveyed coastline types, in accordance with the coastline type, terrain features, and development and utilization situation. The length of a single coastline evaluation unit is greater than 100m.

[0129] Specifically, remote sensing images can provide large-scale and high-resolution coastline information, clearly showing the morphology, distribution of the coastline, and the characteristics of the surrounding environment. Through the analysis of remote sensing images, basic data such as the geometric shape, length, and width of the coastline can be obtained, and the types of ground objects around the coastline, such as buildings, vegetation, and water areas, can also be identified. For example, using high-resolution satellite remote sensing images, it can be accurately determined whether there are port facilities, industrial factories, or nature reserves on a certain section of the coastline, providing an intuitive basis for the division of evaluation units.

[0130] According to another aspect of the present invention, there is provided a coastline update potential evaluation device. When using the coastline update potential evaluation device for evaluation, it includes the coastline update potential evaluation method described in the above claims.

[0131] As shown in Figure 3 the figure, the coastline update potential evaluation device includes:

[0132] A shoreline classification unit 10 for determining the shoreline type of the shoreline to be evaluated;

[0133] A model construction unit 20 for constructing an update potential evaluation model according to the shoreline type of the shoreline to be evaluated. The evaluation model includes a target layer, a criterion layer, and an index layer. The target layer is the output of the shoreline update potential evaluation. The criterion layer includes shoreline utilization status data, planning situation data, and supporting degree data. The index layer is the shoreline evaluation index system;

[0134] A model processing unit 30 for constructing the update potential evaluation model into a multi-level structure model according to the analytic hierarchy process, scoring the evaluation indexes by using the Delphi method to obtain index scores, normalizing the index scores and performing consistency tests;

[0135] An output unit 40 for obtaining the data set of the shoreline to be evaluated and inputting it into the multi-level structure model to obtain the shoreline update potential evaluation result;

[0136] Among them, the output unit 40 further includes:

[0137] An evaluation unit division module 41 for dividing a number of evaluation units according to the data set of the shoreline to be evaluated;

[0138] A weighted score calculation module 42 for performing weighted scoring on a number of the evaluation units based on the linear weighted method and the multi-level structure model to obtain a score value;

[0139] An evaluation result output module 43 for outputting the shoreline update potential evaluation result according to the score value.

[0140] The present invention determines the shoreline type of the shoreline to be evaluated, and constructs a dedicated update potential evaluation model based on this type. This targeted approach enables the evaluation model to fit the actual situations of various shorelines, improving the accuracy of the shoreline update potential evaluation. The adaptability evaluation method of the present invention can fully consider shoreline differences, formulate evaluation indicators and weights that meet the actual development needs of different shoreline types, and improve the accuracy of the shoreline update potential evaluation. The present invention constructs an update potential evaluation model including an objective layer, a criterion layer and an index layer, which has hierarchy and systematicness compared with the single or simple evaluation system in the prior art. The present invention performs weighted scoring on the evaluation units through the linear weighting method and the multi-level structure model, fully considering the importance of each evaluation index in the evaluation. By reasonably allocating weights, the influence of key factors on the shoreline update potential is highlighted, making the scoring result more accurately reflect the actual potential of the shoreline.

[0141] It should be understood that various forms of the processes shown above can be used, with steps reordered, added or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in the present invention can be achieved, and no limitation is made herein.

