A method for evaluating the suitability of fish habitats

Abstract

This invention discloses a method for evaluating the suitability of fish habitats, belonging to the technical field of fish habitat suitability evaluation. The method includes: determining a target area; collecting conditional data of the target area to obtain regional conditional data; splitting and merging the target area according to the regional conditional data to obtain various evaluation areas; collecting regional evaluation analysis data based on the evaluation area information; analyzing the regional evaluation analysis data to obtain supplementary collection items and suitability values ​​corresponding to each evaluation area; generating corresponding evaluation curves based on the supplementary collection items and suitability values; collecting data from the target area according to the supplementary collection items to obtain supplementary collection data; inputting the supplementary collection data into the evaluation curve for matching to obtain a representative suitability value; classifying each evaluation area into equivalent areas to obtain equivalent areas; setting suitability correction values ​​corresponding to each equivalent area; and setting evaluation vectors based on the suitability correction values ​​corresponding to each equivalent area.

Description

Technical Field

[0001] This invention belongs to the technical field of fish habitat suitability assessment, specifically a method for assessing fish habitat suitability. Background Technology

[0002] With increasing human activities, fish habitats are being increasingly disturbed and damaged, leading to declining fish populations and threatening ecological balance. Therefore, the protection and restoration of fish habitats has become particularly important. Habitat suitability assessment is a crucial tool for fish conservation and management, capable of predicting the survival and reproductive potential of fish in different environments and providing a scientific basis for developing effective conservation measures.

[0003] However, existing methods for assessing fish habitat suitability have several shortcomings. On the one hand, traditional methods are mostly based on qualitative descriptions, lacking scientific rigor and objectivity, and thus failing to accurately reflect the true condition of fish habitats. On the other hand, while some quantitative assessment methods can provide more precise results, they are often complex to operate and costly, hindering practical application and widespread adoption. Furthermore, existing assessment methods often focus only on a single environmental factor, neglecting the complexity and diversity of fish habitats. In reality, fish habitats are influenced by multiple factors, including water quality, water temperature, food supply, water flow velocity, and substrate type. These factors are interconnected and interact with each other, jointly affecting fish survival and reproduction. Therefore, an assessment method that comprehensively considers multiple environmental factors is needed to more fully evaluate the suitability of fish habitats.

[0004] Based on this, the present invention provides a method for evaluating the suitability of fish habitats. Summary of the Invention

[0005] To address the problems of the above-mentioned solutions, this invention provides a method for evaluating the suitability of fish habitats.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A method for evaluating the suitability of fish habitats, the method comprising:

[0008] Step 1: Determine the target area, and collect conditional data from the target area according to the preset collection items to obtain the regional conditional data corresponding to the target area;

[0009] Step 2: Based on the regional condition data, the target region is split and merged to obtain each evaluation region;

[0010] Furthermore, methods for splitting and merging target regions based on regional condition data include:

[0011] A regional model corresponding to the target region is established based on the regional condition data; the regional condition data is then marked accordingly in the regional model.

[0012] The regional model is divided into several unit regions; each unit region is merged and evaluated, and the unit regions that meet the unit merging requirements are merged to obtain the evaluation region.

[0013] Furthermore, the methods for dividing unit regions include:

[0014] Analyze the terrain information in the regional model to obtain various terrain classification zones; identify the regional condition data corresponding to each location in the spatial region of the regional model, and set the location features of each location based on the obtained regional condition data;

[0015] Merge adjacent locations with the same location characteristics until no more locations can be merged within the region model, and mark each merged region as a unit region.

