Search Results (291)

This research examines how the relationship between cities and rural areas has evolved in light of the profound transformation affecting rural areas of high landscape value, which has been driven by the expansion opportunities granted to the real estate sector by urban planning regulations. The role of the landscape dimension in interpreting the relationship between territorial wealth and landscape value is considered, based on the convergence of two complementary disciplinary perspectives on territory: land planning and valuation science. Against this backdrop, and with a view to containing the progressive contamination of rural and agricultural heritage by the real estate sector, this study proposes a structured observation, valuation, interpretation, and regulatory tool to support the development of territorial planning in areas significantly characterized in terms of rural landscape value. The proposed tool is based on evidence regarding the phenomenon of building expansion in the agricultural territory of a municipality in southeastern Sicily, where favorable conditions for the development of the building sector exist, such as the vastness of the municipal territory and extensive farming as the mainstay of agricultural activity. This wider sub-regional area has also received attention due to the over-tourism phenomenon that has occurred in its cities of art. The evaluation approach experienced is a value-based representation of the evolution of this process over three observation periods: 2000, 2007, and 2012, relating the quantitative observation of the building expansion to the connected qualitative impact on rural landscape. It is the result of coordinating a large set of data in a hierarchical model of indices that converge to construct a synthetic index of rural landscape resilience. This achievement is based on the linguistic progression of “lexicon”, “semantics”, “syntax”, and “pragmatics”, each of which robustly supports “observation”, “valuation”, “interpretation”, and “planning”, respectively. The final stage is based on the convergence of explanatory indices, which are developed by coordinating evidence and assessments (factual and value judgements). This stage enables the proposal of a constraints system that supports a modus vivendi between the interests of the real estate sector and the values of the rural landscape in such a rich and fragile area. Full article

Large trees are keystone ecological structures that sustain biodiversity and ecosystem services, particularly in human-altered landscapes. However, their persistence is increasingly threatened by land-use change, urban expansion, and inadequate monitoring. This study develops and validates a scalable, automated framework for monitoring the loss of large individual trees using satellite image time series and breakpoint detection. We compared four spectral indices (SIs): Enhanced Vegetation Index 2–EVI2; Normalized Burn Ratio–NBR; Normalized Difference Red Edge–NDRE, and the Normalized Difference Vegetation Index–NDVI derived from Sentinel-2 imagery (2015–2025) for 691 georeferenced trees in Lousada, northern Portugal. Data were accessed and processed in Google Earth Engine and analyzed using a custom R-based workflow, including cloud masking, gap-filling, temporal interpolation, upper-envelope smoothing, deseasonalization, and break detection. Five breakpoint detection algorithms were compared: BFAST, energy-divisive, linear regression of structural changes, wild-binary segmentation, and change point models. Detected breakpoints were subsequently post-validated to determine whether they were associated with declines in SIs, using three pre-/post-breakpoint methods: comparisons of short- and long-term medians and a randomized trend analysis. As a baseline, these algorithms/post-validation logic were compared against the Continuous Change Detection and Classification (CCDC) approach. The results indicate moderate but consistent break detection performance, with a maximum balanced accuracy of 73% (for EVI2 or NDVI and using the energy-divisive algorithm coupled with the long-term median post-validator) under conservative validation criteria and high specificity for surviving trees. CCDC ranked comparatively lower at 62%. Algorithm performance varied substantially, with the energy-divisive providing the most conservative detection and the wild-binary segmentation yielding higher sensitivity. Performance was further influenced by tree structural attributes and species identity, with larger, taller and isolated trees, as well as particular genera, showing higher detection accuracy, with genus Eucalyptus, Tilia and Celtis yielding top performance results (79–65%) and Quercus, Castanea and Platanus the lowest (62–60%). By integrating satellite observations with large-tree inventory data from the Green Giants citizen science project, this study demonstrates the potential of decentralized, Earth observation-based monitoring to support tree-level loss assessments in fragmented landscapes. The proposed framework provides a transferable foundation for wide-scale monitoring of large trees in peri-urban and mixed-use environments. Full article

