Natural reserve tourism activity management zoning method

Abstract

The invention provides a natural reserve tourism activity management partitioning method, which comprises the following steps: collecting related data information of a natural reserve and carrying out data preprocessing operation to obtain basic data; performing correlation analysis on the basic data through a geographically weighted regression method to obtain a core influence index; grading the core influence indexes according to sensitivity and value attributes, and determining a weight proportion through a weight fusion method; obtaining an area score through the weight ratio and the real terrain score; determining regional function positioning according to the regional score; and determining a space division result by combining a three-dimensional space analysis method based on regional function positioning. According to the method, spatial heterogeneity is captured through geographically weighted regression, a region scoring formula is constructed by combining subjective and objective weight fusion, and a point-line-plane three-dimensional space division method is introduced, so that scientific and flexible region division is realized, and the ecological protection efficiency and the tourist experience quality are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of regional planning, in particular to a method for zoning management of tourism activities in nature reserves. Background Art

[0002] Zoning is the primary means of rationally arranging tourist activity spaces. Its core lies in the rational combination of centralized and decentralized strategies to accommodate specific levels of human activity and ecological protection goals. Currently, there are two common zoning strategies.

[0003] The first is a decentralized strategy, typically used to reduce negative impacts within a small area or a few key regions. This strategy is significantly effective in alleviating biophysical pressures and restoring a relatively balanced ecological environment. However, decentralized strategies are often ineffective in extremely sensitive areas and may even lead to wider ecological damage. In contrast, a centralized strategy confines recreational use to a smaller area and limits negative impacts through strict management.

[0004] However, existing strategies typically use one-time zoning based on historical data and are unable to dynamically respond to changes. Traditional methods often use a weighted summation approach to assess regional development potential, failing to fully consider the nonlinear constraints imposed by ecological sensitivity on development activities and overlooking the significant impact of geographic spatial heterogeneity on regional zoning results. Therefore, it is crucial to design a zoning method for tourism management in nature reserves. Summary of the Invention

[0005] The purpose of this invention is to provide a method for zoning tourism activities in nature reserves, which captures spatial heterogeneity through geographically weighted regression, constructs a regional scoring formula by combining subjective and objective weights, and introduces a three-dimensional spatial division method of points, lines and surfaces to achieve scientific and flexible regional division, and improve ecological protection efficiency and tourist experience quality.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A method for zoning tourism activities in a nature reserve, comprising the following steps:

[0008] Collect relevant data on nature reserves and perform data preprocessing to obtain basic data; relevant data include: ecological environment data, geographic data, tourism data and dynamic data;

[0009] The core impact indicators were obtained by conducting correlation analysis on basic data through geographically weighted regression method;

[0010] Core impact indicators are graded according to their sensitivity and value attributes, and their weights are determined through weight fusion method;

[0011] The regional score is obtained by weight proportion and real terrain score;

[0012] Determine regional functional positioning based on regional scores;

[0013] Based on the regional functional positioning, the spatial division results are determined in combination with the three-dimensional spatial analysis method.

[0014] Optionally, ecological and environmental data include: biodiversity distribution, vegetation cover type, soil sensitivity, water source protection area and wildlife habitat; geographic data include: terrain elevation model, slope aspect and land use status; tourism data include: tourist flow heat map, tourist behavior trajectory and questionnaire survey results; dynamic data include: seasonal climate change, holiday tourist peaks and wildlife activity patterns.

[0015] Optionally, perform correlation analysis on the basic data using the geographically weighted regression method to obtain core impact indicators, including:

[0016] Divide the target area into multiple spatial grid cells;

[0017] The distance decay function is used to determine the spatial weight of the spatial grid cell, and the spatial weight matrix is ​​generated in combination with the spatial position;

[0018] The spatial weights were locally weighted according to the least squares method and combined with tourism data to obtain the raster regression coefficients;

[0019] Obtain local regression coefficients based on the grid regression coefficients and the spatial weight matrix;

[0020] Based on the standard error of the local regression coefficient, the core influencing indicators are determined through significance tests.

