Search Results (919)

In recent years, the city of Naples has seen increasing attention focused on the mural dedicated to Diego Armando Maradona, located in the Spanish Quarter. Originally a spontaneous expression of street art and initially perceived by the local community as a simple artwork, the mural has gradually transformed into a powerful symbol of identity, becoming a true cultural icon of the city. This process has generated effects that transcend the artistic value of the artwork, contributing to the enhancement of the entire surrounding urban context and altering the social and economic dynamics of the quarter. By considering the Maradona Mural as the epicentre of a range of territorial and socio-economic effects, this paper aims to explore the issue of measuring the influence exerted by its presence on the market values of residential properties located in the Spanish Quarter of Naples. From this perspective, street art can be interpreted as a positive externality capable not only of fostering processes of urban regeneration and the redevelopment of formerly marginalised or degraded areas but also of influencing the dynamics of the local real estate market. Property values reflect not only the intrinsic characteristics of the properties but also the environmental and territorial attributes that contribute to the formation of market prices. From this perspective, properties can be considered as beneficiaries of externalities, whose economic value can be estimated through variations in house prices attributable to changes in environmental and territorial conditions. Full article

The pervasive rise in digital platforms has fundamentally recalibrated the relationship between urban communities and their cultural landscapes, reconfiguring not only the sensory experience of these environments but also their interpretive frames and the everyday contestations that surround them. Using coffee spaces in Beijing as an empirical lens, this study integrates 630 validated POI locations, 287,632 online reviews from Dianping, GIS spatial analysis, LDA topic modelling, semiotic coding, and a fine-tuned RoBERTa (Robustly Optimized BERT Pretraining Approach) text classifier to examine the convergence between platform-mediated public perceptions and urban spatial differentiation. Our spatial interrogation identifies a statistically significant centre–periphery divide within this platform-curated corpus—a pattern that describes the geography of platform-mediated visibility rather than the total physical distribution of coffee outlets in Beijing, characterised by pronounced high-density agglomerations nesting within historic urban cores, central business districts, nascent knowledge hubs, and gentrifying lifestyle enclaves. Three landscape prototypes are derived from the data—business corridors, cultural experimental fields, and social-media spectacles. Each type exhibits discernibly different patterns of spatial density, adjacent land-use configurations, perceived experiential qualities, and underlying symbolic discourses. While positive sentiments dominate platform discourse, localised anxieties emerge regarding visual homogenization, intense queuing, premium pricing, and loss of place authenticity. The 630 venues analysed here represent a platform-visibility stratum—establishments sufficiently reviewed to feature on digital intermediaries—and the spatial patterns we map describe the geography of this visibility rather than the total physical distribution of coffee outlets. Full article

While climate change is a significant pressure point for pollinators and honeybees, its long-term relationship with managed honeybee colonies and honey production remains unclear and context sensitive. This study, using FAOSTAT data from 1961 to 2024, examined the relationships between land surface temperature anomalies and the number of registered beehives, the constant-price honey production value, and the normalized honey production value per colony, both globally and specifically for 18 Mediterranean countries. To differentiate between long-term structural trends and short-term temperature relationships, correlation, regression, bootstrap confidence interval, temperature series sensitivity analysis, cross-correlation function, and normalized index analyses were used together. The study results show strong long-term co-movement between temperature anomalies and recorded beekeeping indicators at the global and Mediterranean scale in the level series; however, first-differenced (year-to-year) analyses show this association weakens substantially and, for Mediterranean honey production value, reverses sign, indicating that the level-series correlations are driven largely by common long-term trends. The relationship between temperature anomalies and beekeeping indicators shows a context-dependent structure among Mediterranean countries. The findings show that the increase in colony size does not always coincide with the increase in the constant-price honey production value per colony; in some cases, these two indicators can move in different directions. This indicates the need for an analytical decomposition of the dynamics of quantitative growth and economic production value per colony in the beekeeping sector. Full article

