Search Results (512)

Since the 1970s, the understanding of cultural heritage (CH) has expanded from a focus on monumental conservation to a systemic, socially constructed concept shaped by communities and dynamic values. While recognized as a resource for sustainable development, CH remains marginal in global policy agendas, notably in the UN’s 2030 Agenda. This paper explores how the Historic Urban Landscape (HUL) approach and broader heritage systems can function as enablers of sustainable urban development, moving beyond heritage-as-object to heritage-as-process. It synthesizes conceptual advances, policy frameworks, and empirical cases—such as Capitals of Culture programs, adaptive reuse initiatives, and circular economy models—to analyze how heritage systems contribute to environmental, social, and economic sustainability. Drawing on a value-based and people-centered framework, the paper identifies key principles, models, and success factors for integrating CH into urban planning. Case studies from Europe and Asia illustrate the potential of heritage to foster inclusive governance, community resilience, and innovation, while also exposing challenges such as institutional fragmentation, gentrification, and policy–practice gaps. The findings highlight the need for holistic, cross-sectoral, and participatory strategies to embed CH meaningfully in urban transformation processes, offering concrete insights for advancing heritage-led sustainable development through the lens of systems thinking. Full article

In regional traditional landscape studies where continuous literature and physical relics are scarce, image-based materials serve as a crucial medium for reconstructing historical spatial structures. This study focuses on the sandbar polder landscapes in the Yangzhong area, located in the lower Yangtze River. By integrating historical maps, military cartographic surveys, CORONA satellite imagery, and modern remote sensing data, this study developed a multi-source image interpretation framework to reconstruct the traditional dike–water–field–settlement spatial structure. Employing image recognition and morphological analysis, the study extracted features such as dikes, water systems, and settlements, revealing their adaptation mechanisms to microtopography and associated ecological functions, including multi-level irrigation and drainage, hydrological buffering, and flood prevention. The results demonstrate that traditional sandbar polder landscapes exhibit a high degree of experiential adaptation, and their spatial organization offers valuable insights for future green infrastructure planning. The study confirms the applicability of image-based interpretation methods for historical landscape reconstruction and provides a practical path for the activation and translation of traditional landscape units in contemporary urban–rural governance. Full article

The historic landscape and the value of the ancient city in the stock era present a diversified and mixed problem; as such, this study explores a quantifiable spatial correlation method for landscape layering characteristics and value space, in order to provide support for the urban renewal paths that integrate historical and contemporary needs. Taking as an example Chaozhou Ancient City, a renowned historical and cultural city in China, this study draws on the theory of historical urban landscape layering and comprehensively uses historical graphic interpretation, GIS spatial quantitative analysis, the single-land-use dynamic degree model, the Analytic Network Process, and the Delphi method to quantitatively analyze and evaluate the landscape layering characteristics and value space of the ancient city. Meanwhile, it explores the relationship between the historical landscape layering characteristics and value space of ancient cities using the spatial autocorrelation model and the coupling coordination modulus model. The key findings are as follows: (1) The high-layer space (66.1%) and high-value space (31.1%) of the historic landscape of Chaozhou Ancient City show significant mismatch and imbalance. Spatially, layer spaces increase from the city center toward the periphery, whereas value spaces decrease from the center outward, demonstrating marked spatial heterogeneity. (2) The layer–value space shows a spatial distribution of agglomeration, with Moran’s I index values of 0.2712 and 0.6437, respectively. The agglomeration degree of the value space is much higher than that of the layer space, and both show significant non-equilibrium and associative coupling. (3) Coupling coordination: basically balanced (D = 0.56) indicates a transition toward a more integrated state, although 48% of the region remains in a state of severe dysfunction, mainly consisting of two types of spaces: “high-layer–high-value” and “low-layer–low-value.” These two dysfunctional types should be prioritized in future conservation and renewal strategies. This study provides a more comprehensive quantitative analysis path for identifying and evaluating the landscape layer–value space of the ancient city, providing visualization tools and decision-making support for the future protection and renewal of Chaozhou Ancient City and the declaration of the World Heritage. Full article