[0021] Optionally, the core impact indicators are graded according to their sensitivity and value attributes, and their weights are determined through a weighted fusion method, including:

[0022] The core impact indicators are divided into ecological protection indicators and tourism development indicators according to functional attributes;

[0023] According to ecological fragility, ecological protection indicators are divided into three levels: high sensitivity, medium sensitivity and low sensitivity;

[0024] Tourism development indicators are divided into three levels: high value, medium value and low value according to development potential;

[0025] Construct a judgment matrix based on the comparative scores of experts on ecological protection indicators and tourism development indicators;

[0026] The subjective weight is calculated by judging the eigenvector and the maximum eigenvalue of the matrix;

[0027] The objective weight is calculated by the information entropy after the ecological protection index and tourism development index are graded;

[0028] The subjective weight and objective weight are combined in a ratio of 6:4 to obtain the weight ratio.

[0029] Optionally, a regional score is obtained by weighting and true terrain score, including:

[0030] The real terrain is evaluated based on the landscape data of the real terrain to obtain a real terrain score; the real terrain score includes: terrain complexity score, slope score and landscape score;

[0031] Get the basic score based on the weight ratio and the real terrain score;

[0032] The landscape scores were nonlinearly mapped to obtain the ecological veto score;

[0033] The terrain penalty score is obtained according to the terrain complexity score and the slope score;

[0034] Multiply the base score, ecological veto score, and terrain penalty score to get the regional score.

[0035] Optionally, the basic score is calculated as: Among them, W i is the weight ratio of the i-th core impact indicator, T i is the i-th real terrain score, m is the number of core impact indicators, and n is the number of real terrain scores;

[0036] The calculation formula for the ecological veto score is: Among them, E is the landscape score;

[0037] The terrain penalty score is calculated as follows: Among them, C is the terrain complexity score and S is the slope score.

[0038] Optionally, the regional functional positioning includes: ecological resource conservation, core landscape appreciation, recreational experience interaction and comprehensive service leisure.

[0039] Optionally, based on the regional functional positioning, the spatial division results are determined in combination with a three-dimensional spatial analysis method, including:

[0040] Determine regional functional requirements based on regional functional positioning;

[0041] The target area is determined as a three-dimensional area according to the regional functional requirements; the three-dimensional area includes: point area, line area and surface area;

[0042] Based on data modeling technology, spatial division results are generated according to three-dimensional areas.

[0043] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: The method for tourism activity management zoning in nature reserves provided by the present invention includes: collecting relevant data and information on nature reserves and performing data preprocessing operations to obtain basic data; performing correlation analysis on the basic data through the geographically weighted regression method to obtain core impact indicators; grading the core impact indicators according to sensitivity and value attributes, and determining the weight ratio through the weight fusion method; obtaining regional scores through the weight ratio and the real terrain score; determining the regional functional positioning based on the regional score; and determining the spatial division results based on the regional functional positioning in combination with the three-dimensional spatial analysis method. This method captures spatial heterogeneity through geographically weighted regression, constructs a regional scoring formula by combining subjective and objective weight fusion, and introduces a three-dimensional spatial division method of points, lines, and surfaces, thereby achieving scientific and flexible regional division and improving ecological protection efficiency and tourist experience quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 This is a flow chart of the method for managing zoning of tourism activities in nature reserves of the present invention;

[0046] Figure 2 It is a correlation analysis flow chart of the present invention;

[0047] Figure 3 This is a flowchart of the classification of the core impact indicators of the present invention;

[0048] Figure 4 A flow chart of regional score calculation according to the present invention;

[0049] Figure 5 This is a flow chart of the three-dimensional space analysis of the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0052] like Figure 1 As shown, the present invention provides a method for managing zoning of tourism activities in a nature reserve, comprising the following steps:

[0053] Step 100: Collect relevant data of nature reserves and perform data preprocessing to obtain basic data; the relevant data include: ecological environment data, geographical data, tourism data and dynamic data;

[0054] Specifically, ecological and environmental data include: biodiversity distribution, vegetation cover type, soil sensitivity, water source protection area and wildlife habitat; geographic data include: terrain elevation model, slope aspect and land use status; tourism data include: tourist flow heat map, tourist behavior trajectory and questionnaire survey results; dynamic data include: seasonal climate change, holiday tourist peaks and wildlife activity patterns.