Railway idle land offers a large and underused space for solar power, yet its economic value has not been evaluated. Revenue depends on the volatile System Marginal Price (SMP) and Renewable Energy Certificate (REC) markets, whose uncertainty cannot be fully captured by static discounted cash flow (DCF) analysis. This study asks whether solar development on Korea’s railway idle land is worthwhile over the long term, and at what scale it should proceed. It applies an integrated DCF and real options analysis (ROA) framework to a proposed 438 MW project on the Honam Line in southern Korea. Price volatility is estimated from monthly SMP and REC data with a geometric Brownian motion model, and the options to expand and to contract are valued on a binomial lattice. The DCF yields a marginal net present value of USD 3.2 million. The expansion option adds USD 172.5 million and is exercised in 67% of states, raising the total project value to USD 175.7 million. Rising panel efficiency and falling capital costs move the project firmly into feasibility. Therefore, scale flexibility turns a marginal project into a strongly positive one, supporting the large-scale deployment of solar on railway idle land. Full article

Disamenity and amenity facilities pull property values in opposite directions, yet prior studies have treated disamenities as a homogeneous category and have been constrained by data scattered across agencies and by mismatched spatial scales. This study integrates multi-source spatial data, comprising 3426 sub-districts (eup-myeon-dong) nationwide, a 500 m population grid of 376,668 cells, and the actual point locations of individual facilities, into a single spatial framework and applies a multi-method design that combines a spatial Durbin model (SDM), explainable machine learning (XGBoost–SHAP), an environmental-justice analysis, and a micro-siting analysis. Four findings emerge. First, not all disamenities are associated with lower prices: only pollution-emitting facilities with a clear emission signature, namely, sewage treatment plants and incinerators, capitalize robustly as cross-sectional associations, into both housing prices and officially assessed land values, with the effect extending into neighboring sub-districts rather than staying purely local. The other disamenities show no robust total effect on either price; their estimates are small or unstable across specifications. Second, capitalization of pollution-emitting facilities is pronounced in the urban sample and disappears in the rural one, and the coefficient structure differs overall between urban and rural areas (global Chow test, p < 10⁻²¹). Third, micro-siting analysis shows that where a facility is placed (siting) and what it leaves behind in prices (capitalization) are distinct layers, and that capitalization tracks the population a facility keeps nearby rather than its nuisance type: pollution-emitting facilities retain enough nearby housing for their burden to register, whereas funerary facilities sited far from people do not. Fourth, the environmental inequity of pollution exposure runs along income rather than age and concentrates in cities rather than in rural areas: the exposure rate among residents of low-income urban sub-districts (49%) is 2.5 times that of the urban population as a whole (19%), while the greater Seoul metropolitan area remains comparatively insulated. These layered findings were possible only once the dispersed spatial data had been integrated and standardized, and the study demonstrates that fusing and efficiently managing spatial data is a precondition for evidence-based land-use and environmental policy. Full article

This study investigates the empirical links between climatic/socio-economic factors and Consumer Price Food Indices (CPFIs) across 47 advanced and emerging economies from 2001 to 2022. Utilizing a balanced panel dataset compiled from the World Bank’s World Development Indicators, FAO databases, and UNDP Human Development Reports, the analysis applies fixed-effects and random-effects panel data models to evaluate the drivers of food price dynamics. The empirical results reveal that socio-economic variables, specifically the Human Development Index (HDI), food price inflation, and agricultural productivity, are consistently associated with food indices, underscoring the critical role of structural development and nominal inflationary pressures. Climatic factors, particularly temperature anomalies, also exert a significant impact: a one-degree Celsius increase in temperature anomalies is associated with a 0.82-unit rise in the food price index level, whereas expansions in forest area and agricultural land are linked to price reductions. These findings indicate that food price dynamics are shaped by the intricate interplay of climate variability and socio-economic conditions. Consequently, policy recommendations emphasize targeted investments in socio-economic development, climate adaptation measures (including support for climate-resilient agriculture), and sustainable land management (forest conservation and optimized land use) to enhance food system resilience and support long-term food security. Full article

