Pub Date : 2023-12-18DOI: 10.14712/23361980.2023.18
Christopher Gomez, Jiaqi Liu, Jing Wu, Frans C. Persendt, B. Bradák, Yousefi Saleh, D. Hadmoko
In this article, desertification and dune progression over vegetation was quantified using remote sensing data. However, vegetation buried under sand blowout could not be counted using this method. Therefore, to estimate the extent of buried vegetation, a GPR campaign was conducted over the coastal sand-dune of Tottori Prefecture (Japan) in combination with a high-resolution topographic UAV-based survey of the topography. The results show that buried vegetation exists underneath sand-blowout, especially near the dune ridges, and can extend from 20 to 30 meters further than the estimate based on airborne remote sensing. Furthermore, the presence of palaeo-vegetation in palaeodune layers also provides the information on the long-term evolution of sand dunes, which can be used to reconstruct Quaternary coastal environments.
{"title":"Improving vegetation spatial distribution mapping in arid and on coastal dune systems using GPR in Tottori Prefecture (Japan)","authors":"Christopher Gomez, Jiaqi Liu, Jing Wu, Frans C. Persendt, B. Bradák, Yousefi Saleh, D. Hadmoko","doi":"10.14712/23361980.2023.18","DOIUrl":"https://doi.org/10.14712/23361980.2023.18","url":null,"abstract":"In this article, desertification and dune progression over vegetation was quantified using remote sensing data. However, vegetation buried under sand blowout could not be counted using this method. Therefore, to estimate the extent of buried vegetation, a GPR campaign was conducted over the coastal sand-dune of Tottori Prefecture (Japan) in combination with a high-resolution topographic UAV-based survey of the topography. The results show that buried vegetation exists underneath sand-blowout, especially near the dune ridges, and can extend from 20 to 30 meters further than the estimate based on airborne remote sensing. Furthermore, the presence of palaeo-vegetation in palaeodune layers also provides the information on the long-term evolution of sand dunes, which can be used to reconstruct Quaternary coastal environments.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":" 14","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138963605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.14712/23361980.2023.16
Andrea Lešková, A. Vaishar
This article focuses on the typology of countryside architectonical forms in the region of South-Moravia in southeastern Czechia and on the expression of village identity through architecture in case study villages. Original folk architecture has been altered by new types of constructions built in rural areas since the 1950s, followed by a more recent wave of new architectural forms that have developed since the 1990s. The number of architectural types in case study villages was predominantly calculated using the panoramic sceneries on mapy.cz. The coefficients of countryside identity were allocated to architectural types based on basic folk house features. The value of countryside identity is higher in smaller villages except for suburbanized settlements of the regional capital of Brno.
{"title":"The typology of countryside architectonical forms in South-Moravia, a region of Czechia","authors":"Andrea Lešková, A. Vaishar","doi":"10.14712/23361980.2023.16","DOIUrl":"https://doi.org/10.14712/23361980.2023.16","url":null,"abstract":"This article focuses on the typology of countryside architectonical forms in the region of South-Moravia in southeastern Czechia and on the expression of village identity through architecture in case study villages. Original folk architecture has been altered by new types of constructions built in rural areas since the 1950s, followed by a more recent wave of new architectural forms that have developed since the 1990s. The number of architectural types in case study villages was predominantly calculated using the panoramic sceneries on mapy.cz. The coefficients of countryside identity were allocated to architectural types based on basic folk house features. The value of countryside identity is higher in smaller villages except for suburbanized settlements of the regional capital of Brno.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"32 13","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138974794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-29DOI: 10.14712/23361980.2023.17
Peter Deďo, David Hána
The aim of this article is to analyze the capital drain among individual European Union (EU) member states and its cohesive and political consequences. Since the capital drain has not yet been calculated at the individual country level, the methodological part of this article delves into this calculation in more detail. Between 1999 and 2018, Ireland and Luxembourg had the highest capital drain due to their tax haven policies. Apart from these extremes, Czechia experienced the largest capital drain during this period. Inequalities among EU member states were gradually decreasing in terms of gross domestic product and gross national disposable income, suggesting that the EU’s cohesion policy has partially been successful in reducing inequalities among EU countries. However, capital drain and its populist interpretations may become a significant political problem for the most negatively affected countries.
