Search Results (217)

Urban growth often surpasses the actual needs of the population, leading to inefficient land use and long-term environmental challenges. This study provides an integrated perspective on urban landscape transformation by linking socio-demographic dynamics with ecological consequences, notably vegetation loss and increased impervious surfaces. The study area is Năvodari Administrative-Territorial Unit (ATU), a coastal tourist city located along the Black Sea in Romania. By integrating geospatial datasets such as Urban Atlas and Corine Land Cover with population- and construction-related statistics, the analysis reveals a disproportionate increase in urbanized land compared to population growth. Time-series analyses based on the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) from 1990 to 2022 highlight significant ecological degradation, including vegetation loss and increased built-up density. The findings suggest that real estate investment and tourism-driven development play a more substantial role than demographic dynamics in shaping land use change. Understanding urban expansion as a coupled social–ecological process is essential for promoting sustainable planning and enhancing environmental resilience. While this study is focused on the coastal city of Năvodari, its insights are relevant to a broader international context, particularly for rapidly developing tourist destinations facing similar urban and ecological pressures. The findings support efforts toward more inclusive, balanced, and environmentally responsible urban development, aligning with the core principles of Sustainable Development Goal 11, particularly Target 11.3, which emphasizes sustainable urbanization and efficient land use. Full article

This article analyses the impact of urban sprawl on the Valencia Plain aquifer system from 1990 to 2018, focusing on land use and land cover (LULC) changes and their environmental implications. The study applies the Weighted Environmental Index (WEI), a composite indicator based on a functional landscape perspective, to quantify changes in the environmental value over time. The WEI combines CORINE Land Cover and World Settlement Footprint data to enhance spatial resolution and urban land detection. The results show a significant territorial transformation, with urban surfaces expanding by 70% and rainfed agricultural areas declining by over 59%. Consequently, the WEI decreased from 44.80 in 1990 to 40.68 in 2018, representing a 9.2% reduction in the environmental value. These changes threaten the sustainability of key ecosystems such as the Albufera Natural Park and indicate a reduced capacity to deliver ecosystem services, including aquifer recharging, biodiversity conservation, and climate regulation. The findings underscore the need for integrated land-use planning, the protection of peri-urban agricultural areas, and the implementation of nature-based solutions to counteract the environmental impacts of urban growth in Mediterranean metropolitan contexts. Full article

Increasing anthropogenic disturbance in urban areas and the expansion of built-up zones into surrounding rural landscapes represent one of the most significant spatial and ecological challenges of recent decades. Urban expansion influences not only land use patterns but also the ecological integrity and naturalness of the landscape. In the present study, anthropogenic landscape change trends and changes in land cover categories were investigated within the current administrative boundaries of Nyíregyháza, a county seat located in northeastern Hungary. Using data from the CORINE Land Cover program (1990, 2000, 2012, 2018) and historical military surveys (1819–1869), landscape development trends within the municipality were examined over the past one and a half centuries. Particular attention was focused on examining changes in the extent of built-up areas, which are among the most concerning from a landscape ecological perspective. By comparing the results with data from other Hungarian cities (Debrecen and Szeged), a significant increase—nearly 20%—in built-up areas was identified. The proportion of built-up areas in relation to the total municipal administrative area increased in all the periods studied, even in those where the population was decreasing. This indicates that even in municipalities experiencing demographic decline, internal population redistribution may lead to the spatial growth of certain neighborhoods, which are the primary contributors to the expansion of built-up urban areas. Finally, based on CORINE Land Cover data, the ecological conditions of Nyíregyháza were assessed, and a hemeroby map of the municipality was created, reflecting landscape changes that occurred between 1990 and 2018. It was found that over a 28-year period, the total area of the most ecologically problematic meta- and polyhemerobic categories increased by 6%, in parallel with the growth of built-up areas. Full article

Monitoring built-up dynamics is essential for sustainable urban and territorial planning. This study presents an innovative geospatial methodology integrating multi-temporal satellite data fusion, transfer learning, machine learning classification, and open-access cloud computing to systematically identify, quantify, and map the spatiotemporal evolution of built-up areas. The methodology was applied at a territorial scale in southern Italy using Landsat multispectral imagery acquired and elaborated through Google Earth Engine. Compared to more conventional classification methods, the proposed integrated approach ensures scalability, reproducibility, and computational efficiency. Landsat multispectral imagery from 2006 to 2024 was classified using a Random Forest (RF) algorithm, trained and validated with CORINE Land Cover maps for 2006, 2012, and 2018. For 2024, a transfer learning strategy was adopted, enabling classification through a model fine-tuned with historical data and validated independently. Accuracy assessment returned an Overall Accuracy (OA) of 0.890 and F1-scores between 0.803 and 0.811 for 2006–2018. For 2024, the OA reached 0.926 with an F1-score of 0.926, confirming the effectiveness of the proposed framework. This integrated methodology not only allows for determining the extent of urban expansion over the considered timelines, but, by introducing two spatial metrics, Urban Density and the Urban Dispersion Index (UDI), also enables the characterization of the morphological evolution of urban growth. The methodology ensures spatial and temporal consistency, offering a scalable and automated framework for long-term monitoring that provides a decision support tool for urban growth management and environmental planning, especially in data-limited contexts. Full article

