Ecosystem cultural service supply and demand assessment method, system, device and storage medium

Abstract

The present application provides an ecosystem cultural service supply and demand evaluation method, system, device and storage medium, and relates to the field of ecosystem cultural service evaluation. The ecosystem cultural service supply and demand evaluation method comprises the following steps: collecting social media photo and comment data, determining environmental and socio-economic factors affecting the distribution of ecosystem cultural services and constructing an environmental factor layer; drawing a spatial distribution map of CES supply and demand and performing spatial correlation analysis to identify supply and demand hotspots and coldspots. The supply and demand of the ecosystem cultural service are calculated by using the GeoDa software to obtain a bivariate clustering map. The spatial correlation between supply and demand is analyzed to identify the matching and mismatching conditions of the spatial distribution of supply and demand. The present application solves the problem that the existing evaluation method is difficult to measure the distribution of supply and demand in space, and due to the limitation of time and labor cost, it is difficult to obtain multi-time data, and therefore is not suitable for the analysis of dynamic changes of supply and demand relationship.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecosystem cultural service evaluation, in particular to an ecosystem cultural service supply and demand evaluation method, system, device and storage medium. BACKGROUND

[0002] Ecosystem cultural service (CES) is an important part of ecosystem service, and the subjectivity and intangibility of CES make its quantitative evaluation very difficult. The existing related research on the analysis of the spatial distribution of CES focuses more on the supply side analysis, and there is little comprehensive research on the supply and demand relationship. In the process of rapid urbanization, people's demand for CES is growing, and the imbalance between supply and demand is becoming increasingly prominent, which requires us to pay attention to the balance between supply and demand. The evaluation and analysis methods of the supply and demand relationship of ecosystem cultural service mainly include expert rating, proxy indicators, survey-based analysis and modeling, but the above evaluation methods are often difficult to measure the spatial distribution of supply and demand, and due to the limitation of time and labor cost, it is difficult to obtain multi-time data, so it is not suitable for the analysis of the dynamic change of the supply and demand relationship. SUMMARY

[0003] (I) Technical problems solved

[0004] In view of the defects of the prior art, the present application provides an ecosystem cultural service supply and demand evaluation method, system, device and storage medium, which solves the problem that the existing evaluation method is often difficult to measure the spatial distribution of supply and demand, and due to the limitation of time and labor cost, it is difficult to obtain multi-time data, so it is not suitable for the analysis of the dynamic change of the supply and demand relationship.

[0005] (II) Technical solutions

[0006] In order to achieve the above purpose, the present application is realized by the following technical solutions:

[0007] In the first aspect, an ecosystem cultural service supply and demand evaluation method is provided, comprising:

[0008] Collect and process social media data, determine environmental and socio-economic factors affecting the distribution of ecosystem cultural services and build an environmental factor layer, wherein the social media data includes photo data and comment data;

[0009] Draw the spatial distribution map of ecosystem cultural service supply and demand respectively and perform spatial correlation analysis to obtain the spatial distribution map and spatial clustering distribution map of ecosystem cultural service supply and demand, and identify the hot spots and cold spots of the spatial clustering distribution map of ecosystem cultural service supply and demand;

[0010] A bivariate spatial autocorrelation analysis was performed on the distribution map of supply and demand of ecosystem cultural services to obtain a bivariate spatial clustering map of supply and demand.

[0011] By comparing and analyzing the spatial distribution differences between the supply and demand of ecosystem cultural services, the spatial balance between the supply and demand of ecosystem cultural services and the dependence between supply and demand are determined.

[0012] Preferably, the photo data comes from social media platforms where geotagged photos are publicly available, including but not limited to Flickr, TwoSteps, and SixLegged. The data can be obtained by writing code in Python or by using web crawler software.

[0013] The review data comes from travel websites that provide access to attractions and their ratings, including but not limited to Dianping, Meituan, and Mafengwo, with each attraction having a POI rating of 1-5 points.

