Pub Date : 2014-09-01DOI: 10.2478/s13533-012-0179-7
T. Vince, G. Szabó, Zoltán Csoma, G. Sándor, S. Szabó
In the present study we examined the Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn contamination levels of the soils of Berehove, a small city in West-Ukraine. As a first step we determined the spatial distribution of the heavy metal contents of the urban soils; then, by studying the land use structure of the city and by statistical analysis we identified the major sources of contamination; we established a matrix of correlations between the heavy metal contents of the soils and the different types of land use; and finally, we drew a conclusion regarding the possible origin(s) of these heavy metals. By means of multivariate statistical analysis we established that of the investigated metals, Ba, Cd, Cu, Pb and Zn accumulated in the city’s soils primarily as a result of anthropogenic activity. In the most polluted urban areas (i.e. in the industrial zones and along the roads and highways with heavy traffic), in the case of several metals (Ba, Cd, Cu, Pb, Zn) we measured concentration levels even two or three times higher than the threshold limit values. Furthermore, Cr, Fe and Ni are primarily of lithogenic origin; therefore, the soil concentrations of these heavy metals depend mainly on the chemical composition of the soil-forming rocks.
{"title":"The spatial distribution pattern of heavy metal concentrations in urban soils — a study of anthropogenic effects in Berehove, Ukraine","authors":"T. Vince, G. Szabó, Zoltán Csoma, G. Sándor, S. Szabó","doi":"10.2478/s13533-012-0179-7","DOIUrl":"https://doi.org/10.2478/s13533-012-0179-7","url":null,"abstract":"In the present study we examined the Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn contamination levels of the soils of Berehove, a small city in West-Ukraine. As a first step we determined the spatial distribution of the heavy metal contents of the urban soils; then, by studying the land use structure of the city and by statistical analysis we identified the major sources of contamination; we established a matrix of correlations between the heavy metal contents of the soils and the different types of land use; and finally, we drew a conclusion regarding the possible origin(s) of these heavy metals. By means of multivariate statistical analysis we established that of the investigated metals, Ba, Cd, Cu, Pb and Zn accumulated in the city’s soils primarily as a result of anthropogenic activity. In the most polluted urban areas (i.e. in the industrial zones and along the roads and highways with heavy traffic), in the case of several metals (Ba, Cd, Cu, Pb, Zn) we measured concentration levels even two or three times higher than the threshold limit values. Furthermore, Cr, Fe and Ni are primarily of lithogenic origin; therefore, the soil concentrations of these heavy metals depend mainly on the chemical composition of the soil-forming rocks.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78872748","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 : 2014-09-01DOI: 10.2478/s13533-012-0189-5
Z. Szelepcsényi, H. Breuer, P. Sümegi
The Holdridge life zone system has already been used a number of times for analysing the effects of climate change on vegetation. But a criticism against the method was formulated that it cannot interpret the ecotones (e.g. forest steppe). Thus, in this paper transitional life zones were also determined in the model. Then, both the original and modified life zone systems were applied for the climatic fields of database CRU TS 1.2. Life zone maps were defined in the Carpathian Region (43.5–50.5° N, 15.5–28° E) for each of five 20-year periods between 1901 and 2000. We estimated correctness of the result maps with another vegetation map using Cohen’s Kappa statistic. Finally, temporal changes in horizontal and vertical distribution of life zones were investigated. The coverage of boreal region decreased with 59.46% during the last century, while the warm temperate region became almost two and a half larger (257.36%). The mean centres of those life zones, which were not related to mountains, shifted northward during the investigation period. In case of the most abundant life zone types, the average distribution elevation increased. Using the modified model, the potential distribution of forest steppe could be also identified.