Under the background of global urbanization, the impacts of urban expansion on biodiversity are becoming increasingly significant. Butterflies, as key ecological indicator species and important pollinators, are crucial for studying population dynamics and their driving factors in order to support biodiversity conservation and environmental governance. Butterflies also have important ecological value in urban biodiversity conservation and landscape maintenance. Currently, in many countries, especially developing countries, impervious surfaces and vegetation cover are undergoing significant changes as urbanization intensifies. Existing studies have begun to focus on the effects of these changes on biodiversity conservation. However, most studies primarily focus on the single effects of these two factors on biodiversity, while systematic assessments of their potential interactive effects remain limited. In this study, monthly butterfly population monitoring was conducted in Kunming, China, for two consecutive years. The study aimed to clarify the composition of butterfly diversity in Kunming and to explore the effects of impervious surfaces and vegetation cover on butterfly species richness, abundance, Shannon index, Simpson index, and community structure. The results showed that impervious surface was the primary driving factor influencing both butterfly richness and abundance, while the influence of vegetation cover was relatively limited. The Shannon and Simpson indices were not significantly influenced by either environmental factor. Environmental filtering caused by impervious surfaces and vegetation cover drove species turnover processes. Consequently, butterfly communities exhibited the highest heterogeneity in areas characterized by low impervious surfaces and high vegetation cover. In contrast, areas with high impervious surfaces and low vegetation cover tended to show a pattern of community homogenization. Urban planning should balance the control of impervious surface proportions with the appropriate enhancement of vegetation cover and plant diversity. Such measures may mitigate the negative impacts of intensified urbanization on butterfly diversity to some extent. Full article

Urban agglomerations serve as crucial spatial carriers for advancing people-centered new urbanization. However, the integrated analysis of urban expansion dynamics, landscape pattern responses, and their driving mechanisms, particularly in ecologically sensitive, late-developing urban agglomerations, remains insufficiently understood. Taking the Guanzhong Plain Urban Agglomeration (GPUA) as the study area, this paper utilizes the Urban Expansion Rate Index (UERI), Urban Expansion Intensity Index (UEII), Landscape Expansion Index (LEI), and Landscape Pattern Metrics (LPMs) to examine urban land expansion and landscape pattern changes, and employs GeoDetector to analyze the driving forces behind these changes. The findings indicate that from 1990 to 2020, the urban land area of the GPUA expanded continuously, with UERI and UEII showing an “increase-then-decrease” trend. Significant disparities exist among cities in the urban expansion areas, with the coexistence of “edge” and “infilling” modes profoundly influencing landscape responses. The driving forces of urban expansion have undergone a stage-specific transition from socioeconomic dominance to ecological policies and natural constraints, with policy–institutional control, socioeconomic development drivers, natural endowment constraints, and improved locational conditions collectively shaping the GPUA’s “spatial landscape” system. The findings of this study provide a scientific basis for territorial spatial governance and sustainable development in ecologically fragile urban agglomerations. Full article

Rural settlements are significant carriers of rural production, living, and land use activities and are also significant subjects for researching regional socio-economic development and spatial structural changes. With regard to the unique topographical environment and transportation situation in the Qiongbei volcanic lava area, a settlement form with prominent topographical constraints and transportation orientation is created. This paper utilizes land use/land cover data from different periods, along with rural settlement expansion patch data, to quantitatively analyze the spatial patterns and expansion characteristics of rural settlements, as well as their influencing factors, from 1990 to 2025 using GIS spatial analysis, buffer gradient analysis (BGA), and multi-order adjacency index (MAI). The research results indicate the following: (1) The spatial pattern of rural settlement distribution in the study area is “peripheral agglomeration and core sparsity,” and the general expansion trend is “rapid in the early period and stable in the late period.” The settlement area expands from 37.21 km² in 1990 to 80.87 km² in 2025. (2) The evolutionary pattern of rural settlements in the study area changes from “core–peripheral extension” in the early period to a mixed “core stabilization and peripheral leapfrogging development” model in the later period. The new patches formed in the peripheral areas have obvious discrete features, such as varying land use patterns and differing population densities compared to the core areas. (3) The spatial correlation factors for rural settlement expansion in the study area exhibit stage differences and distinct spatial non-stationary characteristics. During the early period (1990–2008), with strict limitations imposed by the natural material environment, sunlight (interpretability of 0.367) and water systems (0.286) show significant spatial coherence, indicating the great adaptability of rural settlements to the material conditions of the landforms; during the later period (2008–2025), after the implementation of the rural revitalization strategy, the population density (0.135) and transport-related factors become the main spatial correlation factors. The GWR model also shows the percentage of positive and negative influences by influencing factors at each stage and their significant differences in space, proving that human activities break through in the limitations of natural topology in a discontinuous way. According to this research, “inefficient land use” should be understood in a dialectical manner in volcanic geomorphological areas, and spatial optimization should be achieved on the premise of respecting the physicality of volcanic landscapes and rural identity. The research conclusions have important guiding significance for the spatial resilience planning in tropical volcanic areas and traditional settlement culture preservation. Full article

