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Political Trust and Potential of Participatory Dialogue in Mining Areas in Serbia: The Perspective of Local Population of Bor and Majdanpek
No full textPost-socialist countries in Europe that are in the process of EU accession
(Albania, Bosnia and Hercegovina, Montenegro, Serbia) are becoming
attractive for mining investments due to the unregulated land ownership
and weaker environmental standards (Mandacia & Tutan, 2018). Environ
mental protests in Serbia were primarily initiated by the local population
whose immediate surroundings were threatened by the commercial pro
jects of land/water grabbing (Pešić & Vukelić, 2022). They were followed by
growing authoritarian tendencies over the past decade and the insufficient
response of various institutions to citizens' demands (Pešić & Petrović,
2023). The future of civic engagement in such a context of declining demo
cracy and widespread distrust presents a research challenge. The aim of this
presentation is to explore the potential of participatory dialogue in mining
areas by analyzing political trust and participation among the local popula
tion, including both rural and urban perspectives. This is based on empirical
research conducted in Bor and Majdanpek mining communities, using a ran
dom sample (N=300) during July – August 2024. The level of participation
among the local population will be analyzed through their membership in
organizations and involvement in community activities. Trust in institutions
and other relevant actors will be assessed based on their confidence in those
addressing issues caused by mining activities. This research is developed
within the MINIPART project supported by the Science Fund of the Republic
of Serbia, grant #7598
Doprinos Srpskog geografskog društva zaštiti životne sredine
No full textOsnovano 1910. godine, kao prvo te vrste na Balkanskom poluostrvu, Srpsko geografsko društvo pisanom reči višestruko doprinosi poznavanju zaštite i valorizaije životne sredine. Osnovni zadaci su mu bili naučni i stručni rad na upoznavanju fi zičko-geografskih i društveno-geografskih osobenosti prostora i popularizacija naučno proverenih činjenica o čoveku, društvu i njihovom okruženju. Sveobuhvatni odnosi čoveka i ljudskog društva, postali su neizbežne teme Cvijićeve antropogeografske škole, koja čoveka nije odvajala od prirode, kao i prirodu od čoveka. U obimnoj izdavačkoj delatnosti, koja traje od 1912. godine, Srpsko geografsko društvo je više puta publikovalo naučne radove, stručne radove, monografi je i popularnu literaturu, koja se, direktno i indirektno, odnosi na probleme zaštite, unapređenja i valorizacije životne sredine. Posebno se ističu knjige i radovi: Geografski lik Srbije u doba Prvog ustanka; Kopaonik; Životna sredina i čovek; Ekologija i geografi ja u rešavanju problema životne sredine; Visinsko zoniranje voda u slivu Zapadne Morave; Naši predeli; Zaštita prirode - reke, more, jezera; Biogeografska utemeljenost formiranja mreža zaštićenih prostora; Osvrt na kompleksni pristup proučavanju interakcija čovek (društvo) - priroda; Hidrološka analiza i mere zaštite od poplava u Srbiji u periodu 1999-2009 godine; Ruralni prostor u svetlu koncepcije aktivne zaštite životne sredine; Pozitivni i negativni uticaji turizma na životnu sredinu; Lokacija industrije po metodologiji Ujedinjenih nacija; Recentna erozija - globalni problem sveta; Vodni resursi Srbije, njihovo iskorišćavanje i zaštita; Planiranje životne sredine; Životna sredina - polje integralnog istraživanja u savremenoj geografi ji; Dinamika iskorišćavanja i zaštite voda u svetu do kraja XX veka; Erozija i biljna proizvodnja. Radovi objavljeni u izdanjima Srpskog geografskog društva, bili su, i ostaju, nezaobilazna literatura za dalja istraživanja niza pojava, procesa, objekata i događaja u životnoj sredini.Urednici: Dejan Filipović, Velimir Šećerov, Dušan Ristić, Marina Ili
Klimatski uslovi kao faktor razvoja ratarstva Bačkog Podunavlja
No full textPoljoprivredna proizvodnja je usko vezana za klimatske uslove prostora, a sadašnje promene klime bitno utiču na uslove i mogućnost poljoprivredne proizvodnje. U radu je analizirana povezanost klimatskih elemenata i (prosečna temperatura vazduha, maksimalna temperatura vazduha, padavine) i indeksa (uzastopni broj suvih dana) sa prinosom ratarskih kultura (pšenica, kukuruz, šećerna repa, suncokret, pasulj, krompir, detelina i lucerka) na teritoriji Bačkog Podunavlja u periodu 2005-2015. Rezultati ukazuju da prosečne i maksimalne temperature vazduha imaju najznačajniji uticaj na godišnje prinose. Od izabranih ratarskih kultura, prinos suncokreta i krompira je značajno povezan sa temperaturnim uslovima. Identifi kovana su tri pravca razvoja poljoprivredne proizvodnje: apsolutni žitarični pravac, dominantni žitarični pravac sa učešćem industrijskog bilja i pretežni žitarični pravac sa većim učešćem industrijskog bilja. Razumevanje povezanosti klimatskih elemenata i prinosa, kao i pravaca razvoja može doprineti prilagođavanju poljoprivredne proizvodnje izmenjenim klimatskim uslovima.Urednici: Dejan Filipović, Velimir Šećerov, Dušan Ristić, Marina Ili