{"title":"The climate of Carpathian Region in the 20th century based on the original and modified Holdridge life zone system","authors":"Z. Szelepcsényi, H. Breuer, P. Sümegi","doi":"10.2478/s13533-012-0189-5","DOIUrl":"https://doi.org/10.2478/s13533-012-0189-5","url":null,"abstract":"The Holdridge life zone system has already been used a number of times for analysing the effects of climate change on vegetation. But a criticism against the method was formulated that it cannot interpret the ecotones (e.g. forest steppe). Thus, in this paper transitional life zones were also determined in the model. Then, both the original and modified life zone systems were applied for the climatic fields of database CRU TS 1.2. Life zone maps were defined in the Carpathian Region (43.5–50.5° N, 15.5–28° E) for each of five 20-year periods between 1901 and 2000. We estimated correctness of the result maps with another vegetation map using Cohen’s Kappa statistic. Finally, temporal changes in horizontal and vertical distribution of life zones were investigated. The coverage of boreal region decreased with 59.46% during the last century, while the warm temperate region became almost two and a half larger (257.36%). The mean centres of those life zones, which were not related to mountains, shifted northward during the investigation period. In case of the most abundant life zone types, the average distribution elevation increased. Using the modified model, the potential distribution of forest steppe could be also identified.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85891238","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 : 2014-08-06DOI: 10.2478/s13533-012-0178-8
A. Orlik, Lucie Orlikova
With the rise in the number of applications using geospatial data and the number of GIS applications, the number of people who come into contact with geospatial data is increasing, too. Despite many attempts to introduce standardized formats in this area, they are often ignored by software developers as well as the users themselves for various reasons. When creating or exporting geographical data, users choose the format with regard to the software they use, or for which the data are intended. Users then have to deal with conversion of data formats, and considering its use also the issue of their transformation to the appropriate spatial reference system. This work presents findings related to this issue, obtained from several years of operation of an online service for the conversion and transformation of geographical data which is heavily used by users from all over the world. It presents statistics of individual formats use and spatial reference systems of geospatial data use from the point of view of both input and output data. The results, besides other things, are shown in the form of a pie chart map in which various needs of users from a variety of countries can be seen. The results of this work can be used especially by developers of applications which use geospatial data; it will allow them to quickly understand current user needs.
{"title":"Current trends in formats and coordinate transformations of geospatial data — based on MyGeoData Converter","authors":"A. Orlik, Lucie Orlikova","doi":"10.2478/s13533-012-0178-8","DOIUrl":"https://doi.org/10.2478/s13533-012-0178-8","url":null,"abstract":"With the rise in the number of applications using geospatial data and the number of GIS applications, the number of people who come into contact with geospatial data is increasing, too. Despite many attempts to introduce standardized formats in this area, they are often ignored by software developers as well as the users themselves for various reasons. When creating or exporting geographical data, users choose the format with regard to the software they use, or for which the data are intended. Users then have to deal with conversion of data formats, and considering its use also the issue of their transformation to the appropriate spatial reference system. This work presents findings related to this issue, obtained from several years of operation of an online service for the conversion and transformation of geographical data which is heavily used by users from all over the world. It presents statistics of individual formats use and spatial reference systems of geospatial data use from the point of view of both input and output data. The results, besides other things, are shown in the form of a pie chart map in which various needs of users from a variety of countries can be seen. The results of this work can be used especially by developers of applications which use geospatial data; it will allow them to quickly understand current user needs.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73779493","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 : 2014-08-06DOI: 10.2478/s13533-012-0177-9
A. K. Torghabeh, R. Rezaee, R. Moussavi-Harami, B. Pradhan, M. Kamali, A. Kadkhodaie-Ilkhchi
Identifying reservoir electrofacies has an important role in determining hydrocarbon bearing intervals. In this study, electrofacies of the Kockatea Formation in the Perth Basin were determined via cluster analysis. In this method, distance data were initially calculated and then connected spatially by using a linkage function. The dendrogram function was used to extract the cluster tree for formations over the study area. Input logs were sonic log (DT), gamma ray log (GR), resistivity log (IND), and spontaneous potential (SP). A total of 30 reservoir electrofacies were identified within this formation. Integrated geochemical and petrophysics data showed that zones with electrofacies 3, 4, 9, and 10 have potential for shale gas production. In addition, the results showed that cluster analysis is a precise, rapid, and cost-effective method for zoning reservoirs and determining electrofacies in hydrocarbon reservoirs.
