Search Results (1,586)

Throughout the long history of human development, a large number of activity relics have been left on the earth, among which settlements are important carriers for studying human construction activities. In the era without modern active environmental control technology, humans used their experience to create the miracle of harmonious coexistence between humans and nature. Especially in the construction of settlements under complex environmental stress, it is the crystallization of human wisdom. For China, the settlements of ethnic minorities, due to their unique culture and harsh living environment, are undoubtedly key objects for studying the wisdom of human settlement construction. Therefore, this study takes the Tujia rural settlements in the mountainous environment of northeastern Sichuan as the research object and uses the spatial analysis function of ArcGIS to construct a complete “culture-space” environmental adaptation wisdom research system. The research results show that there is a close relationship between the cultural wisdom and spatial construction wisdom of the Tujia people in northeastern Sichuan. Cultural wisdom plays a key role in guiding settlements to adapt to terrain, water resources, and climate, etc., thus presenting a highly coordinated mechanism between the overall distribution of Tujia rural settlements in northeastern Sichuan and the construction of settlement space and the environment. The “culture-space” environmental adaptation research framework proposed in this study can provide a reference for the study of rural settlement space worldwide, and the clear settlement environmental adaptation strategies in the research can provide guidance for the construction of modern mountainous town spaces. Full article

Wildfires at the wildland–urban interface (WUI) have increased in frequency and severity under global warming and intensified human activities. As a representative high-altitude mountainous region in southwestern China, Yunnan features complex topography, steep climatic gradients, and dispersed settlements interwoven with wildlands, making it a fire-prone area where wildfire management is particularly challenging. However, a fine-scale WUI dataset is currently lacking for this region. To address this gap, we refined WUI classification thresholds using a one-factor-at-a-time (OFAT) method and generated the first fine-resolution WUI map of Yunnan. Seasonal wildfire driving factors from 2004 to 2023 were quantified, and machine learning models were applied to produce seasonal susceptibility maps. SHapley Additive exPlanations (SHAP) were employed to interpret the dominant contributing factors. The resulting WUI covers 25,730.67 km², accounting for 6.5% of Yunnan’s land area. Random forest models effectively captured seasonal wildfire susceptibility patterns, with AUC values exceeding 0.83 across all seasons. High susceptibility zones (>0.5) comprised 30.09% of the WUI in spring, 25.74% in winter, 22.61% in autumn, and 13.74% in summer. SHAP analysis revealed that anthropogenic factors consistently drive wildfire occurrence, while climatic conditions in the preceding season influence vegetation status and subsequently affect wildfire likelihood in the current season. By integrating static “where” mapping with dynamic “when” susceptibility analysis, this study establishes a comprehensive “When–Where” framework that supports both long-term WUI planning and short-term seasonal early warning. The integration of fine scale WUI mapping with seasonal susceptibility modeling enhances wildfire risk management in complex high-altitude regions. These findings provide a scientific basis for location-specific, time-sensitive, and full-chain wildfire management in mountainous landscapes and contribute to cross-border ecological security governance in the Indo-China Peninsula. Full article

The global mental health issue is becoming increasingly prominent. The fair supply of psychological therapeutic landscape spaces in urban high-density residential areas is a core path to ensuring the physical and mental health of residents and maintaining social health equity. This study takes the theory of spatial justice as the core framework, selects 20 typical high-density residential areas in Shijiazhuang City as empirical samples, and collects basic data through structured questionnaire surveys and on-site observations to explore the justice dilemma, evaluation system, and group demand differentiation characteristics of psychological therapeutic landscape spaces in high-density residential areas. The research results show that there are three core injustice problems in the psychological therapeutic landscape spaces of high-density residential areas: insufficient spatial inclusiveness, lack of ecological space justice, and incomplete facilities and management systems. Residents’ evaluations of the spatial justice of therapeutic landscapes can be divided into four dimensions: practical, ecological, social, and management. Among them, the ecological dimension is the core dimension that residents pay the most attention to. Individual characteristics such as gender, age, identity category, community activity duration, and governance participation willingness have a significant impact on residents’ evaluations of spatial justice. This study constructs an evaluation system for the spatial justice of therapeutic landscape spaces suitable for high-density residential areas, providing theoretical support and practical guidance for the planning, design, and optimization and renewal of fair and inclusive psychological therapeutic landscapes in high-density residential areas in northern China. At the same time, it provides a scientific basis for the construction of healthy cities and the practical application of spatial justice in the field of human settlements. Full article

