Integrating Cross-Regional Ecological Networks in Blue–Green Spaces: A Spatial Planning Approach for the Yangtze River Delta Demonstration Area

Abstract

The rapid pace of urbanization is contributing to ecological degradation and poses a threat to regional ecological security. Addressing these issues requires effective strategies to mitigate existing environmental challenges. Ecological networks, as the spatial foundation for ecosystem services, play a critical role in reducing environmental degradation. By reconfiguring the spatial relationship between human activities and natural ecosystems, anthropogenic pressures on land can be alleviated. However, most current research focuses on administrative boundaries, which limits spatial continuity and regional coordination. Therefore, constructing ecological networks from a cross-regional perspective is essential for integrated ecological management. This study uses the Yangtze River Delta Ecological Green Integration Demonstration Area as a case study. We construct a blue–green ecological network by applying ecological footprint analysis, Morphological Spatial Pattern Analysis (MSPA), landscape connectivity assessments, the Minimum Cumulative Resistance (MCR) model, and gravity modeling. Practical strategies for integrating the ecological network into territorial spatial planning are also explored. The key findings are as follows: (1) The demonstration area contains 33 ecological source areas, including 20 primary sources located near administrative boundaries and central lakeshore wetlands. A total of 333 ecological corridors were identified. First-grade corridors are primarily located in rural areas, traversing agricultural land and water bodies. (2) We recommend corridor widths of 200 m for first-grade corridors, 60 m for second-grade corridors, and 30 m for third-grade corridors. These widths are based on species characteristics and land use types, and are found to be conducive to species migration and habitat connectivity. (3) We propose the development of tourism landscape zones from a cross-regional perspective, leveraging existing ecological and cultural resources. The multifunctionality of corridors is redefined through the integration of ecological and social values, enhancing their spatial implementation. This framework provides a practical reference for constructing cross-regional blue–green ecological networks and informs spatial planning efforts in other multi-jurisdictional areas.

1. Introduction

The rapid increase in urbanization and the unregulated growth of cities have fragmented ecological spaces and disrupted ecological corridors, jeopardizing the ecological integrity and water security of the Yangtze River Basin [1]. The extinction of the Yangtze River’s iconic white-flag dolphin in 2006 highlights the profound impacts of human-induced pressures, while ongoing pollution continues to degrade water quality and accelerate eutrophication in Lake Taihu [2]. These challenges emphasize the urgent need to address regional ecological security, a key environmental issue in China. At the heart of these problems lies a spatial disconnect between human development and ecological systems. National land use planning plays a vital role in spatial governance, facilitating regional coordination and fostering sustainable development. The development of ecological networks presents a comprehensive strategy to combat climate change, manage human–land interactions, and enhance ecological security. Building cross-regional blue–green ecological networks is critical in this context. These networks help to identify and protect vital ecological sources, restore fragmented ecological corridors, and effectively implement ecological planning. These efforts enhance the regional ecological security framework and reinforce spatial resilience [3]. Furthermore, blue–green ecological networks provide a practical spatial approach to reconcile ecological conservation with economic development [4]. They promote the integration and optimal distribution of ecological resources across regions, facilitate the sharing of ecological benefits, aid in the creation of composite cultural and tourism corridors, and foster the synchronized advancement and mutual prosperity of ecological and economic systems.

An ecological network characterized by blue–green features is a continuous and integrated spatial structure that includes ecological sources, corridors, and landscape matrices [5]. Identifying and categorizing ecological sources and corridors are crucial steps in developing effective ecological networks [6]. International research in this field generally focuses on ecological security related to land use and tourism, as well as the balance between supply and demand for ecological services [7,8,9]. In contrast, domestic studies tend to concentrate on the development of ecological security frameworks within administrative boundaries, spatial landscape arrangements, and the spatiotemporal evolution of ecological components [10,11,12]. However, contemporary ecological network planning is constrained by administrative boundaries, even though natural geographic units often span multiple jurisdictions. This rigid spatial segmentation hampers the ecological integrity and functionality of the network. As a result, it is essential to overcome these administrative barriers, use natural units as the foundational framework, and establish cross-regional blue–green ecological networks to achieve regional ecological sustainability. Moreover, current research often evaluates source regions and corridors purely from an ecological perspective, neglecting their roles within the broader land use framework [13]. For example, when two source areas connected by a corridor serve recreational purposes, the corridor may be inadequate for species migration. Defining corridor types based on the functional characteristics and developmental conditions of source areas allows for more precise planning techniques. Functionally diversified corridors promote natural connectivity and enhance human utilization, attracting tourism and fostering synergistic ecological and economic development. A commonly used study model involves identifying ecological sources, constructing ecological resistance surfaces, and extracting ecological corridors [14]. Sources are typically defined through comprehensive evaluation methods, ecological redline boundaries, and MSPA [15,16,17]. The creation of resistance surfaces involves selecting various ecological resistance variables, assigning graded values, and applying weights to generate a comprehensive resistance surface [18]. Researchers frequently use graph theory, circuit theory, and MCR for corridor extraction [19,20]. Recently, the combined use of MCR and gravity models has become a common approach for corridor extraction and classification by level. Ecological footprint analysis has been widely applied in assessing regional ecological sustainability in recent years. In this context, integrating blue–green spaces within a cross-regional framework is critical. This approach supports the creation of more robust and efficient ecological networks, enhances regional ecological security, and facilitates a balanced relationship between human development and natural systems.

According to the above study, current research on ecological network design exhibits various shortcomings: (1) The majority of research emphasizes administrative units, neglecting cross-regional perspectives; (2) Planning strategies for ecological corridors are primarily formulated from ecological perspectives, disregarding existing social functions. This study advocates for the establishment of a blue–green ecological network from a cross-regional viewpoint to rectify existing deficiencies, particularly the absence of cross-regional research subjects and inadequate investigation of practical implementation strategies. Moreover, ecological corridors are categorized based on the prevailing societal functions of their associated ecological resources. This research designates the Yangtze River Delta Ecological Green Integration Demonstration Area in China (hereafter referred to as the demonstration area) as the study region. In response to growing concerns over ecological sustainability, this study focuses on the Yangtze River Delta Ecological Green Integration Demonstration Area (hereafter referred to as the demonstration area) to explore the construction of a blue–green ecological network from a cross-regional perspective. Positioned at the convergence of Shanghai, Jiangsu, and Zhejiang, the demonstration area serves as a frontier for institutional innovation in regional integration and a valuable reference for promoting coordinated spatial development across provinces. With its well-preserved ecological base and strategic location within the Yangtze River Basin, the area is particularly suited for addressing broader regional ecological security concerns. The ecological footprint model is applied to evaluate the equilibrium between resource supply and consumption. Following this, MSPA is integrated with landscape connectivity indices to identify and categorize ecological source areas. Ecological corridors are subsequently delineated using the Least-Cost Path model, while the gravity model helps to classify these corridors based on interaction intensity, resulting in a tiered ecological network. Building upon this structure, planning strategies are proposed that consider both the current roles of ecological source areas and the developmental characteristics of adjacent land uses, aiming to foster synergistic ecological and economic outcomes. The technical roadmap of this study is illustrated in Figure 1.