{"title":"Consequences of capital drain among EU member states","authors":"Peter Deďo, David Hána","doi":"10.14712/23361980.2023.17","DOIUrl":"https://doi.org/10.14712/23361980.2023.17","url":null,"abstract":"The aim of this article is to analyze the capital drain among individual European Union (EU) member states and its cohesive and political consequences. Since the capital drain has not yet been calculated at the individual country level, the methodological part of this article delves into this calculation in more detail. Between 1999 and 2018, Ireland and Luxembourg had the highest capital drain due to their tax haven policies. Apart from these extremes, Czechia experienced the largest capital drain during this period. Inequalities among EU member states were gradually decreasing in terms of gross domestic product and gross national disposable income, suggesting that the EU’s cohesion policy has partially been successful in reducing inequalities among EU countries. However, capital drain and its populist interpretations may become a significant political problem for the most negatively affected countries.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"76 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139211504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-21DOI: 10.14712/23361980.2023.15
Petr Horák
This paper aims to explore the influence of related variety on direct state-supported R&D cooperation across various geographical levels to understand regional performance differentiation and economic base restructuring in Czechia by employing Frenken et al.’s (2007) methodological approach to calculate a related and unrelated variety for all NACE and NACE C-Manufacturing. Findings indicate that the city of Prague has the highest unrelated and related variety, followed by the cities of Brno, Ostrava, and Pilsen. Calculation just for C-Manufacturing changes the ordering significantly. Furthermore, intra-regional and extra-regional pairwise R&D cooperation in joint projects is calculated. The cluster analysis of Czech microregional data (SO ORP) reveals patterns such as emerging collaborators and collaboration powerhouses. Linear regression analyses established a strong positive association between R&D collaboration intensity and related variety, while a negative link was observed with unrelated variety. Similar relationships were observed in the manufacturing sector (NACE-C).
本文采用 Frenken 等人（2007 年）的方法，计算了所有 NACE 和 NACE C 制造业的相关和非相关品种，旨在探讨相关品种在不同地理层次上对国家直接支持的研发合作的影响，以了解捷克的地区绩效差异和经济基础结构调整。结果表明，布拉格市的非相关和相关品种最多，其次是布尔诺市、俄斯特拉发市和比尔森市。仅计算 C 制造业，排序就发生了显著变化。此外，还计算了联合项目中的区内和区外成对研发合作。对捷克微观地区数据（SO ORP）的聚类分析揭示了新兴合作者和合作强国等模式。线性回归分析表明，研发合作强度与相关品种之间存在密切的正相关关系，而与非相关品种之间则存在负相关关系。在制造业（NACE-C）中也观察到了类似的关系。
{"title":"Related variety and state-sponsored R&D collaboration: a geographical and industrial analysis in Czechia","authors":"Petr Horák","doi":"10.14712/23361980.2023.15","DOIUrl":"https://doi.org/10.14712/23361980.2023.15","url":null,"abstract":"This paper aims to explore the influence of related variety on direct state-supported R&D cooperation across various geographical levels to understand regional performance differentiation and economic base restructuring in Czechia by employing Frenken et al.’s (2007) methodological approach to calculate a related and unrelated variety for all NACE and NACE C-Manufacturing. Findings indicate that the city of Prague has the highest unrelated and related variety, followed by the cities of Brno, Ostrava, and Pilsen. Calculation just for C-Manufacturing changes the ordering significantly. Furthermore, intra-regional and extra-regional pairwise R&D cooperation in joint projects is calculated. The cluster analysis of Czech microregional data (SO ORP) reveals patterns such as emerging collaborators and collaboration powerhouses. Linear regression analyses established a strong positive association between R&D collaboration intensity and related variety, while a negative link was observed with unrelated variety. Similar relationships were observed in the manufacturing sector (NACE-C).","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"232 ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139250718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.14712/23361980.2023.14
Daniel Bicák
Machine learning algorithms are widely used methods in geographical research. However, these algorithms are not properly exploiting the underlying spatial relationships present in the geographical data. One of the approaches, which addresses this problem, is based on an ensemble of local models, which are constructed from samples in close proximity to the location of prediction. This concept was applied to the Random Forest (RF) algorithm, creating a Geographical Random Forest (GRF). This study aims to further develop GRF by tuning the spatial parameters for each location in case of agricultural drought. In addition to tuning, the explanatory property of RF within the framework GRF is explored. Four machine learning models were constructed; regular RF, regular RF with spatial covariates, GRF, and GRF with the tuning of spatial parameters. Models were evaluated using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Although the decrease in RMSE in this very case is relatively small, the method may provide higher improvement with different datasets.