With the increasing number of wildfire events, people living close to the wildland–urban interface (WUI) are more likely to be exposed to these events. To mitigate the hazards related to wildfires, it is of great importance to identify areas where human settlements are at a greater risk. Remote sensing-based techniques for mapping and quantifying the inhabitants possibly affected by these events are crucial to reduce the loss of life as well as reduce the negative impact that wildfires pose to the people living in WUIs, the surrounding areas, and the environment. Fine-scale mapping is a suitable auxiliary tool to indicate areas at greater risk. Hence, the dasymetric method was applied to generate a high-resolution map of the study area’s population, using products generated from Sentinel-2 imagery, a census, and Light Detection and Ranging (LiDAR) data. The findings of the proposed methodology show that around 59% of the population in the study area currently lives inside the WUI, while in 2025, most of the people affected by wildfires—77%—lived outside the WUI. This is expected, since wildfires vary in space and time, and they are seen as spatial–temporal processes. In addition, the results demonstrated that women are slightly more exposed to wildfires than other population groups. These results showed that the proposed methodology could not only help identify high-risk areas but also the number of people living in these areas due to the high-resolution dasymetric methodology. The proposed methodology described in this work shows that fine-scale mapping could enrich forest management in order to protect the populations susceptible to the negative impacts of wildfires, consequently protecting the environment. Full article

Accurate urban expansion mapping in dryland environments is essential for sustainable planning, infrastructure management, and heritage-sensitive development, yet it remains methodologically challenging because built-up surfaces often exhibit strong spectral similarity to bright bare soils. This study comparatively evaluates three widely used urban mapping approaches in Diriyah, Saudi Arabia, a rapidly transforming heritage district of high relevance to Saudi Vision 2030: the Global Human Settlement Layer (GHSL), the Normalized Difference Built-up Index (NDBI), and unsupervised k-means classification. Built-up extent was mapped for 2015, 2020, and 2025, and method performance was assessed using 150 stratified reference points interpreted from high-resolution imagery. The results reveal substantial quantitative differences among methods. GHSL produced the most conservative estimates of urban extent (2.80, 4.94, and 5.31 km²), while NDBI and unsupervised classification generated much larger and less realistic built-up areas due to spectral confusion with bright bare soil. Accuracy assessment confirmed the superiority of GHSL, which achieved the highest overall accuracy (0.88) and Kappa coefficient (0.83), compared with NDBI (0.53; 0.41) and unsupervised classification (0.61; 0.50). To support integrative interpretation, the study also developed a Hybrid Built-up Detection Model (HBDM), which combines the three outputs into a continuous urban intensity layer that helps distinguish persistent urban cores from uncertain transition zones. The findings demonstrate that conservative global built-up products provide a more reliable baseline than index-based or unsupervised methods in bright-soil dryland settings. More broadly, the study offers practical methodological guidance for urban monitoring and sustainable land management in desert cities undergoing rapid transformation under large-scale development agendas such as Saudi Vision 2030. Full article

The current global population aging trend has intensified, especially in rural areas. As vital spatial carriers supporting multiple activities of older adults, rural human settlements have become key settings for addressing the challenges of aging. However, current efforts to improve rural human settlements primarily focus on enhancing the overall appearance of villages. This approach fails to adequately address the specific needs of older adults. Chongqing is a typical mountainous city, facing deep aging and significant regional disparities. It is also confronted with realities such as spatial fragmentation, scattered facilities, and low service accessibility. So Chongqing urgently requires systematic assessment and targeted interventions. To transcend the traditional one-size-fits-all governance in rural human settlements, the concept of “rural human settlements for aging” is introduced in this article, to establish an age-sensitive governance logic. Based on 2023 cross-sectional data, this article evaluates the level of the rural human settlements in Chongqing by establishing an index system, and employs global spatial correlation and local spatial correlation to analyze the spatial correlation patterns. The geographic detector model and the obstacle degree model are used to delve into the key obstacle factors influencing and hindering rural human settlements. The results indicate that despite exhibiting a pronounced spatial clustering pattern, spatial disparities remain quite evident. The spatial differentiation presents a pattern of “high in the west and low in the east, led by a single core area.” Elderly service facilities constitute the main external obstacle. The relationship between social security and family support within welfare systems represents the primary internal obstacle. Transportation conditions serve as the key interactive obstacle. Based on an analysis of the primary obstacles in each region, the promotion strategy is categorized into three types: facility enhancement type, characteristic amplification type and comprehensive upgrading type. This article aims to advance the transformation of rural human settlements from “universal design” to “age-friendly design.” It provides a reference framework for rural human settlements development in the context of an aging population. Full article

