Search Results (364)

Universal health coverage requires simultaneous progress in service coverage and financial protection, yet these dimensions are commonly assessed separately. We conducted a secondary ecological panel analysis using official World Health Organization/World Bank indicators. A document-oriented workflow preserved irregular subgroup structures before conversion to an unbalanced country–year panel comprising 981 observations from 159 countries/economies between 2000 and 2023. The primary inferential specification was a two-way fixed-effects model with country and year effects and country-clustered standard errors; a country fixed-effects model with a linear time trend, a random-intercept model, and generalized estimating equations were complementary robustness analyses. We also examined service domains, wealth- and rural-urban inequalities, beta convergence, and exploratory country typologies. Mean service coverage rose from 58.9 in 2000 to 74.0 in 2023, whereas mean financial hardship fell from 24.0% to 17.3%. In the primary model, each one-point increase in service coverage was associated with a 0.441-percentage-point reduction in hardship (95% confidence interval, −0.707 to −0.175; p = 0.001). Mean poorest–richest and rural–urban hardship gaps were 53.7 and 12.5 percentage points, respectively. The inverse association was largest in low-income settings, where socioeconomic gradients were also steepest. Service coverage gains should therefore not be interpreted as sufficient evidence of equitable universal health coverage; monitoring systems and financing reforms should jointly target access, financial protection, and distributional gaps. Full article

Urban expansion generates habitat fragmentation, light pollution, and vegetation loss, driving biodiversity decline globally. Insectivorous bats are particularly suited to track these changes: their taxonomic and functional diversity, combined with their differential sensitivity to landscape configuration and roost availability, makes them reliable bioindicators of urbanization impacts. This study characterized bat acoustic diversity and community composition along an urban–rural gradient in Tacna, Peru, using passive acoustic monitoring. Twenty-three stations equipped with autonomous ultrasonic recorders were established between December 2024 and April 2025. Sonotype identification was validated through linear discriminant analysis (DFA), achieving 94.47% accuracy by Leave-One-Out Cross-Validation (LOOCV). Nine sonotypes were identified, seven Molossidae and two Vespertilionidae; Myotis atacamensis showed the highest detection frequency across all districts. Diversity indices were highest in the peri-urban zone of Pocollay (S = 8; H′ = 1.664) and lowest in Gregorio Albarracín (S = 4; H′ = 0.964). The high dissimilarity between Pachía and the urban core of Tacna (BC = 0.817) points to marked compositional differences linked to urbanization intensity. Records of Nyctinomops laticaudatus and N. macrotis constitute the first documentation for the urban area of Tacna. These results suggest urban and peri-urban sectors may function as ecological oases for bat sonotypes within a hyperarid matrix, providing a baseline for evaluating the role of green spaces, landscape connectivity, and artificial lighting in arid cities. Full article

Background/Objectives: Disordered eating behaviours are increasingly common among young adults, yet nutrition-focused, region-specific data from Romania and Central and Eastern Europe (CEE) remain scarce. We characterised nutritional patterns, weight-control practices, disordered-eating indicators, body image, and psychosocial factors among Romanian young adults and tested how these differed across body mass index (BMI) categories. Methods: In a cross-sectional online survey (March–April 2026), 753 Romanian adults aged 18–30 years (93.5% female) completed a 30-item questionnaire. Self-reported anthropometric measurements were classified using WHO BMI cutoffs. Prevalences (with Wilson 95% confidence intervals [CIs]) were compared across BMI categories using the chi-square test, and multivariable logistic regression, adjusted for age and sex, estimated odds ratios (ORs). Results: Most participants were normal weight (59.1%); 11.6% were underweight, 29.3% were overweight or obese, and 86.3% were omnivorous. Dietary restriction (57.4%) and physical exercise (46.7%) were the leading weight-control methods; self-induced vomiting (6.4%) and medication (4.5%) were less frequent. Lifetime compulsive/emotional eating was reported by 50.1%, current stress-related eating by 49.1%, and guilt after eating by 66.1%. Lifetime night eating reached 31.9% (current, 12.9%). Body dissatisfaction (36.1% “not at all satisfied”), difficulty looking in the mirror (66.7%) and self-reported stress (82.2%) were widespread. In adjusted models, dietary restriction, emotional eating and guilt after eating rose steeply and monotonically with BMI (overweight/obesity vs. normal weight: aOR 2.34, 2.49 and 2.73, respectively; all p < 0.001), whereas current night eating and frequent self-weighing did not differ across BMI categories (p = 0.92 and p = 0.82). Dietary restriction increased from 24.1% in underweight to 55.5% in normal-weight and 74.2% in overweight/obesity participants; corresponding gradients were also observed for emotional eating and food-related guilt. Conclusions: In this predominantly female, largely urban online convenience sample of Romanian young adults, self-reported behavioural risk indicators related to disordered eating were common. Restriction, emotional eating and food-related guilt increased with BMI, whereas night eating and self-weighing showed no clear BMI gradient. These findings should be interpreted cautiously and should not be generalised to Romanian young men or rural populations without confirmation in more representative samples. Full article

