Method for evaluating recreational utilization suitability of ecological space of urban agglomeration

Abstract

The present application relates to the technical field of ecological space evaluation, in particular to a kind of urban agglomeration ecological space recreation utilization suitability evaluation method, the present application takes urban agglomeration as research area, comprehensively considers the influence of regional natural environment, social and economic factors on ecological space recreation utilization suitability, based on ecological suitability, recreation potential and social and economic support condition three aspects to build evaluation index system, and combined with GIS and entropy weight method empirical evaluation global scale ecological space recreation utilization suitability, by comparing the existing ecological recreation space distribution pattern and recreation utilization suitability level distribution pattern, the future optimization direction of urban agglomeration ecological space recreation utilization pattern is proposed, also provide effective support for land space planning layout.

Description

Technical Field

[0001] This invention relates to the field of ecological space evaluation technology, specifically a method for evaluating the suitability of ecological space recreational use in urban agglomerations. Background Technology

[0002] Urban green spaces provide ecological support, supply, regulation, and cultural services to humankind, serving as a crucial guarantee for residents' physical and mental health. Cities require a sufficient supply of high-quality ecological recreation spaces. Ecological spaces are a vital pillar of urban ecological security, exhibiting sensitivity and vulnerability. Urban agglomerations are characterized by high population density and significant demand for ecological recreation. Therefore, a comprehensive assessment of the suitability of ecological space for recreational use is a fundamental task for optimizing the pattern of ecological space recreational use in urban agglomerations. This helps promote the orderly use of ecological spaces while protecting the ecological environment, expanding the supply of ecological recreation spaces, improving residents' well-being, and ultimately promoting high-quality development of urban agglomerations.

[0003] While existing technologies have conducted some research on the supply and demand of ecological recreation spaces, recreational topography, and the suitability of ecological spaces for recreational use in small- to medium-scale areas such as ecological functional zones and nature reserves, research at the scale of urban agglomerations is relatively limited. Furthermore, existing research often focuses on revealing the suitability level of ecological space recreational use without further comparing and analyzing this suitability level with existing utilization patterns. Therefore, with the further development of urban agglomeration integration, as urban agglomerations gradually become closely interconnected wholes, and with residents' increasing demands for livability and leisure quality, there are still many shortcomings in exploring the overall allocation of regional ecological recreation space layout under the premise of ecological protection from a regional holistic perspective.

[0004] Based on the above reasons, this invention designs a method for evaluating the suitability of ecological space recreational use in urban agglomerations. Taking urban agglomerations as the research area, it comprehensively considers the impact of regional natural environment, social and economic factors on the suitability of ecological space recreational use. Based on three aspects—ecological suitability, recreational potential, and socio-economic support conditions—an evaluation index system is constructed. Furthermore, it combines GIS and the entropy weight method to empirically evaluate the suitability of ecological space recreational use at the whole-area scale. By comparing the existing distribution patterns of ecological recreational spaces with the distribution patterns of recreational use suitability levels, it proposes future optimization directions for the ecological space recreational use patterns of urban agglomerations, balancing ecological protection and rational utilization, and providing effective support for the layout of national land spatial planning. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a method for evaluating the suitability of ecological space recreational use in urban agglomerations. Taking urban agglomerations as the research area, this method comprehensively considers the impact of regional natural environment, social and economic factors on the suitability of ecological space recreational use. Based on three aspects—ecological suitability, recreational potential, and socio-economic support conditions—an evaluation index system is constructed. Furthermore, GIS and the entropy weight method are used to empirically evaluate the suitability of ecological space recreational use at the whole-area scale. By comparing the existing distribution patterns of ecological recreational spaces with the distribution patterns of recreational use suitability levels, this invention proposes future optimization directions for the ecological space recreational use patterns of urban agglomerations, and also provides effective support for the layout of national land spatial planning.

[0006] To achieve the above objectives, the present invention provides a method for evaluating the suitability of recreational use of ecological spaces in urban agglomerations, comprising the following steps:

[0007] S1, Data Collection:

[0008] S1-1, the data includes: digital elevation, normalized vegetation index, soil erosion dataset, water system, land use type, ecological recreation space, crop production and price, primary purification capacity, soil conservation function, precipitation, points of interest, population, road network and gross national income.

[0009] S1-2, the data types include: raster, vector line data, vector point data, and vector polygon data;

[0010] S1-3, the raster data is converted to a spatial resolution of 2500m through resampling to ensure the consistency and accuracy of data processing;

[0011] S1-4. The grid was selected as the basic evaluation unit. The size of the evaluation unit was referenced in relevant literature and the data availability was taken into account. The grid scale was determined to be 2500m×2500m. An effective grid was constructed in the cluster area using ArcGIS.