Cultural heritage plays a pivotal role in shaping identity, fostering social cohesion, and advancing sustainable development. However, a vast number of non-designated historic buildings face ongoing risks of degradation or disappearance due to their unacknowledged value. Addressing this issue, this study investigates pathways for their sustainable reuse. Employing a multi-criteria decision-making framework, we developed a post-occupancy evaluation model comprising four dimensions: historical value preservation, adaptive reuse efficacy, regional development impact, and management service quality. The model was empirically applied to three cases of Meizhou Hakka architecture, in which such buildings were repurposed as guesthouses. The findings reveal that, unlike officially protected heritage buildings, the successful reuse of non-designated historic buildings depends not primarily on the strict preservation of historical value, but rather on superior adaptive reuse efficacy—namely, contemporary performance metrics such as functional adaptation rationality, spatial utilization efficiency, environmental comfort, and structural safety and reliability. Quantitative weighting results indicate that historical value preservation functions as a fundamental baseline, while empirical analysis demonstrates that adaptive reuse efficacy is the decisive determinant of successful regeneration. Achieving sustainability requires establishing a dynamic conservation model based on community symbiosis, wherein a building’s vitality is continually sustained through interaction with its social and cultural context. This study provides both a scientific tool and practical guidance for the assessment and management of non-designated historic buildings. It also underscores the necessity of a broader paradigm shift, contributing both theoretical and practical insights to the advancement of more inclusive and sustainable human settlements. Full article

This study aimed to analyze changes in vegetation, built-up areas, and population growth in Lahore city from 1990 to 2023. The data was acquired from Google Earth Engine, and the spectral bands were retrieved from Landsat 5 and Landsat 8. The decadal analysis of the landscape was conducted from 1993 to 2001, 2001 to 2012, and from 2013 to 2023. Further analysis was conducted in ArcGIS version 10.3 to evaluate the Normalized Difference Vegetation Index and the Normalized Difference Built-up Index to assess vegetation and built-up areas, respectively. To analyze the urban population of Lahore, data were obtained from the Global Human Settlement Layer for 1990, 2000, 2010, and 2020. Results revealed that the total vegetated area of Lahore city decreased from 1453.0 km² in 1993–2001 to 788.2 km² in 2013–2023. Moreover, the urban built-up area expanded from 319.6 km² in 1993–2001 to 966.8 km² in 2013–2023. Sub-district-level analysis indicated that Model Town and Raiwind areas of Lahore depicted better vegetation recovery in this decade. The population of Lahore has been increasing steadily, with the 2010s being a particularly rapid period of growth. The projections for 2030 also depict a continuous growth pattern. This study was further developed by integrating multi-decadal averaging coupled with selected-year analysis to distinguish gradual land transformation from relatively accelerated phases of urban expansion of Lahore. Also, by combining NDVI and NDBI values on both Lahore and its tehsil level, the research provides a collective sub-district- and district-level perspective into the spatial heterogeneity of peri-urban transformations. The findings of the study explain how major infrastructural projects shape the urban growth patterns of cities like Lahore and cause a decline in the green areas of fast-growing cities in South Asia. This study further highlights the consequences of unplanned urban expansion in regions where high population growth has compromised green infrastructure and threatened ecological balance. In addition, it supports several Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land) by providing spatial evidence of urban expansion of the city and losses of its green spaces. The findings offer empirical insights to support climate-resilient developments. The study also demonstrates the necessity of integrating green infrastructure and providing robust strategies for forthcoming urban planning projects and policy development regarding urban expansion. Full article