Wetland ecosystems are critical for biodiversity conservation and carbon sequestration, underpinning climate regulation and sustainable development. Accurate prediction of wetland evolution is therefore essential for informed regional planning, particularly in International Wetland Cities. As one of the first designated International Wetland Cities, Haikou exemplifies the intensifying pressures faced by coastal wetlands in rapidly urbanizing regions, balancing economic development imperatives with ecological conservation. This study addresses this challenge by employing the PLUS model to simulate the spatiotemporal dynamics of wetland evolution in Haikou from 2010 to 2030 under four distinct scenarios: Business-as-Usual (BAU), Ecological Conservation (EC), Economic Development (ED), and Multi-Objective Development (MOD). The integrated approach combines landscape pattern dynamics analysis, land-use transition matrices, and quantitative assessment of driving factor contributions. Key findings reveal significant historical wetland loss between 2010 and 2020 (21.01 km²), characterized by substantial declines in artificial wetlands (paddy fields: −14.43 km²; agricultural ponds: −8.99 km²) alongside resilient growth in natural wetlands (rivers: +2.70 km²; mangroves: +1.25 km²), highlighting fundamental trade-offs between economic and ecological priorities. Scenario projections indicate that unregulated development (ED) would exacerbate wetland loss (−26.33 km²; dynamic change rate: −0.61%), including unprecedented river fragmentation (−16.0%). Conversely, strict conservation (EC) achieves near net-zero wetland loss (−0.05%) but constrains economic development capacity by 24%. Critically, the MOD scenario demonstrates an effective balance, maintaining 86% of EC’s wetland preservation efficacy while satisfying 73% of ED’s development demand. This is achieved through strategic interventions including establishing wetland protection constraints and optimizing bidirectional land conversion rules, yielding synergistic benefits. Spatial analysis identifies key conflict hotspots such as Nandu River shoreline, Dongzhai Port mangroves, necessitating targeted management strategies aligned with the heterogeneity of driving factors. This study advances the framework for sustainable wetland governance by demonstrating how multi-objective spatial planning can transform ecological-economic trade-offs into synergistic co-benefits. It provides a transferable methodological approach for coastal cities in the Global South and other International Wetland City. Full article

This study contributes to the growing interest in evaluating environmental qualities and characteristics for the enhancement of social and individual well-being by introducing and validating the Landscape Assessment Scale (LAS), a standardized tool designed to assess key environmental qualities across both natural and urban landscapes within metropolitan settings. The scale comprises 30 items related to 10 key environmental components: coherence, complexity, ephemera, imageability, naturalness, safety, visual scale, stewardship, disturbance, and historicity of places. In study 1, the LAS was first tested on 327 participants, who evaluated either a natural (N = 176) or urban (N = 151) environment. Exploratory Factor Analysis (EFA) revealed three correlated factors: Landscape Disharmony, Landscape Organized Complexity, and Landscape Naturalistic Impact. In study 2, participants (N = 185) were asked to select and to assess two environments (natural and urban) using the shortened LAS and the Perceived Restorativeness Scale (PRS). A Confirmatory Factor Analysis (CFA) was used to investigate the invariance of the LAS factor structure in both natural and urban environments, and the correlational analysis was used to investigate LAS convergent validity. The CFA supported the three-factor structure and showed significant correlations between LAS and PRS components, supporting convergent validity. By capturing key perceptual dimensions that are relevant across landscape types, the LAS offers a practical and scientifically robust tool for informing evidence-based urban planning and landscape design. Full article

At present, industrial heritage preservation in China often focuses on individual industrial buildings, lacking a holistic consideration of industrial settlements (e.g., industrial cities, towns, and villages). This study draws upon the Historic Urban Landscape (HUL) approach to construct a research framework that applies to industrial settlements, considering both integrity and layering. Taking the case of Tongguan Ancient Town—a typical industrial settlement—this study uses the integrated approach of historical materials acquisition, oral interview, and field investigation to review the interactive evolution of industry and space across three historical periods. It identifies a comprehensive set of heritage elements within the Tongguan industrial settlement and proposes a preservation framework for its industrial heritage. The key findings are threefold: industrial settlement heritage possesses characteristics of integrity and layering; the HUL approach can be effectively applied to industrial settlement studies; and the protection of industrial settlements is a crucial step toward establishing a complete system for the inheritance and preservation of China’s urban and rural historical and cultural heritage. Full article