This study presents a multi-temporal analysis of vegetation cover changes in the Guayepo stream watershed (Cartagena de Indias, Colombia) for 2000, 2010, and 2020 and their impact on surface runoff generation. Hydrological data from 1974 to 2019 were processed to model intensity–duration–frequency (IDF) curves and simulate heavy rainfall events using six storms of nine-hour duration. Following the Soil Conservation Service guidelines, these were used to estimate runoff flows for return periods of 25, 50, and 100 years via the curve number method in HEC-HMS. Vegetation cover was assessed using the CORINE land cover methodology applied to official land use maps. The analysis revealed a significant loss of natural vegetation: dense forest cover declined dramatically from 14.38% in 2000 to 0% in 2020, and clean pastures were reduced by 46%. In contrast, weedy pastures and pasture mosaics with natural areas increased by 299% and 136%, respectively, reflecting a shift towards more degraded land cover types. As a result of these changes, total runoff flows of the model increased by 9.7% and 4.3% under antecedent moisture conditions I and II, respectively, for the 100-year return period. These findings reveal ongoing degradation of the watershed’s natural cover, linked to expanding agricultural uses and changes in vegetation structure. The decline in forested areas has increased surface runoff, elevating flood risk and compromising the watershed’s hydrological regulation. The study suggests that integrated land management and ecological restoration strategies could be key in preserving hydrological ecosystem services and reducing the negative impacts of land use change. Full article

Understanding the impacts of land use/land cover (LULC) changes on ecological processes is essential for addressing biodiversity loss, habitat fragmentation, and climate change. This study analyzes the effects of LULC changes on habitat quality and landscape connectivity in İzmir, Turkey’s third-largest city, using the Integrated Valuation of Ecosystem Services and Trade-offs Habitat Quality (InVEST HQ) model, Conefor 2.6 connectivity analysis, and Circuitscape 4.0 resistance-based modeling. This study relies on Coordination of Information on the Environment (CORINE) Land Cover data from 1990 to 2018. Findings indicate that artificial surfaces increased by 82.5% (from 19,418 ha in 1990 to 35,443 ha in 2018), primarily replacing agricultural land (11,721 ha converted). Despite this expansion, high quality habitat areas remained relatively stable, though habitat fragmentation intensified, with the number of patches rising from 469 in 1990 to 606 in 2018, and the average patch size decreasing from 394.31 ha to 297.39 ha. Connectivity analysis highlighted Mount Nif and the Urla–Çeşme–Karaburun Peninsula as critical ecological corridors. However, resistance to movement increased, reducing the likelihood of connectivity-supporting corridors. These findings emphasize the importance of integrating spatial modeling approaches into urban planning and conservation strategies to mitigate future habitat loss and fragmentation. Full article

Forest ecosystems in the Mediterranean basin are significantly affected by summer wildfires. Drought, extreme temperatures, and strong winds increase the fire risk in Greece. This study explores the potential of NDVI for assessing and forecasting post-fire regeneration in burnt areas of the Peloponnese (2007) and Evros (2011). NDVI data from Landsat 7 and 9 were analyzed to identify the stages of the regeneration process and the dominant vegetation species at each stage. Comparing pre-fire and post-fire values highlighted the recovery rate, while the trendline slope indicated the regeneration rate. This combined analysis forms a methodology that allows drawing conclusions about the vegetation type that prevails after the fire. Validation was conducted using photointerpretation techniques and CORINE land cover data. The findings suggest that sclerophyllous species regenerate faster, while fir forests recover slowly and may be replaced by sclerophylls. To predict vegetation regrowth, two time series models (ARMA, VARIMA) and two machine learning-based ones (random forest, XGBoost) were tested. Their performance was evaluated by comparing the predicted and actual numerical values, calculating error metrics (RMSE, MAPE), and analyzing how the predicted patterns align with the observed ones. The results showed the overperformance of multivariate models and the need to introduce additional variables, such as soil characteristics and the effect of climate change on weather parameters, to improve predictions. Full article