The remainder of this paper is organized as follows. Section 2 presents the study area and research methods. It first introduces the geographical context of the study area and the rationale for its selection. It then specifies the types and sources of geographic and socio-economic data used in this study. Finally, it outlines the methodological framework for constructing the blue–green ecological network, which includes the following components: (1) Ecological supply–demand assessment: Ecological footprint analysis estimates demand, while ecological carrying capacity determines supply. The equilibrium coefficient (EC) is then applied to evaluate whether supply meets demand; (2) Identification of ecological sources: MSPA (Morphological Spatial Pattern Analysis) and landscape connectivity indices are used to identify and classify ecological sources; (3) Construction of the ecological resistance surface: An ecological resistance surface is developed using the Analytic Hierarchy Process (AHP). (4) Ecological corridor construction: Ecological corridors are delineated based on the Minimum Cumulative Resistance (MCR) and gravity models. Section 3 presents the research results. It begins with an overview of current land use patterns in the study area, followed by detailed results from the ecological network construction based on the methods described in Section 2. This section also introduces the formation of landscape corridors and function-based corridors from a cross-regional perspective. Section 4 provides a discussion of the main findings and research limitations. Section 5 concludes the paper.

2. Materials and Methods

2.1. Study Area and Date

2.1.1. Study Area

The Yangtze River Delta Ecological Green Integration Demonstration Area (hereafter referred to as the demonstration area) is located in the central part of the Yangtze River Delta in China (Figure 2). It encompasses Qingpu District of Shanghai, Wujiang District of Suzhou in Jiangsu Province, and Jiashan County of Jiaxing in Zhejiang Province, covering an area of approximately 2413 km². Geographically, it lies between 30°40′ and 31°10′ north latitude and 120°50′ and 121°20′ east longitude, near the convergence of provincial and municipal boundaries. Situated on the alluvial plain of the Yangtze River Delta, the region is predominantly flat, characterized by a gently undulating landscape with no prominent mountain peaks. The demonstration area borders Taihu Lake to the west and forms part of the lake’s eastern outflow system. It includes several major water bodies, such as the Beijing–Hangzhou Grand Canal, Taipu River, Yuandang Lake, and Dianshan Lake, with a combined water surface area of approximately 350 km². The area is defined by a complex mosaic of rivers, lakes, agricultural lands, and forested areas, providing a robust natural foundation for the development of a blue–green ecological network [21].

The demonstration area was officially established on November 1, 2019. This initiative reflects a strong commitment to the principle of “ecological priority and green development”, with the aim of overcoming administrative barriers in spatial planning, resource allocation, and ecological conservation. The demonstration area functions as a testing ground for exploring cross-jurisdictional governance mechanisms and for integrating ecological civilization with economic and social development. It plays a leading role in promoting high-quality, integrated regional development through the coordinated management of land use, ecological protection, and the green economy. Unlike traditional administrative units, the demonstration area spans two districts and one county across three different provincial-level jurisdictions, making it a distinctive case for studying cross-regional ecological planning. In recent years, unregulated urban and rural expansion has led to the fragmentation of ecological spaces. Therefore, the establishment of a cohesive blue–green ecological network is essential to reconcile ecological preservation with sustained economic development in the region.

2.1.2. Data Source

The land use data for this study were sourced from the 2020 WorldCover land cover dataset provided by the European Space Agency (ESA), with a spatial resolution of 10 m (https://esa-worldcover.org/en accessed on 1 July 2023). Using ArcGIS for visualization and classification, eight primary land cover types were identified within the demonstration area: tree land, shrubland, grassland, cropland, construction land, bare land, permanent water bodies, and wetlands. Additional geospatial datasets utilized in this study are presented in

Table 1. Geospatial datasets and sources.

Data Type	Year	Source
Land use data	2020	European Space Agency, WorldCover dataset (https://esa-worldcover.org/en accessed on 1 July 2023)
Digital elevation model	2019	European Space Agency, Copernicus DEM, GLO-30 (https://dataspace.copernicus.eu/ accessed on 1 July 2023)
Road and river shapefiles	2020	OpenStreetMap (https://openstreetmap.org/ accessed on 1 July 2023)
Administrative boundaries	2024	National Geomatics Center of China, Map Review No. GS(2024)0650 (https://cloudcenter.tianditu.gov.cn/dataSource accessed on 1 July 2023)
Point of Interest (POI)	2020	Amap (https://lbs.amap.com/ accessed on 1 July 2023)

.

To ensure consistency and accuracy in spatial analysis, all datasets were standardized to a 10 m × 10 m resolution and projected into the WGS_1984 coordinate system. Socio-economic data were sourced from the China Energy Statistical Yearbook (2021), the Qingpu Statistical Yearbook (2020), the Wujiang Statistical Yearbook (2020), the Jiaxing Statistical Yearbook, and the Statistical Bulletins of National Economic and Social Development for Qingpu District, Wujiang District, and Jiashan County (2021 editions). These sources provide indicators such as regional permanent population, biological product output, and per capita product consumption [22].

2.2. Research Methods

2.2.1. Ecological Footprint Supply–Demand Analysis Method

(1) Ecological Footprint-Based Estimation of Ecological Resource Demand

Human activities consume ecological resources, which are quantified as the total biologically productive land required to supply these resources and absorb the waste generated [23]. The ecological footprint model provides a framework for measuring this consumption. Initially proposed by Canadian economist William Rees in 1992, the model has been refined through various applications [24,25]. Today, ecological footprint analysis is widely employed at different scales, from regions and cities to households, playing a crucial role in assessing sustainability at various spatial levels [26,27]. This study uses the ecological footprint model to evaluate the ecological supply–demand balance in the demonstration area. Specifically, the total biologically productive land required to support human activities is calculated to determine the region’s ecological resource demand. The analysis proceeds in three main steps: (1) calculating the ecological footprint of the demonstration area based on socio-economic data; (2) estimating the ecological carrying capacity; and (3) comparing the two values to assess the region’s ecological deficit (ED) status and determine its level of sustainability.

$$\mathrm{E}\mathrm{F}=\mathrm{N}\times \mathrm{e}\mathrm{f}=\mathrm{N}\times {\mathrm{r}}_{\mathrm{j}}\times \sum _{\mathrm{i}=1}^{\mathrm{n}}({\mathrm{p}\mathrm{a}}_{\mathrm{i}})=\mathrm{N}\times {\mathrm{r}}_{\mathrm{j}}\times \sum _{\mathrm{i}=1}^{\mathrm{n}}{\displaystyle \frac{{\mathrm{C}}_{\mathrm{i}}}{\mathrm{E}{\mathrm{P}}_{\mathrm{i}}}}$$

(1)

In the equation, EF represents the ecological footprint; N denotes the resident population of the area; $\mathrm{e}\mathrm{f}$ stands for the per capita ecological footprint; $\mathrm{p}{\mathrm{a}}_{\mathrm{i}}$ represents the per capita land area required for the production of the ith category of goods; ${\mathrm{C}}_{\mathrm{i}}$ represents the per capita consumption of the ith category of goods; $\mathrm{E}{\mathrm{P}}_{\mathrm{i}}$ represents the global average production of the ith category of goods; and ${\mathrm{r}}_{\mathrm{j}}$ represents the equivalence factor of the jth type of biologically productive land.