{"title":"Tuning spatial parameters of Geographical Random Forest: the case of agricultural drought","authors":"Daniel Bicák","doi":"10.14712/23361980.2023.14","DOIUrl":"https://doi.org/10.14712/23361980.2023.14","url":null,"abstract":"Machine learning algorithms are widely used methods in geographical research. However, these algorithms are not properly exploiting the underlying spatial relationships present in the geographical data. One of the approaches, which addresses this problem, is based on an ensemble of local models, which are constructed from samples in close proximity to the location of prediction. This concept was applied to the Random Forest (RF) algorithm, creating a Geographical Random Forest (GRF). This study aims to further develop GRF by tuning the spatial parameters for each location in case of agricultural drought. In addition to tuning, the explanatory property of RF within the framework GRF is explored. Four machine learning models were constructed; regular RF, regular RF with spatial covariates, GRF, and GRF with the tuning of spatial parameters. Models were evaluated using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Although the decrease in RMSE in this very case is relatively small, the method may provide higher improvement with different datasets.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135161161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.14712/23361980.2023.13
Bui B. Thien, Vu T. Phuong, Akinola A. Komolafe
Deforestation in the tropics continues inexorably with severe implications for biodiversity conservation, climate regulation and ecosystem services. This study investigated variation in forest cover in Thua Thien Hue province, Vietnam, using the Landsat Thematic Mapper and Operational Land Imager satellite images over the period 1989–2021. Imageries were classified using the maximum likelihood classification technique for the years 1989, 2006, and 2021 and were evaluated for accuracy using the kappa coefficient for each year. Furthermore, forest cover losses and gains were evaluated using the Normalized Difference Vegetation Index and Soil Adjusted Vegetation Index, which were compared with the output of the supervised classification. Results showed that the forest cover of Thua Thien Hue province has drastically declined over the years. The forest cover, which was estimated at 68.88% (3461.46 km2) of the total land area in 1989, increased to 69.04% (3469.51 km2) in 2006 and subsequently decreased to 57.55% (2891.81 km2) in 2021. Severely reduced forest cover is often associated with the expansion of agriculture on the forest edge; other contributing factors include logging, illegal production land, and forest fires. Overall, our results show the necessity of forest management, rational land-use planning policy, and increased community awareness of conservation and sustainable development of forest resources in the study area in the future.
