A Two-Stage Evaluation Framework for Underground Space Development in Green Spaces: A Case Study of Binjiang District, Hangzhou

Abstract

In the current context of tight constraints on land resources in major Chinese cities, the development of underground space in green spaces (USGSs) has become an important approach to exploit land use potential and alleviate the contradiction between human and land resources. Evaluating USGS development potential scientifically is crucial for project site selection and improving underground space utilization. However, most studies have focused on underground space as a whole, with limited attention to single land use types, and research on USGSs has mainly concentrated on planning and design. This study proposes a two-stage evaluation framework for urban green spaces, identifying suitable development areas while safeguarding ecological functions. The framework evaluates from “restrictiveness” and “suitability”: first extracting developable green spaces by restrictiveness evaluation and then assessing development potential by suitability evaluation. This approach overcomes traditional methods that disregard prerequisite relationships among factors. A case study in Binjiang District, Hangzhou, showed that small green spaces and connectivity were key limiting factors for the development of USGSs. The proposed framework could provide some degree of reference for future development potential evaluation of USGSs, and the results could provide actionable guidance for high-density built environments similar to Binjiang District.

1. Introduction

China’s urbanization process continues to advance; the urbanization rate of its urban population reached 67% in 2024 [1], leading to increasingly prominent constraints on urban land resources [2]. Under the national strategic framework of ecological civilization construction [3], the allocation of new construction land quotas is subject to stringent regulation. Meanwhile, public demand for enhanced public service quality is growing. Therefore, the optimization and intensive use of existing urban land resources have become a central challenge in contemporary urban development.

Underground space constitutes a valuable urban resource [4,5]. Its rational utilization and coordinated three-dimensional development with aboveground infrastructure have become essential strategies to alleviating land scarcity, enhancing living environments, and addressing urban challenges [6,7,8,9]. Underground space in green spaces (USGSs), which refers to spaces developed beneath urban green spaces such as parks, square green spaces, and protective greenbelts, represents a distinctive type of urban underground space that integrates the ecological functions of green spaces with the utilization functions of underground construction [10]. Due to the limited surface structures and manageable ecological sensitivity of urban green spaces, USGS development substantially reduces functional conflicts during construction. Moreover, as public assets, these areas typically involve significantly lower implementation costs compared with other land use types. Therefore, the USGS approach has attracted increasing attention. Globally, several cities have accumulated extensive experience in the comprehensive development and utilization of USGSs, as exemplified by the underground stadium in Osaka Central Park, Japan, and the redevelopment projects in Beijing’s historic districts, China [11]. However, existing research on the development of USGSs has primarily focused on functional exploration and design optimization [12,13,14]. Pre-development assessments, including potential evaluation, spatial siting, and development suitability analysis, remain relatively insufficient. These assessments are critical for supporting evidence-based decision-making and reducing the risks associated with planning and construction. Most approaches rely on qualitative judgments employing functional and spatial design paradigms [15], with limited quantitative analysis. Therefore, it is essential to establish systematic and quantitative methods to evaluate the development potential of USGSs.

In recent years, preliminary evaluation indicator systems for underground space development have progressively evolved from having a singular emphasis on geological conditions to multidimensional and integrated frameworks, establishing a relatively systematic basis for assessment [16,17,18,19]. Numerous scholars have investigated the suitability [20], potential [21], and overall quality [22] of underground space development from diverse perspectives, thereby developing indicator systems that encompass geological conditions, socio-economic values, ecological and environmental constraints, as well as existing facilities and protection requirements. Within the geological dimension, primary considerations include fundamental factors such as topography and geomorphology (e.g., surface elevation, slope), engineering geology (soil and rock types, bearing capacity), hydrogeology (groundwater depth, aquifer characteristics), and geological hazards (seismic effects, sand liquefaction, and fault structures) [23,24,25]. The socio-economic dimension focuses on aspects such as population density, transportation conditions, land prices, and locational attributes to assess the potential economic and social benefits of development [26,27]. Ecological and environmental constraints primarily address restrictive elements, including ecological redlines, water source protection zones, and cultural heritage sites [28]. The dimension concerning existing facilities and protection requirements incorporates the type and height of surface buildings, underground infrastructure (such as metro systems, pipelines, and civil air defense structures), various regulatory planning controls [29], and the connectivity of underground spaces [30]. Building on these foundations, the integrated quality dimension synthesizes geological suitability, development difficulty, potential socio-economic returns, and ecological and environmental benefits to provide a holistic assessment of overall development potential. Overall, evaluation systems for underground space development have expanded from a geology-centered, single-dimensional perspective to multidimensional and multilayered comprehensive frameworks, thereby offering a more robust scientific basis for planning and decision-making. Nevertheless, the existing research predominantly focuses on evaluating underground space either at a regional scale or in relation to specific functional types (such as underground commercial spaces or metro systems) [31,32], with limited attention paid to assessment frameworks tailored to underground space beneath green spaces or other particular land use categories. Different land use types inherently possess unique constraints and value characteristics, underscoring the urgent need for targeted research into indicator construction and methodological approaches.