Following the established literature, this model classifies land into six categories based on biological productivity and functional attributes: forestland, grassland, cropland, water bodies, construction land, and energy land [28]. Since no energy land exists within the demonstration area, it is excluded from the analysis [29]. As construction land typically occupies cropland, the same equivalence factor is applied to both land types [30]. Wetlands are identified according to the European Space Agency’s land cover classification standards, using visual interpretation of remote sensing images. These wetlands are primarily composed of herbaceous vegetation such as reeds and rice. Given that the study area lies within a rice cultivation region in southern China, wetlands are classified as cropland in this analysis. Additionally, shrubland is classified as tree cover due to its similar ecological function [31] (

Table 2. Land equivalence factors in the study area in 2020.

Land Type	Equivalence Factor
Tree cover	1.299
Grassland	1.074
Cropland	1.081
Water bodies	0.760
Construction land	1.081

).

(2) Method for Estimating Ecological Supply Capacity within Ecological Carrying Framework

Ecological carrying (EC) capacity refers to the entire geographical area that can provide the biological resources necessary for human survival and productivity within specific socio-economic contexts. It measures the maximum amount of ecological resources that a region can sustainably yield. Ecological carrying capacity is a critical metric for maintaining ecological balance, representing a region’s potential to supply natural resources and provide ecological services. It defines the ecological threshold that the environment can support [29]. Regions with a higher ecological carrying capacity generally cover larger areas of ecological land and demonstrate greater resource production capabilities.

$$\mathrm{E}\mathrm{C}={\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{S}}_{\mathrm{i}}\times {\mathrm{r}}_{\mathrm{i}}\times {\mathrm{P}}_{\mathrm{i}}$$

(2)

In the above equation, $EC$ represents the ecological carrying capacity; ${\mathrm{r}}_{\mathrm{i}}$ denotes the equivalence factor for the $i$th type of biologically productive land; ${\mathrm{S}}_{\mathrm{i}}$ is the total area of land for the ith land use type; and ${\mathrm{P}}_{\mathrm{i}}$ stands for the yield factor of the ith type of biologically productive land.

The yield factor for construction land is assumed to be equivalent to that of farmland, based on the previously established equivalence factors for other land types. This study determined the equivalence and yield factors using 2020 land use data and statistical yearbooks from Qingpu District, Wujiang District, and Jiashan County to ensure consistency and comparability across datasets. The ecological footprint and carrying capacity were calculated using established equations to facilitate the subsequent quantitative assessment of regional ecological sustainability (

Table 3. Land yield factors in the study area in 2020.

Land Type	Qingpu District	Wujiang District	Jiashan County
Tree cover	0.311	0.574	1.167
Grassland	0.067	0.695	20.054
Cropland	6.848	7.943	12.512
Water bodies	1.690	3.350	6.700
Construction land	6.848	7.943	12.512

).

(3) Method for Evaluating Supply–Demand Relationship of Ecological Deficit (ED)

Ecological surplus or ecological deficit (ED) refers to the difference between a region’s ecological carrying capacity and its ecological footprint. This indicator reflects whether there is a balance between the demand generated by human activities and the supply of natural resources, serving as a key metric for assessing regional sustainability. When the ecological carrying capacity exceeds the ecological footprint, the region exhibits an ecological surplus, indicating a state of sustainable development [29]. Conversely, if the demand exceeds the carrying capacity, an ecological deficit occurs. By analyzing the magnitude of the ED value, it is possible to assess the level of regional ecological services and provide strategic guidance for improving the coordination between human activities and land use.

$$\mathrm{E}\mathrm{D}=\mathrm{E}\mathrm{F}-\mathrm{E}\mathrm{C}$$

(3)

2.2.2. Method for Identifying Ecological Sources Based on MSPA and Landscape Connectivity

(1) Ecological Source Identification Method Based on MSPA

MSPA applies mathematical morphology to raster image data in order to accurately identify landscape pattern types [32]. This method provides a foundation for extracting and classifying key ecological source areas in subsequent analyses. In ArcGIS, woodland, shrubland, cropland, and wetland are classified as natural elements and designated as the foreground in the MSPA. In contrast, grassland, construction land, bare land, and permanent water bodies are treated as non-natural elements and assigned as the background. The final output is a binary GeoTIFF raster dataset.

This study used Guidos Toolbox to conduct MSPA for the demonstration area. Based on previous studies, when constructing regional ecological networks without species-specific data, the edge width parameter is typically set to the default value of 1 [33]. Since this research focused on constructing a blue–green ecological network at the regional scale, targeting all species rather than any specific one, and lacked detailed species distribution data, the eight-neighborhood connectivity rule was adopted, and the edge width was set to 1 [34]. The analysis resulted in seven mutually exclusive landscape categories: core, edge, bridge, loop, branch, perforation, and islet. The core category served as the basis for identifying primary ecological source patches in the subsequent analysis stage.

(2) Ecological Source Selection Method Based on Landscape Connectivity

Landscape connectivity refers to the capacity for species movement and energy flow between ecological patches at a given spatial scale [35,36]. It measures the degree of connection among patches, and plays a critical role in maintaining regional ecological security and enhancing ecological carrying capacity. The ecological source areas identified through connectivity analysis are crucial for supporting ecosystem integrity and spatial resilience. Standard landscape connectivity indices include the Integral Index of Connectivity (IIC), Probability of Connectivity (PC), Connectivity Importance (dI), Number of Links (dNL), and Node Contribution (dNC). In this study, we selected three representative indices, IIC, PC, and dPC, to assess the connectivity of core ecological patches. These indices effectively capture both regional-level connectivity and the contribution of individual patches to the overall ecological network (

Table 4. Landscape connectivity indices and their interpretations.

Index Type	Equation	Interpretation
IIC	$\mathrm{I}\mathrm{I}\mathrm{C}={\displaystyle \frac{\sum _{\mathrm{i}=1}^{\mathrm{n}}\sum _{\mathrm{j}=1}^{\mathrm{n}}\frac{{\mathrm{a}}_{\mathrm{i}}\times {\mathrm{a}}_{\mathrm{j}}}{1+{\mathrm{n}\mathrm{l}}_{\mathrm{i}\mathrm{j}}}}{{\mathrm{A}}_{\mathrm{L}}^2}}$	n represents the number of ecological core areas; $a_i$ and $a_j$ denote the areas of core areas $i$$\mathrm{and} j$; ${nl}_{ij}$ indicates the number of connections between core areas $i$ and $j$; and $A_L$ is the total area of the study region. A higher IIC value indicates greater overall landscape connectivity.
PC	$\mathrm{P}\mathrm{C}={\displaystyle \frac{\sum _{\mathrm{i}=1}^{\mathrm{n}}{\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{P}}_{\mathrm{i}\mathrm{j}}^{*}{\mathrm{a}}_{\mathrm{i}}{\mathrm{a}}_{\mathrm{j}}}{{\mathrm{A}}_{\mathrm{L}}^2}}$	$P_{ij}^{*}$ represents the maximum product of probabilities among all possible connecting paths between core areas i and $j$. PC represents the potential connectivity among all patches. Higher PC values suggest better landscape connectivity.
dPC	$\mathrm{d}\mathrm{P}\mathrm{C}={\displaystyle \frac{\mathrm{P}\mathrm{C}-{\mathrm{P}\mathrm{C}}_{\mathrm{r}\mathrm{e}\mathrm{m}\mathrm{o}\mathrm{v}\mathrm{e}}}{\mathrm{P}\mathrm{C}}}\times 1000\mathrm{\%}$	This measures the reduction in connectivity when a specific patch is removed. A higher dPC value indicates that the patch is more important for maintaining landscape connectivity.