{"title":"Electrofacies in gas shale from well log data via cluster analysis: A case study of the Perth Basin, Western Australia","authors":"A. K. Torghabeh, R. Rezaee, R. Moussavi-Harami, B. Pradhan, M. Kamali, A. Kadkhodaie-Ilkhchi","doi":"10.2478/s13533-012-0177-9","DOIUrl":"https://doi.org/10.2478/s13533-012-0177-9","url":null,"abstract":"Identifying reservoir electrofacies has an important role in determining hydrocarbon bearing intervals. In this study, electrofacies of the Kockatea Formation in the Perth Basin were determined via cluster analysis. In this method, distance data were initially calculated and then connected spatially by using a linkage function. The dendrogram function was used to extract the cluster tree for formations over the study area. Input logs were sonic log (DT), gamma ray log (GR), resistivity log (IND), and spontaneous potential (SP). A total of 30 reservoir electrofacies were identified within this formation. Integrated geochemical and petrophysics data showed that zones with electrofacies 3, 4, 9, and 10 have potential for shale gas production. In addition, the results showed that cluster analysis is a precise, rapid, and cost-effective method for zoning reservoirs and determining electrofacies in hydrocarbon reservoirs.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78983682","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 : 2014-08-06DOI: 10.2478/s13533-012-0181-0
C. Romulus, Fontanine Iulia, Corodescu Ema
Sǎrǎţel River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in Sǎrǎţel catchment, between 1990–2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.
{"title":"Assessment of surface runoff depth changes in Sǎrǎţel River basin, Romania using GIS techniques","authors":"C. Romulus, Fontanine Iulia, Corodescu Ema","doi":"10.2478/s13533-012-0181-0","DOIUrl":"https://doi.org/10.2478/s13533-012-0181-0","url":null,"abstract":"Sǎrǎţel River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in Sǎrǎţel catchment, between 1990–2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89317114","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 : 2014-08-06DOI: 10.2478/s13533-012-0180-1
C. E. Can, G. Ergun, C. Gokceoglu
Earthquakes are one of the most important natural hazards to be evaluated carefully in engineering projects, due to the severely damaging effects on human-life and human-made structures. The hazard of an earthquake is defined by several approaches and consequently earthquake parameters such as peak ground acceleration occurring on the focused area can be determined. In an earthquake prone area, the identification of the seismicity patterns is an important task to assess the seismic activities and evaluate the risk of damage and loss along with an earthquake occurrence. As a powerful and flexible framework to characterize the temporal seismicity changes and reveal unexpected patterns, Poisson hidden Markov model provides a better understanding of the nature of earthquakes. In this paper, Poisson hidden Markov model is used to predict the earthquake hazard in Bilecik (NW Turkey) as a result of its important geographic location. Bilecik is in close proximity to the North Anatolian Fault Zone and situated between Ankara and Istanbul, the two biggest cites of Turkey. Consequently, there are major highways, railroads and many engineering structures are being constructed in this area. The annual frequencies of earthquakes occurred within a radius of 100 km area centered on Bilecik, from January 1900 to December 2012, with magnitudes (M) at least 4.0 are modeled by using Poisson-HMM. The hazards for the next 35 years from 2013 to 2047 around the area are obtained from the model by forecasting the annual frequencies of M ≥ 4 earthquakes.