[0012] S2, Construction of the evaluation index system:

[0013] S2-1, the evaluation index system includes the target layer, the criterion layer, the indicator factor layer and the influence path; the target layer is the evaluation of the adaptability of ecological space recreational use in urban agglomerations, the criterion layer includes ecological suitability, recreational potential and socio-economic support conditions, and ecological suitability includes ecological sensitivity and ecological importance.

[0014] The indicator factor layer includes the following indicators: elevation, slope, normalized difference vegetation index, soil erosion, water buffer zone, area ratio of nature reserves, ecosystem service value, landscape diversity, distribution density of public toilets, distribution density of catering and accommodation facilities, distribution density of cultural and sports facilities, distribution density of scenic spots, accessibility, road network density, and regional GDP.

[0015] S3 uses the entropy weight method to calculate the index weights, obtains standardized weighted scores, and then uses ArcGIS for spatial analysis:

[0016] The calculation steps of the entropy weight method are as follows:

[0017] S3-1, Establish the decision matrix:

[0018] Suppose there are m decision objects that need to be evaluated, and each decision object has n evaluation indicators. Establish a decision matrix as shown in Formula 1:

[0019] Formula 1: ;

[0020] S3-2, Standardization: The evaluation matrix is ​​transformed into a standardized matrix using a linear scaling transformation method to address the homogeneity issue among different indicator values. When the indicator is positive, the standardization formula is shown in Formula 2.

[0021] Formula 2: ;

[0022] When the indicator is negative, its standardized formula is shown in Formula 3:

[0023] Formula 3: ;

[0024] in It is the maximum value of the j-th indicator. It is the value of the j-th index of the i-th sample in the original matrix. It is the value of the j-th indicator of the i-th sample in the standardized data;

[0025] S3-3, Translation: After standardization, some data may contain 0 or negative values. To avoid this, the standardized values ​​are translated, as shown in Formula 4:

[0026] Formula 4: ;

[0027] Where H is the translation magnitude, taken as 0.01. This represents the data of the j-th indicator of the i-th sample in the translated data;

[0028] S3-4, Dimensionless Transformation: Dimensionless transformation is performed using the specific gravity method. Suitable variable substitutions are found to eliminate some or all units in equations involving physical quantities, simplifying calculations. The resulting formula is shown in Formula 5.

[0029] Formula 5: ;

[0030] in, It is the value of the j-th index of the i-th sample in the dimensionless data;

[0031] S3-5, Entropy Calculation: The formula for calculating entropy is shown in Formula Six:

[0032] Formula Six: ;

[0033] The difference coefficient of the j-th indicator is calculated as shown in Formula 7:

[0034] Formula 7: ;

[0035] S3-6, Weight Calculation: The formula for calculating the indicator weight is shown in Formula 8:

[0036] Formula 8: ;

[0037] S3-7, Suitability Score Calculation: Multiply the standardized value by the weight to obtain the comprehensive evaluation score. The calculation formula is shown in Formula Nine:

[0038] Formula Nine: ;

[0039] S4. Overlay analysis was performed using ArcGIS to obtain the results of the suitability of ecological space for recreational use;

[0040] S5. Based on the results of the suitability of ecological space recreational use obtained from ArcGIS in S4, we analyze the impact of the indicator factor layer and its influence path on the criterion layer from the various levels of the evaluation index system in S2-1.

[0041] S6, using the natural breakpoint method, divides the recreational use suitability index into 5 different levels: low suitability, lower suitability, medium suitability, higher suitability, and high suitability;

[0042] The five different levels are based on the area and proportion of the results obtained in S4.

[0043] The calculation methods for each indicator in S2-1 are as follows:

[0044] Elevation: The elevation of the raster cell in which the raster unit is located;

[0045] Slope: Calculated in ArcGIS based on DEM data;

[0046] NDVI: The NDVI of the raster cell in which it is located;

[0047] Soil erosion: A = R·K·L·S·C·P, where A is the soil erosion rate in t / km². 2(Year), R is precipitation erosion force, K is soil erosion force, L and S are the surface slope length and slope, respectively, C is vegetation cover factor, and P is soil and water conservation measure factor;

[0048] Water buffer zone: the distance of each grid cell from the water area;

[0049] Percentage of area in nature reserves: The proportion of the area of ​​nature reserves in the total land area;

[0050] Ecosystem service value: Based on a dynamic improved equivalent factor method using the value per unit area, the formula is as follows: ;in, is the proportion of area occupied by landscape type i; m is the number of landscape types;

[0051] Distribution density of public toilets, catering and accommodation facilities, cultural and sports facilities, and scenic spots: Based on the 15-minute community life circle theory, the distribution density is calculated as the number of relevant facilities within a radius of 1km, that is, within and around the ecological space grid unit within a 15-minute walking distance, divided by the grid area based on POI data.

