Spatial Characteristics of Brownfield Clusters and “City-Brown” Patterns: Case Studies of Resource-Exhausted Cities in China

Abstract

In the post-industrial era, many cities have experienced the decline of heavy industry and traditional manufacturing, leading to the widespread emergence of brownfields. These often cluster geographically, forming “brownfield clusters” characterized by shared spatial and functional traits. Our research examined these phenomena within 10 resource-exhausted cities in China, employing kernel density analysis to explore the spatial dynamics within and among these clusters and their urban contexts. We identified three distinct spatial relationships between brownfield clusters and their host cities (coupling, juxtaposition, and encircling), with a detailed case study in Huangshi City further classifying the clusters into five categories based on their dominant factors, spatial morphologies, types of brownfields, and internal dynamics. The study reveals that the spatial configurations of brownfield clusters are significantly influenced by geographic features, transportation infrastructure, and policy frameworks. Based on these findings, we propose targeted regeneration strategies for each cluster type. This research not only enhances our understanding of brownfield challenges and opportunities in China’s resource-exhausted cities but also serves as a valuable reference for other cities and regions worldwide facing similar challenges.

1. Introduction

Brownfields are broadly defined as sites with known or potential contamination resulting from human activities, where reuse is contingent upon site-specific risk assessment and remediation tailored to the intended use [1,2,3,4]. The primary types of brownfields include idle industrial and infrastructure sites, mining waste sites, landfills, war brownfields, cemeteries, and disaster sites [5]. In the information age, the decline of heavy industry and traditional manufacturing has led many cities to witness the closure of many factories and businesses, giving rise to numerous brownfields [6,7,8]. These brownfields are typically not isolated but tend to be concentrated in specific areas. This concentration is driven by factors such as the availability of natural resources, transportation infrastructure, and other location-specific advantages that once supported industrial activities [9]. Scholars have referred to this phenomenon as “brownfield clusters” [5,10,11,12]. Although there is no universally accepted definition of a brownfield cluster, the concept generally acknowledges the geographic grouping of brownfields [12] driven by shared resources, production factors, and infrastructural conditions. This clustering has been observed in various industrial and mining regions worldwide, including the Rust Belt in the United States, the Ruhr area in Germany, and post-socialist cities in the Czech Republic.

Brownfield clusters are notably more prevalent in China than in the United States and Europe, largely due to the country’s top-down regulatory policies that can quickly generate numerous brownfield sites within specific regions. For instance, the enactment of land policies aimed at phasing out secondary industries in favor of tertiary sectors has led to the shutdown of many small industrial enterprises in Chinese cities such as Guangzhou, Shijiazhuang, and Ningbo. This has resulted in the creation of brownfield clusters. While the rapid proliferation of brownfields presents significant challenges to urban development—both financially and strategically—it also offers opportunities for innovative land use practices. These include intensive land repurposing and the adoption of holistic regional urban planning strategies [13]. It is estimated that there are currently around 1 million brownfield sites in China [14], with brownfield clusters being the predominant form. These clusters typically consist of former industrial sites that are geographically concentrated in a particular area. This trend is especially pronounced in China’s resource-exhausted cities, many of which were initially established for mining and industrial purposes. Consequently, large tracts of industrial and mining land occupy central city areas, eventually evolving into underutilized urban spaces following their closure.

Brownfield clusters embedded within cities have a profound impact on the spatial structure and ecological configuration of urban areas [7,13,15,16,17,18,19]. As urbanization in China accelerates, there has been a shift from extensive urban expansion to intensive stock renewal, with brownfield regeneration playing a crucial role in urban planning and revitalization. This approach is crucial not only for contemporary urban development but also as a key strategy in the construction of ecological civilization and new urbanization. From a regional perspective, brownfield regeneration offers benefits such as guiding urban growth, creating employment opportunities, and stimulating economic activity [20,21,22,23]. Additionally, addressing urban decay and improving environmental quality on a large scale contribute positively to promoting environmental equity and alleviating urban sprawl [24,25]. Thus, a systematic understanding of brownfield clusters and their spatial interplay between these clusters and cities within a regional context is fundamental for devising effective regeneration strategies.

The primary objective of systematically understanding “brownfield clusters” is to analyze their spatial characteristics, specifically identifying patterns of aggregation and the underlying logic within these formations. Although previous research has not formally defined these aggregation patterns, it has consistently recognized the presence of clustered brownfield sites around specific features. For example, a study in Brno, Czech Republic, identified 124 brownfield sites grouped into three distinct clusters within the city center. These clusters were concentrated at intersections of railway lines, along rivers, or near energy plants [12]. The economic downturn of the 1960s, which was marked by crises in the coal and steel industries, resulted in the emergence of numerous mining and steel brownfields along the banks of the Emscher River [26]. Many studies acknowledge the critical role of location in the regeneration of brownfield sites [26]. Heberle and Wernstedt [27] advocate for a comprehensive evaluation of brownfield sites that extends beyond their immediate spatial context to include higher hierarchical levels, promoting a shift towards a “regional scale approach” as opposed to the conventional “site-based approach”. For instance, Liu et al. (2022) [28] observed regeneration efforts in the brownfield clusters of industrial zones in Longhua, Shenzhen, amidst significant industrial restructuring and urban transformation. Pizzol et al. (2016) [29] developed a prioritization screening tool for brownfield regeneration that assesses sites based on their economic, social, and ecological potential as well as stakeholder preferences to identify high-priority sites within clusters on a regional scale. In a systemic evaluation, Zhong et al. (2020) [19] assessed the ecosystem services provided by brownfield clusters in Xuhui District, Shanghai. They advocated for implementing green initiatives in densely populated and economically vibrant areas rather than limiting such efforts to designated ecological construction zones.