[0016] Furthermore, the methods for setting up terrain classification zones include:

[0017] Step SA1: Establish a foreignization analysis model. The expression for the foreignization analysis model is: In the formula: s is the input data; the output data is the alienated value, which includes 1 or 0;

[0018] Step SA2: Identify terrain information for each location in the regional model; determine the initial location;

[0019] Step SA3: Integrate the terrain information of the initial location and the adjacent terrain locations into a terrain information set; analyze the terrain information set through a differentiation analysis model to obtain the differentiation value of each terrain location adjacent to the initial location;

[0020] Step SA4: Merge adjacent terrain locations with a distortion value of 0 with the initial location to obtain the initial region;

[0021] Step SA5: Mark the various terrain locations at the initial region boundary as the initial location; integrate the terrain information of the initial location and the terrain locations adjacent to it into a terrain information set; analyze the terrain information set through a differentiation analysis model to obtain the differentiation values ​​of the terrain locations adjacent to the initial location;

[0022] Step SA6: Merge adjacent terrain locations with a distortion value of 0 with the initial region to obtain a new initial region;

[0023] Step SA7: Repeat steps SA5 to SA6 until there are no adjacent terrains with a heterogeneity value of 0, and mark the current initial area as a terrain classification area;

[0024] Step SA7: Return to step SA2 until there is no initial position.

[0025] Furthermore, methods for merging and evaluating various unit areas include:

[0026] Establish a merger assessment model; the expression for the merger assessment model is as follows: In the formula: h is the input data;

[0027] By analyzing adjacent unit regions using a merge analysis model, unit regions that meet the merge requirements are merged to obtain the evaluation region.

[0028] Step 3: Obtain assessment area information corresponding to each assessment area, and collect regional assessment analysis data based on the assessment area information; analyze the regional assessment analysis data corresponding to each assessment area to obtain the supplementary collection items and suitability values ​​corresponding to each assessment area.

[0029] Step 4: Generate the corresponding assessment curve based on the supplementary data collection items and suitability values ​​for each assessment area;

[0030] Furthermore, the methods for generating the evaluation curve include:

[0031] Obtain regional assessment and analysis data to determine various supplementary data for the assessment area, establish a coordinate system with the supplementary data on the horizontal axis and the suitability representative value on the vertical axis; adjust the horizontal axis according to each supplementary data.

[0032] Obtain the fitness values ​​corresponding to each supplementary data collection, labeled as SYi, i = 1, 2, ..., n, where n is a positive integer; according to the formula Calculate the suitability representative value for each supplementary data collection; where: DSY is the suitability representative value;

[0033] Based on the suitability representative values ​​of each supplementary data collection, corresponding coordinate points are generated in the coordinate system, and corresponding evaluation curves are generated based on each coordinate point.

[0034] Step 5: Collect data from the target area according to each supplementary collection item to obtain the supplementary collection data corresponding to each assessment area; input the supplementary collection data into the assessment curve for matching to obtain the suitability representative value corresponding to each assessment area;

[0035] Step Six: Classify each assessment area into equivalent categories to obtain each equivalent area; set the suitability correction value corresponding to each equivalent area;

[0036] Furthermore, the method for setting the suitability correction value includes:

[0037] Obtain the representative fitness values ​​for each equivalent region and the region volume corresponding to each representative fitness value;

[0038] According to the formula Calculate the corresponding suitability correction value;

[0039] In the formula: QA is the fitness correction value; j represents the assessment area corresponding to the equivalent area; Vj is the corresponding area volume; DSY is the corresponding fitness representative value.

[0040] Step 7: Set the corresponding evaluation vector according to the suitability correction value of each equivalent region, and substitute each suitability correction value as an element value into the preset vector template; evaluate the suitability of the target region according to the evaluation vector to obtain the corresponding suitability evaluation data.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] This invention comprehensively considers various environmental factors, such as water quality, food sources, water temperature, water depth, current velocity, and substrate, to accurately assess the suitability of fish habitats. This helps to more accurately understand the actual condition of fish habitats, providing a scientific basis for fish conservation and ecological restoration. It allows for the timely identification of habitat problems and deficiencies, enabling corresponding measures to be taken for improvement. This helps to create a more suitable living environment for fish, promote the stability and growth of their populations, and maintain the balance of the ecosystem. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0045] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0046] like Figure 1 As shown, a method for evaluating the suitability of fish habitats includes:

[0047] Step 1: Determine the target area, collect conditional data from the target area according to the preset collection items, and obtain the corresponding regional conditional data for the target area;

[0048] The target area refers to the fish habitat area that needs to be assessed for suitability.