[0052] Transportation accessibility: In the formula Let be the accessibility index of the i-th grid; The shortest commute time from [location] to [location] is calculated using point distance in ArcGIS, assuming a vehicle speed of 26.63 km / h for each grid cell; Pi is the population of the i-th grid cell; and TP is the total population of the Pearl River Delta urban agglomeration.

[0053] Road network density: the density of expressways, national highways, provincial highways, county roads, township roads, and urban expressways;

[0054] Regional GDP: The GDP of a grid cell.

[0055] The higher the ecological sensitivity in the ecological suitability layer of S2-1, the lower the suitability for recreational use of ecological space; ecological importance characterizes the superiority of natural ecosystems, and the higher the value, the greater the suitability for recreational use of ecological space.

[0056] Compared with existing technologies, this invention takes urban agglomerations as the research area and comprehensively considers the impact of regional natural environment, social and economic factors on the suitability of ecological space recreation. It constructs an evaluation index system based on three aspects: ecological suitability, recreation potential and socio-economic support conditions. Furthermore, it uses GIS and entropy weight method to empirically evaluate the suitability of ecological space recreation at the whole-area scale. By comparing the existing ecological recreation space distribution pattern and the recreation suitability level distribution pattern, it proposes future optimization directions for the ecological space recreation utilization pattern of urban agglomerations, and also provides effective support for the layout of national land spatial planning. Attached Figure Description

[0057] Figure 1 This is a schematic diagram showing the area proportions of the suitability of ecological spaces for recreational use at different levels in nine cities according to the present invention. Detailed Implementation

[0058] The present invention will now be further described with reference to the accompanying drawings.

[0059] See Figure 1 This invention provides a method for evaluating the suitability of ecological space recreational use in urban agglomerations. This embodiment uses the Pearl River Delta urban agglomeration as an example.

[0060] The Pearl River Delta city cluster consists of nine cities in Guangdong Province, including Guangzhou, Shenzhen, Zhuhai, Foshan, Huizhou, Dongguan, Zhongshan, Jiangmen, and Zhaoqing, and is a major component of the Guangdong-Hong Kong-Macao Greater Bay Area.

[0061] The Pearl River Delta urban agglomeration is one of the most densely populated and economically vibrant urban agglomerations in China, with a significant demand for nature recreation.

[0062] 1. Data sources are shown in Table 1 below:

[0063]

[0064] The data required for this study are those used to calculate the evaluation indicators, including DEM, NDVI, soil erosion datasets, water system data, and land use type data. All raster data were resampled to a spatial resolution of 2500m to ensure consistency and accuracy in data processing. Furthermore, the administrative division data were obtained from the multi-year administrative boundary data of China in the Resource and Environmental Science Data Registry and Publication System.

[0065] Raster was selected as the basic evaluation unit. Referring to relevant literature (the spatiotemporal characteristics of the decoupling of surface thermal environment and ecosystem service value in the Pearl River Delta urban agglomeration) and considering data availability, the grid scale was determined to be 2500m×2500m. 9373 effective rasters were constructed in the agglomeration area using ArcGIS.

[0066] 2. The evaluation index system is constructed as shown in Table 2 below:

[0067]

[0068] "+" indicates a positive indicator, meaning the larger the value, the higher the evaluation value; "-" indicates a negative indicator, meaning the larger the value, the lower the evaluation value. Urban agglomeration ecological spaces are characterized by large scale, complex interaction of elements, overlapping recreational needs, and coordination between protection and utilization. Therefore, it is necessary to construct a comprehensive evaluation index system to assess the suitability of ecological space recreational use.

[0069] Based on the regional characteristics of the Pearl River Delta urban agglomeration and the influence of natural, social and economic factors, this embodiment constructs an evaluation index system from three aspects: ecological suitability, recreational potential and socio-economic support conditions, as shown in Table 2.

[0070] The calculation methods for the evaluation indicators are shown in Table 3 below:

[0071]

[0072] Among them, soil erosion, water conservation, ecosystem service value, and accessibility are calculated using methods found in existing literature; altitude, slope, NDVI, and landscape diversity are calculated using generally accepted methods; the proportion of nature reserves is the ratio of the area of ​​a nature reserve within a grid cell to the total area of ​​that grid cell; the distribution density of related facilities is calculated based on the 15-minute community living circle theory; the road network density is calculated based on various types of roads in the country; and the regional GDP uses grid-scale data.

[0073] 3. The entropy weight method is used to calculate the index weights, obtain standardized weighted scores, and then use ArcGIS for spatial analysis.