[0014] Preferably, the environmental factor layer includes:

[0015] Environmental data: hydrology, distance to roads, landscape diversity index, NDVI, elevation, habitat quality, land use type, and distance to attractions;

[0016] Socioeconomic data: population density, nighttime light data.

[0017] Preferably, the step of drawing spatial distribution maps of ecosystem cultural service supply and demand and performing spatial correlation analysis to obtain spatial distribution maps and spatial cluster distribution maps of ecosystem cultural service supply and demand, and identifying hotspots and cold spots in the spatial cluster distribution maps of ecosystem cultural service supply and demand, specifically includes:

[0018] The processed environmental factor layer and coordinate point data were imported into MaxEnt software for calculation. The parameters were set to run 10 times, and 25% was used as the training factor to generate a supply space distribution map. The mean AUC was greater than 0.9, and the model ran well.

[0019] The supply spatial distribution map in .asc format was imported into ArcGIS for grid-based statistical analysis and spatial autocorrelation analysis to identify hotspots and cold spots in the supply of ecosystem cultural services. A 300*300 pixel grid was created using the fishing net tool, and the grid was cropped according to the boundary of the study area. The average supply within each grid cell was calculated using the zonal statistical tool. The global Moran index and local Moran index of ecosystem cultural service supply were calculated to obtain a global Moran index report and a spatial cluster distribution map of ecosystem cultural service supply and demand.

[0020] Preferably, the calculation of the global Moran index for the supply of cultural services in the ecosystem specifically involves:

[0021]

[0022] in, n is the total number of spatial units, y i and y j Let represent the attribute values ​​of the i-th and j-th spatial units, respectively. w is the mean of all spatial unit attribute values. ij This represents the spatial weight value.

[0023] Preferably, the calculation of the local Moran index of cultural service supply in the ecosystem specifically involves:

[0024]

[0025] Among them, w ij Here, I represents the spatial weight value, n is the total number of regions in the study area, and I represents the spatial weight value. i This represents the local Moran index of the i-th region.

[0026] Preferably, the step of performing bivariate spatial autocorrelation analysis on the distribution map of supply and demand of ecosystem cultural services to obtain a bivariate spatial clustering map of supply and demand specifically includes:

[0027] The distribution map of supply and demand of ecosystem cultural services was calculated using GeoDa software. The grid layer with average supply and demand fields was imported into GeoDa software to calculate the bivariate Moran index and the bivariate local Moran index, generating a bivariate spatial clustering map of supply and demand.

[0028] Secondly, an ecosystem cultural services supply and demand assessment system is provided for implementing the above-described method, characterized by comprising:

[0029] The image processing module is used to collect and process social media data;

[0030] The environmental factor processing module is used to identify the environmental and socioeconomic factors that affect the distribution of ecosystem cultural services and to construct an environmental factor layer.

[0031] The mapping module is used to draw spatial distribution maps of the supply and demand of ecosystem cultural services and perform spatial correlation analysis to obtain spatial distribution maps and spatial cluster distribution maps of the supply and demand of ecosystem cultural services, and to identify hot spots and cold spots in the spatial cluster distribution maps of the supply and demand of ecosystem cultural services.

[0032] The analysis module is used to perform bivariate spatial autocorrelation analysis on the distribution map of the supply and demand of ecosystem cultural services to obtain a bivariate spatial cluster map of supply and demand; and is used to determine the spatial balance state of the supply and demand of ecosystem cultural services and the dependence of supply and demand by comparing the differences in the spatial distribution of the supply and demand of ecosystem cultural services and analyzing the correlation.

[0033] Thirdly, a device is provided, comprising:

[0034] One or more processors;

[0035] Memory, used to store one or more programs.

[0036] When the one or more programs are executed by the one or more processors, the one or more processors execute the ecosystem cultural service supply and demand assessment method.

[0037] Fourthly, a computer-readable storage medium is provided that stores a computer program, which, when executed by a processor, implements the aforementioned method for assessing the supply and demand of ecosystem cultural services.