).

Larger patches provide more resources for the organisms they sustain. Existing studies suggest that a minimum area of 5 km² is required for a habitat patch to support species, including plants and mammals [37,38]. Consequently, this study identified core areas exceeding 5 km² as potential ecological sources. Using Conefor 2.6 software, we established a connectivity threshold of 20,000 m and a connection probability of 0.5. Landscape connectivity was then assessed using the IIC, PC, and dPC indices. We evaluated the significance of each patch within the core areas based on the results. Ecological source sites were then identified, ranked, and categorized into primary and secondary sources based on their relative significance.

2.2.3. Resistance Surface Construction Method Based on AHP

The Analytic Hierarchy Process (AHP) is a multi-criteria decision-making method that integrates both qualitative and quantitative approaches. Developed by American operations researcher Thomas L. Saaty in the 1970, the core principle of AHP is to compare the relative importance of each factor in a pairwise manner to determine their respective weights [39]. This method is particularly suitable for situations that require integration of subjective judgment with objective data, such as factor weighting in spatial modeling [40]. The resistance surface represents the degree to which different geographic units hinder species dispersal. It is a critical input for constructing ecological corridors, and reflects the potential movement pathways of species [41]. Based on previous research and the specific characteristics of the demonstration area, six resistance factors were selected: elevation, slope, land use type, MSPA, water bodies, and roads. Each factor was assigned a resistance value based on its level of obstruction, with higher resistance levels corresponding to higher resistance values. This process yielded a single-factor resistance surface for each variable. Since each factor contributed differently to the overall ecological resistance, we applied the AHP to assign weights to the resistance factors. The pairwise comparison matrix and weight calculation were performed using Yaahp software. By overlaying the single-factor resistance layers according to their AHP-derived weights, we generated an integrated resistance surface for the study area [42]. On this surface, lower values indicate lower resistance and are more conducive to species movement and ecological network construction, while higher values represent more significant barriers to connectivity [43] (

Table 5. Ecological resistance evaluation index system.

Indicator	Grading	Resistance Value	Weights
Elevation	0–6	1	0.09
	6–12	25
	12–18	50
	18–24	75
	24–73	100
Slope	≤2°	1	0.07
	2–6°	25
	6–15°	50
	15–25°	75
	≥25°	100
Land use type	10	5	0.17
	20	20
	30	30
	40	40
	50	100
	60	80
	80	60
	90	10
MSPA	Core	5	0.23
	Bridge	10
	Loop	20
	Branch	30
	Islet	50
	Edge	60
	Perforation	70
	Background	100
Distance from water bodies	0–500	100	0.11
	500–1000	75
	1000–1500	50
	1500–2000	25
	≥2000	1
Distance from railway	≤1000	100	0.15
	1000–1500	75
	1500–2000	50
	2000–2500	25
	≥2500	1
Distance from high speed	0–500	100	0.10
	500–1000	75
	1000–1500	50
	1500–2000	25
	≥2000	1
Distance from other roads	≤500	100	0.08
	500–1000	75
	1000–1500	50
	1500–2000	20
	≥2000	1

).

2.2.4. Ecological Corridor Construction Method Based on MCR and Gravity Models

(1) Ecological Corridor Construction Method Based on MCR

The Minimum Cumulative Resistance model is a widely used and effective method for constructing ecological corridors. It relies on the integrated resistance surface and utilizes the Least-Cost Path tool in ArcGIS to calculate the Minimum Cumulative Resistance required for movement between ecological source areas [44]. The resulting Least-Cost Paths correspond to the routes with the lowest resistance, and are identified as ecological corridors.

$$\mathrm{M}\mathrm{C}\mathrm{R}={\mathrm{f}}_{\mathrm{m}\mathrm{i}\mathrm{n}}\sum _{\mathrm{j}=\mathrm{n}}^{\mathrm{i}=\mathrm{m}}\left({\mathrm{D}}_{\mathrm{i}\mathrm{j}}\times {\mathrm{R}}_{\mathrm{i}}\right)$$

(4)

In the equation, $f$ denotes a positive correlation function, $D_{ij}$ represents the spatial distance from ecological core area $j$ to landscape unit $i$, and $R_i$ is the ecological resistance of landscape unit $i$.

(2) Ecological Corridor Classification Method Based on Gravity Model

The gravity model, based on the physical law of gravitation, assesses the significance of ecological corridors by quantifying the interaction strength among ecological patches [45]. A more robust interaction between two source areas signifies a more vital ecological corridor. Ecological corridors can be categorized into varying levels of significance based on the intensity of the interaction force.

$${\mathrm{G}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{{\mathrm{N}}_{\mathrm{i}}{\times \mathrm{N}}_{\mathrm{j}}}{{\mathrm{D}}_{\mathrm{i}\mathrm{j}}^2}}={\displaystyle \frac{[\frac{1}{{\mathrm{P}}_{\mathrm{i}}}\times \ln ({\mathrm{S}}_{\mathrm{i}})]\times [\frac{1}{{\mathrm{P}}_{\mathrm{j}}}\times \ln ({\mathrm{S}}_{\mathrm{j}})]}{(\frac{{\mathrm{L}}_{\mathrm{i}\mathrm{j}}}{{\mathrm{L}}_{\mathrm{m}\mathrm{a}\mathrm{x}}})^2}}={\displaystyle \frac{{\mathrm{L}}_{\mathrm{m}\mathrm{a}\mathrm{x}}^2\ln ({\mathrm{S}}_{\mathrm{i}})\times \ln ({\mathrm{S}}_{\mathrm{j}})}{{\mathrm{L}}_{\mathrm{m}\mathrm{a}\mathrm{x}}^2{\mathrm{P}}_{\mathrm{i}}{\mathrm{P}}_{\mathrm{j}}}}$$

(5)

In the equation, ${\mathrm{P}}_{\mathrm{i}\mathrm{j}}^{*}$ represents the maximum product of the probabilities of all possible path connections between patch i and patch j; ${\mathrm{P}}_{\mathrm{i}\mathrm{j}}$ denotes the probability of direct connection between patch i and patch j; and ${\mathrm{a}}_{\mathrm{i}}$ and ${\mathrm{a}}_{\mathrm{j}}$ refer to the quality of patch i and patch j, respectively. Building on previous research, this study adopts patch area as the measure of patch quality, as larger patches can provide more available resources for the region’s biota. ${\mathrm{A}}_{\mathrm{L}}$ denotes the total sum of the region’s quality, and ${nl}_{ij}$ indicates the quantity of connections between patch i and patch j.