Urban green spaces are increasingly threatened by rapid urban expansion, making their continuous monitoring and prediction essential for sustainable urban management. This study investigates the spatiotemporal dynamics of urban garden landscapes in Shiraz, Iran, by integrating multi-temporal Landsat imagery, GIS analysis, and CA–Markov modeling. Landsat data from 2003, 2013, and 2023 were processed to derive the Normalized Difference Vegetation Index (NDVI), which was classified into four vegetation-density categories to quantify land-cover transitions. A CA–Markov framework implemented in IDRISI TerrSet (Version 20.0) was then employed to simulate spatial dynamics and predict vegetation changes for 2033. Results reveal a significant expansion of non-vegetated areas from 711.93 ha in 2003 to 976.66 ha in 2023, accompanied by a decline in dense vegetation from 403.68 ha to 382.64 ha. Model projections indicate a further reduction in dense vegetation to 239.35 ha by 2033, suggesting ongoing fragmentation of urban green infrastructure driven by development pressures. By combining time-series remote sensing, GIS-based spatial analysis, and predictive modeling, this study provides an integrative framework for detecting, interpreting, and forecasting urban land-cover change. The findings offer evidence-based insights to support sustainable urban planning, green infrastructure protection, and climate-resilient city management in rapidly growing urban environments. Full article

The Linpan in western Sichuan is a composite rural landscape of “household-water-forest-field” on the Chengdu Plain. Under the interference of human activities, problems such as landscape fragmentation and ecological function degradation have become increasingly serious, threatening regional ecological security. The specific components involved in the “study on ecological risk sequence” include landscape disturbance degree, landscape vulnerability degree, landscape connectivity, and human activity intensity. Given the lack of long-term ecological risk research on the Linpan landscape in Chongzhou City to support conservation decisions, this study takes it as the object. Based on five phases of land use data from 2003 to 2023, a landscape ecological risk assessment model was constructed. This model is a deterministic and nonlinear comprehensive evaluation model. The determinism is reflected in the fact that, based on specific influencing factors, a unique and definite result can be obtained through a fixed indicator system and calculation method. The nonlinearity is reflected in the fact that the comprehensive risk index does not involve a simple linear superposition of the various factors; instead, the evaluation result is obtained by integrating the factors through nonlinear approaches such as weighted coupling. Using ArcGIS and spatial analysis methods, based on a temporal resolution of 5 years and a spatial resolution of 30 m, the spatiotemporal evolution characteristics were revealed. The results show that: (1) From 2003 to 2023, the Linpan landscape pattern in Chongzhou City underwent significant evolution, characterized by “reduction in agricultural land, expansion of construction land, and slight recovery of ecological land”. Landscape fragmentation intensified, connectivity decreased, but overall aggregation remained stable. (2) The evolution of the landscape pattern drove the ecological risk to show a stable pattern of “low in the northwest and high in the southeast”. The global Moran’s I value decreased from 0.887 to 0.832, indicating that risk aggregation intensified in the early period and was alleviated in the later period. (3) Landscape disturbance degree is the key factor dominating the change in the comprehensive ecological risk index. Compared with similar studies, this research shares the commonality of urbanization-driven fragmentation exacerbation risk, but also exhibits the uniqueness of Linpan structural resilience and conservation policies promoting a reduction in high-risk areas. This study can provide a scientific basis for Linpan protection, land use optimization, and ecological security pattern construction in Chongzhou City. Full article

Virtual reality (VR) has been increasingly adopted as a digital tool in rehabilitation for balance training, coordination improvement, and motor recovery, yet the literature remains dispersed across clinical rehabilitation, exercise-based interventions, and broader motor-related applications. This fragmentation makes it difficult to determine how the field has evolved and where research emphasis has shifted. This study mapped the research landscape and thematic evolution of VR for balance, coordination, and motor rehabilitation using bibliometric analysis and topic modeling. A total of 1258 articles indexed in the Web of Science Core Collection from 2011 to 2025 were analyzed. Only English language articles and reviews relevant to VR-based balance, coordination, or motor rehabilitation research were included, yielding a final dataset of 1258 publications. CiteSpace and VOSviewer were used to examine keyword co-occurrence, clustering patterns, and temporal trends, while Latent Dirichlet Allocation (LDA) was applied to identify latent themes and their temporal dynamics. The field has moved beyond early feasibility testing toward a more differentiated landscape shaped by distinct clinical targets, population groups, and training purposes. Seven recurring themes were identified, including vestibular rehabilitation and immersive training, post-stroke upper-limb rehabilitation, efficacy and adverse-effect assessment, balance and gait training interventions, evidence synthesis and review-based evaluation, elderly exercise and cognitive interventions, and skill-oriented virtual task training with recent expansion toward broader population groups and task-specific applications beyond traditional rehabilitation settings. VR research on balance, coordination, and motor rehabilitation has evolved into a more thematically differentiated field rather than remaining a single rehabilitation-oriented domain. By combining bibliometric mapping with topic modeling, this study clarifies where evidence is concentrated and which thematic directions are gaining visibility, providing a clearer basis for future evidence synthesis and more comparable intervention reporting. Full article