To date, researchers have developed and applied a range of evaluation methods. Among these methods, the Analytic Hierarchy Process (AHP) [33,34,35,36] remains the most widely used traditional approach, deriving indicator weights by constructing pairwise comparison matrices and synthesizing expert judgments. However, the strong reliance on subjective expertise in AHP often introduces potential bias. To address this limitation, subsequent studies have employed entropy weight methods based on the objective distribution characteristics of indicators [30], the CRITIC method for weighting based on inter-indicator correlations [37], and various combinations thereof [38,39]. Additionally, mathematical models, such as multi-objective linear weighting, fuzzy comprehensive evaluation, and multilevel gray evaluation, have also been applied in practice [40,41,42]. However, integrated evaluation results derived from existing methods generally rely on the weighted aggregation of multiple factors and often neglect the sequential or preconditional relationships among indicators. To mitigate the potential underestimation of risks associated with highly sensitive factors such as geological conditions, Zhu et al. (2016) [43] introduced the Most Unfavorable Rating Method (MURM) into the evaluation process, thereby enhancing the prudence and reliability of assessment outcomes. Nonetheless, significant limitations persist. Specifically, the absence of a mandatory distinction between high-sensitivity risk indicators (e.g., geological hazards, protected areas) and development potential indicators (e.g., population density, land value, and surrounding environment) can result in misleading conclusions. In such cases, areas subject to absolute development constraints—such as severe geological risks or critical habitats—may be erroneously identified as having development potential merely because of their high scores in terms of their socio-economic suitability. This bias is particularly pronounced in fine-grained, parcel-level assessments and may lead to substantial decision-making risks.

In view of this, this study proposed a novel two-stage evaluation framework for assessing the development potential of USGSs. Building upon existing indicator systems for underground space development evaluation, the framework integrates the bottom-line requirements for green space protection and the needs of urban development into a dual-dimensional system based on “restrictiveness” and “suitability”. Through the staged identification of non-developable zones, the framework then evaluates suitability in the remaining areas. The framework effectively mitigates the risks of misjudging high-sensitivity indicators, thereby significantly enhancing reliability. Using high-density built-up areas such as Binjiang District in Hangzhou as a case study, this research quantitatively identifies key constraints to USGS development and formulates targeted improvement strategies. The framework provides methodological support for USGS planning, with findings that provide actionable guidance for Binjiang District and similar high-density built environments.

2. Materials

2.1. Study Area

Binjiang District (72.2 km²) is situated on the south bank of the Qiantang River in Hangzhou City (see Figure 1). This district achieved a GDP of CNY 218.48 billion in 2022 (ranking fifth among China’s national high-tech zones) [44]. As the core zone of the Hangzhou National Innovation Demonstration Zone and the smallest of China’s ten world-class sci-tech park pilots, Binjiang District exhibits intense land use pressure, with 61.2% urban built-up coverage (44.16 km²) and only 7.69 km² of developable reserves. This scarcity necessitates underground space development as a critical solution.