[0049] The data collection items are set based on various factors that affect the assessment of fish habitat, such as water quality, watershed topography, flow velocity, temperature, season, and other relevant data. The specific settings are configured by professionals.

[0050] Step 2: Split and merge the target area based on the regional condition data to obtain each evaluation area;

[0051] Methods for splitting and merging target regions based on regional condition data include:

[0052] A regional model corresponding to the target area is established based on regional condition data, and a 3D display model is established based on 3D visualization technology. Relevant data such as water quality, watershed topography, and flow velocity at each location in the regional condition data are marked in the regional model accordingly. Ideally, the model should be adjusted based on the corresponding data to make it more intuitive.

[0053] Based on the principle of data similarity, the regional model is divided into several unit regions, that is, a continuous region with the same data for each factor is a unit region, and the division is carried out in three dimensions.

[0054] The unit areas are merged and evaluated, and the unit areas that meet the unit merging requirements are merged to obtain the evaluation area.

[0055] The methods for dividing unit regions include:

[0056] The terrain information in the regional model is analyzed to obtain various terrain classification zones; the regional condition data corresponding to each location in the regional model space is identified, and the location features of each location are set according to the obtained regional condition data. The location features are composed of the data corresponding to each collection item, where the terrain information is replaced by the terrain classification zone to which it belongs.

[0057] Merge adjacent locations with the same location characteristics until no more locations can be merged within the region model, and mark the merged regions of each location as unit regions.

[0058] The methods for setting up terrain classification zones include:

[0059] Step SA1: Obtain a large amount of potential terrain information and establish a corresponding alienation analysis model based on the obtained terrain information. The alienation analysis model is based on the isolated forest algorithm, which considers terrain adjacent to the location and having the same impact on fish as normal terrain, and vice versa as abnormal terrain, i.e., the corresponding terrain information is anomalous data; the expression is: In the formula: s is the input data, that is, the set of terrain information, that is, the set of terrain information of a certain location and the set of terrain information of neighboring places. The output data is the alienated value, which includes 1 or 0.

[0060] Step SA2: Identify the terrain information of each terrain location in the region model, referring to the bottom terrain; select any terrain location as the initial location, which is a terrain location outside the terrain classification area;

[0061] Step SA3: Integrate the terrain information of the initial location and the adjacent terrain locations into a terrain information set; analyze the terrain information set through a differentiation analysis model to obtain the differentiation value of each terrain location adjacent to the initial location;

[0062] Step SA4: Merge adjacent terrain locations with a distortion value of 0 with the initial location to obtain the initial region;

[0063] Step SA5: Mark the various terrain locations at the boundary of the initial region as the initial location, which belongs to the initial region; integrate the terrain information of the initial location and the terrain locations adjacent to it into a terrain information set, excluding the initial region to avoid duplicate analysis; analyze the terrain information set through a differentiation analysis model to obtain the differentiation values ​​of the terrain locations adjacent to the initial location.

[0064] Step SA6: Merge adjacent terrain locations with a distortion value of 0 with the initial region to obtain a new initial region;

[0065] Step SA7: Repeat steps SA5 to SA6 until there are no adjacent terrains with a heterogeneity value of 0, and mark the current initial area as a terrain classification area;

[0066] Step SA7: Return to step SA2 until there is no initial position.

[0067] Methods for merging and evaluating different unit areas include:

[0068] A large amount of historical fish habitat assessment data was acquired. Based on this data, it was determined which data ranges could be considered identical for fish habitat and suitability assessments, meaning they had the same impact on fish within that data range. A merged assessment model was then established based on this. The model was used to analyze whether the unit characteristics corresponding to two unit areas could be equivalent, i.e., whether the merged assessment requirements were met. The unit characteristics are the original location characteristics. The expression is: In the formula: h is the input data, that is, the unit features that need to be compared and analyzed;

[0069] The adjacent unit regions are analyzed by a merge analysis model, and the unit regions that meet the merge requirements are merged to obtain the evaluation region.