[0038] (III) Beneficial Effects

[0039] (1) The method, system, equipment, and storage medium for assessing the supply and demand of ecosystem cultural services provided in this invention offer a convenient and quick method for analyzing the spatial distribution of supply and demand for ecosystem cultural services, solving the difficulties in assessing the spatial distribution of supply and demand in CES (Cultural Services Economy). Social media data (photos and comments) are all publicly available, allowing for the acquisition of large amounts of data from different time periods in a short time. This method is universally applicable to any region where social media data is available and is not limited by scale, thus solving the problem that existing assessment methods often struggle to measure the spatial distribution of supply and demand, and are difficult to acquire data over long periods due to time and manpower constraints, making them unsuitable for analyzing dynamic changes in supply and demand relationships.

[0040] (2) The ecological system cultural service supply and demand assessment method, system, equipment and storage medium of the present invention provide a CES supply and demand analysis method that can draw a spatial distribution map of supply and demand to identify the cold and hot spots of CES supply and demand; and analyze the correlation between the two through a bivariate spatial autocorrelation tool to identify the type and spatial distribution of supply and demand mismatch, thereby providing corresponding guidance for the spatial optimization of supply and demand in tourist destinations. Attached Figure Description

[0041] Figure 1 This is a flowchart of the method of the present invention;

[0042] Figure 2This is a spatial distribution map of the supply of ecosystem cultural services in the implementation of this invention;

[0043] Figure 3 This is a spatial distribution map of the supply of ecosystem cultural services in the implementation of this invention, calculated using a grid system.

[0044] Figure 4 This is a local Moran cluster distribution map of the ecosystem cultural service supply in the implementation of this invention;

[0045] Figure 5 This is a global Moran report for the supply of ecosystem cultural services in the implementation of this invention;

[0046] Figure 6 This is a spatial distribution map of the ecosystem cultural service demand in the implementation of this invention;

[0047] Figure 7 This is a spatial distribution map of ecosystem cultural service demand in the implementation of this invention, calculated using a grid system.

[0048] Figure 8 This is a local Moran cluster distribution map of the ecosystem cultural service demand in the implementation of this invention;

[0049] Figure 9 This is a global Moran report representing the ecosystem cultural service needs in the implementation of this invention;

[0050] Figure 10 This is a bivariate spatial clustering map of the supply and demand of ecosystem cultural services in the implementation of this invention. Detailed Implementation

[0051] The technical solutions in the embodiments of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0052] Example

[0053] like Figures 1-10 As shown in the figure, this embodiment of the invention provides a method for assessing the supply and demand of ecosystem cultural services, including the following steps:

[0054] Step 1: Collect and process social media data to identify environmental and socioeconomic factors influencing the distribution of ecosystem cultural services and construct an environmental factor layer. The social media data includes photo data and comment data.

[0055] Step 2: Draw spatial distribution maps of the supply and demand of ecosystem cultural services and conduct spatial correlation analysis to obtain spatial distribution maps and spatial cluster distribution maps of the supply and demand of ecosystem cultural services, and identify hot spots and cold spots in the spatial cluster distribution maps of the supply and demand of ecosystem cultural services.

[0056] Step 3: Perform bivariate spatial autocorrelation analysis on the distribution map of supply and demand of ecosystem cultural services to obtain a bivariate spatial clustering map of supply and demand;

[0057] Step 4: By comparing and analyzing the spatial distribution differences between the supply and demand of ecosystem cultural services, determine the spatial balance between the supply and demand of ecosystem cultural services and the dependence between supply and demand.

[0058] Furthermore, the photo data comes from social media platforms where geotagged photos are publicly available, including but not limited to Flickr, TwoSteps, and Six Feet. The data can be obtained by writing code in Python or by using web crawler software.

[0059] The review data comes from travel websites that provide access to attractions and their ratings, including but not limited to Dianping, Meituan, and Mafengwo, with each attraction having a POI rating of 1-5 points.