Casablanca, Morocco’s most populous and economically dynamic metropolis, is undergoing rapid and unregulated expansion, leading to accelerated agricultural land artificialization, landscape fragmentation, and growing socio-environmental vulnerability in peri-urban territories. This study investigates the spatio-temporal dynamics of urban expansion within a 40 km buffer around the city, using multi-temporal Landsat imagery (2015–2025), a GIS-based framework, and supervised classification. Four land-cover classes were extracted (urban, vegetation, forest and water) enabling a diachronic comparison of land transformation processes. Two spatial indicators were mobilized to quantify urban dynamics: the Average Urban Expansion Rate (AUER) and the Urban Expansion Intensity Index (UEII). Results reveal that urban areas expanded by up to 387.9% in some communes, with 15 exceeding an AUER of 25% and 17 falling within the “very high development” category based on UEII thresholds. Land artificialization was most intense along southern and southeastern peripheries, notably Deroua, Tit Mellil, Had Soualem, and Sidi Moussa Ben Ali, resulting in severe fragmentation of agricultural land. The classification of communes into four profiles (fast, slow, consolidated, and stable) highlights varying degrees of territorial vulnerability. By integrating demographic trends (2014–2024), the study exposes mismatches between population growth and land consumption, underscoring the urgent need for integrated spatial diagnostics and governance reforms toward sustainable peri-urban land management. Full article

This study focuses on the Dabie Mountain Comprehensive Station in Anhui Province, constructing a multi-scale analytical framework and integrating remote sensing and socio-economic data to systematically assess the spatiotemporal evolution of ecosystem service bundles (ESBs) and landscape ecological risks using SOFM, XGBoost, and SHAP models. The research categorizes ecosystem service functions into four types: water conservation core areas, carbon storage–habitat optimization areas, carbon storage–water production composite areas, and multifunctional synergy areas. From 2013 to 2023, the proportion of multifunctional synergy areas increased from 39.85% to 42.86%, while carbon storage-habitat optimization areas and water conservation core areas decreased by 28,035.47 hm² and 2118.8 hm², respectively, indicating significant spatial restructuring of regional ecosystem service functions. The landscape ecological risk exhibits a pattern of “medium risk dominance with high-low polarization,” where high-risk areas overlap with urban expansion zones, and low-risk areas are concentrated in ecological conservation zones. Quantitative analysis reveals that climatic factors (e.g., annual precipitation) dominate the risk patterns in water conservation core areas and ecological conservation zones, topographic factors (e.g., elevation) influence regional spatial differentiation, and socio-economic factors (e.g., nighttime light index) significantly affect agricultural production core areas. The findings elucidate the evolutionary patterns of ecosystem service functions and the mechanisms of risk formation in the Dabie Mountain region, providing a scientific basis and technical support for regional land use optimization, ecosystem function enhancement, and ecological security assurance. Full article

Prolonged drought and rapid land-use transformation are reshaping peasant farming systems worldwide, particularly in regions exposed to extractive agribusiness expansion. This study examines how socio-ecological resilience varies across farming systems differentiated by ethno-cultural background under Chile’s megadrought (2009–2019) in the Araucanía Region. We conducted a longitudinal assessment of 78 smallholder farms (30 Mapuche, 30 Chilean, 18 European descent) using a resilience index integrating vulnerability (water access, proximity to exotic forest plantations, cultivated homogeneity) and response capacity (drought-resistant crops, knowledge and preventive practices for dealing with water deficit, social networks). The results show that Mapuche farming systems consistently exhibited higher resilience, associated with greater cultivated diversity, a lower presence of neighboring forest plantations, and greater knowledge of how to deal with drought events. In contrast, non-Mapuche systems displayed higher vulnerability indicators linked to increased cultivated homogeneity. Over the 10-year period, 32% of the farms included in this study collapsed, primarily due to conversion to exotic forest plantations, disproportionately affecting European-descent and Chilean farms. The higher permanence of Mapuche farms demonstrates that resilience is not solely determined by climatic exposure but is strongly mediated by ethno-cultural land-use practices and socio-ecological memory. The interaction between the megadrought and exotic forest plantations-driven landscape homogenization accelerates differential system persistence. Strengthening agroecological diversity and recognizing culturally embedded agricultural management practices are critical for sustaining resilient farm systems under climate change. Full article