These studies demonstrate that the regeneration of brownfield sites is significantly influenced not only by their intrinsic characteristics but also by their urban location, underscoring the need for systemic integration of brownfield clusters into urban development strategies. Nevertheless, much of existing research has focused on characterizing individual brownfield sites, analyzing natural elements (such as vegetation cover, topography, and water bodies), locational factors (including site accessibility and proximity to city centers), and artificial components (such as buildings and structures) [12]. Yet, there has been limited investigation into the spatial relationships between brownfield clusters and urban areas as well as their underlying distribution patterns. Furthermore, the spatiotemporal dynamics between brownfields and cities play a significant role in the regeneration process. For instance, financial resource accessibility often varies significantly between brownfields located in city centers and those on the peripheries and between sites in traditional industrial cities and those in modern manufacturing contexts. This discrepancy extends to the cultural and historical value of brownfields, where sites with industrial heritage are frequently repurposed into museums and heritage parks, while others struggle with challenges related to “industrial upgrading”. Furthermore, there is a notable research gap in understanding the chronology of urban and mining development, which is critical for China’s resource-dependent cities. The complex interplay of Chinese industrial fluctuations, national policies, and broader macro-contextual factors is deeply embedded within the cultural fabric, influencing the redevelopment potential and strategies for these brownfields.

This study examined the distribution of brownfield clusters and spatial dynamics between cities and brownfields in 10 representative Chinese resource-exhausted cities. Resource-based cities constitute a prevalent urban typology within China’s urban system, primarily distinguished by their heavy reliance on the extraction and processing of non-renewable resources (e.g., minerals, lumber, and oil) within their geographical regions [30]. These cities typically feature a significant amount of industrial infrastructure and land. According to the National Sustainable Development Plan for Resource-Based Cities (2013–2020) issued by the State Council in 2013, a total of 262 resource-based cities were identified. These cities are further subdivided into four categories: growing (31 cities), mature (141 cities), exhausted (67 cities), and regenerating (23 cities). Resource-exhausted cities are characterized by mineral resources undergoing a process of decline or depletion, where the cumulative extracted reserves have surpassed 70 percent of the recoverable reserves. These cities, often originating and thriving from mining activities, exhibit a long-term reliance on resources and a homogenous industrial structure [31]. Consequently, they frequently encounter challenges stemming from resource depletion, such as decline of the extractive industry, rapid closure of numerous mines and factories, weakening of governmental financial capacity, and worker unemployment, potentially leading to social conflicts [32,33]. Their brownfield sites are typically extensive and clustered, and the type is mostly dominated by mining brownfields. In comparison to other industrial cities, resource-exhausted cities urgently require brownfield regeneration and urban transformation.

The primary aim is to deepen our understanding of brownfield characteristics and to develop effective regeneration strategies at a regional scale. Furthermore, the insights gained from this research are relevant to cities globally experiencing similar challenges with brownfield clusters. From a larger pool of 67 resource-exhausted cities in China, the 10 cities were carefully selected based on a set of criteria that include their distinctive natural landscape patterns, mineral resource profiles, urban and industrial development histories, key policy impacts, and availability of comprehensive socioeconomic data.

This research was structured to address the following key questions:

(1)

How are brownfield sites distributed in resource-exhausted cities?

(2)

What are the spatial interrelationships between brownfield clusters and urban cities?

(3)

What are the factors affecting the spatial characteristics of brownfield clusters?

Based on the three aforementioned questions, this study first identified brownfield clusters in ten cities using remote sensing images. Subsequently, it analyzed the spatial characteristics of these clusters employing the kernel density estimation method. This analysis encompassed the spatial distribution patterns of brownfield clusters and their relationship with urban built-up areas. Finally, the study examined the types of brownfield clusters and the factors influencing them in order to propose targeted regeneration strategies.

2. Materials and Methods

2.1. Study Areas

The selected cities, chosen for their diversity and representativeness in terms of urban size, geographical characteristics, and industrial development, confront significant challenges, including sluggish urban growth and ecological deterioration. These challenges primarily stem from the depletion of mineral resources and industrial restructuring. The dimensions of urban size can be conceptualized as comprising three interlinked components: economic scale, population scale, and spatial scale [34]. These were represented by urban gross domestic product (GDP) in 2020, the permanent population in 2020, and urban areas, respectively. Cities characterized by resource exhaustion typically exhibit smaller economic scales, with 70% of these cities having a regional GDP less than CNY 50 billion in our sample. Although 80% sampled cities’ GDP exceeded CNY 50 billion, there is a pressing need to face the challenges of brownfield regeneration within these economically viable cities [30,31]. The population scale, an important indicator of urban agglomeration, varied significantly across our sample, ranging from 0.55 million to 2.85 million, encompassing all four types defined by national standards [35]. This highlights the diversity of our sample. The area of these cities ranged considerably, from 1754 to 18,218 km², demonstrating a significant degree of representativeness (Appendix A). Geographically, these cities are spread across five major regions—northeast, northwest, east, central, and southwest China—each showcasing unique regional features and urban morphologies (Figure 1). Moreover, the selection reflects a broad spectrum of natural landscape patterns, types of mineral resources, sequences of urban and industrial development, levels of urban development, and critical industrial development policies (Figure 2). This variability offers a rich context for investigating brownfield regeneration strategies and serves as a microcosm for the larger group of 67 resource-exhausted cities throughout China.