The total area of GS in Binjiang District is 525.28 hectares (ha), with an uneven distribution across the regulatory planning units—Changhe (132.78 ha), Xixing (96.9 ha), Qianjiang (122.63 ha), Puyan (81.54 ha), and Jiangnan (59.57 ha)—as shown in Figure 1. Eight green space sites have been developed as underground spaces, all of which are currently utilized as parking facilities, with a combined capacity of 3274 parking spaces (approximately 11 ha in total floor area), as illustrated in

Table 1. Statistics of the existing USGSs in Binjiang District.

Developed USGS 1	Construction Mode	Parking Capacity	Area of GS (ha)	Underground Floors	The Type of Planned Land Use 2	Underground/ Green Space 3
①	Built separately	361	0.92	2	G3/S4	80%
②	Built separately	920	25.70	1	G1/S42	15%
③	Built separately	195	3.24	1	G1/S42	<50%
④	Built separately	199	19.60	1	G1	82%
⑤	Joint construction	281	0.76	1	G1/S42	85%
⑥	Joint construction	422	0.93	1	G1/S42	90.0%
⑦	Joint construction	133	0.33	2	G1	90%
⑧	Built separately	763	2.31	2	G3/S42	68%

¹ The name of the USGS development site is shown in Figure 2; ² The type of planned land use follows China’s Urban Planning Standard (GB50137-2011): G1 (public parks), S42 (public parking facilities), G3 (plazas), and S4 (transportation hubs); ³ “Underground/Green Space” denotes the ratio of the underground space’s projection area to the ground green space area.

. Among them, five were constructed separately, while three were jointly constructed in combination with the surrounding land. The northeastern public service center and IoT Town exhibit higher density in these underground spaces, and the Smart New Town on the southwest side has formed a relatively continuous underground space along its riverfront greenbelt (Figure 2). Overall, the development of underground spaces in green areas of Binjiang District is characterized by a single form of utilization, a lack of coordinated development, and poor development benefits.

2.2. Data Sources

Geological conditions and planned underground space utilization data were derived from the Special Plan for Underground Space Development and Utilization in Hangzhou (2012–2020) compiled in 2015, which is the most recent official planning document. All planning datasets underwent rigorous quality control by municipal authorities prior to release. They provided information on geological disaster susceptibility, hydrogeological conditions, and geotechnical characteristics.

Key ecological nodes and corridor distributions were derived from the Overall Urban Design of Binjiang District, Hangzhou, which was compiled in 2021. High-resolution remote sensing imagery (2023) was provided by the Binjiang Branch of Hangzhou Municipal Bureau of Planning and Natural Resources for extracting vegetation coverage-related data. These datasets were used for the calculation of ecological factors for evaluation. Imagery consistency was ensured through radiometric calibration and cloud-cover screening (<1%).

The land use data, land grade data, and service population distribution in 2022 were obtained from the Binjiang Branch of Hangzhou Municipal Bureau of Planning and Natural Resources. Point-of-interest (POI) data was obtained via the AutoNavi Map API in April 2023. These datasets were used to generate socio-economic factors, such as development costs and public service demand.

Additionally, field surveys were conducted to document existing underground developments in urban green spaces in 2023.

3. Methods

3.1. Constructing an Evaluation Indicator System for the Development Potential of USGSs

GS has dual ecological and social functions [45]. Ecologically, GS serves as the core of urban natural productivity and a critical component of the urban ecological support system. Socially, as integral components of the urban system, GS interacts with other subsystems to fulfill recreational, interactive, and leisure functions. In this study, urban GS is defined as “Green Space and Square Land” according to the Code for Classification of Urban Land Use and Planning Standards of Development Land (GB 50137-2011) [46], encompassing park green spaces (G1), protective green spaces (G2), and square land (G3).

Conventional assessment approaches focusing solely on geotechnical and hydrogeological parameters prove inadequate for evaluating underground space potential while preserving multifunctional requirements [47,48]. Instead, this study followed the “National Territorial Spatial Development Suitability Assessment” framework, integrating ecological and social functions into the objective layer through a conservation–development dialectical approach. This is because the National Territorial Spatial Development Suitability Assessment establishes a “restrictiveness–suitability” dual evaluation paradigm, which systematically examines human activity suitability based on natural conditions, socio-economic factors, and ecological constraints while ensuring ecosystem service stability and territorial security [49,50,51]. The restrictive assessment focuses on identifying existing human activities and issues within ecological conservation areas, as well as the scale and status of built-up areas. This can be applied to the threshold control of ecological security in urban green spaces and the identification of potential underground spaces for development. In contrast, a suitability assessment focuses on mapping the spatial distribution of suitable underground development within GS, enabling the full exploitation of social and economic benefits from the development of USGSs.