[0074] The entropy weight method calculates the weights of evaluation indicators based on raw data. When the value of an evaluation object varies significantly for a certain indicator, it indicates that the indicator provides a large amount of effective information, and therefore the indicator's weight is also larger, and vice versa. The advantage of the entropy weight method is that it assigns weights based on the dispersion of the data, eliminating the interference of human factors and making the results relatively objective.

[0075] The calculation steps of the entropy weight method are as follows:

[0076] (1) Establishing a decision matrix: Assuming there are m decision objects that need to be evaluated, and each decision object has n evaluation indicators, then a decision matrix as shown in equation (1) can be established:

[0077] (1)

[0078] (2) Standardization: The linear proportional transformation method is used to perform dimensionless processing, transforming the evaluation matrix into a standardized matrix to solve the problem of homogeneity among different indicator values. When the indicator is positive, its standardization formula is shown in equation (2):

[0079] (2)

[0080] When the index is negative, its standardized formula is shown in equation (3):

[0081] (3)

[0082] in It is the maximum value of the j-th indicator. It is the value of the j-th index of the i-th sample in the original matrix. It is the value of the j-th indicator of the i-th sample in the standardized data.

[0083] (3) Translation: After standardization, some data may have values ​​of 0 or negative. To avoid this, the standardized values ​​are translated, as shown in equation (4):

[0084] (4)

[0085] Where H is the translation magnitude, typically taken as 0.01. This represents the data of the j-th indicator of the i-th sample in the translated data.

[0086] (4) Dimensionless transformation: Dimensionless transformation is performed using the specific gravity method, finding suitable variable substitutions to eliminate some or all units in the equations involving physical quantities, thus simplifying the calculation. The processing formula is shown in equation (5):

[0087] (5)

[0088] In the formula, It is the value of the j-th index of the i-th sample in the dimensionless data.

[0089] (5) Entropy calculation: The formula for calculating entropy is shown in equation (6):

[0090] (6)

[0091] The difference coefficient of the j-th indicator is calculated as shown in equation (7):

[0092] (7)

[0093] (6) Weight Calculation: The formula for calculating the weight of the indicator is as shown in equation (8):

[0094] (8)

[0095] (7) Suitability score calculation: The comprehensive evaluation score is obtained by multiplying the standardized value by the weight. The calculation formula is shown in equation (9):

[0096] (9)

[0097] The weighting results (as shown in Table 4 below) indicate that, in the criteria layer of the evaluation system, recreational potential has the largest weight, followed by ecological suitability, while socioeconomic support conditions have the smallest weight. Among the individual indicators, the distribution density of catering and accommodation facilities has the largest weight, followed by the distribution density of public toilets and cultural and sports facilities, while soil erosion has the smallest weight.

[0098]

[0099] 4. The analysis and corresponding effects of the ecological space recreational use suitability evaluation results according to the present invention are as follows:

[0100] ArcGIS was used for overlay analysis to obtain the results of the suitability of ecological space for recreational use. The natural discontinuity method was applied to divide the recreational use suitability index into 5 different levels: low suitability, lower suitability, medium suitability, higher suitability, and high suitability.

[0101] Ecological suitability is a comprehensive reflection of ecological importance and sensitivity. Ecological importance represents the superiority of a natural ecosystem. The higher the value, the greater the suitability for recreational use of ecological space. Conversely, the higher the ecological sensitivity, the smaller the suitability for recreational use of ecological space.

[0102] The ecological sensitivity assessment results show that highly sensitive areas are mainly distributed in mountainous and forested regions, including Zhaoqing, Jiangmen, Huizhou, Shenzhen, western Foshan and western Zhuhai, southern Zhongshan and southern Dongguan, and northern Guangzhou. Other areas have lower sensitivity. Ecological importance is determined by the proportion of nature reserve area and the total value of ecosystem services. The proportion of nature reserve area is a negative indicator, while the value of ecosystem services is a positive indicator. The distribution pattern shows that low- and medium-value areas dominate, while high-value areas are only sporadically distributed within the built-up areas of Guangzhou, Shenzhen, Dongguan, Foshan, and Zhongshan.

[0103] Based on a comprehensive analysis of ecological importance and ecological sensitivity, a spatial pattern of ecological suitability is derived. Due to the relatively even distribution of ecological importance, highly suitable areas are mainly distributed in highly sensitive spaces, namely the urban agglomeration edges in the southwest, northwest, and east, as well as the Shenzhen-Dongguan metropolitan area and the Zhongshan-Zhuhai metropolitan area.