Urban–rural governance and planning systems, as viewed through the lens of online public attention, are reshaping approaches to achieving coordinated development of cultural heritage conservation and urban space. Taking Nanchang as a case study, this paper investigates the application mechanism of online public attention in the evaluation of heritage corridor nodes and the formulation of optimization strategies. Employing multi-source data collection, we extracted textual content from online travelogues. We quantified the online attention level of each cultural heritage unit and analyzed its spatial distribution using kernel density estimation and standard deviational ellipse methods. We then applied a minimum resistance model, incorporating geographic data on land use and transportation networks, to identify potential heritage corridor routes. Based on attention classification, we propose a three-tier optimization strategy: core-leading, marginal-activating, and gradient-linking. Specifically, high-attention heritage units are positioned as central nodes that reinforce corridor connectivity; low-attention nodes are targeted for activation through corridor links to overcome spatial isolation; and attention gradients serve as the basis for hierarchical integration across the network. Our results reveal a pronounced spatial pattern of “core agglomeration and peripheral dispersion” in Nanchang’s heritage corridors. High-attention resources are heavily concentrated in the historic urban core, anchoring the main corridor axes, whereas low-attention resources are scattered across peripheral counties, exhibiting a clear urban–rural attention gradient. Importantly, attention levels show a positive correlation with corridor hierarchy. These findings provide a novel perspective for heritage corridor spatial planning and offer practical insights for sustainable cultural heritage governance and culture–tourism integration in an era of pervasive internet and urban expansion. Full article

Ground-level ozone (${\mathrm{O}}_3$) is a secondary photochemical pollutant whose formation under intense Mediterranean solar radiation makes Greece prone to elevated concentrations, with well-documented respiratory and cardiovascular health effects. Forecasting of ozone in Greece has nonetheless remained limited: prior work has been largely statistical, focused on one or two sites in Athens, and restricted to a single horizon, and no study has compared machine learning forecasts across the urban-to-rural gradient of the national monitoring network. This study addresses that gap with, to our knowledge, the first multi-site comparison of machine learning ozone forecasts spanning the full urban-to-rural typology gradient of a Greek monitoring network, introducing a typology × model accuracy cross-matrix that links site character directly to forecasting performance and offers concrete, horizon-specific operational guidance for early warning deployment. We develop a single, reproducible pipeline and compare three model families, Support Vector Regression (SVR), Random Forest (RF) and gradient boosting (GBM), against a naïve persistence baseline, for next-hour and next-day-maximum ${\mathrm{O}}_3$ prediction at eight urban, suburban and rural stations of the National Air Pollution Monitoring Network (2021–2024). All predictors are derived from the ozone series itself (lagged, rolling and cyclical calendar features); models were tuned and evaluated using a strictly chronological 70/15/15 train/validation/test split per station, with hyperparameters selected on the validation partition and the test partition evaluated only once to prevent temporal leakage. At the next-hour horizon, all models outperformed persistence at every site, with the single exception of SVR at the rural THR site; gradient boosting was best or joint-best (test $R^2$ from 0.83 at the heavily titrated central-urban site to 0.94 at a rural site), and a Wilcoxon signed-rank test on paired per-sample errors confirmed that GBM significantly outperformed Random Forest at all seven evaluated stations ($p<0.05$, and $p<0.001$ at six of them). The next-day-maximum task was substantially harder ($R^2$ between 0.41 and 0.79), and the ranking reversed, with SVR being the best model almost everywhere. Crucially, forecast accuracy declined systematically from rural and suburban toward central-urban sites: the same nitric oxide titration that suppresses urban ozone is also associated with degraded predictability. These results, summarised in the typology × model accuracy cross-matrix, indicate that an operational early warning system for Greece should adopt horizon-specific models, gradient boosting for next-hour nowcasting and SVR for day-ahead maxima, with explicitly higher uncertainty in the urban core, and can be deployed on the network’s real-time (IoT) data stream using ozone observations alone. Full article