[0055] Step 200: Perform correlation analysis on basic data using the geographically weighted regression method to obtain core impact indicators; the specific steps are as follows: Figure 2 Shown, including:

[0056] Step 201: Divide the target area into a plurality of spatial grid cells;

[0057] Specifically, the size of each grid cell is set according to the management accuracy requirements, and the grid boundaries are aligned with the geographic coordinates. The grid division combines high-resolution remote sensing imagery and field survey data, taking terrain relief, vegetation cover, and existing road networks as references.

[0058] Step 202: Determine the spatial weight of the spatial grid cell using a distance decay function, and generate a spatial weight matrix based on the spatial position;

[0059] Specifically, this embodiment calculates the influence strength of adjacent grids using a Gaussian kernel function and sets the bandwidth (search radius) to 2 km to obtain a symmetrical spatial weight matrix, in which the matrix diagonal values ​​are 0 to eliminate self-influence.

[0060] Step 203: Locally weight the spatial weights using the least squares method and combine them with tourism data to obtain the grid regression coefficients;

[0061] Specifically, the regression model is constructed with tourist flow as the dependent variable and ecological environment data as the independent variable. The spatial weight matrix is ​​diagonalized and the formula β is used to calculate the regression model. i =(X T WX) -1 X T WX gets the grid regression coefficient, where β iis the regression coefficient of the i-th grid, X is the diagonalized independent variable, and W is the spatial weight matrix.

[0062] Step 204: Obtaining local regression coefficients based on the grid regression coefficients and the spatial weight matrix;

[0063] Specifically, the grid regression coefficient is multiplied by the spatial weight matrix and then added to obtain the local regression coefficient.

[0064] Step 205: Based on the standard error of the local regression coefficient, determine the core impact indicator through a significance test.

[0065] Specifically, the standard error is calculated using the t-test method, and the ratio of the local regression coefficient to the standard error is used as the t-value. If an indicator passes the significance test of p < 0.1 in more than 70% of the grids, it is identified as a core impact indicator.

[0066] It should be noted that the construction of a spatial weight matrix accurately quantifies the mutual influence of neighboring areas, and the local regression coefficient reveals the uniqueness of the role of indicators in different geographical units. The significance test combines spatial distribution characteristics to avoid the risk of misjudgment in a single statistical test. Compared with the static zoning method, this embodiment can dynamically respond to geographical changes, such as automatically reducing slope weights in landslide risk areas or temporarily adjusting ecological sensitivity thresholds during migratory bird migration.

[0067] Step 300: Classify the core impact indicators according to their sensitivity and value attributes, and determine the weight ratios through weight fusion method; the specific steps are as follows: Figure 3 Shown, including:

[0068] Step 301: Divide the core impact indicators into ecological protection indicators and tourism development indicators according to functional attributes;

[0069] Specifically, ecological protection indicators include: biodiversity index, soil erosion risk and water source protection level; tourism development indicators include: landscape attractiveness score, ecotourism resource density and road accessibility.

[0070] Step 302: Classify ecological protection indicators into three levels: high sensitivity, medium sensitivity, and low sensitivity according to ecological fragility;

[0071] Specifically, experts grade the ecological protection indicators to reflect ecological fragility. The sensitivity grading of ecological protection indicators in this embodiment is as follows:

[0072] Highly sensitive: Located in ecological protection priority areas (such as endangered species habitats and first-level water source protection areas), ecological damage is irreversible, and the classification standards are: biodiversity index (Shannon-Wiener index) > 2.5, soil erosion risk level ≥ 4 (levels 1 to 5), and water source protection level is first-level protection area or key ecological function area;

[0073] Moderately sensitive: Located in an ecological protection area, ecological damage can be repaired but at a high cost. The classification standards are: biodiversity index (Shannon-Wiener index) is 1.5-2.5, soil erosion risk level is 2-3, and water source protection level is Class II (restricted development);

[0074] Low sensitivity: Located in experimental areas or marginal areas (such as artificial forests and developed areas), the impact of ecological damage is relatively small. The classification standards are: biodiversity index (Shannon-Wiener index) ≤ 1.5, soil erosion risk level ≤ 1, and it does not belong to drinking water source protection areas.