{"title":"Prediction of earthquake hazard by hidden Markov model (around Bilecik, NW Turkey)","authors":"C. E. Can, G. Ergun, C. Gokceoglu","doi":"10.2478/s13533-012-0180-1","DOIUrl":"https://doi.org/10.2478/s13533-012-0180-1","url":null,"abstract":"Earthquakes are one of the most important natural hazards to be evaluated carefully in engineering projects, due to the severely damaging effects on human-life and human-made structures. The hazard of an earthquake is defined by several approaches and consequently earthquake parameters such as peak ground acceleration occurring on the focused area can be determined. In an earthquake prone area, the identification of the seismicity patterns is an important task to assess the seismic activities and evaluate the risk of damage and loss along with an earthquake occurrence. As a powerful and flexible framework to characterize the temporal seismicity changes and reveal unexpected patterns, Poisson hidden Markov model provides a better understanding of the nature of earthquakes. In this paper, Poisson hidden Markov model is used to predict the earthquake hazard in Bilecik (NW Turkey) as a result of its important geographic location. Bilecik is in close proximity to the North Anatolian Fault Zone and situated between Ankara and Istanbul, the two biggest cites of Turkey. Consequently, there are major highways, railroads and many engineering structures are being constructed in this area. The annual frequencies of earthquakes occurred within a radius of 100 km area centered on Bilecik, from January 1900 to December 2012, with magnitudes (M) at least 4.0 are modeled by using Poisson-HMM. The hazards for the next 35 years from 2013 to 2047 around the area are obtained from the model by forecasting the annual frequencies of M ≥ 4 earthquakes.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76933952","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 : 2014-08-06DOI: 10.2478/s13533-012-0182-z
N. Popkhadze, R. Moritz, V. Gugushvili
This study focuses on a well-exposed section of the Artvin-Bolnisi zone located in the open pit of the Madneuli ore deposit, Lesser Caucasus, Georgia. Detailed field and petrographic observations of the main volcano-sedimentary lithofacies of its Upper Cretaceous stratigraphic succession were carried out. Whole rock geochemistry studies support the interpretation of intense silicification of the rocks, and supports our petrographic studies of samples from the Madneuli open pit, including lobe-hyaloclastite described in detail during this study. A particular focus concerned lobe-hyaloclastite exposures in the Madneuli open pit, singled out for first time in this area of the Lesser Caucasus. Two types of hyaloclastite are recognized at the Madneuli deposit: hyaloclastite with pillow-like forms and hyaloclastite with glass-like selvages. The petrographic description shows a different nature for both: hyaloclastite with glass-like selvages represented by devitrification of volcanic glass, which is replaced by quartz and K-feldspar overgrowth of crystals in the groundmass and elongated K-feldspar porphyry phenocrysts. Perlitic cracks were identified during thin section observation. The Hyaloclastite with pillow-like forms consists of relicts of volcanic glass and large pumice clasts replaced by sericite. Key observations are presented in the case of lobe-hyaloclastite and their immediate host volcano-sedimentary environment to constrain their depositional setting. A paleoreconstruction of their environment is proposed, in which hyaloclastite record the interaction of magma emplaced in unconsolidated volcano-sedimentary rocks associated with a submarine rhyodacite dome, emplaced during several magmatic pulses. Our study shows that the predominant part of the host rock sequence of the Madneuli polymetallic deposit was deposited under submarine conditions, which is in agreement with volcanogenic massive sulfide models or transitional, shallow submarine magmatic to epithermal models that were proposed by previous studies.