Cultural diversity holds an irreplaceable ecological value in biodiversity conservation. Jingxi is a county-level city in Baise City, Guangxi Zhuang Autonomous Region. In Jingxi, where the Zhuang ethnic group accounts for 99.4% of the population, a symbiotic relationship has developed between its unique ethnic culture and ecological environment. According to the 2017 census of old trees (OTs) in Jingxi, a total of 1361 OTs were recorded, of which 63.3% (865 trees) were concentrated in human settlements, including village entrances or exits, and cultivated lands, demonstrating significant spatial differentiation. This distinctive distribution pattern raises two core research questions: (1) What are the spatial distribution patterns of OTs within human settlements? (2) Do cultural factors play a significant role in OTs conservation? Therefore, an ethnobotanical study of OTs in Jingxi is necessary. The objectives of this study are to: (1) conduct a comprehensive ethnobotanical investigation of the OTs among the Zhuang people in the region; (2) summarize the environmental spaces of OTs based on their geographical locations; (3) analyze the symbolic cultural meaning associated with OTs across different environmental spaces. This study also aims to reveal conservation strategies for OTs from a cultural perspective and to integrate cultural values into biodiversity conservation, thereby providing significant insights into the mechanisms underlying cultural–ecological synergy. Full article

Urbanization and climate change are exerting significant pressure on the living environments of traditional rural settlements. In western Sichuan, the persistently cold and humid winter further intensifies the risks for local residents. Linpan, a distinctive agricultural settlement form that has evolved over centuries, embodies climate-responsive construction wisdom shaped by long-term human–environment interaction. Within Linpan, residential units—composed of outdoor and indoor spaces—serve as the primary activity spaces for inhabitants. Their spatial configuration and construction practices directly regulate the thermal environment and consequently influence daily life. However, whether the winter thermal environment satisfies contemporary thermal comfort requirements, and which landscape and construction determinants can effectively enhance thermal adaptation, remains insufficiently understood. To address this gap, this study integrated meteorological field measurements, thermal comfort questionnaire surveys, and coupled numerical simulations to systematically investigate winter thermal conditions in both outdoor and indoor spaces of Linpan residential units. The optimization performance of key landscape determinants (vegetation configurations and ground materials) and construction determinants (building layouts and envelope materials) was evaluated. The results reveal climate-responsive passive design strategies based on actual inhabitants’ thermal adaptation, establishing a sustainable design framework for improving winter thermal comfort in traditional agricultural settlements. The findings provide scientific support for rural revitalization and contribute theoretical insights into climate-resilient preservation of vernacular dwellings under changing environmental conditions. Full article

As a result of China’s rapid urbanization, new urban districts are characterized by a superblock development paradigm that contrasts sharply with core urban areas, where service facilities remain largely congruent with the population distribution. This planning approach has resulted in a pronounced spatial mismatch, with an intensive concentration of public service facilities within commercial cores and a critical lack of facilities proximate to high-density residential clusters. Within the framework of the 15 min community life circle policy, evaluating and optimizing these configurations is imperative for mitigating such structural imbalances. Using Xi’an’s Qujiang New District as a representative empirical case, this study integrates Point of Interest (POI) geospatial data with 330 resident behavioral questionnaires to assess facility distribution and utilization patterns. The findings reveal a distinct spatial pattern of core–periphery polarization, which is significantly influenced by cultural landscapes and commercial land values. Furthermore, the utilization patterns differ markedly across age groups. The reliance of young and middle-aged groups on digital life circles should be viewed not only as a lifestyle preference but also as an adaptation to mitigate physical facility deficits. While digital services compensate for physical facility shortages, they mask the actual lack of community spaces. This further disadvantages older adults, who still rely heavily on walking to access daily services. Addressing the unique characteristics of new urban districts, this study proposes a synergistic physical–digital dual-tier system in which physical infrastructure safeguards the equity baseline, while digital platforms enhance operational efficiency, providing a scientific basis for constructing age-friendly communities. Full article

Optical and passive remote sensing-based estimation of aboveground biomass (AGB) using forest structural stratification has shown improvements over global models. This study investigated whether stratification by human-mediated disturbances improves prediction accuracy. Disturbance variables included proximity to mines, roads, and settlements, evaluated across three regimes: the full Atewa landscape (“FSR”), the Atewa Range Forest Reserve (“FR”), and the surrounding disturbed area (“SR”). Predictor selection for regimes was performed using recursive feature elimination with cross-validation, applied to random forest (RF) and support vector machine (SVM) algorithms. AGB was then estimated using local, global, and retuned global models, and the results were compared using the coefficient of determination (r²) and root mean square error (RMSE). The global RF model achieved the best performance (r² = 0.54; RMSE = 57.71 Mg/ha), likely due to structured heterogeneity captured across combined regimes. The “SR” models, however, performed poorly, indicating that excessive unstructured heterogeneity introduces noise and redundancy that weaken predictions. The low performance of the “FR” regime was attributed to spectral saturation and limited variance in observed AGB. Although disturbance factors added minimal bias, heteroscedasticity was evident in the “SR” and “FSR” regimes. Overall, this study indicates that disturbance-based stratification may not necessarily improve AGB estimation accurately compared to global models. However, it highlights the value of disturbance information for AGB modeling in heterogeneous forest landscapes. Full article