{"title":"Assessment of forest cover and forest loss using satellite images in Thua Thien Hue province, Vietnam","authors":"Bui B. Thien, Vu T. Phuong, Akinola A. Komolafe","doi":"10.14712/23361980.2023.13","DOIUrl":"https://doi.org/10.14712/23361980.2023.13","url":null,"abstract":"Deforestation in the tropics continues inexorably with severe implications for biodiversity conservation, climate regulation and ecosystem services. This study investigated variation in forest cover in Thua Thien Hue province, Vietnam, using the Landsat Thematic Mapper and Operational Land Imager satellite images over the period 1989–2021. Imageries were classified using the maximum likelihood classification technique for the years 1989, 2006, and 2021 and were evaluated for accuracy using the kappa coefficient for each year. Furthermore, forest cover losses and gains were evaluated using the Normalized Difference Vegetation Index and Soil Adjusted Vegetation Index, which were compared with the output of the supervised classification. Results showed that the forest cover of Thua Thien Hue province has drastically declined over the years. The forest cover, which was estimated at 68.88% (3461.46 km2) of the total land area in 1989, increased to 69.04% (3469.51 km2) in 2006 and subsequently decreased to 57.55% (2891.81 km2) in 2021. Severely reduced forest cover is often associated with the expansion of agriculture on the forest edge; other contributing factors include logging, illegal production land, and forest fires. Overall, our results show the necessity of forest management, rational land-use planning policy, and increased community awareness of conservation and sustainable development of forest resources in the study area in the future.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"362 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135216438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-20DOI: 10.14712/23361980.2023.12
Faezeh Afarideh, Mohammad Hossein Ramasht, Graham Mortyn
Tehran is one of the most polluted cities in the world with 48 days of air pollution exceeding the admissible threshold (AQI > 150) for 3 months of the 15 years studied. This period coincides with the time when Tehran’s inversion reaches its maximum stability. The purpose of this study was to determine the height of air pollution in Tehran in the days when pollution exceeds the permissible limit. Continuing to study the pressure and temperature conditions of these days, we then considered the geographical and topographic conditions, and finally identified the best of these cells for potential theoretical air turbulence. The results of this study, based on the Harmonic Analysis method and based on Tehran temperature and pressure data over a 15-year period (2003–2017), show that the highest elevation of Tehran inversion does not exceed 1800 m on polluted days. Only within 6 days of those beyond the admissible threshold, temperature and pressure cells with the highest Newtonian mass are formed. The center of these cells formed with a compressive difference of 32 mg in November, 7 mg in January, 11 mg in December, and temperature difference of 1.1° in November, 4.4° in January, and 1.9° in December. Generally, we considered the formed cells by the temperature and pressure difference and the gradient between them, as well as the difference in height between the cells and their location. This information, combined with the local winds causing the differences in temperature and pressure, allows us to elucidate conditions for creating air turbulence in Tehran and mitigating the amount and degree of air pollution.
{"title":"Air pollution and topography in Tehran","authors":"Faezeh Afarideh, Mohammad Hossein Ramasht, Graham Mortyn","doi":"10.14712/23361980.2023.12","DOIUrl":"https://doi.org/10.14712/23361980.2023.12","url":null,"abstract":"Tehran is one of the most polluted cities in the world with 48 days of air pollution exceeding the admissible threshold (AQI > 150) for 3 months of the 15 years studied. This period coincides with the time when Tehran’s inversion reaches its maximum stability. The purpose of this study was to determine the height of air pollution in Tehran in the days when pollution exceeds the permissible limit. Continuing to study the pressure and temperature conditions of these days, we then considered the geographical and topographic conditions, and finally identified the best of these cells for potential theoretical air turbulence. The results of this study, based on the Harmonic Analysis method and based on Tehran temperature and pressure data over a 15-year period (2003–2017), show that the highest elevation of Tehran inversion does not exceed 1800 m on polluted days. Only within 6 days of those beyond the admissible threshold, temperature and pressure cells with the highest Newtonian mass are formed. The center of these cells formed with a compressive difference of 32 mg in November, 7 mg in January, 11 mg in December, and temperature difference of 1.1° in November, 4.4° in January, and 1.9° in December. Generally, we considered the formed cells by the temperature and pressure difference and the gradient between them, as well as the difference in height between the cells and their location. This information, combined with the local winds causing the differences in temperature and pressure, allows us to elucidate conditions for creating air turbulence in Tehran and mitigating the amount and degree of air pollution.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"69 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135567482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-20DOI: 10.14712/23361980.2023.11
V. Ștîrba
This article aims to analyze the effects of cancer mortality on life expectancy at birth in 15 European high-income countries between 1950 and 2019. To establish the 1950–2019 time series of deaths from cancer, mortality data were harmonized from the available datasets of the World Health Organization Mortality database, coded according to the International Classification of Diseases of the 7th, 8th, 9th, and 10th editions. The estimation of the cancer mortality effect on the life expectancy at birth was performed using the algorithm of stepwise replacement for the life expectancy decomposition. The increase in cancer mortality contributed to a decline in overall life expectancy growth until the mid-1990s, coinciding with the aging cohorts of heavy smokers and a long-term reduction in mortality from other non-communicable diseases. Subsequently, since the 1990s, the reduction in cancer mortality has contributed to a significant increase in life expectancy at birth, especially in males. Reduction in cancer mortality was the outcome of various factors, such as alcohol and tobacco control policies, advances in cancer prevention and its treatment, general increase in population well-being, and reduction in risk-factors.