[0104] Spatial distribution pattern of recreational potential and socio-economic support conditions:

[0105] Recreation potential is influenced by factors such as landscape diversity index, density of public toilets, density of catering and accommodation facilities, density of cultural and sports facilities, density of tourist attractions, and accessibility. Urbanized areas, due to their relatively well-developed transportation infrastructure and recreational facilities, generally have medium to high recreational potential in their ecological spaces, primarily distributed in urban sprawl areas, county towns, and surrounding suburban towns. Overall, high recreational potential areas are more concentrated in the central built-up area of ​​the Pearl River Delta urban agglomeration, while their distribution is more scattered and lacks continuity in Huizhou, Jiangmen, Zhaoqing, western Foshan, and northern Guangzhou.

[0106] Socioeconomic support conditions include road network density and GDP. The evaluation results show that regions with high socioeconomic support condition values ​​are mainly distributed in the Guangzhou-Foshan metropolitan area, Shenzhen, Dongguan, Zhongshan city proper, and Zhuhai city proper, with Shenzhen, Guangzhou, Foshan, and Dongguan scoring the highest. Huizhou, Jiangmen, and Zhaoqing mainly contain areas with low socioeconomic support condition values. Furthermore, linear corridors with high socioeconomic support condition levels have formed along major transportation arteries in each city, forming a ring-shaped distribution in the Guangzhou-Foshan metropolitan area, fully reflecting the supporting role of major transportation arteries and urban ring roads in the recreational use of ecological spaces.

[0107] Spatial distribution and clustering characteristics of suitable recreational use of ecological spaces:

[0108] Based on the comprehensive evaluation results of single indicators, the spatial distribution of ecological space suitability for recreational use in the Pearl River Delta urban agglomeration was obtained. The results show that there are a relatively large number of ecological spaces with high suitability for recreational use around the urban sprawling areas of the Pearl River Delta urban agglomeration. Specifically, although the core area of ​​the Pearl River Delta urban agglomeration has densely populated urban areas, the preserved ecological spaces have relatively high suitability for recreational use due to good socio-economic support conditions, high accessibility, and strong ecological suitability. In the peripheral areas of the urban agglomeration, highly suitable patches are mainly distributed in and around the built-up areas of Huizhou, Zhaoqing, Jiangmen, western Foshan, and northern Guangzhou, with sporadic distributions in other areas, but exhibiting a fragmented and dispersed distribution pattern.

[0109] To further identify clusters with high suitability for recreational use of ecological spaces, this paper conducts kernel density analysis based on grid cells with high suitability for recreational use of ecological spaces.

[0110] The study results show that western and southern Guangzhou, most of Shenzhen, southeastern Foshan, central and southern Huizhou, small areas in central and eastern Sihui City of Zhaoqing, small areas in central Zhongshan, western Dongguan, and small areas in central and southern Huicheng District of Huizhou are high suitability clusters. The distribution density of high suitability areas in Jiangmen and Zhuhai is generally lower. Among these, the Shenzhen-Dongguan metropolitan area and the Guangzhou-Foshan metropolitan area are the two largest and most densely concentrated clusters with relatively high and high suitability for ecological space recreational use.

[0111] A hotspot analysis (Getis-Ord Gi*) was conducted on the distribution of ecological space recreational use suitability levels to identify statistically significant hotspot and coldspot areas. It can be seen that southern Guangzhou, Shenzhen, Dongguan, Foshan, Zhongshan, southwestern Huizhou, northeastern Jiangmen, northeastern Zhuhai, and eastern Zhaoqing are hotspot areas with high ecological space recreational use suitability levels; while western and northern Zhaoqing, northeastern Guangzhou, southern Jiangmen, and southern Zhuhai are significant coldspot areas, i.e., areas with low ecological space recreational use suitability levels. This indicates that the hotspot areas for ecological recreational use in the Pearl River Delta urban agglomeration are mainly distributed in areas with higher urbanization levels, i.e., the core area of ​​the urban agglomeration, while the coldspot areas are clustered in the mountainous areas on the periphery of the urban agglomeration.

[0112] The LISA spatial cluster map shows that high-value clusters and hotspots of ecological space recreational use suitability highly overlap, mainly distributed in Shenzhen, Dongguan, Foshan, southern Guangzhou, central Zhongshan, eastern Sihui (bordering Zhaoqing and Foshan), northern Jiangmen (bordering Foshan), and southern Huizhou. Among these, high-value ecological space recreational use areas show clustering and continuity in the Guangzhou-Foshan, Shenzhen-Dongguan, and Jiangmen-Zhongshan metropolitan areas. Other areas have lower ecological space recreational use suitability, especially ecologically rich areas on the periphery of urban clusters, such as Zhaoqing, northern Guangzhou, and eastern and northern Huizhou. Zhaoqing, with its mountainous terrain, has a wider and relatively continuous distribution of low-value clusters, while other areas are more dispersed.