Urban centers shaped by industrial histories often exhibit complex patterns of land cover change that are not well-captured by standard classification techniques. This study investigates post-industrial urban change in Ponca City, Oklahoma, using remote sensing, unsupervised machine learning, and socioeconomic contextualization. Using a Jupyter Notebook version 7.0.8 environment for Python libraries, Landsat imagery from 1990 to 2020 was analyzed to detect shifts in land cover patterns across a relatively small, heterogeneous landscape. Principal component analysis (PCA) was applied to reduce dimensionality and enhance pixel distinction across multiband reflectance data. Socioeconomic data and historical context were incorporated to interpret changes in land use alongside patterns of industrial reduction and urban redevelopment. Results revealed changes in five distinct land cover classes of urban, vegetative, and industrial land uses, with observable trends aligning with key periods of economic and infrastructural transition. The trends also aligned with socioeconomic changes of the city, with a larger reduction in industrial and commercial land cover than in residential and vegetation cover types. These findings demonstrate the utility of machine learning classification in small-scale, heterogeneous environments and provide a replicable methodological framework for smaller city municipalities to monitor urban change. Full article

China’s rapid urbanization has presented challenges for sustainably revitalizing the historic and cultural heritage within its urban villages. Often, these efforts overlook the crucial roles of community ties and cultural values. This study focuses on 15 representative urban villages in Guangzhou (2019–2024). It tests the core idea that the physical layout of these spaces reflects underlying community structures and cultural values shaped by specific policies. Integrating this understanding into landscape planning can significantly improve revitalization outcomes. We used a mixed-methods approach: (1) Extended fieldwork to understand community networks and cultural practices; (2) Spatial analysis to measure how building density relates to land uses; (3) Sentiment analysis to reveal how people perceive cultural symbols; (4) A coordination model to link population influx with landscape suitability. Key findings reveal different patterns: Villages with strong clan networks maintained high cultural integrity and public acceptance through bodies like ancestral hall councils. Economically driven villages showed a split—open for business but culturally closed, with very low tenant participation. Successful revitalization requires balancing three elements: protecting physical landmarks in their original locations; modernizing cultural events; and reconstructing community narratives. Practically, we propose a planning framework with four approaches tailored to different village types. For instance, decaying villages should prioritize repairing key landmarks that hold community memory. Theoretically, we build a model linking social and spatial change, extending the cultural value concepts of Amos Rapoport to the context of fast-growing cities. This provides a new methodological perspective for managing urban–rural heritage in East Asia. Full article

Numerous studies have demonstrated that in residential areas of Western cities, both luxury and legacy effects significantly shape tree species diversity dynamics. However, the specific mechanisms driving these diversity patterns in China, where urbanization has progressed at an unprecedented pace, remain poorly understood. In this study we selected 20 residential settlements and 7 key socio-economic properties to investigate the change trend of tree diversity (2006–2021) and its socio-economic driving factors in Beijing. Our results demonstrate significant increases in total, native, and exotic tree species richness between 2006 and 2021 (p < 0.05), with average increases of 36%, 26%, and 55%, respectively. Total and exotic tree Shannon-Wiener indices, as well as exotic tree Simpson’s index, were also significantly higher in 2021 (p < 0.05). Housing prices was the dominant driver shaping total and exotic tree diversity, showing significant positive correlations with both metrics. In contrast, native tree diversity exhibited a strong positive association with neighborhood age. Our findings highlight two dominant mechanisms: legacy effect, where older neighborhoods preserve native diversity through historical planting practices, and luxury effect, where affluent communities drive exotic species proliferation through ornamental landscaping initiatives. These findings elucidate the dual dynamics of legacy conservation and luxury-driven cultivation in urban forest development, revealing how historical contingencies and contemporary socioeconomic forces jointly shape tree diversity patterns in urban ecosystems. Full article

