From Resource-Based City to Sustainable Metropolis: The Infrastructure Logic Behind Thirty Years of Urban Expansion in Panjin

Urban Expansion as an Infrastructure Narrative

Global cities cover less than 1% of the Earth's land surface, yet they host more than half of the global population and generate over 70% of economic output. Urban expansion has never been merely a geographical shift of boundaries outward; it is also a material process in which artificial systems—roads, pipe networks, electricity, communications, water utilities, and public facilities—are continuously densified and extended. A study published in *Scientific Reports*, using Panjin, Liaoning, China as a sample, employed deep learning and time-series remote sensing data to track, pixel by pixel, the trajectory of impervious surface change from 1990 to 2020. The data themselves are academic, but the urban evolution paths they reveal are precisely a mirror of the long-cycle allocation of infrastructure capital.

Panjin: A Typical Sample of a Resource-Based City

Panjin is located in the Liaohe River Delta and flourished because of oil. From the 1960s to the mid-1980s, relying on the Liaohe Oilfield and related petrochemical industries, Panjin experienced rapid economic growth. However, the non-renewability of mineral resources has caused many resource-based cities to encounter weak growth after entering industrial maturity. In order to maintain momentum, cities often expand their built-up areas in a more extensive manner, leading to problems such as inefficient land use, longer commuting distances, and declining returns on infrastructure investment. Oil towns in Alberta, Canada, and the Ruhr region in Germany have all experienced similar phases of spatial disorder.

Panjin's remote sensing data quantify this process: the built-up area was approximately 312.75 square kilometers in 1990, growing to 489.49 square kilometers by 2020, an increase of 56.51%, with an average of nearly 5.89 square kilometers of hardened surface added each year. Behind these figures lies a large number of new roads, industrial parks, residential areas, and supporting facilities, involving a huge engineering contracting and building materials supply chain. Even more noteworthy is the evolution of spatial form—early urban construction showed leapfrog development and edge expansion, resembling "point breakthroughs" and "edge-hugging sprawl" in infrastructure investment. After 2016, however, infill development within the city began to dominate. This marks a structural shift in the logic of Panjin's infrastructure investment.

From "Leapfrog" to "Infill": A Switch in Engineering Capital Logic

Leapfrog expansion usually relies on large-scale transportation infrastructure to provide new accessibility, such as urban expressways or newly developed zones. This model was effective during the period of rapid industrialization, but it also tends to cause redundant allocation of infrastructure and low-density land sprawl. Edge expansion is relatively moderate, yet it still continuously lengthens the physical extent of municipal pipe networks and increases maintenance costs. Infill expansion, in contrast, implies renewal, functional replacement, and density enhancement within the existing built-up area—precisely the model that many sustainable urban planners hope to see.Research indicates that Panjin entered an infill growth stage after 2016. This timing coincides with the deepening of the policy to revitalize the old industrial bases in Northeast China, and also aligns with the overall shift in China's urban development philosophy from "quantitative expansion" to "quality improvement of the existing stock". Infill expansion imposes different demands on the engineering industry: no longer leveling land and laying new pipe networks, but renovating old urban districts, upgrading underground pipe networks, optimizing above-ground space, and embedding smart city infrastructure. The financing structure of such projects also relies more on public-private partnerships, special-purpose bonds, and urban renewal funds, rather than traditional bank loans and land finance.

Rebalancing Infrastructure in Resource-Based Cities

The most serious challenge facing resource-based cities is the "lock-in effect": infrastructure built early on around a single resource industry—such as mining railways, dedicated pipelines, and worker housing areas—can hardly serve new industries after resources are exhausted. Although Panjin's built-up area expansion has slowed, quality issues are becoming increasingly prominent. The declining spatial compactness of impervious surfaces suggests that even though the city has expanded in physical scale, the connectivity efficiency between functional blocks may not have improved correspondingly. Traffic congestion, urban waterlogging, and biodiversity loss have systematically reduced the service efficiency of infrastructure.

Looking at global experience, Germany's Ruhr region reorganized its regional transportation and ecological networks by converting derelict industrial land into green corridors and creative industry parks. Canadian oil cities, meanwhile, have attempted to achieve diversified linkages through regional infrastructure corridors. Panjin is located in the Liaoning Coastal Economic Belt, with port resources and the Liaohe River ecological environment. Its next round of infrastructure upgrading should not focus solely on the increase or decrease of built-up area, but should focus on: a multimodal logistics network connecting the port hinterland with industrial parks, coordination between oilfield equipment renewal and new-energy power grids, resilient renovation of the Liaohe Estuary wetland protection and urban drainage system, and the layout of digital infrastructure centered on data centers.

Data Methods Herald the Upgrading of Infrastructure Planning Tools

What is most noteworthy about this study is not the area data of a particular year, but its methodology. The research team adopted deep learning and a combined "temporal-spectral-textural" optimization method, achieving a trajectory classification accuracy of 93.10% and an urban expansion timing identification accuracy of 84.24%. This means that infrastructure planners can, for the first time, understand the change trajectories of urban impervious surfaces in near real time and with sub-meter accuracy.

For infrastructure investment institutions, such data capability is extremely valuable. Feasibility analyses for PPP projects, long-term demand forecasts for urban public utilities, and traffic assumptions for toll roads and utility tunnels all depend on accurately grasping the boundaries of urban spatial growth. Traditional statistical yearbooks and sample surveys are often lagging and coarse, whereas remote sensing intelligent identification can provide spatial data with high temporal frequency, placing engineering capital allocation on a more reliable physical reality.

Regional Competition and Urban Long-TermismFrom a geo-economic perspective, Panjin is by no means an isolated case. Numerous resource-based cities across Northeast China all need to answer the same question: when the resource dividend fades, what kind of infrastructure can support the next round of growth? The answer may lie not in continuing to expand urban boundaries, but in improving the operational efficiency and digital capabilities of existing assets. Panjin's shift from expansion to infill represents a microcosm of China's urban development model—over the past three decades, China's urbanization rate has risen from 17.9% to 63.89%, and ultimately the intensity of construction must transition from high quantitative growth to deep qualitative improvement.

For resource-based cities in both the Global South and the Global North, Panjin offers a comparable empirical case. The combination of remote sensing and deep learning is becoming a foundational tool for urban infrastructure planning; meanwhile, the transformation of urban form serves as a comprehensive reflection of national strategy, capital flows, and demographic trends. The ten, twenty, and thirty years of Panjin are, in effect, an evolutionary history of how infrastructure shifts from serving industrial cycles to serving the long-term lifecycle of the city.

Future research should also address: Does infill expansion genuinely improve infrastructure utilization efficiency? Does it deliver better accessibility to public services? And how can remotely sensed urban expansion be linked with infrastructure performance indicators such as energy consumption, carbon emissions, and commuting time? Only by coupling spatial form data with engineering-economic models can cities truly move toward sustainable infrastructure governance.