3. Results

3.1. Land Use Status Analysis of Demonstration Area

Cultivated land is the predominant land use type in the demonstration area, accounting for 37.87%. It is primarily distributed around construction land and within the central region, which is characterized by a dense water network. This spatial pattern contributes to the formation of ecological buffer zones and corridors, thereby supporting regional ecological connectivity. Construction land ranks second, covering 23.91% of the area, reflecting a high degree of urbanization. Permanent water bodies, tree cover, and bare land account for moderate proportions, at 14.9%, 11.26%, and 10.34%, respectively. In contrast, grassland, wetlands, and shrubland make up only minor shares, at 1.08%, 0.46%, and 0.18%, respectively. The demonstration area exhibits a moderately balanced ecological land use structure, providing some level of ecological support and regulatory functions. However, key ecological substrates, such as wetlands and shrubland, are severely under-represented. Coupled with the high proportion of construction land, this imbalance poses a threat to regional ecological security in the absence of effective blue–green infrastructure optimization strategies (Figure 3,

Table 6. The area and proportion of each land type in the study area.

Land Type	Area (km2)	Proportion (%)
Forestland	270.46	11.26
Shrubland	4.42	0.18
Grassland	25.93	1.08
Cropland	909.95	37.87
Construction land	574.51	23.91
Bare/sparse vegetation	248.42	10.34
Permanent water bodies	357.95	14.90
Herbaceous wetland	11.07	0.46

).

3.2. Results of Supply–Demand Relationship Analysis Based on Ecological Footprint

3.2.1. Supply and Demand Results Based on Ecological Footprint and Ecological Carrying Capacity

Utilizing the equivalence and yield factors of each biologically productive land type determined in the preceding section, along with statistical yearbook and census data, the per capita ecological footprint and ecological carrying capacity of the demonstration area were calculated using the relevant equations, as shown in

Table 7. The ecological footprint and ecological carrying capacity in the demonstration area.

Province City	Forestland (hm2)	Grassland (hm2)	Cropland (hm2)	Water Body (hm2)	Construction Land (hm2)	Total Population (Thousand)	Ecological Footprint Per Capita (hm2)	Ecological Carrying Capacity Per Capita (hm2)
Qingpu District	4180	980	24590	16310	20910	127.140	0.054	0.283
Wujiang District	13788	2803	21388	33407	41325	87.470	0.130	0.725
Jiashan County	3872	142	19329	9481	17778	40.980	0.128	1.364

. The results indicate that in the Qingpu District, Wujiang District, and Jiashan County areas encompassed within the demonstration area, the per capita ecological carrying capacity exceeds the per capita ecological footprint. This suggests a balance between ecological supply and demand, indicating a sustainable state in which the intensity of human activities remains within the region’s ecological carrying capacity.

3.2.2. Evaluation Results of Supply–Demand Relationship Based on ED

The per capita ecological footprint and ecological carrying capacity of the three regions within the demonstration area were calculated as described above. The difference between these two values, representing the ecological surplus or deficit (ED), is presented in

Table 8. The ecological surplus or ecological deficit of the demonstration area.

Region	Value
Qingpu District	0.23
Wujiang District	0.60
Jiashan County	1.24
Demonstration area (Average)	0.69

.

The results indicate that the demonstration area as a whole is currently in a state of ecological surplus. According to previous studies, the region experienced an ecological deficit from 2010 to 2018 [22]. The transition to a surplus suggests that, since the formal establishment of the demonstration area in 2019, policies emphasizing ecological protection and green development have begun to produce positive outcomes. However, the Overall Program of the Yangtze River Delta Ecological Green Integration Demonstration Area sets explicit ecological targets: a green coverage rate of over 42% and a forest coverage rate of over 20%. The earlier land use analysis shows that current coverage levels fall short of these goals. Therefore, further efforts in ecological construction are needed to ensure the long-term stability and sustainability of the region’s ecological surplus.

An examination of the ED values reveals that Qingpu and Wujiang Districts have significantly lower ecological surpluses than Jiashan County, falling below the average for the entire demonstration area. This disparity is primarily due to the higher intensity of urban development in Qingpu and Wujiang, which reduces ecological space and diminishes the regional ecological surplus. Continued economic development is expected to increase ecological demand across the region. In this context, it is essential to closely examine the spatial relationship between areas of high human activity, such as tourist destinations and ecological core zones. To support the coexistence of ecological protection and economic growth, tourism and other economic activities should be guided by spatial planning principles that avoid compromising ecological source areas. This approach can promote the coordinated development of urban–rural ecology and the regional economy.

3.3. Results of Ecological Source Identification Based on MSPA and Landscape Connectivity

3.3.1. Results of Ecological Source Identification Based on MSPA

The MSPA identification results (Figure 4,

Table 9. Statistics of landscape types.

Land Type	Area (km2)	Foreground Coverage (%)
Core	929.72	73.96
Bridge	11.07	0.88
Loop	10.25	0.82
Branch	28.24	2.25
Islet	59.61	4.74
Edge	14.41	1.15
Perforation	203.79	16.21
Background	1163.53	-

) indicate that the core regions occupy the largest area, totaling 979.72 km², which accounts for approximately 73.96% of the potential biological elements. While core areas dominate, islets, edges, branches, and loops make up smaller proportions. The core regions exhibit signs of spatial dispersion and fragmentation, primarily due to the influence of adjacent construction zones. The larger core patches are mainly located in the central region, which is characterized by a dense network of lakes, and along the periphery of the demonstration area. In contrast, other regions contain smaller, more isolated core patches. The significant proportion of pore spaces suggests the presence of numerous internal “gaps” within the core areas, indicating a high level of landscape fragmentation. This fragmentation further weakens ecological connectivity and impedes species migration, particularly for species that depend on continuous habitats. The prevalence of pore areas intensifies edge effects, increasing the vulnerability of core patches to human disturbance.

In summary, although the demonstration area contains substantial blue and green spaces, the central regions remain fragmented and poorly connected. Strengthening ecological linkages is essential for improving the landscape’s overall connectivity and functional integrity.

3.3.2. Results of Ecological Source Selection Based on Landscape Connectivity

Ecological source areas were identified based on patch area and landscape connectivity indices. Core areas exceeding 5 km² were selected from the MSPA results. Subsequently, core areas with dIIC > 2.5 and dPC > 2 were further screened according to their connectivity significance. In total, 33 ecological source regions were identified. Among them, 20 were classified as primary ecological sources (dPC > 5) and 13 as secondary ecological sources (2 < dPC ≤ 5) (Figure 5 and Figure 6).