Therefore, a two-stage evaluation framework was proposed to assess the development potential of USGSs, grounded in bottom-line thinking (illustrated in Figure 3). First, it eliminated GS with non-developable underground spaces at the restrictive objective layer; then, it evaluated the underground developable potential of the remaining GS at the suitability objective layer. The selection of related indicators was based on previous studies and relevant standards for urban green space planning.

The restrictive objective layer was structured around two fundamental criteria: ecological criterion and safety criterion, aiming to determine the upper limit of underground space development in GS without breaching the bottom-line thinking. The ecological criterion was designed to maintain the ecosystem services of GS. At the individual green space scale, underground development should not disrupt surface ecological environments or impair vegetation growth. At the urban scale, underground development in any single green space should not compromise the fundamental functions of the urban green space ecosystem. The safety criterion focused on identifying surrounding risk factors. Underground space development was constrained by geological structures, topography, geomorphology, and hydrogeological conditions, while also impacting adjacent patches [52]. A risk identification should be conducted to ensure the safety of GS and the surrounding lands (see

Table 2. Evaluation indicators for the restrictive objective layer.

Criterion	Indicator	Evaluation Criteria
		Developable Underground Space in Green Spaces	Non-Developable Underground Space in Green Spaces (One-Vote Veto)
Ecological criterion	Subsurface development suitability of surface vegetation	Tree crown projection area coverage < 70%	Tree crown projection area coverage > 70%
	Importance of green space for ecological function	Secondary and tertiary landscape corridors and general green spaces	Water source protection areas, mountain core protection zones, primary ecological landscape corridors
	Impact of protected plants	No presence of ancient or rare trees	Presence of ancient or rare trees
Safety criterion	Slope suitability for construction	<20°	≥20°
	Engineering geology	Other rock and soil mass characteristics	The characteristics of rock and soil mass are soil–rock interfaces, a large distribution of soft soil, and the distribution area of strongly weathered soft rock
		Bearing capacity of rock and soil mass ≥ 90 Kpa	Bearing capacity of rock and soil mass < 90 Kpa
		Soft soil thickness < 5 m	Soft soil thickness ≥ 5 m
	Hydrogeology	Underground water depth ≥ 3 m	Underground water depth < 3 m
		Aquifer thickness ≤ 9 m	Aquifer thickness > 9 m
		Water outflow from a single well ≤ 3000 m3/d	Water outflow from a single well > 3000 m3/d
		Weak or non-corrosive groundwater	Strongly corrosive groundwater
	Geological disasters	Low-prone region of geological disaster	High-prone region of geological disaster
	Surrounding environmental factors	Setback blue line ≥ 10 m	Setback blue line < 10 m
		Distance from the outer rail centerline of railway trunk lines ≥ 30 m	Distance from the outer rail centerline of railway trunk lines < 30 m
		Distance from the high-voltage tower ≥ 15 m	Distance from the high-voltage tower < 15 m

).

In the suitability objective layer, GS patches determined to have development potential by the restrictive objective layer were assessed using three key criteria: economic, human orientation, and connectivity. This layer conducted a comprehensive benefit assessment that integrated economic, social, and urban development aspects to rank the potential of a GS patch for underground development. The economic criterion took into account both the costs and benefits of underground space development. This included the influence of the construction status of GS on the development costs of underground spaces, as well as the impacts of the scale, the morphological attributes of the GS patches themselves, and the surrounding land prices on the operational revenues of USGSs. The human orientation criterion prioritized meeting residents’ public service needs. The functions of USGSs should not only align with the primary functions of GS but also address the daily requirements of surrounding communities, thereby promoting equitable and high-quality public services. The connectivity criterion emphasized integrated underground space development, avoiding “isolated” green space underground layouts and aiming to promote interconnectedness between USGSs and adjacent underground infrastructure (see

Table 3. Evaluation indicators for the suitability objective layer.