[0060] Specifically, the social media photo data was obtained from the Six Feet platform, crawling photos uploaded between July 2021 and July 2022, located in Suzhou City and categorized as "hiking." Photos within the Xishan boundary area were extracted, yielding 41,418 raw photos with latitude and longitude coordinates. Random sampling was performed on these photos, resulting in a sample of 2,000. These samples were then filtered according to the rule that each user could select no more than two photos, and the content of the photos had to be related to CES. The data was then imported into ArcGIS to remove irrelevant points, ultimately resulting in a usable sample size of 10, which served as the photo dataset. The review and POI data came from Dianping, crawling data on attractions and ratings within the Xishan scenic area. A total of 32 attractions and ratings that could provide CES information were obtained, and the latitude and longitude coordinates of these attractions were obtained using the Tencent Location Service platform.

[0061] Furthermore, the environmental factor data includes environmental data such as hydrology, distance to roads, landscape diversity index, NDVI, elevation, habitat quality, land use type, and distance to attractions; and socioeconomic data such as population density and nighttime light index. The distances to roads and attractions are calculated using Euclidean distance in ArcMap 10.6, habitat quality is calculated using the habitat quality module in InVEST 3.9.2, and the landscape diversity index is calculated using Fragstats 4.2. All of these, along with the environmental factors, are directly downloadable open-source data. The environmental factor data can be adjusted according to the type of CES being studied and the attributes of the study area. For example, for recreational value, the factor influencing its CES expression can be adjusted to the distance to recreational venues. Additionally, other relevant environmental factor layers, such as slope, aspect, and land cover, can be added as needed, and the data is not limited to the examples provided in this invention.

[0062] Furthermore, a supply distribution map was drawn using MaxEnt. Photo point data and environmental factor data were input into MaxEnt 3.4.4 for calculation, with parameters set to run 10 times and a 25% training factor. Figure 2 As shown, a spatial distribution map of the supply was obtained. The results show that the average AUC value after 10 runs is greater than 0.9, indicating that the model runs well and has high reliability.

[0063] The generated supply spatial distribution map in ASCII format is imported into ArcMap 10.6 for spatial correlation analysis. First, the image is cropped using the boundaries of the study area, such as... Figure 3 As shown, a spatial distribution map of the supply in the Xishan Scenic Area was obtained. A 300*300 pixel grid was created using a netting tool, cropped according to the boundaries of the Xishan Scenic Area. Then, a zonal statistical tool was used to calculate the average supply within each grid cell. Finally, the global and local Moran's indices were used to calculate spatial correlation, as shown in the figure. Figure 4 , Figure 5 As shown, a Moran's Index report on supply and a spatial clustering distribution map of demand are generated.

[0064] The Moran index ranges between -1 and +1. When the Moran index is greater than 0, it indicates that the data shows a positive spatial correlation, and the larger the value, the more obvious the spatial correlation. When the Moran index is less than 0, it indicates that the data shows a negative spatial correlation, and the smaller the value, the greater the spatial difference.

[0065] Since the Moran's index is greater than 0, the closer its value is to 1, the higher the spatial correlation. The calculation results show that the Moran's index for supply is 0.76, indicating a significant positive correlation in supply space. Hotspots (high-high clustering) and cold spots (low-low clustering) in supply are identified based on the cluster distribution map.

[0066] Furthermore, the global Moran index for the supply of cultural services in the ecosystem is calculated as follows:

[0067]

[0068] in, n is the total number of spatial units, y i and y j Let represent the attribute values ​​of the i-th and j-th spatial units, respectively. w is the mean of all spatial unit attribute values. ij This represents the spatial weight value.

[0069] The local Moran index for the supply of cultural services in an ecosystem is calculated as follows:

[0070]

[0071] Among them, w ij Here, I represents the spatial weight value, n is the total number of regions in the study area, and I represents the spatial weight value. i This represents the local Moran index of the i-th region.

[0072] A demand distribution map was drawn using ArcMap 10.6. Points of Interest (PoIs) and rating data were imported into ArcMap 10.6. The kernel density tool was used to calculate the kernel density of PoIs based on the rating field, and the map was then cropped using scenic area boundaries. Figure 5 As shown, a spatial distribution map of the demand for Xishan Scenic Area is obtained.