[0075] Step 303: Classify tourism development indicators into three levels: high value, medium value, and low value according to development potential;

[0076] Specifically, the tourism development indicators are evaluated by experts and graded to reflect the intensity of development restrictions. The tourism development indicator value grades of this embodiment are as follows:

[0077] High value: Landscape attractiveness score ≥ 8 (out of 10 points), ecotourism resource density ≥ 30 / km 2 , road accessibility <1000m;

[0078] Medium value: Landscape attractiveness score is 6 to 8 (out of 10 points), and ecotourism resource density is 10 to 30 / km 2 , road accessibility is 1000~3000m;

[0079] Low value: Landscape attractiveness score ≤ 6 (out of 10 points), ecotourism resource density 10-20 / km 2 , road accessibility ≥3000m.

[0080] Step 304: constructing a judgment matrix based on the comparative scores of the experts on the ecological protection indicators and tourism development indicators;

[0081] Specifically, invite more than 10 experts with experience in nature reserves and tourism management to compare the importance of the classified ecological protection indicators and tourism development indicators. For example, ask the experts to answer "How important are the highly sensitive indicators of ecological protection relative to the highly attractive indicators of tourism development?" and make quantitative evaluation scores based on the 1-9 scale (1 means equally important, 9 means absolutely important). Based on the expert scoring results, construct a judgment matrix. This embodiment takes the example that most experts believe that ecological protection clearly takes precedence over development, and generates a judgment matrix. Matrix a ij It represents the importance ratio of the i-th indicator to the j-th indicator.

[0082] Step 305: Calculate the subjective weight by judging the eigenvector and the maximum eigenvalue of the matrix;

[0083] Specifically, the power method is used to iteratively solve the eigenvector and maximum eigenvalue of the judgment matrix, and the preliminary weights of each indicator are obtained after normalization. Then, the preliminary weights of all judgment matrices are weighted and summarized to obtain the subjective weight.

[0084] Step 306: Calculate objective weights based on information entropy after grading ecological protection indicators and tourism development indicators;

[0085] Specifically, the information entropy and difference coefficient of each indicator are calculated, and the ratio of information entropy to difference coefficient is regarded as the objective weight.

[0086] Step 307: The subjective weight and the objective weight are integrated in a ratio of 6:4 to obtain a weight ratio.

[0087] It should be noted that the impact of subjective factors on the zoning scheme was determined through expert experience, and the entropy weight law objectively corrected the weights based on the actual data distribution. The proportional integration of the two not only retains the subjective influence, but also enhances the driving force of objective data, improves the flexibility of zoning, and provides reliable technical support for the sustainable development of nature reserves.

[0088] Step 400: Obtain the regional score by weight proportion and real terrain score; the specific steps are as follows Figure 4 Shown, including:

[0089] Step 401: Evaluate the real terrain based on the landscape data of the real terrain to obtain a real terrain score;

[0090] Specifically, the real terrain score includes: terrain complexity score, slope score, and landscape score. The terrain complexity score reflects the degree of surface undulation and is calculated using the standard deviation of elevation. A higher score indicates greater development difficulty and a higher ecological protection value. The slope score is calculated using a DEM model; a higher score indicates greater development restrictions. The landscape score is determined by experts after comprehensively considering unique landforms, vegetation coverage, and water distribution. The terrain complexity score, slope score, and landscape score are all normalized.