Understanding ecological resilience (ER) across urban–rural gradients is important for differentiated management in arid metropolitan areas. Using 2 km grid data for 2013, 2018, and 2023, this study delineated travel-time-based urban–rural catchments in the Urumqi Metropolitan Area. The optimal-parameter Geodetector and multiscale geographically weighted regression were used to examine global explanatory patterns and local ER–factor associations, while spatially constrained clustering identified management types. The results showed that (1) mean ER values were 0.49, 0.50, and 0.48, respectively. ER was lower in urban centers and higher in rural areas and hinterlands. Compared with 2013, ER in 2023 was higher in urban centers and peri-urban regions but lower in rural areas and hinterlands. (2) Socioeconomic factors were more prominent in urban centers and peri-urban regions, whereas rural areas exhibited temporally variable natural and socioeconomic patterns. Elevation and soil organic matter were more prominent in hinterlands, and factor interactions were predominantly characterized by bi-factor or nonlinear enhancement. (3) Local ER–factor associations varied in direction, magnitude, and spatial scale. Negative associations with nighttime light intensity, road density, and built-up land proportion were concentrated in more urbanized areas. (4) Overlaying four spatial clusters with four catchment categories produced 16 integrated management types. These units provide a spatial basis for differentiated ecological management and regional planning in the Urumqi Metropolitan Area. Full article

Metropolitan fringe areas are transitional spaces where urban expansion, industrial relocation, residential spillover, transport infrastructure, and ecological recreation jointly reshape land-use functions. However, urban vitality research has mainly focused on central urban areas, leaving limited evidence on how activity intensity is organized in metropolitan fringe spaces. Taking the Chengdu Metropolitan Area, China, as a case, this study delineates metropolitan fringe areas using POI kernel density analysis and density–distance relationships, calibrated with impervious-surface and remote-sensing evidence, measures village-level relative activity intensity using Baidu heatmap data, and examines nonlinear associations between built-environment variables and urban vitality using LightGBM and SHAP. The results show that vitality across the delineated fringe does not form a uniform core–periphery gradient. Instead, high-vitality units are clustered around industrial parks, residential spillover zones, transport corridors, public-service nodes, and ecological recreation spaces. Population density, nighttime light, gross domestic product, building density, and commercial POI density are the main predictors in both weekday and weekend models. Several variables show nonlinear and saturation-like associations rather than simple linear effects. These findings suggest that higher predicted fringe vitality is more likely to occur where population concentration, development intensity, service provision, transport linkage, and socioeconomic activity coexist, rather than where densification occurs alone. The study extends urban vitality research to metropolitan fringe areas and provides evidence for differentiated land-use planning in urban-rural transition zones. Full article

Identifying the spatio-temporal evolutionary patterns and driving mechanisms of rural tourism network attention is essential for predicting the development trends of the rural tourism industry and delivering refined industrial governance. Taking 356 prefecture-level cities in China from 2015 to 2024 as basic research units, this paper constructs a comprehensive evaluation system for rural tourism network attention based on multi-source data. Furthermore, its spatio-temporal evolution characteristics and internal influencing factors are systematically investigated by means of spatial autocorrelation analysis and geographically weighted regression. The results indicate that the overall level of rural tourism network attention in China shows an obvious fluctuating growth trend, which can be divided into three successive stages, namely steady growth (from 0.8530 in 2015 to 1.2028 in 2019), explosive growth (from 1.9563 in 2020 to 3.7471 in 2021) and high-level fluctuation (maintained in the high range of 2.4–3.4). In addition, with the continuous iteration of internet communication media, the guiding influence of traditional search platforms has gradually weakened, while emerging social media and short-video platforms have become the core carriers of online tourism traffic. Correspondingly, media innovation persistently reshapes the spatial distribution pattern of rural tourism network attention. In terms of spatial characteristics, rural tourism network attention has undergone a significant transformation from geographical gradient polarization to overall regional equilibrium. Specifically, from 2015 to 2024, the overall Moran’s I index remained positive, with values ranging from 0.0116 to 0.1358, indicating an overall trend of gradual decline. High-attention areas are predominantly concentrated in economically developed urban agglomerations, whereas remote and economically underdeveloped regions exhibit contiguous low-value aggregation characteristics, which reveals a remarkable trend of balanced development nationwide. In view of driving mechanisms, highway network density, tourism income, rural tourism resource and enrollment of university students are identified as the core driving factors dominating the spatio-temporal evolution of rural tourism network attention. Moreover, the intensity of the influence of each factor presents distinct spatial heterogeneity. This study further reveals that the spatial heterogeneity of rural tourism network attention calculated using multi-source fused data shows a remarkable convergent characteristic, which can reflect the actual distribution of the rural tourism market more objectively and accurately. Meanwhile, rural tourism network attention is typically characterized by scale-dependent with the spatial distribution at the macro-scale being more balanced than that at the meso- and micro-scales. Full article