[0073] Using the fishing net tool in ArcMap 10.6, a 300*300 pixel grid was created, cropped according to the boundaries of the Xishan Scenic Area. Then, a zoning statistical tool was used to perform zoning statistical analysis on the spatial distribution map of demand in the Xishan Scenic Area, calculating the average demand within each grid cell. Spatial correlation was calculated using global and local Moran's indices, such as... Figure 5 , Figure 6 As shown, the Moran's Index report and spatial clustering diagram for the generated requirements are displayed.

[0074] Since the Moran's index is greater than 0, the closer its value is to 1, the higher the spatial correlation. The calculation results show that the Moran's index for demand is 0.92, indicating a significant positive correlation. Based on the cluster distribution map, hotspots (high-high clustering) and coldspots (low-low clustering) of demand are identified.

[0075] Furthermore, the distribution map of ecosystem cultural service supply and demand was calculated using GeoDa software. Specifically, a grid layer containing supply and demand value fields was input into GeoDa software, and spatial correlation was calculated using bivariate Moran's index and bivariate local Moran's index tools, such as... Figure 7 ,Figure 8 and Figure 9 As shown, a bivariate spatial clustering map of supply and demand is generated.

[0076] Since the Moran index is greater than 0, the closer its value is to 1, the higher its spatial correlation. The calculation results show that the Moran index for the two variables of supply and demand is 0.278, indicating a low correlation between supply and demand, and a significant imbalance between supply and demand in the Xishan Scenic Area.

[0077] Step 4 specifically involves using a spatial clustering map to identify supply-demand mismatch areas and calculating the area of ​​each mismatch type. High-low clustering represents "high-low spatial mismatch" (high demand - low supply) areas, while low-high clustering represents "low-high spatial mismatch" (low demand - high supply) areas. The statistical results show that "high-low spatial mismatch" areas account for 5.6%, and "low-high spatial mismatch" areas account for 16.0%.

[0078] Another embodiment of the present invention provides an ecosystem cultural services supply and demand assessment system for performing the methods described in the above embodiments, including:

[0079] The image processing module is used to collect and process social media data;

[0080] The environmental factor processing module is used to identify the environmental and socioeconomic factors that affect the distribution of ecosystem cultural services and to construct an environmental factor layer.

[0081] The mapping module is used to draw spatial distribution maps of the supply and demand of ecosystem cultural services and perform spatial correlation analysis to obtain spatial distribution maps and spatial cluster distribution maps of the supply and demand of ecosystem cultural services, and to identify hot spots and cold spots in the spatial cluster distribution maps of the supply and demand of ecosystem cultural services.

[0082] The analysis module is used to perform bivariate spatial autocorrelation analysis on the distribution map of the supply and demand of ecosystem cultural services to obtain a bivariate spatial cluster map of supply and demand; and is used to determine the spatial balance state of the supply and demand of ecosystem cultural services and the dependence of supply and demand by comparing the differences in the spatial distribution of the supply and demand of ecosystem cultural services and analyzing the correlation.