Most resource-exhausted cities were initially established around mining production sites and residential areas, driven by the availability of mineral resources, which are typically distributed along mineral veins. In the early stages, the extraction, processing, and transportation of these resources often depended heavily on natural water bodies, which significantly influenced the spatial distribution of brownfield sites. Consequently, the layout of these sites is closely linked to natural landscape patterns. Meanwhile, the spatial distribution of brownfield sites exhibits a strong spatiotemporal correlation with the development of the city and its respective industries [36]. Resource-exhausted cities occupy a unique position as transitional zones between industrial and information societies, encompassing a blend of traditional heavy industries and emerging sectors. The spatial arrangement of these cities is primarily influenced by several factors, including the availability of natural resources (e.g., water and minerals), national policies (including initiatives for industrial upgrading and transformation), and urban planning efforts. Furthermore, the development of industries within these cities is further shaped by the specific types and availability of mineral resources as well as overarching national policies. For instance, during China’s third-line construction era, many cities were encouraged to ramp up heavy industrial production. The key factors influencing the spatial characteristics of brownfield clusters include the natural landscape configuration, the distribution and nature of mineral resources, the chronology of urban mining development, and relevant policies.

2.2. Data Collection

In the first step of collecting geographic information for the 10 cities, the study acquired city administrative boundaries from the Resource and Environmental Science and Data Center (RESDC). This was complemented by digital elevation models (DEM) sourced from the Geospatial Data Cloud. Additionally, information on water bodies within the cities was collected from the National Catalogue Service for Geographic Information (NCSGI). The second step involved gathering socioeconomic data for the 10 cities. This included key socioeconomic indicators such as GDP, population, and city historical data, which were obtained from sources like the “China Statistical Yearbook” and the “Statistical Communiqué of the People’s Republic of China on the National Economic and Social Development”. Moreover, information on the type and spatial distribution of mineral resources was sourced from the National Mineral Database (NMRD). The third step focused on collecting data essential for identifying brownfield sites. This included remote sensing images from Google Earth Pro, points of interest (POIs) from Baidu maps, urban functional zoning maps from government official websites, and Baidu heatmaps. All data are exclusively from the year 2020 (

Table 1. Data resources.

Data	Type	Contents	Usage	Resources
Administrative subdivision	Vector data, shapefile data of surface	Administrative boundaries	Basic geographic information	Resource and Environment Science and Data Center (RESDC): http://www.resdc.cn/Default.aspx, accessed on 20 August 2020.
Digital elevation models (DEM)	Raster data in 30 m resolution	Topographic elevation	Basic geographic information	Geospatial Data Cloud (GDC): http://www.gscloud.cn/, accessed on 20 August 2020.
Water bodies	Vector data, shapefile data of surface	River, lake, etc.	Basic geographic information	National Catalogue Service for Geographic Information (NCSGI): http://www.webmap.cn/main.do?method=index, accessed on 20 August 2020.
Built-up area	Vector data, shapefile data of surface	Built-up area	Basic geographic information
Socioeconomic data	Text	GDP, resident population, urbanization rate	Basic information about the city	China Statistical Yearbook and National Economic and Social Development Statistical Bulletin
Mineral resources	Image	Type and spatial distribution of mineral resources	Basic information about the city	National Mineral Database (NMRD): http://data.ngac.org.cn/mineralresource/index.html, accessed on 2 December 2020.
City chronicle	Text, image	Urban history and industrial development	Basic information about the city	Government websites, government departments, literature, library
		Industrial closures, industrial and mineral distribution, significant brownfield projects, etc.	Brownfield identification
Remote sensing images	Image in resolution: 15 m to 15 cm	Satellite Imagery	Brownfield identification	Google Earth Pro
Industrial and mining POIs	Vector data, shapefile data of point	Industrial and mineral distribution	Brownfield identification	Baidu Map
Land use/cover	Image	Current land use/planning map	Brownfield identification	Government websites

).