[0113] Area distribution of recreational use suitability for different levels of ecological spaces:

[0114] Table 5 below shows the area and proportion of ecological spaces with different levels of recreational suitability within the Pearl River Delta urban agglomeration. The area of ​​ecological spaces with low recreational suitability is 16,874.05 km². 2 This area accounts for 35.70% of the total area of ​​the Pearl River Delta urban agglomeration, with the main land use types being forest land, cultivated land, and water areas. Less suitable ecological spaces for recreational use are mainly distributed in the northeastern part of the Pearl River Delta urban agglomeration, covering an area of ​​16,393.01 km². 2 It accounts for 34.68% of the total area, with the main land use types being cultivated land and forest land; the area of ​​ecological space suitable for moderate recreational use is 8960.14 km². 2 Forest land accounts for 18.95% of the total area, and the main land use type is forest land; the area of ​​ecological space suitable for higher recreational use is 3851.22 km². 2 It accounts for 8.15% of the total area, with the main land use types being water and forest land; the area of ​​suitable ecological space for high recreational use is 1192.51 km². 2 It accounts for only 2.52% of the total area, and the main land use type is forest land.

[0115]

[0116] The proportion of ecological spaces of different levels in different cities suitable for recreational use was statistically analyzed (e.g.) Figure 1 As shown in the figure, for the "highly suitable" and "very suitable" levels, Shenzhen (21.16%) had the highest proportion, followed by Dongguan (15.78%). Guangzhou (15.56%), Foshan (12.46%), Zhongshan (11.83%), and Zhuhai (11.67%) had similar proportions, while Huizhou (9.59%), Jiangmen (9.04%), and Zhaoqing (8.70%) had lower proportions. For the "lowly suitable" and "lower suitable" levels, Zhaoqing (78.06%) had the highest proportion, followed by Jiangmen (75.64%), Huizhou (73.07%), and Zhuhai (69.87%). Foshan (59.96%), Guangzhou (57.31%), and Zhongshan (56.85%) had similar proportions, while Shenzhen (43.67%) and Dongguan (41.80%) had relatively lower proportions. For the medium level, Dongguan (42.41%) had the highest proportion, followed by Shenzhen (35.17%), Zhongshan (31.32%), Foshan (27.58%), and Guangzhou (27.13%). Zhuhai (18.46%), Huizhou (17.34%), and Jiangmen (15.32%) had similar proportions, while Jiangmen (15.32%) and Zhaoqing (13.25%) had relatively lower proportions. In summary, Dongguan, Shenzhen, and Guangzhou had higher proportions of high suitability and lower proportions of low suitability, while Zhaoqing, Jiangmen, and Huizhou showed the opposite trend.

[0117] Optimization of the spatial pattern of ecological space recreation:

[0118] A comparison of the distribution pattern of ecological space recreational suitability in the Pearl River Delta urban agglomeration with the distribution pattern of 539 existing ecological recreation spaces reveals large areas of ecological space patches with moderate to high suitability that are not being used for recreation in the surrounding areas of built-up areas in Guangzhou, Foshan, Zhongshan, Jiangmen, and Huizhou. Furthermore, significant areas of ecological spaces with moderate to high recreational suitability also remain unused in northern Guangzhou, eastern and northern Huizhou, western Jiangmen, and northwestern and southwestern Zhaoqing. In addition, fragmented ecological spaces with moderate to high suitability also exist in other areas that are not being used for recreation. Overall, the matching level between the development of ecological recreation spaces and their recreational suitability needs improvement, and the Pearl River Delta urban agglomeration still has significant potential for ecological space recreational utilization.

[0119] It is worth noting that some developed and utilized ecological recreation spaces are located in areas with low suitability for ecological space recreation, such as parts of northwestern Zhaoqing City, northeastern Huizhou City, western Jiangmen City, and northern Guangzhou City, which are located on the edge of urban agglomerations. In these areas, ecological environment monitoring and management should be strengthened, and recreational functional zoning should be established to ensure that recreational use is coordinated with ecological protection.

[0120] Within the Pearl River Delta urban agglomeration, a large number of ecological spaces with high and relatively high suitability for recreational use remain undeveloped. These areas should be equipped with corresponding public infrastructure and service facilities to improve their recreational utilization rate. Based on this, recreational products such as resorts, nature tours, cultural experiences, and outdoor sports can be developed. For ecologically valuable and ecologically fragile nature reserves (including forest parks, scenic spots, and geological parks) and water conservancy scenic areas, ecotourism activities such as nature education and ecological health care can be carried out while strictly adhering to ecological red lines. Ecological spaces with moderate suitability for recreational use have good potential for recreational use and can be considered as potential development targets for ecotourism spaces. Existing ecotourism spaces with low and relatively low suitability for recreational use should be appropriately "de-recreationalized" to focus on restoring and protecting the ecosystem and environment.