The Brazilian Amazon is a contested frontier, shaped by destructive and conservationist forces. Most forest clearing is driven by agro-extractivism, an agrarian pathway based on raw commodity production. The socio-biodiversity economy (SBE) has emerged in response, widely regarded as a transformative agrarian pathway capable of reconciling environmental conservation and rural livelihoods. However, recent research suggests that, as socio-biodiversity products scale up, agro-extractivist dynamics can be reproduced within the SBE. We examine this tension in the cocoa frontier of the Transamazon, where cocoa is institutionally promoted as an SBE alternative. We conduct an exploratory, mixed-methods study combining a geospatial analysis of land use and land cover (LULC) change (2020–2025, random forest classification) with a qualitative analysis drawing on participatory mapping and 87 semi-structured interviews with farmers, cooperatives, buyers, and institutional actors. Using a gradient framework, we read LULC transitions and farmers’ land use practices along an agro-extractivism–SBE continuum. The cocoa frontier emerges as a hybrid geography. The landscape is predominantly stable but internally reorganizing: anthropogenic forest declines while full-sun monoculture expands over pasture, with intensification concentrated in peri-urban areas and restoration in remote ones. Land use practices form five recurring configurations, two firmly anchored at the socio-biodiversity or agro-extractivist poles and three whose alignment with the SBE depends on access to markets, knowledge, and institutions. We argue that the frontier contestation unfolds not only between distinct economies but within the cocoa economy itself, and we identify the policy areas relevant to sustaining SBE-oriented practices in the Transamazon. More broadly, this study suggests that the classification of Amazonian forest-based economies as inherent alternatives to agro-extractivism should be treated as an empirical question rather than an assumption. Full article

Accurate and transferable land cover mapping from satellite imagery is a prerequisite for national-scale agrienvironmental monitoring and climate change impact assessment. The joint use of Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 multispectral imagery offers complementary structural and spectral information, yet systematic evaluation of fusion strategies and their geographic transferability remains limited. We trained and tested five U-Net fusion architectures S1-only, S2-only, early (input-level), feature-level (middle), and decision-level (late) alongside a SegFormer-b2 transformer baseline over two German cities (Munich and Berlin) using the Multi-Sensor Land Cover Classification (MSLCC) dataset (single-date 2017 Sentinel-1B/Sentinel-2A acquisitions) at 10 m resolution. Three cross-city transfer protocols (Munich → Berlin, Berlin → Munich, and combined training) quantify model transferability across contrasting urban–rural gradients. Early fusion achieved the highest in-city macro-averaged F1 score among U-Net variants (0.8278), a small but statistically significant improvement over the optical-only baseline (0.8236; patch-level paired bootstrap, $p=0.006$); feature-level (middle, 0.8164) and decision-level (late, 0.8196) fusion were, by contrast, significantly worse than the optical-only baseline ($p<0.001$ and $p=0.030$, respectively), and the SAR-only model (0.6864) trailed substantially. The built-up class was the primary beneficiary of SAR inclusion under early fusion. SegFormer-b2 (0.8214) was numerically close to, but statistically significantly below, the best convolutional configuration ($p=0.005$), and exhibited strong cross-city transfer (0.8632–0.8608 macro-F1), consistent with the geographic invariance conferred by its ImageNet-pretrained encoder. Combined training across both cities improved over the single-direction transfer average by 0.012 macro-F1 points for U-Net and 0.006 points for SegFormer, offering a practical route to national-scale deployment without requiring explicit domain adaptation. Spectral index augmentation (NDVI, NDWI, ExG) and SE channel attention did not significantly improve over plain early fusion when derived from percentile-normalized inputs, with the best variant statistically indistinguishable from the baseline at macro-F1 = 0.8268 ($p=0.365$); the result is attributable to a specific preprocessing dependency: NDVI, NDWI, and ExG are only physically meaningful when computed from calibrated reflectance, whereas here they were derived after scene-level 2nd–98th percentile stretching, which strips the absolute radiometric referencing the indices rely on; practitioners combining spectral indices with percentile-normalized (rather than physically calibrated, e.g., Level-2A surface-reflectance) inputs should expect a similar null result. Full article

