Search Results (27)

Climate change, particularly the increasing frequency of droughts, poses a critical challenge for agriculture. Rising temperatures and water scarcity threaten both agricultural productivity and ecosystem stability, making the identification of effective drought mitigation strategies essential. This study introduces an innovative approach to agricultural drought monitoring in Poland, utilizing remote sensing (RS) satellite data, collected from 2001 to 2020, and the Drought Identification Satellite System (DISS) index at a 1 km × 1 km spatial resolution, in combination with Copernicus High-Resolution Layers (HRL). To assess areas’ capacities to mitigate drought risks, a multi-criteria decision (MCD) analysis of regional environmental conditions was conducted. Focusing on the Mazowieckie Voivodeship, an algorithm was developed to evaluate regional susceptibility to drought. Spatial datasets were used to analyze environmental indicators, producing a map of communal temperature mitigation capacities. Statistical analysis identified drought vulnerability, highlighting areas in need of urgent intervention, such as increased mid-field tree planting. The study revealed that the frequency of droughts in this region during the growing season from 2001 to 2020 exceeded 40%. As a result, 40 LAU 2 administrative units have been affected by multiple negative environmental factors that contribute to drought formation and its long-term persistence. The proposed methodology, integrating diverse satellite data sources and spatial analyses, offers an effective tool for drought monitoring, mitigation planning, and ecosystem protection in a changing climate. This approach provides valuable insights for policymakers and land managers in addressing agricultural drought challenges and enhancing regional resilience to the impacts of climate change. Full article

Wine tourism plays an important role in the development of the local economy but also in the promotion of Portuguese wines in Europe and the world. Enotourism is also a tool to achieve sustainable development through the promotion of wine producers and the preservation of the cultural landscape. At the same time, it can increase the living standards of the population, generating jobs and additional income. The main objective of the study was to present the level of development of wine tourism and to identify the benefits associated with its development in accordance with the concept of sustainable development. The study used qualitative and quantitative research. A spatial analysis of the determinants of demographic development and wine production based on diagnostic indicators was carried out using the Charvat and Schneider indexes. A correlation relationship was identified between the following diagnostic characteristics: wine production and wine tourism development, on the one hand, and tourism development and demography. The study identified problem areas, e.g., demographic regression and economic progression (based on wine production), and identified the relationship between wine production and wine tourism development and demographic development. The study area was the traditional European wine region of Douro wine region in Portugal. The UNESCO cultural landscape has been shaped by human activities over the centuries. An original research procedure was developed to diagnose the state of the LAUs and determine the impact of wine tourism on their development. The results of the research indicate that wine tourism is an example of tourism on the UNESCO trail, where production and consumption take place for the benefit of both tourists and entrepreneurs. Enotourism is also seen as an important source of income and an enabler of socio-economic development. Full article

In 44 BC, Julius Caesar established Colonia Laus Iulia Corinthiensis, strategically reviving Corinth to dominate Isthmian trade routes and extend Rome’s commercial influence eastwards. At the centre of the colony lies Temple E, an enigmatic structure with an unidentified associated cult. This study investigates the architectural characteristics of Temple E, focusing on the use of marble as the primary building material. Petrographic analysis, elemental chemical profiling (Mn, Mg, Fe, Sr, Y, V, Cd, La, Ce, Yb, U), and isotopic measurements (δ¹⁸O ‰, δ¹³C ‰) are employed to analyse marble samples from the surrounding region, exploring sourcing and construction practices. Statistical comparisons with ancient quarry databases indicate a strong reliance on locally sourced Doliana marble, underscoring the economic significance of regional quarries and suggesting the existence of a local workshop dedicated to architectural production in Roman Corinth. By integrating geological and archaeometric approaches, this study highlights Corinth’s pivotal role in the regional marble trade and its broader economic importance during the Roman Imperial period. The findings emphasise the use of local resources, illustrating a flourishing marble-working industry and enhancing our understanding of the relationship between local materials and Roman architectural practices. Full article