Mangroves are highly productive ecosystems due to their great capacity to store carbon, but they are also vulnerable to human activities and adverse environmental conditions. Their conservation is often constrained by the opportunity costs of shifting from traditional economic activities to blue carbon projects. This work analyzes the prices of the different carbon markets in ecosystems, compares them with the benefits obtained from other productive activities, and evaluates the viability of implementing carbon projects in mangroves. An exhaustive literature search is conducted to assess the carbon prices of ecosystems worldwide. The opportunity costs of mangrove carbon capture projects in Mexico are estimated from site-specific and regionally relevant economic data; additionally, broader national benchmarks are presented for contextual comparison but are not interpreted as direct opportunity costs where they do not represent realistic land-use alternatives for the mangrove sites analyzed. The price of carbon ranges from 4 to 86 USD per Mg CO₂e. The most studied natural ecosystems are forests. The highest gross annual profit (GAP) from carbon sales is observed in Tabasco and Campeche. GAP with mangrove wood harvesting ranges from 628.0 USD ha⁻¹ year⁻¹ to 3917.7 USD ha⁻¹ year⁻¹. The highest GAP for crops is obtained for white corn in the state of Hidalgo. GAP of the economic activity of livestock ranges from 3167.59 USD ha⁻¹ year⁻¹ to 3365.71 USD ha⁻¹ year⁻¹. The blue carbon projects are competitive with other productive activities at relatively high prices (86 USD per Mg CO₂e). In Tabasco, under certain high-price and high-sequestration scenarios, blue carbon projects can be competitive with local agricultural activities; however, this competitiveness is highly conditional on carbon price, sequestration rates, and local opportunity costs, and therefore cannot be generalized to all mangrove owners without site-specific appraisal. Fair carbon prices are required to make mangrove conservation projects attractive to producers. Full article

This article asks a practical question: do current renewable-energy rules encourage end users to become prosumers, or do they mainly serve those already prepared to invest? This analysis maps recent Polish reforms, especially the shift from net metering to value-based net billing and later adjustments to settlements: the return to monthly average pricing for many early adopters, an optional hourly price model, and a strengthened prosumer deposit intended to reduce the sell–buy gap. It also examines the expanding catalogue of prosumer statuses, from the individual prosumer, through collective prosumption in multi-unit buildings, to the virtual prosumer, which may include people without a suitable roof or land. The article then considers civic forms of organisation—energy cooperatives, energy clusters and citizen energy communities—and the role of municipalities as conveners and intermediaries. It argues that regulatory responsiveness, even when market-oriented and technologically aware, is not enough. Uptake depends on whether the rules fit real constraints: finance, administrative effort, grid capacity and fair allocation of risk. Full article

Land-use conflicts in non-urbanized areas are fundamentally governance problems rather than purely environmental ones: sustainability outcomes increasingly depend on integrated, cross-sectoral decision-making reconciling forestry, agriculture, tourism, infrastructure, and urbanization within a finite land resource. This study examines whether statutory land acquisitions by a public forest administration can be understood as such a governance instrument rather than simply forest-area expansion, using an original transaction-level database of 911 land purchases by the Polish State Forests (Lasy Panstwowe) through statutory pre-emption rights between 2022 and mid-2026. The database covers 2806.1 hectares and, for the 903 transactions with a determinable price, approximately 114.2 million PLN. Using descriptive statistics, concentration indices (Gini, Herfindahl–Hirschman), an exploratory hedonic-style log–log regression of unit price on parcel area with location and year fixed effects, and a spatial-autocorrelation analysis (Moran’s I), the study examines spatial concentration, price differentiation, and parcel-size effects. Results show pronounced sub-regional concentration (county-level Gini = 0.615, more than double the voivodeship-level value of 0.284), a systematic price premium for parcels below 0.5 ha, and a dominant role of location over parcel size in explaining price variation (R-squared rising from 0.042 to 0.198 with location fixed effects); these are descriptive associations rather than causal estimates, given the absence of parcel-level quality covariates and a fully specified spatial–econometric model. The findings support interpreting statutory pre-emption purchases as a market-based institutional mechanism contributing to boundary rationalization, ownership consolidation, and mediation of competing land-use pressures, with implications for county-level monitoring and cross-sectoral coordination with spatial planning. Full article