Wildfire Susceptibility Mapping Using Deep Learning and Machine Learning Models Based on Multi-Sensor Satellite Data Fusion: A Case Study of Serbia
No full textTo prevent or mitigate the negative impact of fires, spatial prediction maps of wildfires are created to identify susceptible locations and key factors that influence the occurrence of fires. This study uses artificial intelligence models, specifically machine learning (XGBoost) and deep learning (Kolmogorov-Arnold networks—KANs, and deep neural network—DNN), with data obtained from multi-sensor satellite imagery (MODIS, VIIRS, Sentinel-2, Landsat 8/9) for spatial modeling wildfires in Serbia (88,361 km2). Based on geographic information systems (GIS) and 199,598 wildfire samples, 16 quantitative variables (geomorphological, climatological, hydrological, vegetational, and anthropogenic) are presented, together with 3 synthesis maps and an integrated susceptibility map of the 3 applied models. The results show a varying percentage of Serbia’s very high vulnerability to wildfires (XGBoost = 11.5%; KAN = 14.8%; DNN = 15.2%; Ensemble = 12.7%). Among the applied models, the DNN achieved the highest predictive performance (Accuracy = 83.4%, ROC-AUC = 92.3%), followed by XGBoost and KANs, both of which also demonstrated strong predictive accuracy (ROC-AUC > 90%). These results confirm the robustness of deep and machine learning approaches for wildfire susceptibility mapping in Serbia. SHAP analysis determined that the most influential factors are elevation, air temperature, and humidity regime (precipitation, aridity, and series of consecutive dry/wet days)
Geospatial Patterns of Cardiovascular Diseases: A Case Study from the Institute for Cardiovascular Diseases of Vojvodina (Northern Serbia)
No full textCardiovascular diseases (CVDs) represent one of the most
dominant categories of non-communicable diseases, with a high prevalence
both in the Republic of Serbia and globally. Understanding their spatial
distribution provides valuable insights for public health planning and disease
prevention. This study applies geospatial analysis to examine the patterns of
CVDs among patients treated at the Institute for Cardiovascular Diseases of
Vojvodina (ICDV) in the Republic of Serbia, over the period 1995–2023. The
spatial dimension of the research was addressed using the Emerging Hot Spot
Analysis tool in ArcGIS Pro, which implements the Getis-Ord Gi* statistic to
detect statistically significant clusters of high and low values. The results
revealed 12 clusters categorised as Consecutive Hot Spots and 3 clusters
categorised as Sporadic Hot Spots, including 48 and 18 settlements in those
clusters, respectively. The remaining clusters showed no patterns. To further
refine the spatial representation of CVD clusters, the Kriging interpolation
method was applied. For this analysis, settlements’ polygons were converted
to points, after which a Kriging-interpolated raster was generated and
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subsequently transformed into contour lines to facilitate interpretation and
presentation. The number of patients per settlement over the entire study
period ranged from 1 to 357,076. A total of 37 settlements recorded only one
patient. The highest number of patients was observed in Novi Sad, indicating
that settlements within South Bačka County exhibited the greatest disease
burden in the ICDV. The findings underscore the significance of geospatial
methods in pinpointing high-risk areas in cardiovascular diseases, providing
an evidence-based foundation for targeted healthcare interventions and
resource allocation. Moreover, this study demonstrates the potential of
integrating spatial geostatistics with health data to support the development of
preventive strategies and to guide future epidemiological research on noncommunicable diseases in Serbia and beyond.Editors: Slobodan B. Marković, Srđan Rončević, Lazar Lazi
Application of Artificial Intelligence for Terrain Slope Mapping
No full textA terrain slope map represents one of the fundamental geospatial