[0142] The above specific embodiments do not constitute a limitation to the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for evaluating the potential of coastline update, characterized in that The method includes: S10. Construct a shoreline type database according to relevant standard guidelines, and judge the shoreline type of the shoreline to be evaluated based on the shoreline type database; S20. Construct an update potential evaluation model according to the shoreline type of the shoreline to be evaluated. The evaluation model includes an objective layer, a criterion layer, and an index layer. The objective layer is the output of the shoreline update potential evaluation. The criterion layer includes shoreline utilization status data, planning situation data, and supporting degree data. The index layer is the shoreline evaluation index system; S30. Construct the update potential evaluation model into a multi-level structure model according to the analytic hierarchy process, score the evaluation indicators by using the Delphi method to obtain index scores, normalize the index scores and conduct a consistency test; S40. Obtain the data set of the shoreline to be evaluated and input it into the multi-level structure model. Through the multi-level structure model, output the shoreline update potential evaluation result. The specific steps are as follows: S41. Divide a number of evaluation units according to the data set of the shoreline to be evaluated; S42. Conduct weighted scoring on a number of the evaluation units based on the linear weighted method and the multi-level structure model to obtain a score value; S43. Output the shoreline update potential evaluation result according to the score value.

2. The coastline update potential evaluation method according to claim 1, wherein The criterion layer includes shoreline utilization status data, planning situation data, and supporting degree data.

3. The coastline update potential evaluation method according to claim 1, characterized in that The shoreline evaluation index system is constructed according to comprehensive shoreline update conditions and demand data, shoreline utilization status data, shoreline utilization benefit data, shoreline ownership situation data, planning situation data, and supporting perfection degree data.

4. The coastline update potential evaluation method according to claim 1, wherein The specific steps for constructing the multi-level structure model in S30 are: S31. Establish a hierarchical structure model according to the objective layer, the criterion layer, and the index layer; S32. Gradually construct a judgment matrix according to the criterion layer and the index layer; S33. Establish an expert scoring library and use the weighted average method to summarize the judgments of the expert scoring library for the evaluation indicators to generate a number of final judgment matrices; S34. Conduct normalization processing on each of the final judgment matrices, calculate the weights of each level and calculate the quantization value of each evaluation indicator in the final judgment matrix.

5. The coastline update potential evaluation method according to claim 4, wherein The method includes: For evaluation indicators that can be directly standardized, conduct negative standardization processing on the quantization values of the evaluation indicators.

6. The coastline update potential evaluation method according to claim 1, wherein The method further includes: Propose an update strategy according to the shoreline update potential evaluation result.

7. The coastline update potential evaluation method according to claim 1, wherein The method for dividing a number of evaluation units in S41 is: Divide according to remote sensing image data and the surveyed shoreline type according to the shoreline type, terrain features, and development and utilization conditions. The length of a single shoreline evaluation unit is greater than 100m.

8. An apparatus for evaluating the potential of coastline update, characterized in that, When using the shoreline update potential evaluation device for evaluation, it includes the shoreline update potential evaluation method according to any one of claims 1-7.

9. The coastline update potential evaluation device according to claim 8, characterized in that The device includes: A shoreline classification unit, which constructs a shoreline type database according to relevant standard guidelines and judges the shoreline type of the shoreline to be evaluated based on the shoreline type database; A model construction unit, which is used to construct an update potential evaluation model according to the shoreline type of the shoreline to be evaluated. The evaluation model includes an objective layer, a criterion layer, and an index layer. The objective layer is the output of the shoreline update potential evaluation. The criterion layer includes shoreline utilization status data, planning situation data, and supporting degree data. The index layer is the shoreline evaluation index system; A model processing unit, which is used to construct the update potential evaluation model into a multi-level structure model according to the analytic hierarchy process, score the evaluation indexes by using the Delphi method to obtain index scores, normalize the index scores and conduct consistency tests; An output unit, which obtains the data set of the shoreline to be evaluated and inputs it into the multi-level structure model, and outputs the evaluation result of the shoreline update potential through the multi-level structure model; Among them, the output unit further includes: An evaluation unit division module, which is used to divide a number of evaluation units according to the data set of the shoreline to be evaluated; A weighted score calculation module, which is used to conduct weighted scoring on a number of the evaluation units based on the linear weighting method and the multi-level structure model to obtain a score value; An evaluation result output module, which is used to output the evaluation result of the shoreline update potential according to the score value.

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