This study investigates the concept of landscape services (LS), which integrate environmental and sociocultural dimensions of sustainable development. Recognizing landscapes as essential to daily life and well-being, the research aims to support sustainable spatial planning by analyzing both their potential and their actual use. The study has three main objectives: (1) to assess the potential of 16 selected landscape types to provide six key LS through expert evaluation; (2) to determine actual LS usage patterns among the local community (residents); and (3) to identify agreements and discrepancies between expert assessments and resident use. The services analyzed include providing space for daily activities; regulating spatial structure through diversity and compositional richness; enhancing physical and mental health; enabling passive and active recreation; supporting personal fulfillment; and fostering social interaction. Expert-based surveys and participatory mapping with residents were used to assess the provision and use of LS. The results indicate consistent evaluations for forest and historical urban landscapes (high potential and use) and mining and transportation landscapes (low potential and use). However, significant differences emerged for mountain LS, rated highly by experts but used minimally by residents. These insights highlight the importance of aligning expert planning with community needs to promote sustainable land use policies and reduce spatial conflicts. Full article

The landscapes of China’s multi-ethnic areas are rich in natural and cultural value, but they are threatened by homogenization and urbanization. This study aims to establish a method for identifying and classifying the landscape characters in China’s multi-ethnic areas to support the protection and sustainable development of the landscape in these areas. Taking the Miao Frontier Corridor as an example, the study optimized a parameterization method of landscape character assessment (LCA), integrated relevant cultural and natural elements, and used the K-means clustering algorithm to determine the landscape character types and regions of the Miao Frontier Corridor. The results show that (1) the natural conditions, ethnic exchanges, and historical institutions of the Miao Frontier Corridor have had a significant impact on its overall landscape; and (2) using ethnic group culture as a cultural element in LCA helps to reveal the unique cultural value of areas with different landscape characters. This study expands the LCA framework and applies it to multi-ethnic areas in China, thereby establishing a database that can serve as the basis for cross-regional landscape protection, management, and development planning in these areas. The research methods can be widely used in other multi-ethnic areas in China. Full article

The research is grounded in the perspective of urban historical landscape (HUL), exploring the connections between cultural heritage and a broader urban context, as well as the general public and communities. It also focuses on small cultural heritage sites (SCHSs) in urban areas that have been overlooked in previous studies. By integrating various types of data, an assessment framework and methodology comprising six dimensions and 24 indicators were established and applied to the empirical research of 30 SCHSs in the Beijing section of the Grand Canal. The empirical research demonstrated the operability, effectiveness, and flexibility of the HUL assessment for SCHSs. The research findings are as follows. (1) The method provides differentiated recommendations for the formulation of tailored policies and planning management schemes based on heritage types, conservation levels, and the urban districts in which they are located. (2) The comprehensive quality of the open spaces where SCHSs are situated is critical for the cognition of the general public and community residents. (3) The overall conservation of the community areas containing SCHSs is highly significant, and the linkage between social development levels and cultural resources enhances public cognition of the SCHSs. (4) Cluster analysis offers guidance for the refined improvement of different SCHSs. The research aims to establish an action-oriented assessment framework, with a dimensional framework responding to the requirements of HULs and allowing for indicator flexibility. This study is significant for supporting the conservation and utilization of SCHSs in urban areas and for promoting their sustainable development. Full article