layers used for assessing soil stability, erosion risk, infrastructure planning,
and environmental monitoring. With the advancement of Geographic
Information Systems (GIS) and automated algorithms, the process of
generating such maps has become increasingly accurate and efficient. This
study examines the feasibility of utilising artificial intelligence (AI) to
generate a slope map for Serbia's entire territory, with a focus on developing
Python code for map creation. The research presents the workflow from
acquiring a digital terrain model (DTM), through data processing in ArcGIS
Pro, to the final visualisation of the slope map. The objective is to examine the
effectiveness of AI in optimising GIS workflows and to evaluate the accuracy
and reliability of AI-generated scripts compared with conventional spatial data
processing methods. The findings demonstrate that the application of AI in
slope map production offers multiple advantages, particularly in automating
procedures, accelerating the generation of Python scripts, and reducing the
likelihood of errors. Although some cases required additional code
verification, the results confirmed that AI can serve as a valuable tool in GIS
analyses. Automating Python script generation with AI has substantially
accelerated spatial data processing while minimising potential errors. The
spatial analysis produced a representation of slopes across the DTM area,
incorporating cartographic elements of the map as geographic coordinates,
legend, north arrow, and scale bar, essential for accurate interpretation.
Additionally, the use of the matplotlib library enabled interactive data
visualisation, including zooming and panning functions, which significantly
enhanced terrain analysis. Future research may extend this methodology to
other spatial analyses, such as erosion modelling, slope stability assessment,
or hydrological simulations. Moreover, integrating AI with GIS tools and
further optimising algorithms could improve both the precision and efficiency
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of spatial analyses. This study confirms that the adoption of modern AI
technologies in GIS can substantially enhance the quality and efficiency of
spatial data processing, opening new opportunities for the application of AI in
geospatial research.Editors: Slobodan B. Marković, Srđan Rončević, Lazar Lazi
Assessment of Future Precipitation Changes in Mediterranean Climate Regions From CMIP6 Ensemble
No full textPrevious studies have indicated a large model disagreement in the future projections of precipitation changes over Mediterraneanclimate (MedClim) regions worldwide. The majority of these highly populated regions have experienced major droughts in therecent decades, raising concerns about future precipitation changes and their impacts. Here, we examine precipitation projec-tions in five MedClim regions from the CMIP6 ensemble, focusing on model consensus regarding the direction and magnitudeof future precipitation changes. Our analysis spans the period 2050–2079 relative to 1970–1999, considering two climate changescenarios (SSP2- 4.5 and SSP5-8.5) across the Mediterranean Basin (MED), California (CAL), the central coast of Chile (SAA),the Cape Province area of South Africa (SAF), and southwest Australia (AUS). The CMIP6 ensemble mean suggests that annualmean cumulative precipitation will decrease over all the regions except northern California, primarily due to a reduction inwinter precipitation, and except over the Mediterranean Basin, where the most significant decrease occurs in autumn. Modelagreement on the sign of future precipitation changes is high where the ensemble mean indicates a decrease, but lower where anincrease or no changes are projected. Additionally, consecutive dry days (CDD) are expected to increase across all regions, whilstconsecutive wet days (CWD) are expected to decrease. Maximum 1-day precipitation is projected to increase uniformly across allregions. We conclude that despite substantial improvements to the new CMIP6 generation of models, the model spread in futureprecipitation projections in MedClim regions continues to be high. Impact studies need to account for these uncertainties andconsider the whole intermodel range of projected precipitation changes
Exposure to the noise or pollution: evidence across European countries