[0091] Step 402: Obtain a basic score based on the weight ratio and the actual terrain score;

[0092] Specifically, the calculation formula for the basic score is:

[0093]

[0094] Among them, W i is the weight ratio of the i-th core impact indicator, T i is the i-th real terrain score, m is the number of core impact indicators, and n is the number of real terrain scores. The base score uses the natural logarithm to compress the contribution of high-scoring intervals and avoid the situation where a single indicator dominates.

[0095] Step 403: Perform nonlinear mapping on the landscape scores to obtain ecological veto scores;

[0096] Specifically, the calculation formula for the ecological veto score is:

[0097]

[0098] Among them, E is the landscape score.

[0099] Step 404: Obtain a terrain penalty score based on the terrain complexity score and the slope score;

[0100] Specifically, the terrain penalty score is calculated as follows:

[0101]

[0102] Among them, C is the terrain complexity score and S is the slope score.

[0103] Step 405: Multiply the basic score, the ecological veto score, and the terrain penalty score to obtain the regional score.

[0104] It's important to note that by compressing the marginal effects of high-scoring ranges, the over-influence of a single indicator is avoided. The Ecological Veto Score strengthens conservation priorities through nonlinear mapping. It also considers the synergistic effects of terrain complexity and slope, making it more tailored to actual management needs.

[0105] Step 500: Determine the regional functional positioning according to the regional score;

[0106] Specifically, regional functional positioning includes: ecological resource conservation, core landscape appreciation, recreational experience and interaction, and comprehensive service and leisure. If the regional score is less than 0.2, the region is determined to have an ecological resource conservation function; if 0.2≤regional score<0.4, the region is determined to have a core landscape appreciation function; if 0.4≤regional score<0.7, the region is determined to have a recreational experience and interaction function; and if the regional score is ≥0.7, the region is determined to have a comprehensive service and leisure function.

[0107] Step 600: Based on the regional functional positioning, the spatial division results are determined in combination with the three-dimensional spatial analysis method. Figure 5 Shown, including:

[0108] Step 601: Determine regional functional requirements based on regional functional positioning;

[0109] Specifically, ecological resource conservation areas will prioritize ecological protection, with some areas open to small-scale, reservation-based eco-tourism and nature education activities. Core landscape viewing areas will host low-intensity tourism activities, open to the public for viewing iconic landscapes, set up fixed viewing platforms and ecological trails for visitors to explore, and moderately develop ecological experience activities. Recreational and interactive areas will host moderate-intensity tourism activities, including outdoor adventures and eco-health tourism. Comprehensive service and leisure areas will provide transportation hubs, commercial facilities, and visitor services, while also supporting nature education activities based on popular science exhibition halls.

[0110] Step 602: Determine the target area as a three-dimensional area according to the regional function requirements; the three-dimensional area includes: point area, line area and surface area;

[0111] Specifically, the core landscape viewing area is defined as a point area, limiting development intensity and protecting the ecological environment. The recreational experience and interaction area is defined as a line area, organizing tourist flows through shortest path analysis to reduce interference with ecologically sensitive areas. The comprehensive service and leisure area is defined as a fusion of point and surface areas, with the surface area representing the range of tourist activities, and the point and surface areas connected by line areas.

[0112] Step 603: Generate a spatial division result based on the three-dimensional area based on data modeling technology.

[0113] The beneficial effects of the present invention are as follows:

[0114] 1) Accurately identify the spatial heterogeneity of ecologically sensitive areas and development potential areas through geographically weighted regression;

[0115] 2) The subjective and objective weight fusion mechanism integrates expert experience and objective data, ensuring that the management strategy is both scientific and socially acceptable;

[0116] 3) Significantly reduce manual decision-making costs through standardized data processing and automated weight calculation processes.