The figure shows that the most critical ecological source regions are concentrated in Wujiang District, particularly around Zhenze Town, Taoyuan Town, and Pingwang Town in the southern part of the district. This distribution is primarily attributed to ecological policies enacted since the 19th National Congress, which have promoted afforestation and forest quality enhancement programs, significantly increasing forest coverage in Taoyuan Township. Several important source areas are located along the boundaries of the three administrative units. Dianshan Lake–Yuandang, Qingxi Country Park, and the Jiashan County segment of the Taipu River serve as cross-regional ecological resources. These areas are generally distant from major urban centers and experience minimal human disturbance, thereby offering higher ecological service value. In contrast, secondary ecological sources are usually found adjacent to urbanized areas. These patches are smaller, more fragmented, and more vulnerable to external disturbances. The spatial distribution of ecological source areas is fragmented, shaped by ongoing urban expansion. Notably, no ecological sources were identified in Taihu New District, Shengze Town, Qingpu City, or the Jiashan County portion of Wujiang District. In the future, blue–green spaces may serve as ecological stepping stones to enhance connectivity and ecological resilience. These interventions could mitigate the scarcity of ecological resources in urban environments and help to alleviate the urban heat island effect [46].

3.4. Ecological Network Construction and Analysis

3.4.1. Results of Resistance Surface Construction Based on AHP

The final integrated resistance surface of the demonstration area was generated by overlaying the individual resistance layers (Figure 7 and Figure 8). The results illustrate that areas with high resistance values form a network-like pattern, primarily linking urban centers. Four key zones—Taihu Lake New Area, Shengze Town, Qingpu Urban Area, and Jiashan County Town—exhibit significantly elevated resistance values, mainly due to their dense transportation infrastructure. These regions are characterized by high population density, extensive construction activity, fragmented landscape patches, and pronounced ecological stress. Consequently, they pose substantial resistance to species movement and human activity within the demonstration area. The spatial distribution of high resistance values is closely aligned with land use types and road networks. With ongoing urban expansion, construction land is likely to continue encroaching outward. Therefore, it is essential to define and enforce development boundaries for metropolitan areas to prevent uncontrolled urban sprawl and preserve ecological connectivity.

3.4.2. Ecological Corridors Identified Using MCR and Gravity Models

According to the MCR model, 333 ecological corridors were identified by removing duplicates from the initial results based on 33 ecological sources and the integrated resistance surface. These corridors form a relatively dense network, mainly concentrated in the central and southern parts of the demonstration area, where the water infrastructure is well developed. In contrast, urban construction zones lack ecological core areas due to intense human disturbances, resulting in fragmented corridors and disrupted ecological continuity [46].

The gravity model was used to calculate an interaction matrix among the 33 ecological source areas. A stronger interaction force between two sources indicates a more critical ecological corridor. In this study, 145 corridors with $G_{ij}\ge$ 100 were classified as primary ecological corridors. Corridors with 100 $>G_{ij}\ge$ 50 were designated as secondary corridors, totaling 67, while the remaining corridors were categorized as tertiary (Figure 9). Primary ecological corridors are mainly located along the administrative borders of the demonstration area, away from densely developed zones. These corridors form the structural backbone of the blue–green ecological network and play a vital role in maintaining ecosystem stability and connectivity, thereby requiring priority protection. Secondary and tertiary corridors are mostly distributed around villages and historic towns. Although they connect more isolated source patches, they demonstrate lower interaction strength and are more vulnerable to external disturbances.

Many ecological corridors pass through agricultural and aquatic ecosystems. The demonstration area has historically served as a major agricultural production zone with a deep-rooted farming tradition. Although some arable land has been converted to construction land due to urban expansion, a large portion of high-quality farmland is still preserved under the permanent basic farmland protection system. These areas act as critical ecological buffers between urban and rural environments. Moving forward, it is essential to continue safeguarding cultivated land and strictly control the expansion of urban development boundaries. In the southwestern part of Jiashan County and the central region of the demonstration area, large and densely interconnected water bodies present barriers to species movement. Therefore, it is crucial to prioritize the construction of wetland habitats around these aquatic areas to provide temporary stopover sites and shelters for migratory species.

3.4.3. Results of Blue–Green Ecological Network in Demonstration Area

(1) Recommended Width for Ecological Corridor Construction

The ecological corridors delineated in the demonstration area by the MCR and gravity models require appropriate width allocations to effectively provide ecological services [47]. Corridors only offer significant ecological value when they are sufficiently wide. The width of an ecological corridor greatly influences its function; wider corridors typically support greater species richness and enhanced biodiversity. The ideal width of a corridor depends on several factors, including species type, adjacent land use, corridor length, internal vegetation composition, and species dispersal behaviors [48]. The primary goal of blue–green ecological corridors is to maintain regional ecological stability and protect biodiversity. This study assigned width values based on the ecological characteristics of each corridor type. Primary corridors, which are located along the suburban periphery of the demonstration area and mainly pass through agricultural land, support small mammals and bird species; their width was set at 200 m. Secondary corridors, mostly found at the urban–rural interface and accommodating species such as fish and amphibians, were assigned a width of 60 m. Tertiary corridors, generally situated in rice paddies and supporting invertebrate species, were given a width of 30 m (

Table 10. Land use area and proportion within ecological corridors of different widths.

Corridor Type	Tree Cover	Shrubland	Grassland	Crop Land	Construction Land	Bare Land	Water Bodies	Wetland	Total (km2)
Primary corridor	36.34	0.44	0.93	74.08	12.82	11.13	5.01	1.15	141.91
	25.61%	0.31%	0.66%	52.2%	9.03%	7.84%	3.53%	0.81%
Secondary corridor	4.54	0.18	0.19	17.95	1.60	1.69	0.61	0.06	26.83
	16.92%	0.69%	0.72%	66.92%	5.96%	6.29%	2.28%	0.22%
Tertiary corridor	10.25	0.25	0.20	20.00	1.44	1.29	1.07	0.31	44.80
	22.87%	0.56%	0.44%	66.95%	3.23%	2.87%	2.40%	0.69%

). In these three corridor categories, arable land predominates the landscape, followed by tree cover, while the proportion of developed land is minimal. This composition suggests that the designated corridor lengths are environmentally suitable. The significant prevalence of biological land types, such as agriculture, woodland, and shrubland, provides a solid ecological foundation within the corridors. The minimal presence of construction land indicates that the corridors do not significantly encroach upon established urban areas, thus reducing potential conflicts with economic development. Furthermore, the limited development within the corridors minimizes disruptions to species movement and ecological connectivity. The ecological corridors defined by the MCR and gravity models, once assigned appropriate widths, proved to be ecologically valuable, promoting species migration and enhancing regional ecological resilience.

(2) Analysis of Blue–Green Ecological Network in Demonstration Area

The blue–green ecological network in the demonstration area consists of ecological core areas and corridors. This study identified 33 ecological core areas and 333 ecological corridors. These elements were spatially overlaid to form the final blue–green ecological network of the demonstration area (Figure 10).