[0070] Step 3: Obtain information for each assessment area, i.e., the unit characteristic data corresponding to the respective unit area; based on the assessment area information, obtain a large amount of historical suitability assessment data under the same conditions, i.e., various suitability assessments that fish habitats with the same impact as the assessment area may have, and mark the corresponding data as regional assessment analysis data; organize the regional assessment analysis data corresponding to each assessment area to obtain supplementary collection items and various suitability values ​​for each assessment area; the suitability values ​​are set according to the various possible suitability assessments, converted using a percentage system to form the corresponding scores; the supplementary collection items are obtained by comparing the regional assessment analysis data with the assessment area information. Because the regional assessment data is retrieved based on the assessment area information, other factors in the regional assessment data are the same as those in the assessment area information, but there are still some factors that are not included in the assessment area information, which are also the reasons and influencing factors for the differences in suitability assessments. Therefore, supplementary collection items are set according to the corresponding influencing factors, such as fish species, fish quantity, etc.

[0071] Step 4: Generate the corresponding assessment curve based on the supplementary data collection items and suitability values ​​for each assessment area;

[0072] That is, calculate the representative value of suitability under the same factor by averaging the suitability values ​​of each factor; use the different data corresponding to each different supplementary collection item as the horizontal axis and the representative value of suitability as the vertical axis, input the corresponding representative value of suitability into the coordinate system, and connect them to form the evaluation curve.

[0073] Step 5: Collect data from the target area according to each supplementary collection item to obtain the supplementary collection data corresponding to each assessment area; input the supplementary collection data into the assessment curve for matching to obtain the suitability representative value corresponding to each assessment area.

[0074] Step Six: Classify each assessment area into equivalent regions; that is, group assessment areas that are identical but not adjacent into one equivalent region, as adjacency is a criterion when merging unit regions. This can be done using a merge assessment model; assessment areas that meet the merging requirements can be grouped into one category, becoming one equivalent region. Adjust the value based on the suitability representative value corresponding to each equivalent region to obtain a suitability correction value for each equivalent region. Further adjustments are made using the different suitability representative values ​​of the equivalent regions to obtain a more accurate suitability value for that region, reducing errors caused by various external factors.

[0075] The methods for setting the suitability correction value include:

[0076] Obtain the representative fitness values ​​for each equivalent region and the region volume corresponding to each representative fitness value;

[0077] According to the formula Calculate the corresponding suitability correction value;

[0078] In the formula: QA is the fitness correction value; j represents the assessment area corresponding to the equivalent area; Vj is the corresponding area volume; DSY is the corresponding fitness representative value.

[0079] Step 7: Set the corresponding evaluation vector according to the suitability correction value of each equivalent region, and substitute each suitability correction value as an element value into the preset vector template; evaluate the suitability of the target region according to the evaluation vector to obtain the corresponding suitability evaluation data.

[0080] The above method simulates various possible evaluation vectors based on historical data of the target area, sets corresponding suitability evaluation data for each evaluation vector, and integrates them into a training set; a corresponding suitability evaluation model is established based on neural networks such as CNN or DNN, trained using the established training set, and analyzed using the successfully trained suitability evaluation model to obtain the corresponding suitability evaluation data.

[0081] The above formulas are all numerical calculations after removing dimensions. The formulas are obtained by software simulation based on a large amount of data and are closest to the real situation. The preset parameters and preset thresholds in the formulas are set by those skilled in the art according to the actual situation or obtained by simulation based on a large amount of data.

[0082] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for evaluating the suitability of fish habitats, characterized in that, The methods include: Step 1: Determine the target area, and collect conditional data from the target area according to the preset collection items to obtain the regional conditional data corresponding to the target area; Step 2: Based on the regional condition data, the target region is split and merged to obtain each evaluation region; Step 3: Obtain assessment area information corresponding to each assessment area, and collect regional assessment analysis data based on the assessment area information; analyze the regional assessment analysis data corresponding to each assessment area to obtain the supplementary collection items and suitability values ​​corresponding to each assessment area. Step 4: Generate the corresponding assessment curve based on the supplementary data collection items and suitability values ​​for each assessment area; Step 5: Collect data from the target area according to each supplementary collection item to obtain the supplementary collection data corresponding to each assessment area; input the supplementary collection data into the assessment curve for matching to obtain the suitability representative value corresponding to each assessment area; Step Six: Classify each assessment area into equivalent categories to obtain each equivalent area; set the suitability correction value corresponding to each equivalent area; Step 7: Set the corresponding evaluation vector according to the suitability correction value of each equivalent region, and evaluate the suitability of the target region according to the evaluation vector to obtain the corresponding suitability evaluation data.