{"title":"Architecture of Upper Cretaceous rhyodacitic hyaloclastite at the polymetallic Madneuli deposit, Lesser Caucasus, Georgia","authors":"N. Popkhadze, R. Moritz, V. Gugushvili","doi":"10.2478/s13533-012-0182-z","DOIUrl":"https://doi.org/10.2478/s13533-012-0182-z","url":null,"abstract":"This study focuses on a well-exposed section of the Artvin-Bolnisi zone located in the open pit of the Madneuli ore deposit, Lesser Caucasus, Georgia. Detailed field and petrographic observations of the main volcano-sedimentary lithofacies of its Upper Cretaceous stratigraphic succession were carried out. Whole rock geochemistry studies support the interpretation of intense silicification of the rocks, and supports our petrographic studies of samples from the Madneuli open pit, including lobe-hyaloclastite described in detail during this study. A particular focus concerned lobe-hyaloclastite exposures in the Madneuli open pit, singled out for first time in this area of the Lesser Caucasus. Two types of hyaloclastite are recognized at the Madneuli deposit: hyaloclastite with pillow-like forms and hyaloclastite with glass-like selvages. The petrographic description shows a different nature for both: hyaloclastite with glass-like selvages represented by devitrification of volcanic glass, which is replaced by quartz and K-feldspar overgrowth of crystals in the groundmass and elongated K-feldspar porphyry phenocrysts. Perlitic cracks were identified during thin section observation. The Hyaloclastite with pillow-like forms consists of relicts of volcanic glass and large pumice clasts replaced by sericite. Key observations are presented in the case of lobe-hyaloclastite and their immediate host volcano-sedimentary environment to constrain their depositional setting. A paleoreconstruction of their environment is proposed, in which hyaloclastite record the interaction of magma emplaced in unconsolidated volcano-sedimentary rocks associated with a submarine rhyodacite dome, emplaced during several magmatic pulses. Our study shows that the predominant part of the host rock sequence of the Madneuli polymetallic deposit was deposited under submarine conditions, which is in agreement with volcanogenic massive sulfide models or transitional, shallow submarine magmatic to epithermal models that were proposed by previous studies.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77254496","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 : 2014-08-06DOI: 10.2478/s13533-012-0183-y
Saro Lee, H. Oh, C. Heo, I. Park
This study aims to elaborate on the mineral potential maps using various models and verify the accuracy for the epithermal gold (Au) — silver (Ag) deposits in a Geographic Information System (GIS) environment assuming that all deposits shared a common genesis. The maps of potential Au and Ag deposits were produced by geological data in Taebaeksan mineralized area, Korea. The methodological framework consists of three main steps: 1) identification of spatial relationships 2) quantification of such relationships and 3) combination of multiple quantified relationships. A spatial database containing 46 Au-Ag deposits was constructed using GIS. The spatial association between training deposits and 26 related factors were identified and quantified by probabilistic and statistical modelling. The mineral potential maps were generated by integrating all factors using the overlay method and recombined afterwards using the likelihood ratio model. They were verified by comparison with test mineral deposit locations. The verification revealed that the combined mineral potential map had the greatest accuracy (83.97%), whereas it was 72.24%, 65.85%, 72.23% and 71.02% for the likelihood ratio, weight of evidence, logistic regression and artificial neural network models, respectively. The mineral potential map can provide useful information for the mineral resource development.
{"title":"A case study for the integration of predictive mineral potential maps","authors":"Saro Lee, H. Oh, C. Heo, I. Park","doi":"10.2478/s13533-012-0183-y","DOIUrl":"https://doi.org/10.2478/s13533-012-0183-y","url":null,"abstract":"This study aims to elaborate on the mineral potential maps using various models and verify the accuracy for the epithermal gold (Au) — silver (Ag) deposits in a Geographic Information System (GIS) environment assuming that all deposits shared a common genesis. The maps of potential Au and Ag deposits were produced by geological data in Taebaeksan mineralized area, Korea. The methodological framework consists of three main steps: 1) identification of spatial relationships 2) quantification of such relationships and 3) combination of multiple quantified relationships. A spatial database containing 46 Au-Ag deposits was constructed using GIS. The spatial association between training deposits and 26 related factors were identified and quantified by probabilistic and statistical modelling. The mineral potential maps were generated by integrating all factors using the overlay method and recombined afterwards using the likelihood ratio model. They were verified by comparison with test mineral deposit locations. The verification revealed that the combined mineral potential map had the greatest accuracy (83.97%), whereas it was 72.24%, 65.85%, 72.23% and 71.02% for the likelihood ratio, weight of evidence, logistic regression and artificial neural network models, respectively. The mineral potential map can provide useful information for the mineral resource development.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84942483","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 : 2014-08-06DOI: 10.2478/s13533-012-0184-x
F. Wang, Xiaolei Zhang, Zhaoping Yang, Fuming Luan, Heigang Xiong, Zhaoguo Wang, Huiqiu Shi
This study presents the Pearson correlation analyses of the various factors influencing the Chinese National Geoparks. The aim of this contribution is to offer insights on the Chinese National Geoparks by describing its relations with geoheritage and their intrinsic linkages with geological, climatic controls. The results suggest that: 1) Geomorphologic landscape and palaeontology National Geoparks contribute to 81.65% of Chinese National Geoparks. 2) The NNI of geoparks is 0.97 and it belongs to causal distributional patternwhose regional distributional characteristics may be best characterized as’ dispersion in overall and aggregation in local’. 3) Spatial distribution of National Geoparks is wide. The geographic imbalance in their distribution across regions and types of National Geoparks is obvious, with 13 clustered belts, including Tianshan-Altaishan Mountain, Lesser Higgnan-Changbai, Western Bohai Sea, Taihangshan Mountain, Shandong, Qilianshan-Qinling Mountain, Annulus Tibetan Plateau, Dabashan Mountain, Dabieshan Mountain, Chongqing-Western Hunan, Nanling Mountain, Wuyishan Mountain, Southeastern Coastal, of which the National Geoparks number is 180, accounting for 82.57%. 4) Spatial distribution of National Geoparks coincide with latitudinal tectonic zone and longitude tectonic zone of geological structure features, which is consistent with the areas around the Pacific Rim of volcanic tectonic zones. The coupling relationships are obvious between the spatial distributional pattern and the natural and geological conditions.