Assessing land use/land cover changes currently represents an important avenue for achieving a better understanding of the urbanization phenomenon. Various free datasets based on satellite imagery are available, but the user should decide which one is the most suitable for their study area. The aim of the present paper is to perform an accuracy assessment of built-up areas using four datasets: Corine Land Cover Backbone (CLC Backbone), High Resolution Layers (HRL)–Imperviousness, Esri Land Cover and Dynamic World. The study case is represented by 12 major metropolitan areas (MAs) in Romania which have the most dynamic economic development and urban expansion. Confusion matrices were created, and the following metrics have been computed: overall accuracy (OA), kappa coefficient (k) and user accuracy (UA). The analysis was performed on three levels: for the entire surface of the MAs and separately for the urban and rural sides. The results at the metropolitan level show that even though CLC Backbone 2018 is the most suitable for extracting the built areas (0.85 overall accuracy), HRL and Esri Land Cover could also be used, as they share the same overall accuracy values (0.67). Significant differences exist between the urban and rural areas. CLC Backbone performed better in the rural areas (0.87) than in the urban areas (0.84). The other three datasets recorded major variations in the overall accuracy for the urban and rural areas. Esri Land Cover has the second greatest overall accuracy for the urban areas (0.81), while HRL is the second most accurate, after CLC Backbone, for assessing the rural areas (0.67). In conclusion, CLC Backbone has the best accuracy performance for all three levels of analysis. The significance of the study lies in the accuracy assessment results on the four datasets, performed at urban and rural levels. This paper aims to help researchers and decision makers choose the best dataset for assessing land use changes. Additionally, having a reliable dataset may help compute the indicators used to monitor the Sustainable Development Goals (SDGs). Full article

Economic pressure on agricultural land is generating major changes in affected territorial systems. The development of methodologies to analyze the pressure on agricultural land is one of the main concerns regarding food security and how to provide fresh produce to large cities. The methodology used uses the Corine Land Cover database, provided by Copernicus Land Monitoring Services (CLMS), from 1990–2018. Data processing and analysis was performed using the open-source software package QGIS, a process that started by reprojecting the data into the national coordinate reference system Pulkovo 1942(58)/Stereo 70, EPSG: 3844. The methodology used was able to highlight the transformations that have taken place in land use, highlighting when and how the land was transformed. Our results show that quantitative and land-use changes due to the socio-economic pressures generated by the transition to a different type of economy can be highlighted. Urban sprawl has led to dramatic changes in land use, with agricultural land being the category that has seen the largest reductions in area. Full article

The Urban Heat Island (UHI) phenomenon, combined with reduced vegetation and heat generated by human activities, presents a major environmental challenge for many European urban areas. The UHI effect is especially concerning in hot and temperate climates, like the Mediterranean region, during the summer months as it intensifies the discomfort and raises the risk of heat-related health issues. As a result, assessing urban heat dynamics and steering sustainable land management practices is becoming increasingly crucial. Analyzing the relationship between land cover and Land Surface Temperature (LST) can significantly contribute to achieving this objective. This study evaluates the spatial correlations between various land cover types and LST trends in Thessaloniki, Greece, using data from the Coordination of Information on the Environment (CORINE) program and advanced vegetation index techniques within Google Earth Engine (GEE). Our analysis revealed that there has been a gradual increase in average surface temperature over the past five years, with a more pronounced increase observed in the last two years (2022 and 2023) with mean annual LST values reaching 26.07 °C and 27.09 °C, respectively. By employing indices such as the Normalized Difference Vegetation Index (NDVI) and performing correlation analysis, we further analyzed the influence of diverse urban landscapes on LST distribution across different land use categories over the study area, contributing to a deeper understanding of UHI effects. Full article

Gold mining is an activity that has developed in Colombia due to the great availability of mineral resources geographically distributed throughout the territory. The extraction techniques used are linked to the domain of illegality and to armed actors who have generated notable landscape impacts. This study, focused on the Municipality of Ayapel, Colombia, identifies the landscape units and analyzes the changes in land use and cover resulting from gold mining between the years 1987, 2002, and 2022, applying the CORINE Land Cover methodology, an adapted legend for Colombia, using Landsat satellite images. For this, the recognition of the physical geographical characteristics of the area was carried out in order to group homogeneous landscape units through a cartographic overlay of various layers of information, considering variables such as topography, geomorphology, and lithology. This research identifies a total of 16 landscape units, 8 of which were intervened in 1987, mainly associated with denudational hills. However, in 2022, 13 landscape units were intervened, with a considerable increase in the affected area. Particularly noteworthy is the occupation of landscape units associated with alluvial valleys, with an average of more than 30% of their total area. This demonstrates that they are the most attractive and vulnerable areas for mining exploitation, as they are the zones with the greatest potential for hosting mineral deposits. This impact has worsened over the last decade due to the introduction of other extraction techniques with machinery (dredges, dragon boats, backhoes, and bulldozers) that generate higher productive and economic yields but, at the same time, cause deep environmental liabilities due to the lack of administrative controls. The changes in extraction techniques, the increase in the international price of the commodity, and the absence of government attention have been the breeding ground that has driven gold mining activity. Full article