[0117] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0118] The present invention uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for zoning tourism activities in nature reserves, characterized in that: The steps include: Collect relevant data and information about nature reserves and perform data preprocessing operations to obtain basic data; the relevant data and information include: ecological environment data, geographical data, tourism data and dynamic data; The core impact indicators were obtained by conducting correlation analysis on the basic data using the geographically weighted regression method; The core impact indicators are graded according to their sensitivity and value attributes, and their weights are determined through the weight fusion method; Obtaining a regional score by using the weight ratio and the true terrain score; determining the regional functional positioning according to the regional scores; Based on the functional positioning of the region, the spatial division results are determined in combination with the three-dimensional spatial analysis method.

2. The method for managing tourism activities in nature reserves according to claim 1, characterized in that: The ecological and environmental data include: biodiversity distribution, vegetation cover type, soil sensitivity, water source protection area and wildlife habitat; geographic data include: terrain elevation model, slope aspect and land use status; tourism data include: tourist flow heat map, tourist behavior trajectory and questionnaire survey results; dynamic data include: seasonal climate change, holiday tourist peaks and wildlife activity patterns.

3. The method for managing tourism activities in nature reserves according to claim 1, characterized in that: The correlation analysis of the basic data was conducted using the geographically weighted regression method to obtain the core impact indicators, including: Divide the target area into multiple spatial grid cells; The spatial weight of the spatial grid cell is determined by using a distance decay function, and a spatial weight matrix is ​​generated in combination with the spatial position; Locally weighting the spatial weight according to the least square method and obtaining a grid regression coefficient by combining the tourism data; Obtaining a local regression coefficient according to the grid regression coefficient and the spatial weight matrix; Based on the standard error of the local regression coefficient, the core influencing indicator is determined through a significance test.

4. The method for managing tourism activities in nature reserves according to claim 1, characterized in that: The core impact indicators are graded according to their sensitivity and value attributes, and their weights are determined through a weight fusion method, including: Divide the core impact indicators into ecological protection indicators and tourism development indicators according to functional attributes; According to ecological fragility, the ecological protection indicators are divided into three levels: high sensitivity, medium sensitivity and low sensitivity; The tourism development indicators are divided into three levels: high value, medium value and low value according to development potential; Constructing a judgment matrix based on the comparative scores of the experts after grading the ecological protection indicators and the tourism development indicators; Calculating subjective weights by using the eigenvectors and maximum eigenvalues ​​of the judgment matrix; Calculating objective weights through information entropy after grading the ecological protection index and the tourism development index; The subjective weight and the objective weight are fused in a ratio of 6:4 to obtain the weight ratio.

5. The method for managing tourism activities in nature reserves according to claim 1, characterized in that: The regional score is obtained by using the weight ratio and the real terrain score, including: Evaluate the real terrain according to the landscape data of the real terrain to obtain the real terrain score; the real terrain score includes: terrain complexity score, slope score and landscape score; Obtaining a basic score according to the weight ratio and the real terrain score; Performing nonlinear mapping on the landscape scores to obtain ecological veto scores; Obtaining a terrain penalty score according to the terrain complexity score and the slope score; The base score, the ecological veto score, and the terrain penalty score are multiplied to obtain the regional score.

6. The method for managing tourism activities in nature reserves according to claim 5, characterized in that: The calculation formula of the basic score is: Among them, W i is the weight ratio of the i-th core impact indicator, T i is the i-th real terrain score, m is the number of core impact indicators, and n is the number of real terrain scores; The calculation formula of the ecological veto score is: Among them, E is the landscape score; The calculation formula of the terrain penalty score is: Among them, C is the terrain complexity score and S is the slope score.

7. The method for managing tourism activities in nature reserves according to claim 1, characterized in that: The functional positioning of the area includes: ecological resource conservation, core landscape appreciation, recreational experience interaction and comprehensive service leisure.

8. The method for zoning management of tourism activities in nature reserves according to claim 1, characterized in that: Based on the functional positioning of the region, the spatial division results are determined in combination with the three-dimensional spatial analysis method, including: Determine regional functional requirements based on the regional functional positioning; Determine the target area as a three-dimensional area according to the functional requirements of the area; the three-dimensional area includes: a point area, a line area and a surface area; Based on data modeling technology, the space division result is generated according to the three-dimensional area.

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