Corporate environmental claims often neglect the substantial ecological impact of land-use changes. This case study examines the spatial dimension of retail-driven land-use transformation by analyzing supermarket expansion in the Veneto region (northern Italy), with a focus on a large grocery retailer. We evaluated its corporate environmental claims by assessing land consumption patterns from 1983 to 2024 using Geographic Information Systems (GIS). The GIS-based methodology involved geocoding 113 Points of Sale (POS—individual retail outlets), performing photo-interpretation of historical aerial imagery, and classifying land-cover types prior to construction. We applied spatial metrics such as total converted surface area, land-cover class frequency across eight categories (e.g., agricultural, herbaceous, arboreal), and the average linear distance between afforestation sites and POS developed on previously rural land. Our findings reveal that 65.97% of the total land converted for Points of Sale development occurred in rural areas, primarily agricultural and herbaceous lands. These landscapes play a critical role in supporting urban biodiversity and providing essential ecosystem services, which are increasingly threatened by unchecked land conversion. While the corporate sustainability reports and marketing strategies emphasize afforestation efforts under their “We Love Nature” initiative, our spatial analysis uncovers no evidence of actual land-use conversion. Additionally, reforestation activities are located an average of 40.75 km from converted sites, undermining their role as effective compensatory measures. These findings raise concerns about selective disclosure and greenwashing, driving the need for more comprehensive and transparent corporate sustainability reporting. The study argues for stronger policy frameworks to incentivize urban regeneration over greenfield development and calls for the integration of land-use data into corporate sustainability disclosures. By combining geospatial methods with content analysis, the research offers new insights into the intersection of land use, business practices, and environmental sustainability in climate-vulnerable regions. Full article

The preservation and protection of historic urban centers in climate-sensitive coastal areas contributes to the promotion of culture as a driver and enabler of achieving temporal and spatial sustainability, as it is recognized that urban heritage is an integral part of the urban landscape, culture, and economy. The aim of this study was to enhance the resilience and protection of cultural heritage and historic urban centers (HUCs) in the coastal area of Kaštela, Croatia, by providing recommendations and action guidelines in response to climate change impacts, including rising temperatures, sea levels, storms, droughts, and flooding. Preserving HUCs is essential to maintain their cultural values, original structures, and appearance. Many ancient coastal Roman HUCs lie partially or entirely below mean sea level, while low-lying medieval castles, urban areas, and modern developments are increasingly at risk. Based on vulnerability assessments, targeted mitigation and adaptation measures were proposed to address HUC vulnerability sources. The Historical Urban Landscape Approach tool was used to transition and manage HUCs, linking past, present, and future hazard contexts to enable rational, comprehensive, and sustainable solutions. The effective protection of HUCs requires a deeper understanding of the evolution of urban development, climate dynamics, and the natural environments, including both tangible and intangible urban heritage elements. The “hazard-specific” vulnerability assessment framework, which incorporates hazard-relevant indicators of sensitivity and adaptive capacity, was a practical tool for risk reduction. This method relies on analyzing the historical performance and physical characteristics of the system, without necessitating additional simulations of transformation processes. Full article

(1) Background: The provision of monofunctional or inadequately distributed services in urban park green spaces often constrains residents’ opportunities and diversity for outdoor activities, particularly limiting access and participation for specific age groups or activity preferences. However, functional nodes with temporal and spatial flexibility demonstrate high-quality characteristics of resilient and shared services through integrated development. Accurately identifying user demand provides a solid basis for optimizing the functional configuration of urban parks. (2) Methods: This study took the old city area of Zhengzhou, Henan Province, China, as a case study. By collecting and integrating various types of data, such as geographic spatial data, field investigation data, and behavioral observations, we developed a population demand quantification method and a modular analysis approach for park service functions. This framework enabled correlation analysis between diverse user needs and park services. The study further classified and combined park functions into modular units, quantifying their elastic and shared service capabilities—namely, the adaptive flexibility and shared utilization capacity of park services. Additionally, we established a demand-responsive evaluation system for identifying and diagnosing problem areas in park services based on multi-source data. (3) Results: The demand response index and diagnostic results indicate that the supply of fitness facilities—particularly equipment-based installations—is insufficient within the old urban district of Zhengzhou. Among the three user groups—children, young and middle-aged adults, and the elderly—the elderly population exhibited the lowest demand response index, revealing a significant gap in meeting their specific needs. (4) Conclusions: Based on the research findings, a three-tier optimization strategy is proposed: A. improve green space connectivity to expand the service coverage of parks; B. implement multifunctional overlay and coordinated integration in spatial design based on site characteristics and demand diagnostics; and C. increase the total supply of facilities to enhance spatial efficiency in parks. By integrating the demand assessment data and diagnostic results, this approach enabled a data-driven reorganization of service types and targeted allocation of resources within existing park infrastructure, offering a practical tool and reference for the planning of urban outdoor activity spaces. Full article