This study elaborates on a typology of demographic change and tests this definition at the lowest granular level (LAU2, municipality) with official data. This typology distinguishes between fragile and resilient municipalities based on population dynamics (in terms of duration and intensity) over 1991–2021. This study’s second aim is to elaborate a spatial autoregressive econometric model to evaluate to what extent and in which direction the rate of participation of potential beneficiaries of the Rural Development Programmes (RDPs) of 2014–2020 is affected by demographic change and other explanatory variables. Regression models compare the results of the OLS (aspatial) and spatial autoregressive models (SAR) of four types of participation rates (all RDP schemes; all LEADER schemes; sectoral schemes of RDP and LEADER; non-sectoral schemes of RDPs and LEADER). This comparison makes it possible to understand the differences between centralised and decentralised management and between sectoral and broader rural-targeted schemes. The results of the models appear attractive in interpreting the role of RDP instruments in different regions and local areas. First, the rate of participation is strongly dependent on macro-regional differences. Regarding the demographic factors at the local level, this study highlights that demographic fragility does not necessarily hamper the use of RDP measures. Conversely, the participation rate in RDP policy schemes seems particularly significant in very fragile areas, whereas significance has yet to be proved in other demographic typologies. This result holds particularly true for the policy uptake of non-sectoral schemes. Furthermore, LEADER decentralised interventions fit the fragile areas more than resilient and vital ones due to the territorially targeted approach followed by the Local Action Groups. Full article

Energy is a key driver of all modern economies. Sustainable development is playing an increasingly important role both at regional and local levels. It is a compromise between social and economic needs and the preservation of nature. In the policy of the European Union, the idea of sustainable development and environmental protection is of decisive importance for the implemented programs and economic activities. Contemporary challenges require the transformation of the energy market towards greater use of renewable sources. According to Directive 2009/28/EC of the European Parliament and European Council on promoting energy from renewable sources, Poland has committed itself to achieving a 23% share of renewable energy in gross final energy consumption by 2030. This goal considers total energy consumption in terms of power, engineering, heating, refrigeration, and transport. The aim of this paper was, firstly, an analysis of the share of renewable energy in the European Union over an 18-year period (2004–2021), with particular emphasis on the position of Poland. The second objective was the analysis of renewable energy at the local level in Poland, i.e., at the local government unit (LAU) level. Changes in the share of renewable energy in Poland compared to other European countries were also examined. The study utilized functional analysis of principal components and cluster analysis based on the data from the Central Statistical Office and EUROSTAT. The study found that while Poland does not differ significantly from other countries in using renewable energy, it does fall below the European average. Principal component analysis suggests that Poland responds adequately to European changes in the share of renewable energy in total energy consumption. This dynamic is stable (over 95% explained by the first component) and applies to most countries surveyed. In addition, the authors sought to answer questions relating to the current status of renewable energy sources in Poland, the barriers and challenges facing the introduction of renewable energy in the country, a comparative analysis of Poland’s progress in renewable energy with other global counterparts, and an exploration of the future prospects and potential for the development of renewable energy in Poland. The study found that the potential for renewable energy is greatest in the northern areas of Poland, with photovoltaics and wind power plants providing the greatest capacity. Poland’s renewable energy potential is very high and will be determined by technological development, political, economic, and social issues. Full article

Regional assessments of soil organic carbon (SOC) trends and the carbon sequestration potential of alternative management practices (AMP) are highly relevant for developing climate change mitigation strategies for the agricultural sector. Such studies could benefit from simplified SOC modeling approaches on the scale of administrative units as this often corresponds to the level of policy-making and data availability. However, there is a risk of systematic errors in such scaling operations. To overcome this problem, we performed a scaling experiment where we simulated the SOC dynamics of the arable soils of the State of Saxony (Germany) across a series of scales using the CANDY Carbon Balance (CCB) model. Specifically, we developed model set-ups on four different administrative levels (NUTS1, NUTS2, NUTS3, and LAU) and evaluated the simulation results of the upscaled models against a 500 m grid-based reference model. Furthermore, we quantified the carbon sequestration potential of selected AMP scenarios (addressing field grass, cover crops, and conservation tillage) across all scales. The upscaled model set-ups adequately simulated the SOC trends of Saxon arable land compared to the grid-based reference simulation (scaling error: 0.8–3.8%), while providing significant benefits for model application, data availability and runtime. The carbon sequestration potential of the AMP scenarios (1.33 Mt C until 2050) was slightly overestimated (+0.07–0.09 Mt C) by the upscaled model set-ups. Regardless of the scale of model set-up, we showed that the use of aggregated statistical input data could lead to a systematic underestimation of SOC trends. LAU and NUTS3 levels were shown to be a suitable compromise for effectively quantifying SOC dynamics and allowed for an acceptable spatial prioritization of AMPs. Such simplified, scale-adapted assessments are valuable for cross-regional comparisons and for communication to and among decision-makers, and might provide a quantitative basis for discussions on the effectiveness of AMPs in various stakeholder processes. Full article