No full textEnvironmental issues and climate changes pose a growing threat to the public health and longevity across Europe, with air and noise pollution contributing significantly to premature mortality and diminished quality of life. We estimate the probability to be exposed to the noise or pollution controlling for individual and household level characteristics by using probit method. Dataset is 2023 Survey of Income and Living Conditions for most EU countries and Serbia. Our result reveals significant heterogeneity between European countries, however, in all but one country living in cities or towns vs. living in rural area has significant influence on the probability of exposure to the noise or pollution. The marginal effect for urban areas ranges from 2% in Slovakia to 40% in Greece. There is no significant difference between genders. Elderly people (65+) have lower probability of exposure. Tenures comparing with tenants have lower probability of exposure, which suggests that individuals chose to buy property for living in areas with less environmental problems. In majority of countries people at-risk-of-poverty have higher probability to be exposed to noise or pollution. In Serbia and Latvia, the effect is opposite, poverty is higher in rural than in urban areas and the former areas have lower exposure to the noise or pollution. Our results suggest that effective policy measures are necessary to reduce noise and pollution in urban areas all around the Europe. Additionally, policies for reducing urban-rural inequalities within countries could have direct effect on more equal distribution of risks between cities, towns and rural areas.Editor: Natalija Miri
Geotourism Based on Geoheritage as a Basis for the Sustainable Development of the Golija Nature Park, Southwest Serbia
No full textGolija Mountain, located in the southwestern part of Serbia, has been under
protection as the Golija Nature Park since 2001. It is protected to preserve its forest
ecosystems, diverse landscapes of exceptional beauty, and cultural heritage. Due to its
natural and cultural values, the Golija Nature Park was declared a UNESCO Biosphere
Reserve under the name “Golija-Studenica” in the same year. In addition to its ecosystem
values, due to the complex geological and geomorphological past, there are a significant
number of geodiversity objects on the mountains in the park. Research on these geodiversity
objects has been the focus of the park’s administration in recent years. This protected
natural area faces several challenges, with the sustainable development of tourism being
one of the most significant. The construction of a large ski center is planned, which has
already triggered the spontaneous development of unregulated weekend settlements near
the mountain’s highest peaks. Geotourism provides an alternative to this development.
Geosites, as the most representative landscapes and landforms, serve as key attractions for
geotourists. The main goal of this work was to find appropriate geoactivities related to
geosites that will enhance the geotourism offer, all with the aim of achieving the sustainable
development of the Golija Nature Park
Territorialising globalisation in a post-socialist city: Differences in employment location patterns between foreign and domestic KIBS
No full textForeign investments in knowledge-intensive business services (KIBS) have significantly reshaped the economic and spatial structures of many post-socialist European cities. Despite this, little is known about the intraurban locational behaviour of foreign KIBS and how it differs from their domestic counterparts. This study examines the underlying factors influencing location choices of both foreign and domestic KIBS in Belgrade, a city undergoing complex post-socialist urban economic restructuring. Utilising disaggregated micro-geographic data on KIBS established from 2012 to 2019 and employing a count data model, this analysis reveals key similarities and differences in their employment locational patterns. Both domestic and foreign KIBS are drawn by the economies of localisation, the old CBD, and, to a lesser extent, main streets and commercial areas. However, distinct locational preferences are evident as domestic KIBS are more dispersed, prevalent in densely populated areas and high-status residential neighbourhoods, while foreign KIBS are primarily concentrated in New Belgrade's emerging CBD, characterised by modern commercial infrastructure and better connectivity. These findings contribute to the broader understanding of how globalisation and neoliberal urban policies shape post-socialist cities, highlighting the significant role of foreign KIBS in creating spatially distinct “global city zones” and raising questions about their local embeddedness.Supplementary material: [https://gery.gef.bg.ac.rs/handle/123456789/1998