{"title":"Effects of cancer mortality on life expectancy in European high-income countries between 1950 and 2019","authors":"V. Ștîrba","doi":"10.14712/23361980.2023.11","DOIUrl":"https://doi.org/10.14712/23361980.2023.11","url":null,"abstract":"This article aims to analyze the effects of cancer mortality on life expectancy at birth in 15 European high-income countries between 1950 and 2019. To establish the 1950–2019 time series of deaths from cancer, mortality data were harmonized from the available datasets of the World Health Organization Mortality database, coded according to the International Classification of Diseases of the 7th, 8th, 9th, and 10th editions. The estimation of the cancer mortality effect on the life expectancy at birth was performed using the algorithm of stepwise replacement for the life expectancy decomposition. The increase in cancer mortality contributed to a decline in overall life expectancy growth until the mid-1990s, coinciding with the aging cohorts of heavy smokers and a long-term reduction in mortality from other non-communicable diseases. Subsequently, since the 1990s, the reduction in cancer mortality has contributed to a significant increase in life expectancy at birth, especially in males. Reduction in cancer mortality was the outcome of various factors, such as alcohol and tobacco control policies, advances in cancer prevention and its treatment, general increase in population well-being, and reduction in risk-factors.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"28 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88593272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-21DOI: 10.14712/23361980.2023.10
I. Bollati, V. Caironi, Alessio Gallo, Eliana Muccignato, M. Pelfini, Tullio Bagnati
Geoheritage is recognized as a component of the cultural heritage, especially in areas like UNESCO Global Geoparks. In the Sesia Val Grande UNESCO Global Geopark (northern Italy), the “Comuniterrae project” is a participated project focusing on the elaboration of Community Maps of the Middle Lands and including 10 municipalities located in a “mid” territory between the valley bottom and the highlands. Local communities have inventoried 270 elements, both immaterial and material, as components of their cultural heritage. These sites show a strong link with the geological and geomorphological background. We aimed at enlightening this link by selecting the most iconic geo-cultural sites. An original procedure of classification based on 3 main criteria was set on 70 selected sites: i) the kind of geofeatures; ii) the spatial relation between geofeatures and cultural sites, and the reciprocal conditioning; iii) the relation between humans and geofeatures. The results highlight that heritage stones and natural landforms, especially if conditioning the cultural site location, are the most recurrent categories. The use of geofeatures by humans is the most common kind of relation. These results invite to organize meetings with local populations to discuss these outcomes, and to enrich the touristic offer with multidisciplinary approaches.