Criterion	Indicator	Evaluation Criteria
		0	25	50	75	100
Economic criterion	Development cost of USGSs	Construction land planned as green space	—— 1	Existing green space	——	Vacant land planned as green space
	Economic feasibility of green space size	<0.3 ha green space area	0.3–1 ha green space area	1–2 ha green space area	2–5 ha green space area	>5 ha green space area
	Economic feasibility of green space morphology	Eccentricity > 10	——	Eccentricity 6.6–10	——	Eccentricity < 6.6
	Development value of USGSs	Low land price area	Sub-low land price area	Medium land price area	Sub-high land price area	High land price area
Human orientation criterion	Public service demand	Low-demand area	Sub low-demand area	Medium land price area	Sub-high demand area	High-demand area
	Public service supply gap	Low gap area	Sub-low gap area	Medium gap area	Sub-high gap area	High gap area
Connectivity criterion	Underground space connectivity potential	No adjacent underground space	——	——	——	With adjacent underground space

¹ “——“ indicates that the indicator is not applicable to this score level.

).

3.2. Determining Weights

This process combined entropy weight [53] and expert judgment [54] to establish comprehensive indicator weights. These weights were then utilized to compute the final development potential scores and to classify GS parcels into distinct levels of underground development potential.

The specific weight determination process was as follows. First, eight experts from the fields of urban–rural planning, underground space engineering practice, and urban ecology were recruited. Among them, four were professors/associate professors from well-reputed Chinese universities, and four were senior engineers from planning and design research institutes. All experts demonstrated a clear understanding of the concept of the development potential of USGSs. Through the ordered relation analysis method, they subjectively assigned values to derive the first set of evaluation indicator vectors for each development indicator of USGSs, as shown in Formula (1):

$${\theta }_{k^z}={({\theta }_{{k1}^z},{\theta }_{{k2}^z},\dots ,{\theta }_{{km}^z})}^T,$$

(1)

where ${0<\theta }_{{kj}^z}<1$ and $\sum {\theta }_{{kj}^z}=1$.

Subsequently, the entropy weight method was applied to objectively derive the weights of each evaluation indicator. At this stage, the second set of evaluation indicator weight vectors was obtained, as shown in Formula (2):

$${\theta }_{k^y}={({\theta }_{{k1}^y},{\theta }_{{k2}^y},\dots ,{\theta }_{{km}^y})}^T,$$

(2)

where ${0<\theta }_{{kj}^y}<1$ and $\sum {\theta }_{{kj}^y}=1$.

Finally, the comprehensive weight formula was used to derive the linear weighted combination of the two sets of indicator weight vectors, as shown in Formula (3):

$${\theta }_k=\alpha {\theta }_{k^z}+(1-\alpha ){\theta }_{k^y},$$

(3)

where $\alpha$ represents the subjective preference coefficient, while $1-\alpha$ denotes the objective preference coefficient, $\alpha ϵ\left[\mathrm{0,1}\right]$. The value of $\alpha$ was determined by the subjective judgments regarding the importance of both subjective and objective factors related to the development of USGSs, as well as the information available to decision-makers.

After discussions among the expert panel, the subjective preference coefficient $\alpha$ was set to 0.6. Accordingly, the entropy weight method contributed 0.4 to the total weighting. The final weights for the suitability indices are shown in

Table 4. Weights for the suitability objective layer.

Criterion	Indicator	Weight
Economic criterion	Development cost of USGSs	0.127
	Economic feasibility of green space’s size	0.178
	Economic feasibility of green space morphology	0.140
	Development value of USGSs	0.116
Human orientation criterion	Public service demand	0.154
	Public service supply gap	0.145
Connectivity criterion	Underground space connectivity potential	0.140

.