Ecological source areas are assigned buffer zones to ensure ecological stability, incorporating surrounding land types, such as cultivated land and water bodies. Differentiated management strategies are implemented according to the classification of the source areas. Level 1 ecological sources, primarily wetlands, shelter forests, and areas of permanent basic farmland, require strict protection. Secondary ecological sources, including urban and rural parks, villages, and historic towns, should be subject to controlled development. Planning in these areas should focus on improving the quality of the living environment, while preserving both natural and cultural features. Currently, ecological source areas are largely absent within urban construction zones. Future development in these areas should adopt an ecological approach by increasing blue–green spaces within towns. This can provide stepping stones for species migration from surrounding ecological sources, help to restore fragmented corridors, and strengthen the integrity of the cross-regional blue–green ecological network.

Overall, implementing a blue–green ecological network is a long-term and incremental process. Prioritizing the protection and development of primary ecological sources and corridors will effectively reinforce the core structure of the network. This should be followed by gradually enhancing secondary ecological sources and corridors to improve landscape connectivity across the region.

3.5. Cross-Regional Exploration of the Demonstration Area from the Perspective of Territorial Spatial Planning

The demonstration area boasts a vibrant blue–green spatial foundation and rich historical and cultural resources, providing optimal conditions for developing a cross-regional landscape belt that harmonizes natural and human elements. Establishing a blue–green ecological network enhances the regional ecological security framework, improves environmental quality, and stimulates economically beneficial activities through ecological advancement. Despite the prevailing economic downturn, domestic tourism remains strong, particularly in terms of short-distance travel. Emerging travel trends, such as “reverse tourism” and “suburban micro-vacations”, reflect the “lipstick effect” in consumer behavior, where economic constraints drive consumers to seek cost-effective experiences that offer emotional fulfillment, rather than luxury purchases. Due to its strategic location and abundant natural and cultural assets, the demonstration area is well positioned to become a favored destination for affordable regional tourism among residents of Jiangsu, Zhejiang, and Shanghai. The following sections explore the realization of this vision through a cross-regional territorial planning approach, focusing on the development of landscape belts and the implementation of various ecological corridor strategies.

3.5.1. Analysis of Landscape Corridors Based on Natural and Cultural Resources

This study utilized Amap to gather Point of Interest (POI) data related to natural and cultural resources within the demonstration area, including urban and rural parks, themed specialty parks, historical and cultural towns, and heritage landscape neighborhoods. A kernel density analysis was then conducted in ArcGIS to generate a geographic clustering map of resource distribution (Figure 11). The results reveal six high-density resource clusters: Tongli Ancient Town, Shanghai Grand View Garden–Yuandang, Dianshan Lake–Zhujiajiao Ancient Town, Zhenze Ancient Town–Zhenze Provincial Wetland Park, Lili Ancient Town, and Xitang Ancient Town. Among these, the Dianshan Lake–Zhujiajiao cluster exhibits the highest level of aggregation, forming a highly cohesive area for ecological, cultural, and tourism activities. These six locations, recognized as resource hubs for tourism, show substantial spatial vitality and strategic potential. Future planning in these areas should prioritize the integrated advancement of ecological protection and cultural representation, fostering strong interaction between ecology, heritage, and industry.

By overlaying ecological source data, it becomes apparent that these clustered regions are considerably distant from the ecological core zones (Figure 12). To address this spatial disparity while preserving biological integrity, we propose the development of recreational buffer zones and a trans-regional tourism landscape corridor, governed by regulated expansion rules. The north–south landscape corridor focuses on historical and cultural recreation, linking three key regions: the Tongli Garden Study Area, the Dream of the Red Chamber Ecological Zone, and the Hanfu Cultural Experience Area. The east–west landscape corridor emphasizes natural recreational activities, connecting the folk culture and tourism region, the silk weaving history zone, and outdoor camping areas.

Creating a weekend-focused, short-distance tourism corridor that integrates both natural and cultural elements, while enhancing transit connectivity among key nodes, could generate significant economic benefits for the demonstration area. This approach, in turn, would foster a positive feedback loop for the establishment of ecological civilization. The landscape belt is a spatial strategy designed to harmonize ecological conservation with economic growth by safeguarding essential ecological services, thus promoting high-quality regional development.

3.5.2. Corridor Analysis Based on Current Functional Characteristics of Ecological Source Areas

To facilitate the implementation of the blue–green ecological network within the demonstration area’s territorial spatial planning, this study classifies the previously constructed corridors into four functional types. The classification is based on the current functions of ecological source areas, the characteristics of surrounding ecological substrates, and other relevant factors. The four functional categories are urban–rural park corridors, idyllic leisure corridors, historical and cultural corridors, and ecological resilience corridors (

Table 11. Types of functional corridors and implementation strategies.

Corridor Type	Strategies
Urban–rural park corridors	The majority of these corridors are designated as secondary routes. Residents regularly utilize them for daily and weekend leisure activities, as they link urban and rural parks at both termini. These corridors improve accessibility and communication between parks, while preserving biological integrity. Infrastructure enhancements are scheduled along the corridors, encompassing essential public services, athletic and fitness facilities, and cultural and recreational amenities. Activities including camping, marathons, cycling, and water sports are anticipated to enhance public participation and encourage healthy lifestyles.
Pastoral recreation corridors	These corridors predominantly link rural regions focused on cultural tourism and agricultural sectors. Consequently, they are essential in advancing nature education and recreation rooted in an agrarian legacy. Rural cultural tourism projects are actively created in accordance with local rural features to promote rural rejuvenation and economic growth, while conserving the extent of permanent basic farming. Examples encompass sericulture-oriented cultural experiences, agritourism, and low-altitude economic endeavors, including drone services and aerial sightseeing.
Historical and cultural corridors	This corridor connects various notable old towns within the demonstration region, highlighting the particular cultural landscape of Jiangnan water towns. It functions as a favored locale for brief vacations among local inhabitants. A tourism route linking these ancient towns was designed based on the area’s ecological carrying capacity. Initiatives like Yangtze River Delta ancient town tours and immersive cultural experiences seek to enhance integrated tourism and facilitate the synergistic advancement of the regional economy.
Ecological resilience corridors	The planning strategy emphasizes ecological protection and optimization, as the ecological sources linked by this corridor predominantly comprise forests and farmed areas. The major purpose is ecological construction, with economic operations severely restricted. Human activities are oriented towards the external buffer zones to reduce disruption. Woodland habitats are favored within the corridor to strengthen internal ecological community structures, improve ecological resilience, and foster species diversity. These actions preserve the integrity of the regional ecological framework.

, Figure 13).

(1) Urban–Rural Park Corridors: These corridors are primarily located in the central part of the demonstration area, including regions such as the Fenhu High-tech Zone, Jinze Town, Zhujiajiao Town, Yaozhuang Town, and Xitang Town. They connect various urban and rural parks, such as the East Taihu Lake National Ecological Tourism Zone, Shengdi Ecological Park, Baixian Lake Wetland Park, and Qingxi Country Park. The main function of these corridors is to serve the daily recreational needs of urban and rural residents.