[0121] In the Pearl River Delta urban agglomeration, ecological spaces with moderate and high suitability for recreational use are mostly distributed in patches and are scattered, while many ecological spaces with lower suitability are concentrated and contiguous, mainly located on the periphery of the urban agglomeration. This spatial characteristic suggests that the Pearl River Delta urban agglomeration is suitable for ecological space recreational use under the approach of "area protection and point utilization." To this end, a decentralized, point-based recreational use layout system can be established, that is, providing scattered recreational land in suitable areas, while protecting the overall habitat and ecosystem of areas with lower suitability through "area" protection. "Point-based, decentralized recreational space supply" can not only solve the problem of recreational land supply in ecological spaces, but also rationally utilize the excellent ecological environment background, improve the recreational utilization rate of ecological spaces in the Pearl River Delta urban agglomeration, and protect the overall ecological network.

[0122] After years of urbanization, the urban and rural boundaries of the Pearl River Delta core area have gradually become blurred, forming a continuous urban area of ​​approximately 15,000 square kilometers around the Pearl River Estuary. The 2015 World Bank report, "East Asia: Changing Urban Landscapes – Measuring Decades of Spatial Growth," also pointed out that the Pearl River Delta has surpassed the Tokyo metropolitan area to become the largest "mega-urban area" in East Asia. The ecological space recreation suitability assessment results in this embodiment also show that the suitability for ecological space recreation is moderate to high in the areas within and near the continuous urban area of ​​the Pearl River Delta urban agglomeration, as well as around the built-up areas of prefecture-level city districts. Therefore, it is necessary to construct ecological recreation belts around the continuous urban area (or around the built-up areas of prefecture-level city districts) to provide residents with convenient access to green recreational spaces.

[0123] The above are merely preferred embodiments of the present invention, intended only to aid in understanding the method and core ideas of this application. The scope of protection of the present invention is not limited to the above embodiments; all technical solutions falling within the scope of the present invention's concept are within its protection. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

[0124] This invention comprehensively addresses the shortcomings of existing technologies, such as insufficient research on the supply and demand of ecological recreation spaces, recreational topography, and the limited research on the suitability of ecological spaces for recreational use in small- to medium-scale areas like ecological functional zones and nature reserves at the scale of urban agglomerations. By taking urban agglomerations as the research area, it comprehensively considers the impact of regional natural environment, social, and economic factors on the suitability of ecological spaces for recreational use. Based on three aspects—ecological suitability, recreational potential, and socio-economic support conditions—it constructs an evaluation index system. Furthermore, it uses GIS and the entropy weight method to empirically assess the suitability of ecological spaces for recreational use at the whole-area scale. By comparing the existing distribution patterns of ecological recreation spaces with the distribution patterns of recreational use suitability levels, it proposes future optimization directions for the ecological space recreational use patterns of urban agglomerations, and also provides effective support for the layout of national land spatial planning.

Claims

1. A method for evaluating and optimizing the suitability of recreational use in urban agglomerations' ecological spaces, characterized in that, Includes the following steps: S1, Data Collection: S1-1, the data includes: digital elevation, normalized vegetation index, soil erosion dataset, water system, land use type, ecological recreation space, crop production and price, primary purification capacity, soil conservation function, precipitation, points of interest, population, road network and gross national income. S1-2, the data types include: raster, vector line data, vector point data, and vector polygon data; S1-3, the raster data is converted to a spatial resolution of 2500m through resampling to ensure the consistency and accuracy of data processing; S1-4. The grid was selected as the basic evaluation unit. The size of the evaluation unit was referenced in relevant literature and the data availability was taken into account. The grid scale was determined to be 2500m×2500m. An effective grid was constructed in the cluster area using ArcGIS. S2, Construction of the evaluation index system: S2-1, the evaluation index system includes a target layer, a criterion layer, an indicator factor layer, and an influence path; the target layer is the evaluation of the adaptability of ecological space recreational use in urban agglomerations; the criterion layer includes ecological suitability, recreational potential, and socio-economic support conditions; the ecological suitability includes ecological sensitivity and ecological importance. The index factor layer includes the following indicators: elevation, slope, normalized vegetation index, soil erosion, water buffer zone, area ratio of nature reserves, ecosystem service value, landscape diversity, distribution density of public toilets, distribution density of catering and accommodation facilities, distribution density of cultural and sports facilities, distribution density of scenic spots, accessibility, road network density, and regional GDP. S3 uses the entropy weight method to calculate the index weights, obtains standardized weighted scores, and then uses ArcGIS for spatial analysis: The calculation steps of the entropy weight method are as follows: S3-1, Establish the decision matrix: Suppose there are m decision objects that need to be evaluated, and each decision object has n evaluation indicators. Establish a decision matrix as shown in Formula 1: Formula 1: ; S3-2, Standardization: The evaluation matrix is ​​transformed into a standardized matrix using a linear scaling transformation method to address the homogeneity issue among different indicator values. When the indicator is positive, the standardization formula is shown in Formula 2. Formula 2: ; When the indicator is negative, its standardized formula is shown in Formula 3: Formula 3: ; in It is the maximum value of the j-th indicator. It is the value of the j-th index of the i-th sample in the original matrix. It is the value of the j-th indicator of the i-th sample in the standardized data; S3-3, Translation: After standardization, some data may contain 0 or negative values. To avoid this, the standardized values ​​are translated, as shown in Formula 4: Formula 4: ; Where H is the translation magnitude, taken as 0.