The growing occurrence of emerging contaminants, particularly pharmaceutical residues, in aquatic environments represents a major environmental concern worldwide. While pharmaceutical contamination has been increasingly studied in marine systems, port environments remain largely understudied despite their complex anthropogenic pressures. This study investigates the occurrence, spatial distribution, and potential environmental risk of pharmaceutical residues in surface waters of the port of Cartagena, a multifunctional port on the Spanish Mediterranean coast. Fifteen pharmaceuticals were analysed across nine sampling sites, of which six were not detected. Diclofenac and several antibiotics (erythromycin, azithromycin, clindamycin, and trimethoprim) were the most frequently detected compounds, reaching maximum concentrations of up to 12,294.1 ng/L. Elevated concentrations were observed at sites associated with intense human activity, while the detection of multiple pharmaceuticals at a designated Special Area of Conservation suggests additional diffuse pollution sources, likely linked to insufficient wastewater management in nearby informal settlements. Most detected concentrations exceeded established environmental-quality or risk-threshold values, indicating a potential threat to marine ecosystems. These findings highlight the vulnerability of port environments to pharmaceutical pollution and underscore the need for continuous monitoring programs to support effective environmental management and biodiversity protection in coastal port areas. Full article

The enclave villages of Lake Malawi National Park (LMNP) are human settlements within a World Natural Heritage landscape. While social heterogeneity has been widely discussed in social–ecological systems (SES) scholarship, ethnic diversity has often remained analytically implicit. This study makes ethnic diversity central to analysis by examining how it shapes livelihoods, resource use, and governance across enclave villages. Drawing on an integrated household survey, key informant interviews, and extended field observations, and informed by collaboration theory, the SES framework, and scholarship on social differentiation, the analysis shows that ethnic diversity facilitates exchanges of fishing techniques, farming skills, ecological knowledge, and market linkages, producing plural and seasonally adaptive livelihood portfolios. Households routinely combine fishing, agriculture, tourism, petty trade, and forest use, contributing to diversified resource use. However, pressures on fish stocks, forest resources, and agricultural land highlight the need for more inclusive co-management. Emerging community-based institutions and collaborative initiatives increasingly facilitate coordination, rule-making, and shared stewardship. Overall, the findings identify practical and conceptual entry points through which ethnic diversity, ecological knowledge, and adaptive livelihoods can jointly support more resilient and inclusive pathways for sustainability at the crossroads of resource-dependent livelihoods and conservation, offering insights for socially diverse human–nature landscapes. Full article

Achieving sustainability in prefabricated construction necessitates a balance between operational efficiency and stringent environmental constraints. However, cascading rework chains triggered by assembly defects frequently disrupt this equilibrium. Existing literature predominantly addresses this dynamic through reactive rescheduling, thereby largely overlooking the potential of proactive topological interception. To bridge this gap, this study proposes a proactive bi-level scheduling framework that mathematically integrates strategic quality inspection planning with operational low-carbon project execution. Specifically, a Generalized Total Cost (GTC) model is formulated to internalize multi-objective trade-offs—including time, cost, and carbon emissions—into a unified financial metric through market-based shadow prices. This framework is operationalized through a novel bi-level Hybrid Evolutionary Algorithm (H-TS-CDBO). By combining the global exploration capabilities of Chaotic Dung Beetle Optimization with the local refinement mechanisms of Tabu Search, the proposed solver is specifically engineered to navigate the topological ruggedness induced by proactive inspection interventions. Empirical benchmarking validates the computational robustness of the solver, while an illustrative case study substantiates a critical managerial paradigm shift from “passive remediation” to “active prevention”: compared to traditional methods, a marginal preventive investment of 5.4% functions as an effective containment mechanism, yielding a 40.8% net reduction in the GTC. Furthermore, a sensitivity analysis regarding varying static carbon tax rates simulates algorithmic adaptation under diverse regulatory intensity thresholds, delineating an actionable pathway for project managers to achieve lean, low-carbon synergy amidst evolving regulatory pressures. Full article