Therefore, the mathematical evaluation model for the development potential of USGSs is as follows:

$$L_1=C{\sum }_{j=1}^m{x}_j{\theta }_k$$

(4)

where $L_1$ denotes the potential value of underground space development in GS, $x_j$ represents the score of each indicator, and ${\theta }_k$ is the weight of each indicator. C represents the depth influence coefficient. Given that the assessment was limited to shallow underground space resources, C was set to 1.

The natural breaks method [55] was employed for cluster analysis to classify the evaluation results into different potential development levels. This approach was selected because it partitions data based on inherent natural breaks or inflection points, ensuring maximum inter-class differences and minimum intra-class variances while demonstrating robust statistical significance.

3.3. Detect Limiting Factors

The obstacle degree of each indicator in the suitability objective layer was calculated through the obstacle degree model [56,57], and the main limiting factors were identified. The specific calculation formula for the obstacle degree is as follows:

$$O_i={\displaystyle \frac{I_i\times {\theta }_i}{{\sum }_{i=1}^m{I}_i\times {\theta }_i}},$$

(5)

where $O_i$ represents the obstacle degree of indicator $\mathrm{i}$ to the development potential of USGSs. A higher $O_i$ value indicates greater hindrance. ${\theta }_i$ denotes the weight of indicator $i$, reflecting its degree of contribution. $I_i$ represents the degree of deviation and measures the gap between indicator $\mathrm{i}$ and the overall goal. This was calculated as $1-{\overline{x}}_i$, where ${\overline{x}}_i$ is the average score of indicator $\mathrm{i}$ after dimensionless standardization; m represents the total number of indicators.

The obstacle degree of each indicator in the suitability objective layer was calculated and is shown in

Table 5. Measurement of obstacle degree for indicators at the suitability objective layer.

Indicator	Average Score of the Indicator	Indicator Deviation Degree (I 1)	Obstacle Degree (O 2)
Development cost of USGSs	0.3	0.7	0.179
Economic feasibility of green space size	0.36	0.64	0.248
Economic feasibility of green space morphology	0.79	0.21	0.063
Development value of USGSs	0.52	0.48	0.128
Public service demand	0.67	0.33	0.108
Public service supply gap	0.87	0.13	0.040
Underground space connectivity potential	0.21	0.79	0.235

¹ I: degree of deviation between the indicator and the overall goal (see Equation (5)); ² O: Obstacle degree of the indicator (see Equation (5)).

.

4. Results

4.1. Evaluation Results

Figure 4 illustrates the results of all indicators in the restrictive objective layer. Through the implementation of a one-vote veto, the restrictive assessment results for the development of USGSs in Binjiang District were derived, as shown in Figure 5. Among 1021 patches of planned and existing GS, 385 patches were identified as suitable for underground space development, covering a total area of 366.79 ha, among which (1) G1 comprised 296 patches, totaling 310.38 ha; (2) G2 consisted of 74 patches covering 51.03 ha; and (3) G3 included 15 patches spanning 5.38 ha. According to the Urban Green Line Management Measures of Hangzhou City, the projection area of USGSs should not exceed 50% of the surface green space area [58]. Consequently, the maximum allowable area for developing USGSs in Binjiang District was 183.39 ha. Developable GS patches for underground development were primarily distributed around key civic and innovation hubs, including the Olympic Sports Center, Binjiang District Government, Binjiang Gymnasium, and Smart New Town Innovation Center.

Then, the development potential of GS patches suitable for underground space development was assessed at the suitability objective layer. The results of the indicators in the suitability objective layer are shown in Figure 6. After excluding GS patches where underground spaces had already been developed, the remaining GS patches were categorized into three groups using the natural breaks method based on their development potential. Specifically, GS patches with scores ranging from 6.06 to 8.38 were classified as high-potential GS, those scoring between 4.58 and 6.06 were considered medium-potential GS, and those scoring from 2.26 to 4.58 were identified as low-potential GS, as illustrated in Figure 7. The analysis revealed 94 high-potential GS patches covering 144.58 ha, 166 medium-potential GS patches covering 129.28 ha, and 109 low-potential GS patches covering 40.65 ha. A statistical summary of the development potential grades for GS in each regulatory planning unit is shown in

Table 6. The development potential statistics of GS in regulatory planning units.