{"title":"Analysis on spatial distribution characteristics and geographical factors of Chinese National Geoparks","authors":"F. Wang, Xiaolei Zhang, Zhaoping Yang, Fuming Luan, Heigang Xiong, Zhaoguo Wang, Huiqiu Shi","doi":"10.2478/s13533-012-0184-x","DOIUrl":"https://doi.org/10.2478/s13533-012-0184-x","url":null,"abstract":"This study presents the Pearson correlation analyses of the various factors influencing the Chinese National Geoparks. The aim of this contribution is to offer insights on the Chinese National Geoparks by describing its relations with geoheritage and their intrinsic linkages with geological, climatic controls. The results suggest that: 1) Geomorphologic landscape and palaeontology National Geoparks contribute to 81.65% of Chinese National Geoparks. 2) The NNI of geoparks is 0.97 and it belongs to causal distributional patternwhose regional distributional characteristics may be best characterized as’ dispersion in overall and aggregation in local’. 3) Spatial distribution of National Geoparks is wide. The geographic imbalance in their distribution across regions and types of National Geoparks is obvious, with 13 clustered belts, including Tianshan-Altaishan Mountain, Lesser Higgnan-Changbai, Western Bohai Sea, Taihangshan Mountain, Shandong, Qilianshan-Qinling Mountain, Annulus Tibetan Plateau, Dabashan Mountain, Dabieshan Mountain, Chongqing-Western Hunan, Nanling Mountain, Wuyishan Mountain, Southeastern Coastal, of which the National Geoparks number is 180, accounting for 82.57%. 4) Spatial distribution of National Geoparks coincide with latitudinal tectonic zone and longitude tectonic zone of geological structure features, which is consistent with the areas around the Pacific Rim of volcanic tectonic zones. The coupling relationships are obvious between the spatial distributional pattern and the natural and geological conditions.","PeriodicalId":49092,"journal":{"name":"Central European Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86344288","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 : 2014-08-06DOI: 10.2478/s13533-012-0188-6
Á. Leelőssy, F. Molnár, F. Izsák, Ágnes Havasi, I. Lagzi, R. Mészáros
Modeling of dispersion of air pollutants in the atmosphere is one of the most important and challenging scientific problems. There are several natural and anthropogenic events where passive or chemically active compounds are emitted into the atmosphere. The effect of these chemical species can have serious impacts on our environment and human health. Modeling the dispersion of air pollutants can predict this effect. Therefore, development of various model strategies is a key element for the governmental and scientific communities. We provide here a brief review on the mathematical modeling of the dispersion of air pollutants in the atmosphere. We discuss the advantages and drawbacks of several model tools and strategies, namely Gaussian, Lagrangian, Eulerian and CFD models. We especially focus on several recent advances in this multidisciplinary research field, like parallel computing using graphical processing units, or adaptive mesh refinement.
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