(2) Idyllic Leisure Corridors: Mainly located in Jiashan County and the southern part of Qingpu District, these corridors link rural scenic areas, including the Xingfuli Rural Tourism Area, Changsheng Eco-Village, the Caojia Village Eco-District in Dafang Town, and Shanghai Zhangma. These areas offer rich countryside landscapes that support activities such as farm-based experiences, scenic drives, and hot spring therapy, making them ideal for residential tourism and family-oriented recreation.

(3) Historical and Cultural Corridors: These corridors connect key heritage towns, such as Tongli, Lili, Luhui, Xitang, and Zhujiajiao. They integrate significant cultural resources in the demonstration area, showcasing the Jiangnan water town style, where natural and cultural elements coexist. These corridors provide ideal conditions for educational and cultural tourism.

(4) Ecological Resilience Corridors: Primarily located along administrative boundaries linking the two districts and one county and in the southern part of Wujiang District, these corridors connect natural ecological resources, such as cropland and woodland. Their primary function is to provide migration pathways for species, maintain the structure of internal ecological communities, and incorporate external buffer zones to reduce human disturbance.

Overall, the ecological corridors are differentiated and classified based on their functional roles. Development strategies are tailored to the specific characteristics of each corridor type, aligning with the current development realities of the demonstration area. This approach promotes the coordination of human–environment relationships, supports refined ecological and economic development, and fosters high-quality regional growth, without compromising ongoing economic activities.

4. Discussion

4.1. Discussion of Research Results

Conventional methodologies for ecological network design often involve a sequence of “identifying ecological sources—constructing resistance surfaces—delineating ecological corridors”. This method frequently neglects a crucial initial step: assessing the particular ecological resource supply and demand conditions in the study area. Numerous prior studies have posited that their study regions experience significant urbanization pressure, thus confronting ecological security challenges [49,50]. Nevertheless, they have not evaluated whether the local ecological resource supply and demand are disproportionate, given the present environmental conditions. To bridge this gap, our study presents the ecological footprint model as a novel instrument for quantitatively assessing supply–demand connections prior to the creation of ecological networks. We initially evaluated whether the research area exhibited an ecological surplus or deficit, and then established a blue–green ecological network informed by this evaluation and the region’s ecological development objectives. The results indicate that the study area has lately shifted from an ecological deficit to a surplus, underscoring the necessity of bolstering this favorable trend by strategic network design. Secondly, regarding spatial breadth, this study diverges from the majority of existing ecological network research, which generally concentrates on administrative units [51,52]. Instead, we utilize a cross-regional spatial unit that encompasses many jurisdictions. This planning strategy addresses the constraints of administrative boundaries, promotes the integration of biological and cultural resources, and enhances functional complementarity among areas. We propose an open-space framework consisting of “two corridors and six hubs” that integrates natural systems with cultural landscapes. This study, unlike standard ecological network research that focuses exclusively on ecological features, integrates a social–functional perspective [53]. We categorize ecological corridors according to the present roles of their associated source areas, and provide tailored development options for each corridor type. This method allows the network to more effectively correspond with the region’s genuine land use dynamics and developmental requirements, thereby providing a more pragmatic avenue for planning and execution. This study offers theoretical and practical advances through a pre-assessment of ecological supply and demand, a cross-regional view, and the integration of ecological and social functions. It offers a novel avenue for developing and deploying ecological networks in non-administrative geographical environments.

4.2. Shortcomings and Limitations of Research Contributions

This study enhances the development of ecological networks and suggests techniques for inter-regional advancement. Nonetheless, numerous limitations persist, providing avenues for future investigation: (1) The identification of core areas relied on Morphological Spatial Pattern Analysis (MSPA), followed by the delineation of ecological source areas by utilizing landscape connectivity metrics. The analysis considered connection among sources; nevertheless, the edge width parameter utilized in MSPA was taken from prior research, without additional validation. Future research should investigate the appropriateness of this parameter across diverse spatial scales and for many target species to enhance methodological rigor. (2) This study’s selection of resistance elements incorporated both natural and anthropogenic forces, hence enhancing the scientific validity of the resistance surface. The weighting of these elements was predominantly based on the Analytic Hierarchy Process (AHP), which may involve subjective bias. Future study may include expert-based rating methodologies to improve the objectivity and precision of resistance weight allocations. (3) Following the identification and classification of biological corridors by Minimum Cumulative Resistance (MCR) and gravity models, corridor width values were predominantly assigned based on precedents from the existing literature. To improve ecological relevance, subsequent research should determine corridor width thresholds specific to regional target species and particular land use conditions, and further validate their ecological efficacy through empirical evidence. Mitigating these restrictions will enhance the theoretical underpinnings and actual implementations of cross-regional blue–green ecological networks.

5. Conclusions

This study examines the demonstration area as a case for developing a cross-regional blue–green ecological network, and suggests practical solutions for attaining ecological–economic synergy within the context of national territorial spatial planning. The primary conclusions are as follows:

(1) Following the inception of the demonstration area in 2019, the ecological condition of the region transitioned from a deficit to a surplus by 2020. This favorable shift demonstrates the efficacy of existing policy measures and emphasizes the necessity of perpetuating the “ecological priority and green development strategy.” Nonetheless, concerns persist due to continued development, encompassing habitat fragmentation and corridor disruption. An ecological network is critically needed to guarantee long-term ecological sustainability. The blue–green ecological network demonstrates excellent landscape connectivity among forestland, farmed land, and wetlands near the limits of the demonstration area. These regions are essential for sustaining regional ecological security, and require preservation. The absence of substantial ecological resources in urban construction zones adversely impacts the continuity of ecological corridors, resulting in fragmentation. To rectify this, ecological stepping stones must be systematically implemented to re-establish connectedness.

(2) This study transcends administrative boundaries by amalgamating natural and cultural elements to establish two cross-regional landscape corridors. The north–south corridor underscores the heritage of Jiangnan water towns, whereas the east–west corridor accentuates rural landscapes and agritourism. These belts fulfill many recreational needs and enhance regional tourism branding through visual landscape design and resource integration. This spatial framework serves as a reference for future study on the integration of ecological networks and tourism development at a cross-regional level.

(3) The study classifies ecological corridors into four categories by integrating ecological and socio-functional perspectives: urban–rural park corridors, idyllic leisure corridors, historical and cultural corridors, and ecological resilience corridors. Differentiated implementation options are suggested for each category and integrated into the spatial planning of the demonstration area’s territory. Urban–rural park pathways can be optimized by integrating them with the urban green space system to improve accessibility for routine recreation. Idyllic recreational corridors ought to be integrated with agricultural areas to facilitate leisure agriculture and rural tourism. Historical and cultural corridors necessitate coordinated planning to reconcile heritage preservation with landscape enhancement. Ecological resilience corridors can be integrated with disaster prevention and climate adaptation measures, enhancing water security and resilience to extreme weather events. The demonstration region serves as the inaugural practical instance for the integration of ecological and economic development in the Yangtze River Delta, providing a significant model for future research. It establishes a basis for enhancing cross-regional ecological planning in provincial and municipal border areas, addressing the difficulties of urban–rural disparity, and fostering cohesive, high-quality regional development.