Regulatory Planning Unit	High Potential		Medium Potential		Low Potential
	Quantity	Area (ha)	Quantity	Area (ha)	Quantity	Area (ha)
Xixing Unit	33	64.09	45	38.12	10	4.26
Qianjiang Unit	21	34.92	36	29.15	11	4.14
Jiangnan Unit	9	12.64	25	18.07	2	0.32
Puyan Unit	27	26.42	41	21.39	53	16.42
Changhe Unit	4	6.51	19	22.55	33	15.51

. The Xixing Unit contained a total of 33 high-potential GS patches, occupying an area of 64.09 ha, making it the largest both in terms of quantity and size. In contrast, the Changhe Unit only had four high-potential GS patches, spanning just 6.51 ha, which was the smallest in both aspects. Overall, the distribution of high-potential GS patches demonstrated a significant imbalance.

4.2. Analysis of Limiting Factors

The obstacle degree of the suitability objective layer indicators was calculated as shown in Table 5. The result revealed that the economic feasibility of different green space size and the connectivity potential of underground spaces are the two main factors limiting the development potential of USGSs in Binjiang District. The distribution of GS in this district was primarily characterized by small and fragmented areas. These GS patches were numerous, flexibly located, and mutually independent; used small amounts of land; and exhibited weak connectivity. The economic feasibility of developing underground spaces in small GS patches was relatively low. Moreover, there were strict limitations on the allowable development area for USGSs. Typically, this should not exceed 50% of the surface area of GS, although some cities allow a slightly higher limit of up to 70%. These constraints significantly increase the challenges of utilizing underground spaces in smaller GS patches. On the one hand, small GS patches serve as a mainstay of urban greenery in certain urban areas. On the other hand, due to their proximity to residential areas or commercial office districts, these GS patches serve substantial populations. Therefore, unlocking the potential of underground space development in small GS patches holds significant practical implications for optimizing urban land use efficiency. In terms of the connectivity potential of underground spaces, there are over 400 developed underground space projects with a total floor area exceeding 6.3 million square meters in Binjiang District. However, while some metro stations and commercial facilities, such as the Four Enterprises Joint Construction project in Smart New Town Innovation Centre, have successfully integrated interconnected underground spaces, most existing underground developments remain relatively isolated and lack connectivity.

5. Discussion

5.1. Strategies for Enhancing the Underground Development Potential of Small GS Patches

Given the extensive distribution of small GS patches and their close relationship with daily leisure and recreational activities, it is recommended to further optimize development management approaches by implementing zoning-based minimum size requirements for underground space development in GS. This strategy aims to enhance the development potential of small GS patches while maintaining their ecological and social functions. For instance, the Hangzhou Green Line Management Measures stipulate that green spaces smaller than 3000 square meters shall not be developed. However, with the continuous advancement of engineering technology, these management regulations can be optimized and adjusted in line with the times. Taking the underground parking garage on Miduqiao Road in Hangzhou City as an example, owing to the adoption of the new construction technology of the triple-shaft three-dimensional garage, the parking garage covers an area of 150 square meters and has 19 floors with a total of 125 parking spaces. Each shaft is equipped with a set of vertical lifting parking equipment that can operate independently. The average time for each vehicle to enter or exit the garage is only 90 s. The total investment in this garage is CNY 27.08 million. This parking garage occupies less land, and the average cost per parking space is not high. In urban core areas, which are characterized by high-density development with land at a premium, the adoption of a similar highly efficient use of urban land should be encouraged. It is recommended to implement zoning-based minimum size requirements for underground space development in GS. Specifically, in high-density development zones and aging residential areas with inadequate infrastructure, the minimum size of GS that is allowed for the development underground space could be adjusted downward to 1500–2000 square meters. This adjustment aims to further unlock the underground development potential of small GS patches, thereby enhancing land use efficiency and addressing urgent livelihood issues such as insufficient public facilities.