2.3. Research Framework

From a systematic perception perspective, the spatial characteristics of brownfield clusters can be understood in two dimensions: the spatial distribution characteristics of brownfield clusters within cities and the spatial patterns of brownfield clusters themselves. This necessitates analyzing brownfield clusters at both the city scale and the cluster scale. Firstly, this study introduced the concept of the “City-Brown” spatial pattern to elucidate the spatial relationship between brownfield clusters and the urban built-up areas in resource-exhausted cities. To analyze the “City-Brown” spatial pattern, it was imperative to delineate the boundary of both the urban built-up area and the brownfield clusters. The urban built-up area was determined using the 2017 human settlement data provided by Professor Gong Peng’s research group at the Department of Earth System Science, Tsinghua University [37]. This dataset, with a resolution of 10 m, helped delineate the boundaries of urbanized areas that encompass the brownfield clusters. The extent of the brownfield clusters was identified by selecting the area representing the top 75% of brownfield distribution density, as determined by GIS kernel density analysis tools. This approach defined the spatial boundaries of brownfield clusters based on their concentration and density, a procedure that was conducted across the 10 selected resource-exhausted cities. Secondly, the spatial patterns of brownfield clusters indicate how brownfield sites are aggregated within a certain space. By taking the typical city of Huangshi as a case study, this analysis delved deeper into the dominant factors, spatial morphology, brownfield types, and internal relationships within each brownfield cluster. Finally, tailored brownfield regeneration strategies were proposed based on different spatial pattern types of “City-Brown” and individual brownfield clusters (Figure 3).

2.4. Brownfield Site Identification

Brownfield identification serves as the foundational step for analyzing the spatial characteristics of brownfields. Over the past two decades, many studies have focused on methods for identifying brownfields, primarily through two approaches: artificial intelligence (AI) techniques using high-resolution remote sensing imagery [38,39,40] and manual mapping methods that incorporate both spatial and non-spatial data from various sources [41,42,43,44,45,46,47,48]. The former method is less labor-intensive and quicker than manual approaches. However, challenges include the acquisition of high-resolution satellite imagery, which can be difficult and expansive, and the requirement for technical expertise to train the AI models effectively. The latter approach, while more labor-intensive and time-consuming, often fails to accurately identify specific types of brownfields. Given the vast number and variety of brownfields in urban areas, this study introduced a framework for brownfield identification that relies on a comprehensive analysis of multi-source information [49].

This research focused on industrial and mining brownfields, which are the most typical and representative types of brownfields in resource-exhausted cities. These brownfields include abandoned or idle industrial lands, mining lands, regional transportation facilities, roads, and associated structures such as production plants, warehouses, ancillary facilities, aboveground and underground mining areas, and tailing ponds. The concepts of industrial land, mining land, and regional transportation facilities were derived from the Code for Classification of Urban Land Use and Planning Standards of Development Land (GB50137) (Revised) (Draft for Comment) issued by China’s Ministry of Housing and Urban-Rural Development [50]. This study classified industrial and mining brownfields by considering their historical or current uses, spatial characteristics, contamination features, and the flow processes of industrial materials, identifying them as raw material mining sites, slag heaps, raw material manufacturing sites, non-raw material manufacturing sites, and infrastructure sites.

Brownfield site identification was conducted using Google Earth Pro, leveraging multi-source information through a three-step process (Figure 4). The initial step involved developing identification rules, which included a case library of remote sensing image features, visual interpretation guidelines, and site calibration principles. Specifically, brownfield sites exhibit distinct characteristics in six key areas: boundary, amenities, color, elevation, area, and texture. These characteristics form the basis of the remote sensing imagery feature case library (Figure 5). For example, raw material mining sites that exhibit distinct characteristics are typified by clear working surfaces and irregular boundaries with varying degrees of surface damage. These sites often house machinery such as excavators, large supports, and conveyor belts. The colors of the excavation areas vary by resource: coal mining sites are typically coal-black in color, hematite mines display a soil-brown hue, siderite mines are slate-gray, copper mines are yellow-red, and limestone mines are gray-white. The elevation changes significantly, presenting either as pits or terraced on the hillside. The scale of these mining sites varies with the material: limestone sites are generally smaller, whereas iron, copper, and coal sites are larger. Additionally, the roads within these sites are rugged. The visual interpretation guidelines are designed to assist in identifying the boundaries and operational status of these sites. Moreover, site calibrations took into account the site’s integrity and any artificial or natural boundaries surrounding it.

The second step was visual interpretation. Initially, potential areas were identified in ArcGIS using point of interest (POI) data from open-source map services like Baidu Maps. These areas were then visually examined using remote sensing images in Google Earth. This step specifically involved mapping and refining the spatial boundaries and distribution of various types of subdivided brownfield sites. Google Earth was selected as the tool for visual identification of imagery for two main reasons: firstly, its image resolution of approximately 0.3 m allowed for the clear identification of brownfield characteristics; secondly, it provided access to multi-temporal images, facilitating the examination and comparison of changes over time within the same plots, which assisted in determining the type of the site. This process yielded preliminary identification results. In the third step, the brownfield sites identified in the second step were further calibrated. This calibration process involved removing operational sites using data from Baidu heat maps, urban functional zoning maps, and municipal archives, leading to the final identification of brownfield sites.

2.5. Kernel Density Analysis

Kernel density analysis is a non-parametric testing method used in probability theory to estimate unknown density functions. In ArcGIS, the kernel density analysis tool acts as a spatial analysis tool that calculates the density of point features around raster cells [51]. This tool has been widely applied across various fields, such as analyzing the accessibility of medical service stations [52], determining patterns of disease incidence and identifying critical areas [53], examining the spatial distribution of archaeological sites [54], and evaluating the characteristics of underutilized land [55].