Composite indicators play an important role in the analysis of socio-economic phenomena. A number of different approaches to constructing composite indicators have been proposed in the literature. Depending on the degree of compensation, they can be divided into compensatory, partially compensatory, and non-compensatory. The following article focuses on the method of relative taxonomy and its dynamic modification. While this method is typically applied to metric data, the authors propose using the dynamic approach for interval-valued data, which describes objects of interest more precisely. Metric data are of an atomic nature; i.e., an observation of each variable is expressed as one real number. In contrast, each observation of an interval-valued variable is expressed as an interval. By making use of interval-valued data, it is possible to assess objects not only at the regional level but also at a lower level of territorial aggregation, taking into account spatial variation across districts that make up each region. The study described in the article was conducted by applying relative taxonomy in its dynamic approach to interval-valued data in order to measure the level of social cohesion in Poland’s NUTS2 regions during the period 2010–2019. The target dataset was obtained by aggregating numeric data about social cohesion in districts (LAU1) at the level of regions. The lower and upper limit of the interval for each region was based on district-level data and corresponded to the 2nd and 8th decile, respectively (60% of observations), which helped to mitigate the effect of outliers. By applying dynamic relative taxonomy to interval-valued data, it was possible to graphically represent changes in the level of social cohesion that took place across 17 Poland’s NUTS2 regions between 2010 and 2019. It was found that during the reference period, the level of social cohesion in the regions systematically improved. Despite the observed variation, the distance between the regions consistently decreased over time. The level of social cohesion was found to be higher in regions that had received more EU funding to support regional development. Full article

This study aims to answer the following research questions: (a) to what extent do EU rural development supports for investments address territorial differences of rural areas, especially concerning the differences between rich and intensive areas, on one hand, and marginal and peripheral rural areas on the other hand; (b) how does present governance and the delivery system of measures supporting rural investments contribute to the financial support of marginal and peripheral rural areas? To respond to these questions, the research examined 747 calls for tender in all Italian regions related to 16 types of investment measures and a global amount of EUR 67 billion Euros and 49,410 representative projects approved in 17 Italian regions during the period 2014–2020. Delivery mechanisms included the rules that have been set up to define recipient eligibility and selection criteria of the rural development programmes. The distributive effects of RDP investment support measures appear evidently uneven, especially in agricultural and agro-industrial competitiveness measures, which are mainly allocated in already dynamic and strongly competitive areas. Delivery mechanisms boost disparities when funds are allocated through the “open competition” approach. Instead, the modulation of territorial criteria in the implementation phase can provide effective results in terms of reducing disparities in fund allocation and outreaching the most lagging areas. There are two main novelties of this research: (a) the analysis of territorial criteria in the calls for tenders for investment support, and (b) the effects of these criteria on expenditure distribution at the municipal level (LAU2 in the EU nomenclature). This study has been carried out outside the formal methodological approaches promoted by the European Commission for RDP evaluation and might be considered a complementary approach to evaluation reporting activity. This study might provide two significant contributions to the debate on rural areas. First, a “combined” approach to the definition of rurality (mixing “structural” and “locational” approaches) might provide a better analytical framework in line with the evolution of the literature on rurality. Second, the delivery systems that put more emphasis on territorial targets, as they were presented in this study, might be an essential component of a place-based policy. Full article