[0083] Embodiments of this application may be provided as methods or computer program products. Therefore, this application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application may be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0084] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0085] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0086] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0087] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method for assessing the supply and demand of cultural services in an ecosystem, characterized in that, include: Collect and process social media data to identify environmental and socioeconomic factors influencing the distribution of ecosystem cultural services and construct an environmental factor layer, wherein the social media data includes photo data and comment data; Spatial distribution maps of the supply and demand of ecosystem cultural services were drawn and spatial correlation analysis was conducted to obtain spatial distribution maps and spatial cluster distribution maps of the supply and demand of ecosystem cultural services, and to identify hot spots and cold spots in the spatial cluster distribution maps of the supply and demand of ecosystem cultural services. A bivariate spatial autocorrelation analysis was performed on the distribution map of supply and demand of ecosystem cultural services to obtain a bivariate spatial clustering map of supply and demand. By comparing and analyzing the spatial distribution differences between the supply and demand of ecosystem cultural services, the spatial balance between the supply and demand of ecosystem cultural services and the dependence between supply and demand are determined. The process involves drawing spatial distribution maps of ecosystem cultural service supply and demand, performing spatial correlation analysis, obtaining spatial distribution maps and spatial cluster distribution maps of ecosystem cultural service supply and demand, and identifying hotspots and cold spots in the spatial cluster distribution maps of ecosystem cultural service supply and demand. Specifically, this includes: The processed environmental factor layer and coordinate point data were imported into MaxEnt software for calculation. The parameters were set to run 10 times, and 25% was used as the training factor to generate a supply space distribution map. The mean AUC was greater than 0.9, and the model ran well. Import the supply spatial distribution map in .asc format into ArcGIS, perform statistical analysis by grid, identify hotspots and cold spots in the supply of ecosystem cultural clothing, and use a fishing net tool to establish a 300-pixel grid. A 300-grid was used, and the grid was cropped according to the boundary of the study area; the average supply within each grid cell was calculated using a zonal statistical tool; the global Moran index and local Moran index of ecosystem cultural service supply were calculated, and a global Moran index report and a spatial clustering distribution map of ecosystem cultural service supply and demand were obtained. The global Moran index for calculating the supply of cultural services in the ecosystem is specifically as follows: in, , where n is the total number of spatial units, y i and y j Let represent the attribute values ​​of the i-th and j-th spatial units, respectively. The mean of all spatial unit attribute values. This represents the spatial weight value; The local Moran index for calculating the supply of cultural services in the ecosystem is specifically as follows: in, Here, I represents the spatial weight value, n is the total number of regions in the study area, and I represents the spatial weight value. i This represents the local Moran index of the i-th region.

2. The method for assessing the supply and demand of ecosystem cultural services according to claim 1, characterized in that: The photo data comes from social media platforms where geotagged photos are publicly available, including but not limited to Flickr, TwoSteps, and Six Feet. The data was obtained by writing code in Python or by using web crawler software. The review data comes from travel websites that provide access to attractions and their ratings, including but not limited to Dianping, Meituan, and Mafengwo, with each attraction having a POI rating of 1-5 points.

3. The method for assessing the supply and demand of ecosystem cultural services according to claim 2, characterized in that: The method of performing bivariate spatial autocorrelation analysis on the distribution map of supply and demand of ecosystem cultural services to obtain a bivariate spatial clustering map of supply and demand specifically includes: The distribution map of supply and demand of ecosystem cultural services was calculated using GeoDa software. The grid layer with average supply and demand fields was imported into GeoDa software to calculate the bivariate Moran index and the bivariate local Moran index, generating a bivariate spatial clustering map of supply and demand.

4. An ecosystem cultural services supply and demand assessment system, used to perform the method as described in any one of claims 1 to 3, characterized in that, include: The image processing module is used to collect and process social media data; The environmental factor processing module is used to identify the environmental and socioeconomic factors that affect the distribution of ecosystem cultural services and to construct an environmental factor layer. The mapping module is used to draw spatial distribution maps of the supply and demand of ecosystem cultural services and perform spatial correlation analysis to obtain spatial distribution maps and spatial cluster distribution maps of the supply and demand of ecosystem cultural services, and to identify hot spots and cold spots in the spatial cluster distribution maps of the supply and demand of ecosystem cultural services. The analysis module is used to perform bivariate spatial autocorrelation analysis on the distribution map of the supply and demand of ecosystem cultural services to obtain a bivariate spatial cluster map of supply and demand; and is used to determine the spatial balance state of the supply and demand of ecosystem cultural services and the dependence of supply and demand by comparing the differences in the spatial distribution of the supply and demand of ecosystem cultural services and analyzing the correlation.

5. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors perform an ecosystem cultural service supply and demand assessment method as described in any one of claims 1-3.

6. A computer-readable storage medium storing a computer program, characterized in that, When executed by the processor, the program implements an ecosystem cultural services supply and demand assessment method as described in any one of claims 1-3.

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