Kernel density analysis was performed using ArcGIS 10.4 to identify spatially aggregated clusters of brownfield sites. The analysis was influenced by three key factors: the search radius, weighted value, and pixel size. The search radius impacts the degree to which an individual brownfield site influences its surroundings. A smaller search radius may lead to significant variations in density peaks and troughs, whereas a larger radius can overly smooth the data, reducing distinctiveness. The optimal search radius value is not definitively established and is typically determined through heuristic methods and algorithmic rules [56]. In this study, based on the average area of the largest brownfield type observed in case cities—the slag heap, which averages 48 hectares with a circumscribed circle radius of 400 m—a search radius of 2000 m was selected. This radius approximated the average 30 min walking distance for humans, which is about 2400 m. The weighted value adjusted the influence of specific indicators on the density calculation within the search radius. To address variations where few brownfields cover a large area or many small ones, the weighted value was calculated as the square root of the brownfield area. Furthermore, the pixel size was set at 10 m by 10 m, recognizing that brownfield identification accuracy is meter level. While smaller pixel sizes could increase the precision of kernel density analysis, the chosen size balanced detail with the practical limits of data resolution.

3. Results

3.1. Spatial Patterns of “City-Brown”

The analysis of 10 cities reveals three distinct “City-Brown” spatial patterns. The first type, known as the “City-Brown Coupling” pattern, is observed in cities like Huangshi, Liaoyuan, Qitaihe, and Tongling. In these cities, there is a significant overlap between brownfield clusters and built-up urban areas, indicating a close relationship between brownfields and urban development. Take Tongling as an example. This city is renowned as the “Ancient Copper Capital of China and Contemporary Copper Base” [57]. Tongling has an extensive history in copper mining that dates back over 3000 years, starting in the Shang and Zhou dynasties and continuing through the Han and Tang dynasties [58]. This long history has left behind numerous ancient copper mining sites, such as Phoenix Mountain, Jinshan Mountain, Wanying Mountain, and Huaxing Mountain, covering over 600 square kilometers in the southeastern part of Tongling City. Post the establishment of the People’s Republic of China, Tongling developed China’s first modern copper industrial base, forming a complete industry chain encompassing mining, ore dressing, smelting, and deep processing [59]. This industrial expansion has driven the city’s growth. Industrial and mining enterprises are distributed throughout the city. However, the transition to a post-industrial period and the closure of various industries have led to the emergence of brownfield clusters, primarily in the copper, iron, and gold mining areas in the southeast of the central city and along the Yangtze River. Therefore, this spatial relationship exemplifies the typical coupling pattern between the city and its brownfield clusters (Figure 6).

The second type is the “City-Brown Juxtaposition” pattern, observed in cities such as Wuhai, Fuxin, and Fushun. Unlike the coupling pattern, these cities feature fewer brownfield clusters but cover a larger area. Typically located on the outskirts of the city, these clusters align with the cities’ reliance on single-resource industries, leading to a centralized distribution. Take Wuhai City, known for its abundant coal resources and as a key national coking coal base, as an example. The city’s development was initially fueled by the coal mining industry, with the early mining areas dispersed in the eastern part of Zhuozi Mountain and the western part of Wuhu Mountain from 1958 to 1967. Small settlements accompanied these mining areas near industrial zones. Between 1976 and 1996, Wuhai expanded rapidly between these two mountains and within the Yellow River Basin [60]. Post-1996, mining in Zhuozi Mountain expanded, forming a narrow strip of mining areas on the eastern edge of the city’s main urbanized region. Concurrently, brownfield clusters developed alongside the raw material extraction industry, primarily situated at the foothills of the eastern and western mountains, covering a vast area. In contrast, the main urban area of the city is nestled within the Yellow River basin. Therefore, this “City-Brown” spatial configuration in Wuhai City exemplifies a typical juxtaposition pattern (Figure 7).

The third type is the “City-Brown Encircling” pattern, typically seen in cities like Pingxiang, Xinyu, and Shaoguan. These cities are rich in diverse mineral resources, leading to the proliferation of brownfield sites near the mining areas, which are usually located around and beyond the developed urban areas. For instance, Pingxiang, an old industrial city, has a long history of coal mining dating back to the Song dynasty, which has significantly shaped its economic and social development. The coal industry further expanded, notably in the late 19th century, with the establishment of the Hanyang Iron Works during the Westernization Movement [61]. After the establishment of the People’s Republic of China, coal production surged, reaching its peak by the end of the 20th century but gradually declining after 2000. The main urban area of Pingxiang is located on a flat plain, while the mineral resources are predominantly distributed in the hilly areas that encircle the city. Coal mines, for example, are situated to the south of the city center and quartz mines to the north [62]. Thus, this geographical distribution marks Pingxiang as a typical example of the “City-Brown” spatial pattern with encircling characteristics (Figure 8).

3.2. Spatial Patterns of Brownfield Clusters

It can be observed that brownfields are not isolated areas within a city; rather, they tend to exist as clusters on a regional scale. Due to the diversity in types and quantities of brownfield clusters, this research took Huangshi City as a case study to explore how and why brownfield sites agglomerate. Among the three types of “City-Brown” spatial patterns, coupled cities like Huangshi exhibit the closest spatial relationship between built areas and brownfield clusters and possess the most diverse types of such clusters. Located on the south bank of the middle reaches of the Yangtze River, Huangshi has a rich mining history spanning over 3000 years with iron, copper, coal, and gold mines. Within the central urban area of Huangshi City, which covers 1795 km², there are 555 brownfield sites formed into 19 clusters across five categories (Figure 9). These brownfield clusters are integrally embedded within the main urban built-up areas.