Rapid and accurate identification of landslides is an essential part of landslide hazard assessment, and in particular it is useful for land use planning, disaster prevention, and risk control. Recent alternatives to manual landslide mapping are moving in the direction of artificial intelligence—aided recognition of these surface processes. However, so far, the technological advancements have not produced robust automated mapping tools whose domain of validity holds in any area across the globe. For instance, capturing historical landslides in densely vegetated areas is still a challenge. This study proposed a deep learning method based on Light Detection and Ranging (LiDAR) data for automatic identification of historical landslides. Additionally, it tested this method in the Jiuzhaigou earthquake-hit region of Sichuan Province (China). Specifically, we generated a Red Relief Image Map (RRIM), which was obtained via high-precision airborne LiDAR data, and on the basis of this information we trained a Lightweight Attention U-Net (LAU-Net) to map a total of 1949 historical landslides. Overall, our model recognized the aforementioned landslides with high accuracy and relatively low computational costs. We compared multiple performance indexes across several deep learning routines and different data types. The results showed that the Multiple-Class based Semantic Image Segmentation (MIOU) and the F1_score of the LAU-Net and RRIM reached 82.29% and 87.45%, which represented the best performance among the methods we tested. Full article

The global climate, ecological, and energy crisis has increased the interest in the green economy (GE) concept that aims to resolve environmental problems while promoting economic growth, social stabilization, and creating favorable conditions for sustainable economic growth. The implementation of GE solutions requires an assessment system for evaluating the extent to which business operations are consistent with GE principles. In this study, the environmental, economic, and social dimensions of the quality of life were identified, and agricultural factors were considered to determine the progress in the implementation of GE principles. The correlation between the success of GE implementation and the utilization of environmental funding provided by the Common Agricultural Policy (CAP) was analyzed. A composite GE index composed of 19 variables was developed for this purpose with the use of Hellwig’s taxonomic measure of development. The strength of the correlation between GE implementation and the utilization of green payments under the CAP was evaluated by calculating Pearson’s correlation coefficient. Polish rural areas were analyzed at the level of Local Administrative Units (LAU). The study revealed spatial variations in GE development, and it demonstrated that local projects financed from EU funds had a positive impact on the environment. However, the utilization of EU support schemes differs considerably across Polish regions. The analysis revealed that agri-environmental-climate measures (spending per ha) were most strongly correlated with the economic dimension of the quality of life. Southern Poland and suburban areas differed considerably from Eastern Poland where green payments were less effective in promoting GE development. The results of this study are useful for planning, land management, and the development of socioeconomic development strategies at the municipal, regional, and local level. Full article

Timely crop yield forecasts at a national level are substantial to support food policies, to assess agricultural production, and to subsidize regions affected by food shortage. This study presents an operational crop yield forecasting system for Poland that employs freely available satellite and agro-meteorological products provided by the Copernicus programme. The crop yield predictors consist of: (1) Vegetation condition indicators provided daily by Sentinel-3 OLCI (optical) and SLSTR (thermal) imagery, (2) a backward extension of Sentinel-3 data (before 2018) derived from cross-calibrated MODIS data, and (3) air temperature, total precipitation, surface radiation, and soil moisture derived from ERA-5 climate reanalysis generated by the European Centre for Medium-Range Weather Forecasts. The crop yield forecasting algorithm is based on thermal time (growing degree days derived from ERA-5 data) to better follow the crop development stage. The recursive feature elimination is used to derive an optimal set of predictors for each administrative unit, which are ultimately employed by the Extreme Gradient Boosting regressor to forecast yields using official yield statistics as a reference. According to intensive leave-one-year-out cross validation for the 2000–2019 period, the relative RMSE for voivodships (NUTS-2) are: 8% for winter wheat, and 13% for winter rapeseed and maize. Respectively, for municipalities (LAU) it equals 14% for winter wheat, 19% for winter rapeseed, and 27% for maize. The system is designed to be easily applicable in other regions and to be easily adaptable to cloud computing environments such as Data and Information Access Services (DIAS) or Amazon AWS, where data sets from the Copernicus programme are directly accessible. Full article