The accelerated expansion of advanced technologies—particularly artificial intelligence, intelligent systems, and interactive digital environments—is influencing contemporary media ecosystems and contributing to changes in educational practices. This study provides a systematic and descriptive bibliometric mapping of recent scientific production on artificial intelligence in education, algorithmic ethics, and digital inequality. A total of 229 Scopus-indexed documents published between 2021 and 2026 were analyzed using Biblioshiny and VOSviewer to examine publication patterns, influential authors and sources, and the conceptual structure of the field. Results indicate a marked increase in research output since 2024, with an annual growth rate of 47.58%, an average of 8.68 citations per document, and an international co-authorship rate of 24.45%. These indicators reflect an expanding and increasingly collaborative research landscape, accompanied by a diversification of thematic priorities within the field. The analysis identifies five thematic clusters: (1) the technical foundations of AI and digital transformation; (2) intelligent and immersive learning environments; (3) personalized and adaptive learning systems; (4) AI literacy and pedagogical integration; and (5) ethical considerations, including algorithmic bias and educational robotics. The findings highlight the need for explicit justification of database selection, strengthened critical AI literacy, and context-sensitive strategies that address disparities in access, skills, and institutional capacity. Overall, this study offers a coherent overview of a research area that is currently expanding and undergoing conceptual reorganization, providing evidence-informed insights for future research, policy development, and the design of equitable AI-driven educational technologies. Full article

Regional differences in land use transitions and urban expansion patterns have become increasingly pronounced under rapid urbanization. However, conventional land use and land cover change (LUCC) analyses often rely on independent graphical presentations, limiting systematic cross-regional comparison and the identification of spatial heterogeneity. To address this limitation, this study constructs a comparative land use transition analytical framework integrating LUCC contrastive transition patterns, the landscape expansion index (LEI), and the PLUS model. The framework enables structured identification of transition directions, intensity differentials, and stage-specific characteristics, thereby enhancing the reproducibility and comparability of cross-regional land use analysis. Using Xi’an (inland) and Quanzhou (coastal) as representative cases, this study analyzed their land use changes from 1990 to 2020 based on Intensity Analysis and LUCC contrastive transition patterns and quantified the differences in urban expansion using the urban expansion intensity index and expansion pattern metrics. The results show that the urban expansion of Xi’an and Quanzhou was active during 1990–2020, with crops as the main stable source of urban expansion. This urban expansion mainly took the form of edge-expansion and infilling, with urban development transitioning from disorderly expansion to intensive utilization. Notable regional disparities were observed: Forest conversion to urban land was substantially higher in Quanzhou, reflecting stronger ecological land pressure in coastal areas, whereas grass conversion to crops was more prominent in Xi’an, suggesting agricultural spatial adjustment under food security constraints in inland regions. The PLUS model further demonstrates that urban expansion is jointly influenced by topographic conditions (DEM) and economic growth (GDP), highlighting the coupled effects of natural constraints and development dynamics. This study clarifies the differentiation characteristics and driving forces of coastal and inland urban expansion, providing a scientific basis for differentiated territorial spatial planning, ecological protection, and farmland management in eastern and western regions. It also helps formulate more targeted urban development policies based on regional resource endowments, promoting regional coordination and sustainable urbanization. Full article

Global high-mountain ecosystems are increasingly subjected to intensified anthropogenic disturbances, which facilitate the spread of invasive alien plants and threaten agricultural sustainability and ecological security. Using Laojun Mountain in Yunnan as the study area, this research investigates the relationship between the distribution patterns of invasive plants and land-use changes, based on data from 38 transect surveys conducted in 2023 and 30-m-resolution land-use data spanning 2003–2023. The analysis incorporates a random forest model and a land-use transition matrix. The key findings are as follows: (1) Variable importance analysis revealed elevation as the most critical factor influencing invasion occurrence (mean decrease in Gini index: 8.0), followed by slope, aspect, and land-use type. (2) Cultivated land exhibited the highest probability of invasion, with high-risk areas (>0.8) concentrated in agricultural zones in the central-southern and northeastern regions. (3) From 2003 to 2023, cultivated land increased by a net area of 20.85 km², primarily due to conversion from forests (19.57 km²) and grasslands, while grassland area decreased by 24.70 km². This study concludes that agricultural expansion has intensified habitat fragmentation and anthropogenic disturbances, creating favorable conditions for invasive plant establishment. It is recommended that invasive species monitoring and ecological restoration efforts be strengthened in agroforestry transition zones to enhance landscape resilience against biological invasions. 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