(1) There are iron mining clusters in the southwest and limestone mining in the central regions. These areas comprise raw material mining, manufacturing, and slag heaps associated with the respective minerals. The brownfield clusters in these areas are based on mining resources, typically presenting as groups of many small sites or as linear aggregation stretching homogeneously. For instance, the Huangjinshan Limestone Mining Cluster features multiple quarrying pits of varying shapes and sizes distributed at the foot and midway up the mountain, spanning a length of 11 km. (2) There are clusters of brownfield sites that have linearly aggregated along the Yangtze River. This agglomeration is based on water resources and largely due to the facilitation of industrial water supply, sewage disposal, and transportation. The proximity to the river aids in these operational functions, leading to concentrated industrial activity along its banks. (3) Certain brownfield clusters are strategically located along major traffic arteries, which are identified as transportation-based types. The importance of convenient transportation for the timely movement of raw materials and products has led to these clusters being positioned along key transit routes, enhancing logistic efficiencies for the industries involved. (4) Policy-driven development has led to the formation of several brownfield clusters, such as the Huigui Industrial Zone, Luoqiao Industrial Zone, Lingcheng Industrial Zone, and Jinqiao Industrial Zone. The first two zones are located near the central urban area and are characterized by a clear internal road network and primarily consist of non-raw material manufacturing brownfields. The latter two are situated in suburban areas and feature a mix of one large-scale raw material manufacturing brownfield supplemented by several non-raw material manufacturing sites, along with other functional sites interspersed among them. (5) There are nine compound brownfield clusters, including one copper, two iron, four limestone, and two composite mineral industrial areas. These clusters result from the accumulation of activities related to raw material mining and manufacturing, non-raw material manufacturing brownfields, and the disposal of by-products like slag heaps. An example of such a cluster is the Daye Iron Mining Area, a major iron ore production site located 25 km west of the city center. This area is predominantly in the northern mountainous region, forming two major open-pit mining areas, with the slag heap distributed in the southeast corner of the mining area. Roads crisscross the entire area, which is linked to external locations by the Tieshan railway station, facilitating ore transport. Nowadays, the east mining pit and its surroundings have been regenerated into the National Mining Park, serving tourism and education purposes (Figure 10).

3.3. Factors Affecting the Spatial Characteristics of Brownfield Clusters

Most resource-exhausted cities originated and developed around mining industries, with urban construction primarily centered on industrial and mining production zones. The distribution of mineral resources along geological veins frequently aligns with the natural topography of mountains, creating a close link between mineral exploitation and the spatial configuration of these natural features. The essential processes of early mining, processing, and transportation often relied on natural water bodies, and human settlements were closely tied to these water sources. Consequently, urban built-up areas, brownfields, and natural landscapes in such cities are deeply interconnected. Take Huangshi City as an example. On the one hand, the landscape configuration between Huangjing Mountain and Tieshan Mountain limited the direction and extent of urban land expansion. In its early development, Huangshi could only expand along a narrow strip of land, making it challenging to establish clear demarcations between brownfield sites and urban built-up areas. On the other hand, the strategic advantages of water transportation provided by the Yangtze River not only facilitated the development of urban riverside areas but also supported the supply of industrial water and efficient transportation of ores, finished materials, and industrial products to and from large factories. This close integration of brownfields with urban built-up zones is a significant factor in the formation of the “City-Brown Coupling” spatial pattern observed in Huangshi City.

The phenomenon of brownfield clusters can largely be attributed to their previous utilization as industrial land, mining areas, and transportation facilities. These sites were strategically selected based on inherent logistical advantages and naturally exhibited clustering characteristics. Scholars have identified several critical factors influencing industrial site selection, including industrial commonality, transportation costs, raw material availability, fuel supply, and water conditions [9]. In addition to the previously discussed factors of mineral and water resources, transportation and policy also play significant roles in the formation of brownfield clusters. In China, national policy guidance has been a pivotal driver. For instance, the industrial and mining sectors in resource-based cities witnessed rapid growth due to influential industrial policies like the “156 Projects” and “The Third Front”. Since the policy “Suppress the Second Industry and Develop the Third Industry” was enacted in 2001, China has successively introduced several major macro-plans, such as the “Sustainable Development Plan for National Resource-based Cities (2013–2020)”, the “National Old Industrial Base Adjustment and Transformation Plan (2013–2022)”, and “Supply-side Structural Reform”. These policies mandate industrial structure adjustment and sustainable development for cities and industrial zones that saw rapid early development. As a result, lots of polluting enterprises ceased operations and relocated, leaving behind numerous brownfield sites. This explains why large numbers of brownfield sites often emerge and aggregate in specific areas within a given period. Thus, it is evident from these cases that brownfield sites are closely linked by shared geographical factors such as mining and water resources, common transportation routes like roads and railways, and influential policy factors.