Assessments of regional differences in the accessibility and capacity of health services often rely on indicators based on data from the permanent residents of a given region. However, a patient does not always use health services in their place of residence. The objective of this article is to evaluate the influence of spatial healthcare accessibility on regional differences in the provision and take-up of health services, using outpatient diabetology in Czechia as a case study. The analysis is grounded in monitoring the differences in the patient’s place of residence and the location of the healthcare provided. Anonymized individual data of the largest Czech health insurance company for 2019 are used (366,537 patients, 2,481,129 medical procedures). The data are aggregated at the district level (LAU 1). It has been identified that regions where patients travel outside their area of residence to access more than half of their healthcare needs are mostly in local/regional centres. Moreover, these patients increase the number of medical services provided in local/regional centres, often by more than 20%, which has been reflected in greater healthcare capacity in these centres. To assess regional differences, it is important to take the spatial healthcare accessibility into account and also consider why patients travel for healthcare. Reasons could be the insufficient local capacity, varied quality of health services or individual factors. In such cases, healthcare actors (health insurance companies, local government etc.) should respond to the situation and take appropriate action to reduce these dissimilarities. Full article

The Lau Basin is a back-arc region formed by the subduction of the Pacific plate below the Australian plate. We studied the regional morphology of the back-arc spreading centers of the Northern Lau basin, and we compared it to their relative spreading rates. We obtained a value of 60.2 mm/year along the Northwest Lau Spreading Centers based on magnetic data, improving on the spreading rate literature data. Furthermore, we carried out numerical models including visco-plastic rheologies and prescribed surface velocities, in an upper plate-fixed reference frame. Although our thermal model points to a high temperature only near the Tonga trench, the model of the second invariant of the strain rate shows active deformation in the mantle from the Tonga trench to ~800 km along the overriding plate. This explains the anomalous magmatic production along all the volcanic centers in the Northern Lau Back-Arc Basin. Full article

Biogas production in Poland and Ukraine seems to be a good way to both reduce greenhouse gas emissions and increase energy self-sufficiency by supplementing conventional energy sources. The aim of the research was to assess the potential of biogas production and the possibility of increasing it at the regional level of both studied countries and was conducted in 2018. The study included an analysis of seasonal heat demand, and the results showed biogas heat surpluses and shortages in each region. The financial side of the investment discussed using the example of the selected administrative unit showed that the construction costs of the biogas plant would be paid back after 7~9 years. The presented results also showed that Polish regions have much higher variation of biogas production potential (0.14~1.09 billion m³) than Ukrainian regions (0.09~0.3 billion m³). The analysis of the possibilities of increasing the potential based on the cultivation of maize in wastelands showed that in this respect, the Ukrainian regions have better opportunities compared to Polish regions. In the case of 20 regions, the maximum use of the potential of biogas should result in an increase in the share of renewable sources in the energy mix to above the level of 25%. Poland and Ukraine have comparable biogas production potentials of ~10 billion m³ annually, which results in a comparable number of biogas plants needed to consume that potential as well as the number of new jobs. The above analyses were also carried out at the LAU level (powiats and raions) where the potential of regional cooperation for four border regions is discussed. Full article

Organic farming is one of the most widely known sustainable models of agricultural production. Success in eco-agriculture also depends greatly on agri-environmental, territorial, economic, social, institutional and spatial conditions. Polish eco-farming is very regionally dispersed and diversified. Regarding the important contribution of organic farming, a better understanding of how this phenomenon develops and which factors affect its spatial distribution can be influential for policymakers in planning strategies that pursue sustainable development objectives in rural areas. This paper assesses the development and analyses the spatial distribution of organic farming in Polish LAU-2. The country’s eco-agriculture was mapped and defined using a synthetic measure, described by 27 sub-measurements of ecological crop cultivation, animal maintenance and eco-production. The local spatial patterns (direction, scale, and range) of organic farming were detected by spatial autocorrelation measurements. The analysis was conducted for the period 2014–2020. Possible external and internal determinants of this spatial dispersion were also defined. The results indicate that the distribution and spread of organic farming in Poland are related to public support, institutional regulations, social considerations, environmental concerns, the local job market and spatial dependencies. Full article