Wetlands have been noted to provide us with a wide range of ecosystem services—climate, water quality, flood regulation, and habitat benefits among others. The evidence that supports these service benefits is fairly well documented in the literature. However, it is often scattered across studies, metrics, and valuation methods, making it difficult for planners and landscape architects to use in physical projects and plans. The empirical result of this difficulty is that wetlands are often overlooked and under-utilized as part of broader ecosystem and land based planning solution sets. This paper addresses this usability deficiency using an ecosystem accounting framework that translates wetland science into spatially specific design and planning metrics. The framework follows the System of Environmental-Economic Accounting-Ecosystem Accounting (SEEA EA), an international statistical framework adopted by the UN to measure the environment’s contribution to the economy and human well-being. In our study, wetland extents in the state of Illinois are mapped on a statewide 30 m × 30 m grid. Individual wetland system conditions are estimated from floristic quality using a generalized additive model trained on 244 wetland sites that are part of the long-term Critical Trends Assessment Program (CTAP) at the Illinois Department of Natural Resources (IDNR). A floristic condition scalar, $w\left(x\right)$, provides a screening-level measure of ecological condition. It is applied only to a nonmonetary habitat-condition account and is not used to scale the monetary service accounts. Climate regulation, water purification, and flood regulation are quantified through service-specific physical models and reported as carbon-price and replacement-cost proxies. Under the central scenarios, these three monetary proxy accounts produce a combined subtotal of USD 1408.6 million per year. The annualized surface-storage replacement-cost scenario accounts for USD 1048.5 million, load-gated nitrogen-removal replacement cost for USD 338.0 million, and the climate-regulation carbon-price proxy for USD 22.1 million. These estimates are planning proxies rather than observed market benefits or realized avoided damages. The separate habitat-condition account totals 198,280 condition-weighted hectares, with a statewide mean $w\left(x\right)$ of 0.502, and is not added to the monetary subtotal. Climate performance varies across wetland types: methane emissions cause some emergent wetland categories to function as net greenhouse-gas sources under the central assumptions, while other categories remain net sinks. A protection-gap analysis shows that Tier 4 wetlands contain 70.1% of the classified vegetated-wetland area and 67.0% of the condition-weighted habitat area within the classified domain. Broadly, the framework demonstrates how ecosystem accounting can translate fragmented wetland evidence into consistent spatial metrics for planning. The resulting layers support statewide screening, comparison among wetland categories, conservation and restoration screening, and protection-gap analysis while preserving the distinction between monetary service proxies and nonmonetary ecological condition. Full article

Taking Lankao County as a case study, this study extends the established StrawFeed framework by linking NHPI-derived harvest dates to spatially differentiated straw release and seasonal equipment scheduling. Time-series Sentinel-2 observations were used to characterize harvest timing, while observed road routes were used to calibrate the detour parameter. The mapped harvest progression was compared with reported aggregate harvest progress and provided spatially differentiated timing inputs for logistics simulation. The results demonstrate that: (1) The spatial-economic framework effectively refine the spatial representation of traditional models in complex fragmented plots. (2) Under the annual shared-fleet baseline, the simulated delivered cost was 28.40 USD t⁻¹. (3) Route calibration yielded a road-detour coefficient of 1.36, demonstrating the effect of road geometry on transport distance. The simulated cost represents the result under the specified demand, road, equipment, and price assumptions rather than a causal penalty attributable to land fragmentation. Consequently, we suggest that land management policies should shift toward “precision-targeted” subsidies, and rural spatial planning should prioritize the layout of decentralized pre-processing hubs to optimize spatial logistics efficiency and economic viability. Full article

Cultivated land is a basic factor in agricultural production, but it is also subject to increasingly strict resource constraints. Under such conditions, agricultural development needs to rely more on the effective use of capital, labor, and digital technologies on existing farmland rather than on the expansion of land input. This study examines the impact of digital rural construction on agricultural technological choice under land constraints. Using panel data from 28 Chinese provinces from 2011 to 2024, this paper first measures capital–land and labor–land biased technological progress based on a normalized factor-augmenting CES production function, and then constructs a multidimensional index of digital rural construction. The empirical results show that digital rural construction significantly promotes both capital–land and labor–land biased technological progress, with a stronger effect on the capital–land dimension. This indicates that digital rural construction mainly promotes agricultural technological choice through capital-embodied and digitally enabled technologies, while also improving the role of labor in agricultural production and land management. The mechanism analysis shows that the capital–land effect is mainly driven by the price effect, whereas the labor–land effect is mainly driven by the scale effect. Further heterogeneity analysis indicates that the positive effects are more pronounced in eastern China, while the effects in central and western regions are weaker and more differentiated. These findings suggest that digital rural construction reshapes agricultural technological choice by changing how capital and labor are combined with limited land resources. The study provides evidence for promoting agricultural transformation, improving land-use sustainability, and strengthening digital governance in agriculture. Full article