4. Discussion

4.1. Challenges or Opportunities?

Once upon a time, mining and manufacturing industries, heavily reliant on mineral resources, were central to the development of resource-exhausted cities. However, as these resources dwindled and significant industrial restructuring occurred, coupled with the implementation of urban sustainable development policies, a considerable number of industrial brownfields emerged. These sites subsequently clustered within urban areas. While presenting a myriad of challenges, these brownfields also offer various opportunities for urban redevelopment and transformation.

On the one hand, resource-exhausted cities are challenged by the extensive presence of brownfield sites covering significant land areas. Cities such as Wuhai and Huangshi each have over 500 brownfield sites, with these areas constituting more than 1% of the central urban zones in each case. Notably, in Fushun City, with a total area of 485 km², brownfields account for 55.1 km², representing 11.36% of the city’s area. Within the framework of China’s new urbanization paradigm, which emphasizes optimizing existing land stocks over expansion growth, the economical and intensive use of land stands as a fundamental strategy to promote ecological civilization and sustainable urban development. The large number of brownfield sites highlights issues related to inefficient urban land use and spatial wastage, posing challenges to land use efficiency. However, the redevelopment of brownfield sites presents substantial opportunities to enhance the structure and layout of urban land use, aligning with broader sustainability goals.

On the other hand, the brownfield clusters in these cities showcase a notable diversity in terms of resource composition, including coal, iron ore, non-ferrous metals, and others. These clusters also display varied spatial relationships among individual brownfield sites as well as between brownfields and natural elements, such as mountains and water bodies. The diversity extends to the spatial connections these brownfields maintain with built-up areas. Consequently, the intricate variations within these clusters necessitate careful consideration of their regeneration. Brownfield clusters, characterized by their large scale and complexity, exert a significant impact on urban areas, much more so than isolated brownfield sites. Regenerating these clusters involves not just coordinating the reuse of individual parcels within them but also managing their interaction with the surrounding urban development. This poses a challenge in integrating regional resources and aligning them with overall city planning strategies. Moreover, the spatial relationships between brownfield clusters and the central urban area can be categorized into three types: spatial overlap and intersection, adjacency, and distance. These relationships are intricately linked to the urban development process and should be carefully considered during urban expansion, optimization of stock space, and development of large-scale urban projects. Recognizing these spatial dynamics offers opportunities for differentiated development and enhancing the spatial quality of urban environments.

4.2. Spatial Regeneration Strategies for Brownfield Clusters

Brownfield regeneration presents unique challenges due to factors such as potential contamination and the involvement of numerous stakeholders [63,64]. Compared to developing unused land, brownfield regeneration requires more financial resources, time, and technological advancements due to the complexities of remediation [65,66]. Different brownfield clusters also have various spatial relationships with the main built-up areas of the city, necessitating a comprehensive consideration of these relationships in the broader context of urban development. At the city scale, the approach to brownfield regeneration should align with the specific spatial pattern of the brownfields relative to the urban fabric. In cities exhibiting a “City-Brown Coupling” pattern, brownfield regeneration should be closely integrated with urban renewal. Conversely, in cities with a “City-Brown Juxtaposition” pattern, regeneration could be relatively independent, offering more possibility for large-scale and regional projects. For cities with a “City-Brown Encircling” pattern, regeneration initiatives should align with future development goals and contribute to the coordinated urban and rural development goals. Furthermore, the significance of a brownfield site’s location in determining regeneration priorities is widely recognized [67,68,69,70,71]. This is particularly pertinent when these sites occupy ecologically significant urban spaces or when their regeneration aligns with social and political needs. For instance, brownfield sites impacting the ecological pattern of a city—especially those providing essential ecosystem services or influencing the integrity and connectivity of habitats for valuable species or ecological reserves—should be prioritized. Their regeneration strategies should focus on ecological protection and restoration. In terms of brownfield sites situated in socioeconomically viable areas, their land use value per unit area tends to be higher due to factors such as accessibility, built infrastructure and services, and their potential to attract people and stimulate urban vitality. Therefore, their redevelopment should leverage both social and economic values. Additionally, for brownfields situated within ecologically protected areas, no-mining zones, the Yangtze River Protection Zone, and other areas subject to stringent policy regulations in China, their regeneration must comply with national laws and regulations. For instance, the land reclamation regulations mandate that mining wasteland generated by production and construction activities should be reclaimed as arable land on a priority basis.

