Sustainable three-dimensional (3D) space optimization in high-density urban areas: Drivers, synergies, and multi-method insights

doi:10.1016/j.regsus.2026.100348

Abstract

Abstract:

Spatial conflicts in high-density urban areas impede sustainable development, therefore, such cities urgently require sustainable three-dimensional (3D) space optimization. However, existing studies lack a systematic understanding of driving factors and stakeholder differences. This study established an integrated framework using grounded theory analysis of stakeholder interviews, a bibliometric review of academic literature, and system dynamic model and identified five core drivers (regional suitability, human-centred philosophy, innovative design, management capacity, and transformative technology) for sustainable 3D space optimization in high-density urban areas of Zhejiang Province, China. We compared word frequency counts from interviews using co-occurrence analysis in the literature to highlight divergent stakeholder priorities. Word frequency analysis revealed that residents mentioned keywords about human-centred philosophy approximately three times more frequently than experts, highlighting notable divergences in priorities among the stakeholders. Moreover, while co-occurrence analysis identified management capacity as a central theme in scholarly discourse, word frequency analysis ranked it the last among practitioners, underscoring a notable academic-practical difference. Ultimately, based on grounded theory and co-occurrence analyses, we developed a conceptual framework reflecting the relationships between the five core factors and their internal functions. This framework integrates urban research methodologies, providing planners with flexible tools and suggesting the formulation of policies based on actual circumstances, to achieve sustainable development in high-density urban areas.

Key words: Three-dimensional (3D) space, Co-occurrence analysis, Grounded theory (GT) analysis, System dynamic model, High-density urban areas, Zhejiang Province

KONG Bowen, LIU Haoxuan, ZHANG Luyao, TANG Chun’an, ZOU Baoping. Sustainable three-dimensional (3D) space optimization in high-density urban areas: Drivers, synergies, and multi-method insights[J]. Regional Sustainability, 2026, 7(3): 100348.

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Type	Characteristic	Number	Percentage (%)
Age	18-40 years old	15	62.5
Age	41-70 years old	9	37.5
Residence	Hangzhou City	16	66.7
Residence	Jiaxing City	8	33.3
Group	Resident	12	50.0
Group	Expert	12	50.0
Educational level	Bachelor’s degree	8	33.0
	Master’s degree	11	46.0
	Doctoral degree	5	21.0

Core category	Sub-category	Concept
Regional suitability	(1) Geographical factor	(1) Geological condition, climatic suitability, and topographical complexity
	(2) Historical-cultural compatibility	(2) Historical-cultural preservation and cultural element representation
	(3) Technical adaptability	(3) Supporting facilities condition, technical proficiency, resident acceptance, and technological innovation capacity
	(4) Project economic viability	(4) Fiscal status, market vitality, and commercial development potential
Human-centred philosophy	(5) Livelihood project	(5) Demand-oriented and regional optimization
	(6) Resident quality of life	(6) Human settlement quality, accessibility, comfortability, and public open space
	(7) Inclusivity	(7) Resident participation level, technical barrier, and vulnerable group
Innovative design	(8) Spatial utilization efficiency	(8) Functional diversification and spatial layer connectivity
	(9) Eco-friendly design	(9) Low-carbon energy efficiency and environmental destructiveness
	(10) Specialised design	(10) Targeted design, personalised innovation, barrier-free design, and new technology empowerment
Management capability	(11) Project resilience	(11) Operational cost, project efficiency, and emergency response capacity
Management capability	(12) Management philosophy	(12) Multi-stakeholder collaboration and intelligent management
Transformative technology	(13) Technological disruption	(13) Market disruption, lifestyle transformation, and frequent technology iteration
	(14) Cost reduction	(14) Management efficiency enhancement, construction cost reduction, and design process optimisation
	(15) Holistic improvement	(15) Transportation improvement, environmental quality improvement, and spatial user experience

Cluster	Keyword
Cluster 1: technology-driven spatial optimization	Algorithm, artificial intelligence, autonomous driving, big data, challenge, decision-making, drones, information, Internet, network, optimization, region, safety, smart city, technology, traffic, urban design, and vehicle
Cluster 2: ecological resilience in high-density environment	Adaptation, air quality, air-pollution, climate change, green infrastructure, heat-island, impact, pollution, resilience, risk, temperature, urban planning, and vulnerability
Cluster 3: human-centric spatial experience	Accessibility, benefits, built environment, environment, green space, health, mental health, perception, physical activity, public health, restoration, space, and walking
Cluster 4: governance and policy frameworks	Dynamics, energy, Geographic Information System (GIS), governance, innovation, management, performance, policy, site selection, suitability, sustainability, and urban
Cluster 5: ecological systems and land use dynamics	Biodiversity, conservation, diversity, ecology, ecosystem services, infrastructure, land use, landscape, and urbanization