Sub-Saharan Africa is rich in agricultural biomass, yet its biogas utilization is far below its potential. Most earlier studies failed to identify the nonlinear, multi-factor relationships that shape real national biogas yields and fully clarify this imbalance. This study constructs a 2007–2023 panel dataset for ten sub-Saharan African countries, merging agricultural output, socioeconomic, and infrastructure metrics. Gradient Boosting model and SHapley Additive exPlanations (SHAP) analysis are applied for empirical evaluation. SHAP analysis confirms that charcoal consumption yields the largest contribution to biogas production, with a mean absolute SHAP value of 1.018. The correlation between the two variables is negative under the threshold and becomes positive beyond this critical level. Urbanization has an inverted U-shaped correlation with biogas output, and the marginal contributions of predictors vary substantially across sampled countries. Instead, fragile supply chains, rural labor loss, and fierce competition in clean energy markets curb local biogas production. Forecasts show that regional biogas output will continue to fall until 2030. Targeted national policies matching each country’s core influencing factors are therefore urgently required. Full article

Urbanization alters the local growth environment of vegetation, including local thermal regimes, moisture availability, and human activity intensity. Yet, the gradient-dependent changes in vegetation phenology and the factors responsible for these changes are still not fully clarified. Taking Beijing as the study area, this study used MOD13Q1 EVI records from 2005 to 2024 to reconstruct annual vegetation trajectories with Savitzky–Golay filtering. The start of the growing season (SOS) and the end of the growing season (EOS) were then identified based on a dynamic threshold criterion, and the length of the growing season (LOS) was derived from the interval between the two phenological dates. Urban–rural gradients were constructed by integrating Global Urban Boundary (GUB) and digital elevation model (DEM) data. Theil–Sen slope estimation and the Mann–Kendall test were then applied to analyze trends in vegetation phenology, while partial correlation analysis and the XGBoost-SHAP method were used to identify the relative effects of climatic and urbanization-related factors. The results showed that (1) vegetation phenology in Beijing varied markedly across space. Mountainous areas in the northwest and southwest had a later SOS, earlier EOS, and shorter LOS, whereas the central plain and southeastern regions were characterized by an earlier SOS, later EOS, and longer LOS; (2) from 2005 to 2024, the SOS advanced significantly by −0.65 days/year, EOS showed a weaker delay of 0.46 days/year, and LOS increased significantly by 0.90 days/year, indicating an overall extension of the vegetation growing season over the past two decades. (3) Urban areas had an earlier SOS, later EOS, and longer LOS, but the trends of SOS advancement, EOS delay, and LOS extension were more pronounced in suburban and rural areas; and (4) the SOS was mainly influenced by the combined effects of nighttime lights and heat-related factors, whereas the EOS was primarily affected by temperature and nighttime lights. Along the urban–rural gradient, the importance of nighttime lights gradually decreased from urban areas to suburban and rural areas, while the role of climatic factors became relatively stronger. These findings reveal the gradient differentiation of vegetation phenological status, temporal trends, and associated drivers in Beijing under rapid urbanization, and provide useful information for urban vegetation management and ecological planning. Full article