01. This represents the data of the j-th indicator of the i-th sample in the translated data; S3-4, Dimensionless Transformation: Dimensionless transformation is performed using the specific gravity method. Suitable variable substitutions are found to eliminate some or all units in equations involving physical quantities, simplifying calculations. The resulting formula is shown in Formula 5. Formula 5: ; in, It is the value of the j-th index of the i-th sample in the dimensionless data; S3-5, Entropy Calculation: The formula for calculating entropy is shown in Formula Six: Formula Six: ; The difference coefficient of the j-th indicator is calculated as shown in Formula 7: Formula 7: ; S3-6, Weight Calculation: The formula for calculating the indicator weight is shown in Formula 8: Formula 8: ; S3-7, Suitability Score Calculation: Multiply the standardized value by the weight to obtain the comprehensive evaluation score. The calculation formula is shown in Formula Nine: Formula Nine: ; S4. Overlay analysis was performed using ArcGIS to obtain the results of the suitability of ecological space for recreational use; S5. Based on the results of the suitability of ecological space recreational use obtained by ArcGIS in S4, analyze the influence of the indicator factor layer and its influence path on the criterion layer from the various levels of the criterion layer in the evaluation index system in S2-1. S6, using the natural breakpoint method, divides the recreational use suitability index into 5 different levels: low suitability, lower suitability, medium suitability, higher suitability, and high suitability; The five different levels are divided according to the area and its proportion obtained in S4.

2. The method for evaluating and optimizing the suitability of ecological space recreational use in urban agglomerations according to claim 1, characterized in that, The calculation method for each indicator in S2-1 is as follows: Elevation: The elevation of the raster cell in which the raster unit is located; Slope: Calculated in ArcGIS based on DEM data; NDVI: The NDVI of the raster cell in which it is located; Soil erosion: A = R·K·L·S·C·P, where A is the soil erosion rate in t / km². 2 • In the year, R is the precipitation erosivity, K is the soil erosivity, L and S are the surface slope length and slope, respectively, C is the vegetation cover factor, and P is the soil and water conservation measure factor. Water buffer zone: the distance of each grid cell from the water area; Percentage of area in nature reserves: The proportion of the area of ​​nature reserves in the total land area; Ecosystem service value: Based on a dynamic improved equivalent factor method using the value per unit area, the formula is as follows: ;in, is the proportion of area occupied by landscape type i; m is the number of landscape types; The distribution density of the public toilets, the distribution density of the catering and accommodation facilities, the distribution density of the cultural and sports facilities, and the distribution density of the scenic spots are calculated based on the 15-minute community living circle theory. The distribution density is calculated as the number of relevant facilities within a radius of 1km, that is, within and around the ecological space grid unit within a 15-minute walking distance, based on the POI data divided by the grid area. The aforementioned accessibility: In the formula Let be the accessibility index of the i-th grid; The commute time for the shortest route from [location] to [location] is calculated using point distances in ArcGIS, assuming a vehicle speed of 26.63 km / h for each grid cell; P i TP represents the population of the i-th grid cell; TP represents the total population of the Pearl River Delta urban agglomeration. The road network density refers to the density of expressways, national highways, provincial highways, county roads, township roads, and urban expressways. The regional GDP refers to the GDP of a grid cell.

3. The method for evaluating and optimizing the suitability of ecological space recreational use in urban agglomerations according to claim 1, characterized in that, The higher the ecological sensitivity in the ecological suitability layer of S2-1, the lower the suitability for recreational use of the ecological space; the ecological importance characterizes the superiority of the natural ecosystem, and the higher the value, the greater the suitability for recreational use of the ecological space.

Images