Official cadastral values in Latin American intermediate cities may fail to keep pace with rapidly changing asking-price patterns, weakening the responsiveness of local property-tax bases. This study introduces the Relative Gap Rate (TBR), defined as the proportional divergence between observed vacant-land asking prices and official cadastral values, and applies it to Ambato, Ecuador. A dataset of 182 georeferenced asking-price observations was interpolated across a common cantonal support of 19,231 hexagonal cells. Predictors comprised a hierarchically weighted Urban Vitality Index (UVI), distance to the structural road network, elevation, and traffic-incident count derived from 1787 records. The TBR surface exhibited very strong positive spatial autocorrelation (Moran’s $I=0.956$, $p<0.001$), while the discrete asking-price observations were also spatially autocorrelated (Moran’s $I=0.282$, $p<0.001$). Lagrange Multiplier diagnostics supported a Spatial Autoregressive specification (pseudo-$R^2=0.927$; $\rho =0.885$). The Random Forest model achieved a test-set $R^2$ of 0.8319 and an MAE of 5.3252, with UVI accounting for 64.37% of impurity-based feature importance. The median TBR was 6.0, meaning that the median asking price was seven times the corresponding cadastral value; the maximum TBR reached 43.0. Traffic-incident count retained a positive spatial-regression coefficient but contributed only 5.53% of Random Forest importance. The framework provides an adaptable municipal diagnostic for identifying cadastral–asking-price divergence, subject to local validation and city-specific calibration. Full article

Greenhouse gas emissions from heavy-duty vehicles (HDVs) must be drastically reduced. Battery electric trucks (BETs) are the main option for low-carbon road freight transport, but they require recharging infrastructure. However, a thorough cost analysis of public charging is lacking, especially for the Megawatt Charging System (MCS). This study estimates the infrastructure-related levelised cost of megawatt charging for battery electric trucks in Europe based on simulated truck operations and techno-economic modelling. The analysis combines empirical driving data with cost assumptions for MCS infrastructure. The reported values are infrastructure-only costs and include annualised capital expenditure, installation costs, grid connection costs and operating expenditure. They exclude electricity prices, taxes, levies, land costs and operator margins. Low- and high-cost scenarios differ in assumed charger hardware and installation costs, while grid connection costs and utilisation assumptions are held constant across scenarios. The results show that utilisation is the key driver of cost reductions over time. The infrastructure-related levelised cost of MCS declines to 0.03–0.07 EUR/kWh by 2050 under the analysed cost assumptions. The total annual infrastructure costs for Europe are estimated at 6.6–10.8 billion EUR, or 2.9–4.7 EUR cents/km. The results support policy decisions on infrastructure deployment and highlight the importance of coordinated rollout and demand growth. Full article

Data-driven research is becoming a new paradigm in transportation, but the natural lack of individual socio-economic attributes in transportation data makes research such as activity purpose inference and mobility pattern identification lack convincingness and verifiability. In this paper, a two-stage trip purpose and socio-economic attributes inference model is proposed based on travel resident survey and smart card data. In the first stage, the trip purpose of each trip is inferred by a combination of rule-based and XGBoost models. In the second stage, based on the trip purpose, a machine-learning model is built to infer the socio-economic attributes of individuals. A teacher–student model based on self-training is then applied to the models above to transfer them to smart card data. The impact of independent variables of the socio-economic attributes inference model is also investigated. The results show that the proposed framework achieves an overall accuracy of 92.7% for trip-purpose inference, and an average accuracy of 76.3% across the three socio-economic attributes (age, job status, and income). Travel time, arrival time, departure time, and purpose of the first two trips are the most important factors on age and job status, while the land price related to jobs and housing is significant when inferring individuals’ incomes. Full article