2. The method for evaluating the suitability of fish habitats according to claim 1, characterized in that, Methods for splitting and merging target regions based on regional condition data include: A regional model corresponding to the target region is established based on the regional condition data; the regional condition data is then marked accordingly in the regional model. The regional model is divided into several unit regions; each unit region is merged and evaluated, and the unit regions that meet the unit merging requirements are merged to obtain the evaluation region.

3. The method for evaluating the suitability of fish habitats according to claim 2, characterized in that, The methods for dividing unit regions include: Analyze the terrain information in the regional model to obtain various terrain classification zones; identify the regional condition data corresponding to each location in the spatial region of the regional model, and set the location features of each location based on the obtained regional condition data; Merge adjacent locations with the same location characteristics until no more locations can be merged within the region model, and mark each merged region as a unit region.

4. The method for evaluating the suitability of fish habitats according to claim 3, characterized in that, The methods for setting up terrain classification zones include: Step SA1: Establish a foreignization analysis model. The expression for the foreignization analysis model is: In the formula: s is the input data; the output data is the alienated value, which includes 1 or 0; Step SA2: Identify terrain information for each location in the regional model; determine the initial location; Step SA3: Integrate the terrain information of the initial location and the adjacent terrain locations into a terrain information set; analyze the terrain information set through a differentiation analysis model to obtain the differentiation value of each terrain location adjacent to the initial location; Step SA4: Merge adjacent terrain locations with a distortion value of 0 with the initial location to obtain the initial region; Step SA5: Mark the various terrain locations at the initial region boundary as the initial location; integrate the terrain information of the initial location and the terrain locations adjacent to it into a terrain information set; analyze the terrain information set through a differentiation analysis model to obtain the differentiation values ​​of the terrain locations adjacent to the initial location; Step SA6: Merge adjacent terrain locations with a distortion value of 0 with the initial region to obtain a new initial region; Step SA7: Repeat steps SA5 to SA6 until there are no adjacent terrains with a heterogeneity value of 0, and mark the current initial area as a terrain classification area; Step SA7: Return to step SA2 until there is no initial position.

5. The method for evaluating the suitability of fish habitats according to claim 2, characterized in that, Methods for merging and evaluating different unit areas include: Establish a merger assessment model; the expression for the merger assessment model is as follows: In the formula: h is the input data; By analyzing adjacent unit regions using a merge analysis model, unit regions that meet the merge requirements are merged to obtain the evaluation region.

6. The method for evaluating the suitability of fish habitats according to claim 1, characterized in that, Methods for generating evaluation curves include: Obtain regional assessment and analysis data to determine various supplementary data for the assessment area, establish a coordinate system with the supplementary data on the horizontal axis and the suitability representative value on the vertical axis; adjust the horizontal axis according to each supplementary data. Obtain the fitness values ​​corresponding to each supplementary data collection, labeled as SYi, i = 1, 2, ..., n, where n is a positive integer; according to the formula... Calculate the suitability representative value for each supplementary data collection; where: DSY is the suitability representative value; Based on the suitability representative values ​​of each supplementary data collection, corresponding coordinate points are generated in the coordinate system, and corresponding evaluation curves are generated based on each coordinate point.

7. The method for evaluating the suitability of fish habitats according to claim 1, characterized in that, The methods for setting the suitability correction value include: Obtain the representative fitness values ​​for each equivalent region and the region volume corresponding to each representative fitness value; According to the formula Calculate the corresponding suitability correction value; In the formula: QA is the fitness correction value; j represents the assessment area corresponding to the equivalent area; Vj is the corresponding area volume; DSY is the corresponding fitness representative value.

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