This study investigates the impact of artificial light at night (ALAN) along the Sicilian coasts, using satellite data from 2016 to 2023, focusing on three distinct spatial domains: terrestrial areas within 1 km from the coastline, marine areas extending up to 1 km offshore, and marine areas up to 1 nautical mile from the coast. In coastal zones, ALAN is a significant anthropogenic pressure with potentially detrimental effects on ecosystems. By integrating satellite data with geographic datasets such as Corine Land Cover (CLC), Natura 2000 protected areas, and Posidonia oceanica meadows, this study aims to characterize and analyse the temporal and spatial variations in ALAN across these domains. The findings reveal substantial differences in light pollution between domains and over time, with coastal terrestrial areas exhibiting the highest levels of ALAN. In contrast, marine areas further offshore experience reduced light pollution, particularly within the 1-nautical-mile domain. This study also indicates that protected areas, especially those within the Natura 2000 network, show significantly lower ALAN levels than non-protected areas, highlighting the effectiveness of conservation efforts. Statistical analyses, including ANOVAs, demonstrate that factors such as geographic domain, year, province, and CLC classes significantly influence ALAN distribution. This study advocates for considering ALAN as a critical factor in environmental impact assessments, such as those under the Maritime Spatial Planning Directive (MSP) and Marine Strategy Framework Directive (MSFD), providing valuable insights to support policies aimed at mitigating the environmental impact of light pollution on coastal and marine ecosystems. Full article

Planning for a green–blue infrastructure system around big cities, having the shape of a belt, to connect natural areas—such as green spaces, water, and agricultural land—is a solution for mitigating the challenges of climate change and urban sprawl. In this context, this study presents an innovative information technology solution for assessing the connectivity of the green and blue areas in the metropolitan area of Bucharest, Romania. The solution is to try to stop the sprawl of Bucharest into the adjacent rural areas and answer the need for a green infrastructure providing ecosystem services. The methodology uses datasets compatible with the European databases on environmental issues, CORINE Land Cover 2018 and Urban Atlas, and two tools in the ArcGIS PRO 2.9 software package, namely Cost Raster and Cost Connectivity. Based on the results, we developed a framework for implementing a strategy for the green–blue infrastructure for the Bucharest metropolitan area. Our methodology is a starter for planning a green–blue belt for the metropolitan area of Bucharest and a model of good practice in terms of making green–blue infrastructure part of urban and territorial planning. Full article

Data repositories such as Eurostat and OECD provide important socioeconomic datasets useful to guide decision support towards reaching sustainable development goals. However, socioeconomic data are typically available at a limited spatiotemporal scale. In the Horizon Europe-funded AquaINFRA project, a specific scope is to make EU data more analysis ready. As part of this, transformations of data into common spatial entities are needed to facilitate cross-analysis in, for example, social-ecological modelling. This paper uses CORINE land cover as ancillary data and EUROSTAT population data to investigate binary and weighted dasymetric refinement strategies to arrive at areal interpolation algorithms to estimate population data at smaller spatial scales. Six different algorithms are presented, and their accuracies are tested with quality measures. Their limitations and further development potentials on how to make them more precise and expand their usefulness in the future to other types of socioeconomic data are discussed. Full article

In this study, the landscape and ecological stability of the Dolný Spiš region are investigated, focusing on human-induced changes and land use patterns. The purpose is to assess the impact of industrial, agricultural, and social activities on the landscape structure, using current and historical data. Field mapping and data from the DATAcube (Database of the Slovak Statistical Office) and CORINE Land Cover databases (Landscape cover layer for the whole territory of Europe) were used to evaluate land use, with ecological stability measured through the coefficient of ecological stability (CES). Three methodologies—Míchal, Löw, and Miklós—were applied and adjusted for local conditions. The study area, predominantly covered by forests (over 80%), was classified as highly stable based on CES values, with forested areas contributing significantly to this classification. Additionally, the non-forested areas were analyzed to assess the full scope of anthropic influence, revealing low-intensity human activity, as indicated by the coefficient of anthropic influence (CAI), ranging from 0 to 0.45. The results demonstrate that the landscape’s ability to resist disruptive elements is strong, particularly in forested regions. Overall, in this study, the critical role of forests is highlighted in maintaining the ecological stability in the region and suggests that the landscape structure remains resilient despite ongoing changes in agricultural land use. Full article