At the cluster scale, the characteristics and dominant factors of brownfield clusters significantly influence their regeneration strategies. These factors include spatial characteristics, location attributes, brownfield types, and internal relationships within the clusters. Similar observations have been reported in previous studies [70,72,73,74,75], noting that regeneration approaches can vary significantly depending on the geospatial distribution and historical usage of the sites. This alignment with previous research highlights the consistency of our findings and underscores the complex interplay of factors influencing brownfield regeneration strategies. First, for brownfield clusters predominantly influenced by resource factors, these sites are closely tied to the natural environmental conditions of their locations, necessitating regeneration approaches that consider their ecological impacts. When such clusters are located in the same mining area or near the same river, they often face similar environmental challenges, policy pressures, and contamination issues. Therefore, they could benefit from consistent restoration techniques or ecological protection strategies tailored to their collective needs. However, it is crucial to avoid homogenization; landscape differentiation designs that reflect the unique characteristics of each site can be employed to enhance the distinctiveness of each regeneration project. For instance, consider the restoration and transformation of the Nanlu mining pits on the southern foothills of Huangjing Mountain. From the southern urban areas of the mountain, multiple quarry pits of varying shapes and sizes are distinctly visible, distributed along an 11 km stretch from the mountain’s base to its mid-slope, significantly impacting the overall urban landscape. Similar mountain ecosystem restoration techniques are employed, with selective landscape renewal based on the urban landscape perspective. Consideration can also be given to integrating this with the entrances of the four tunnels passing through Huangjing Mountain (Huangsiwan, Yueliangshan, Jinshan, and Tanshan) to create unique landscapes. Second, brownfield clusters dominated by transportation factors feature convenient links between individual brownfields, allowing the regenerated functions to support one another. In regenerating these clusters, it is important to consider the complementary uses of future land development across brownfields. This approach helps prevent homogenization and competition within the cluster while fostering mutual support and regional development. Third, clusters heavily influenced by policy factors typically cover a large area and contain a large number of brownfields, making a significant impact on urban development and cityscape. Regeneration of these areas should not be isolated; rather, a holistic strategy is required. For example, abandoned industrial and mining areas, as well as industrial parks, should consider urban industry transformation and integration with broader urban planning. In the case of older industrial zones located within central urban areas, the functional replacement and selection processes are more complex. Regeneration efforts in these zones should focus on synergy with the urban renewal and the overarching development plans of the central urban area.

4.3. Limitations

However, we believe this research has potential for further development and refinement. Firstly, while this study concentrated on the spatial characteristics of brownfield clusters, it did not incorporate information on the contamination levels of these sites. The strategies and approaches for brownfield regeneration are significantly influenced by the contamination status and remediation. Future research could explore how both spatial and contamination characteristics of brownfields impact regeneration strategies in varying ways. Secondly, this study analyzed brownfields in 10 different cities at a specific point in time (2020). Urban development and the evolution of brownfield patterns are continuous and dynamic processes, and this study did not fully address the dynamic nature of brownfield clusters and urban development. The spatial patterns of “City-Brown” interactions and brownfield clusters may change over time. Future research should consider longitudinal studies to track one or more cities, mapping the dynamic evolution of spatial patterns and analyzing how various factors influence different stages so as to propose more targeted regeneration strategies aligned with the evolving trends of cities and brownfield clusters. Finally, although resource-exhausted cities face common issues, variations in location, economy, ecology, and population introduce distinct challenges for brownfield regeneration. For example, while both Northeast Chinese cities and Southeast coastal cities experience resource depletion and numerous brownfields, cities in Northeast China are often in the shrinking stage of population outflow, whereas those along the Southeast coast are experiencing ongoing expansion. Consequently, the potential for redevelopment represented by brownfields requires different strategies for future land use and site layout, closely linked to the city’s development stage and characteristics. Cities like Fushun and Wuhai, which exhibit “City-Brown Juxtaposition”, are located in diverse latitudinal and climatic conditions, leading to different ecological and regeneration challenges. Therefore, future research should also address potential disparities and their impacts, with a focus on the specific contexts of host cities.

5. Conclusions

This study explored the phenomenon of brownfields often clustering within certain areas and introduced an approach to analyze the spatial characteristics of these clusters from a systematic perspective. We selected 10 cities from a pool of 67 resource-exhausted cities in China. These cities were chosen based on their distinct natural landscape patterns, mineral resource profiles, histories of urban and industrial development, key policies, and comprehensive socioeconomic data. We then categorized these cities into three “City-Brown” spatial patterns, including coupling, juxtaposition, and encircling patterns, through brownfield site identification and kernel density analysis. Given the close relationship between brownfield clusters and urban built-up areas and the diversity in types and quantities of these clusters, we selected a typical case study representing the coupling pattern. The brownfield clusters in Huangshi were further categorized into five spatial patterns by analyzing dominant factors, spatial morphology, brownfield types, and internal relationships. Building on this analysis, the study elucidated why and how natural features like mountains and water bodies, as well as transportation networks and policy frameworks, influence the spatial characteristics of brownfield clusters. We then discussed the challenges and opportunities these clusters present to resource-exhausted cities. The conclusion offers targeted brownfield regeneration strategies that address the specific spatial characteristics of brownfield clusters at both the city and cluster scales.

For resource-exhausted cities, which are currently in a critical period of transformation, a comprehensive understanding of the spatial relationship between “city” and “brownfield” can lay a solid foundation for formulating high-quality urban spatial renewal strategies. This study is particularly significant for the sustainable planning of cities, especially those characterized by high population density, intense development, and limited land resources. Analyzing the spatial distribution of brownfield clusters and the city-brownfield pattern helps identify potential stock land and assess the impact of redevelopment of these sites on the existing urban fabric. By fully understanding the opportunities and challenges presented by the city, policymakers and urban planners can prioritize maximization of the benefits of brownfield regeneration, encompassing financial and ecological aspects. This research can also be integrated with China’s current territorial spatial planning initiatives, considering it at both urban and regional levels in conjunction with existing stock space, rather than focusing on the management and regeneration of individual brownfields. This approach can enhance the efficient and systematic use of urban land, facilitating smart growth or contraction. Furthermore, the methodology and insights from this study can serve as valuable references for other cities and regions worldwide facing similar challenges.