5.2. Strategies for Enhancing the Connectivity of USGSs

To enhance the connectivity of USGSs, it is essential to prioritize optimizing the planning layout of GS. Guided by the national territorial spatial master plan, local government should promptly develop special plans for underground space. These plans should clearly identify key development zones and define the overall functional layout of underground spaces. For these priority areas, detailed regulatory plans (DRPs) for underground spaces should be formulated in a timely manner. By integrating aboveground and underground planning, the specific requirements for developing USGSs can be incorporated into DRPs. This process should clearly define the refined boundaries, sizes, functions, and development intensity of USGSs. Additionally, it should specify interface requirements for connections to adjacent critical infrastructure, such as metro systems, commercial complexes, and large public service facilities, thereby ensuring seamless interconnection among major underground spaces (as outlined in

Table 7. The proposed underground functional layouts for GS in different locations.

Location	Proposed Underground Facilities in GS
Adjacent to rail transit stations	Commercial pedestrian spaces, cultural exhibition facilities, leisure facilities, and parking facilities
Adjacent to business–office areas	Leisure shopping, catering, fitness, entertainment, and parking facilities
Adjacent to large commercial facilities	Commercial and leisure facilities, cargo storage space, and parking facilities
Adjacent to large residential areas	Convenience–service facilities such as community commerce, health service stations, fitness facilities, and express delivery supporting facilities
Adjacent to municipal facilities	NIMBY (Not In My Back Yard) facilities such as substations and water pump rooms

). Improving the connectivity between USGSs and adjacent facilities can further unlock their development potential. For central GS patches in high-density urban development zones, a radial layout allowing them to connect with underground public spaces is highly encouraged in order to establish links with adjacent underground spaces via connecting corridors (as illustrated in Figure 8a). For linear green spaces along roads or rivers, it is recommended to adopt an axial underground space connectivity pattern (as shown in Figure 8b). The underground spaces of adjacent facilities are situated on either side of the green belt and are interconnected through corridors that link them to the underground spaces within the green belt. Additionally, to enhance the connectivity of USGSs, local regulations or normative documents should explicitly define the connectivity obligations (including financial and construction obligations) for underground space development across different land use categories (including urban green spaces). Relatively unified underground space construction standards should also be established, covering aspects such as floor height, development depth, and access point configurations.

5.3. Considerations for Stakeholder Engagement and Framework Transferability

Beyond technical assessments, the successful implementation of this framework necessitates addressing stakeholder engagement and contextual adaptability. Changes to green space functions may provoke public concerns over ecological and recreational trade-offs, demanding participatory processes—such as integrating co-design workshops during restrictive screening and visualizing development trade-offs via suitability maps—to align technical solutions with community values. Concurrently, while the framework responds to high-density urban conditions, its extension to moisture-stressed regions (e.g., arid cities with <10% green coverage) requires recalibrating restrictive criteria around water-sensitive factors such as aquifer vulnerability and innovating multifunctional typologies that couple stormwater harvesting with public amenities. Future efforts should formalize protocols for embedding social preferences within suitability weighting and establish climate-specific adjustment coefficients to enable robust cross-context transfer.

6. Conclusions

This study proposes a novel two-stage evaluation framework for assessing the development potential of USGSs based on the concept of “dual assessment”. The framework established an evaluation indicator system from two dimensions, “restrictiveness” and “suitability”, integrating green space protection baseline requirements and urban development needs. The indicator system was designed with two objective layers, five criterion layers, and fifteen specific indicators, providing a comprehensive approach. The framework was applied to Binjiang District, Hangzhou City, to demonstrate the maximum allowable USGS development area of 183.39 ha, identifying 94 high-potential green space patches (144.58 ha). An obstacle factor analysis revealed size and connectivity as key limiting factors, informing targeted enhancement strategies.

There are certain limitations in this study. Data constraints prevented the incorporation of factors such as development depth and intensity, which may influence the ecological and social outcomes of underground development. The empirical application is restricted to Binjiang District, Hangzhou, which limits the generalizability of the findings. Comparative analyses involving regions with similar conditions (such as Singapore, and Tokyo) are necessary to validate and enrich the evaluation framework’s applicability. Future research should refine the evaluation system by integrating additional key indicators and investigating how the framework can be adapted to provide guidance under diverse environmental conditions. This will facilitate the development of a more robust and universally applicable framework for underground space development potential assessments and improve its transferability across different urban contexts.