Predicted cardiovascular age (heart age) translates the risk-factor profile into an equivalent age, which may facilitate interpretation of estimated cardiovascular risk. Excess cardiovascular age describes, in years, the integrated burden of modifiable risk factors and its distribution in the population. This study aimed to quantify socioeconomic and geographic inequalities in predicted excess cardiovascular age among Peruvian adults using standardized inequality measures, and to describe its temporal variation from 2014 to 2024. We analyzed ENDES Peru 2014–2024 data for adults aged 30–74 years. Cardiovascular age was estimated using the body mass index (BMI)–based non-laboratory Framingham equation, and excess was defined as the difference between cardiovascular age and chronological age. Weighted means and 95% confidence intervals were estimated accounting for the complex survey design. Socioeconomic inequalities were assessed using absolute and relative gaps between extreme wealth quintiles (Q5–Q1), the Slope Index of Inequality (SII), the Relative Index of Inequality (RII), and the concentration index/curve. Among 163,889 participants, mean excess cardiovascular age was 9.64 years (95% CI: 9.48–9.80), with similar estimates in women (9.73; 95% CI: 9.52–9.94) and men (9.54; 95% CI: 9.33–9.75). Temporal variation was observed, peaking in 2021 (10.91; 95% CI: 10.57–11.25). Excess increased with wealth (Q1: 7.14 vs. Q5: 11.25 years), with an SII of 5.04 years (95% CI: 4.71–5.37) and a concentration index of 0.087. The gradient was steeper in men (SII 6.14) than in women (SII 3.90). Geographically, Metropolitan Lima had higher excess than the Highlands (11.17 vs. 7.45 years), and urban areas exceeded rural areas (10.28 vs. 7.25 years). In Peru, adults aged 30–74 years had a mean predicted excess cardiovascular age of about 10 years, with a consistent pro-rich and urban/coastal concentration pattern, more pronounced among men. Because this metric is derived from a risk prediction equation, these findings should be interpreted as surveillance-oriented evidence of inequalities in estimated risk-factor burden, not as evidence of observed cardiovascular disease, subclinical cardiovascular damage, causal mechanisms, or tested intervention effects. Full article

Background: Environmental degradation and climate-related territorial transformation are increasingly recognized as social determinants of adolescent mental health. However, empirical evidence on solastalgia among young people in the Global South remains limited. This study aimed to examine psychosocial, health-related, school-related, family, and territorial factors associated with solastalgia among school-attending adolescents in Colombia. Methods: A quantitative, cross-sectional analytical study was conducted between August 2025 and February 2026 with 1005 adolescents from three Colombian territories undergoing different forms of environmental transformation: an urban setting affected by construction-related change, a semiurban setting affected by agricultural transformation, and a rural setting affected by extractivism. Solastalgia was assessed using the Brief Solastalgia Scale. Psychosocial, health-related, school-related, and contextual variables were measured using validated or locally supported instruments. Bivariate analyses, multiple linear regression, and non-parametric territorial comparisons were conducted. Results: Solastalgia differed significantly across territorial groups, with the semiurban group showing the highest mean ranks for solastalgia, followed by the rural and urban groups. However, territorial comparisons showed heterogeneous psychosocial and health-related patterns rather than a uniform gradient across all outcomes. Older age was independently associated with higher solastalgia scores. In the final regression model, solastalgia was independently associated with resilience, substance use screening, suicide risk, age, physical health status, conflict resolution, concern about climate change, and territorial origin. The model explained 42.9% of the variance in solastalgia scores. Territorial origin contributed a small but statistically significant additional proportion of explained variance. Conclusions: Adolescent solastalgia in Colombia is not reducible to individual psychological vulnerability. It reflects a broader socioecological configuration involving emotional distress, perceived health, psychosocial resources, school-related experiences, concern about climate change, and place-based environmental transformation. These findings support the need for school-based and community-based public health responses that integrate adolescent mental health care with environmental protection, cultural safety, and territorial justice. Full article

Rural territories on the periphery of Andean intermediate cities are undergoing accelerating peri-urban transformation that threatens agricultural land and the cultural landscapes embedded in vernacular housing traditions. Although vernacular architecture has been studied extensively in heritage conservation and bioclimatic research, its potential as a spatial indicator of territorial change remains underexplored. This study proposes the Vernacular Housing–Landscape Transformation Framework (VH–LTF), an interpretive and methodological framework that reads vernacular housing typologies as indicators of rural–peri-urban landscape transformation, and applies it preliminarily through a composite measure, the Rural–Peri-Urban Landscape Transformation Index (RPLTI). The framework is developed and tested as a settlement-scale proof-of-concept on a documented corpus of 25 vernacular dwellings in Barrio Cera, Taquil parish, Loja, Ecuador, an Andean peri-urban settlement at 2238 m a.s.l. located approximately 20 km from the city of Loja. Three morphological typologies (I, L, and C forms), built with adobe, eucalyptus timber, reedwork, stone, and clay tile, were classified and assessed across five analytical dimensions: territorial, typological, material, socio-spatial, and landscape transformation. Preliminary evidence indicates that typological progression, patterns of material substitution, patio function, and predial vegetation loss vary together along the settlement’s road-accessibility gradient and may serve as observable markers of land-use change and cultural-landscape erosion. The findings are exploratory and context-specific rather than statistically generalizable. The framework may provide planners and researchers with a low-cost diagnostic for characterizing peri-urban Andean settlements; further validation in larger, multi-settlement corpora is required before transfer to other contexts. Full article