{"title":"How to integrate cultural and geological heritage? The case of the Comuniterrae project (Sesia Val Grande UNESCO Global Geopark, northern Italy)","authors":"I. Bollati, V. Caironi, Alessio Gallo, Eliana Muccignato, M. Pelfini, Tullio Bagnati","doi":"10.14712/23361980.2023.10","DOIUrl":"https://doi.org/10.14712/23361980.2023.10","url":null,"abstract":"Geoheritage is recognized as a component of the cultural heritage, especially in areas like UNESCO Global Geoparks. In the Sesia Val Grande UNESCO Global Geopark (northern Italy), the “Comuniterrae project” is a participated project focusing on the elaboration of Community Maps of the Middle Lands and including 10 municipalities located in a “mid” territory between the valley bottom and the highlands. Local communities have inventoried 270 elements, both immaterial and material, as components of their cultural heritage. These sites show a strong link with the geological and geomorphological background. We aimed at enlightening this link by selecting the most iconic geo-cultural sites. An original procedure of classification based on 3 main criteria was set on 70 selected sites: i) the kind of geofeatures; ii) the spatial relation between geofeatures and cultural sites, and the reciprocal conditioning; iii) the relation between humans and geofeatures. The results highlight that heritage stones and natural landforms, especially if conditioning the cultural site location, are the most recurrent categories. The use of geofeatures by humans is the most common kind of relation. These results invite to organize meetings with local populations to discuss these outcomes, and to enrich the touristic offer with multidisciplinary approaches.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"110 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76184987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-16DOI: 10.14712/23361980.2023.6
O. Harbar, O. Lavryk, I. Khomiak, R. Vlasenko, T. Andriychuk, Vitaliy Kostiuk
Landsat satellite images (Landsat-5 for the period of 1990–2010 and Landsat-8 for the year of 2020) were used for the spatiotemporal analysis of the dynamics of the main habitats of the Kozachelaherska arena (Nyzhniodniprovsky sands, Kherson region, Ukraine). The algorithm of minimum distance of automatic k-mean clustering was used for the classification of the satellite images. Habitats were classified according to EUNIS classification principles. The analysis revealed a considerable decrease in a summary area of coniferous plantations in the period of 2000–2010. During the last two decades, the area of losses significantly exceeded the renewal area of coniferous plantations. The area of large permanent aquatic habitats in the north-east part of the arena decreased by 2.5 times in the last thirty years. The water supply of the territory is constantly decreasing, probably due to the reduction in precipitation and in the ground water level. At the same time, the area of territories under open sand doubled, the process of sand overgrowth with vegetation has slowed down, and its losses have increased. All these changes are most likely caused by the increasingly arid climate in southern Ukraine, which may, over time, lead to the replacement of habitats characteristic of sandy steppes with habitats of open sands.
{"title":"Spatiоtemporal analysis of the changes of the main habitats of the Kozachelaherska arena (Nyzhniodniprovsky sands, Kherson region, Ukraine) in the period of 1990–2020","authors":"O. Harbar, O. Lavryk, I. Khomiak, R. Vlasenko, T. Andriychuk, Vitaliy Kostiuk","doi":"10.14712/23361980.2023.6","DOIUrl":"https://doi.org/10.14712/23361980.2023.6","url":null,"abstract":"Landsat satellite images (Landsat-5 for the period of 1990–2010 and Landsat-8 for the year of 2020) were used for the spatiotemporal analysis of the dynamics of the main habitats of the Kozachelaherska arena (Nyzhniodniprovsky sands, Kherson region, Ukraine). The algorithm of minimum distance of automatic k-mean clustering was used for the classification of the satellite images. Habitats were classified according to EUNIS classification principles. The analysis revealed a considerable decrease in a summary area of coniferous plantations in the period of 2000–2010. During the last two decades, the area of losses significantly exceeded the renewal area of coniferous plantations. The area of large permanent aquatic habitats in the north-east part of the arena decreased by 2.5 times in the last thirty years. The water supply of the territory is constantly decreasing, probably due to the reduction in precipitation and in the ground water level. At the same time, the area of territories under open sand doubled, the process of sand overgrowth with vegetation has slowed down, and its losses have increased. All these changes are most likely caused by the increasingly arid climate in southern Ukraine, which may, over time, lead to the replacement of habitats characteristic of sandy steppes with habitats of open sands.","PeriodicalId":41831,"journal":{"name":"AUC Geographica","volume":"123 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90383374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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