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Mediterranean islands are characterized by high biodiversity and cultural value. As the human demand for natural resources increases, the need for assessing the future landscape is prerequisite. This study aimed to simulate the future landscape composition and structure of the Ionian Islands (Western Greece). To do so, we integrated the Future Land Use Model and Markov Chain analysis, taking into consideration fifteen socio-environmental predictors. The results showed that the landscape of the Ionian Islands is expected to develop into two major patterns. The first pattern refers to the expected increase of forests and scrublands, shaping a homogenous landscape. Whereas, the second pattern reveals an expected degradation of natural vegetation, shaping a highly fragmented landscape. In all circumstances, the built-up areas are anticipated to extend, mainly near to touristic hot-spots. This study demonstrated that contemporary spatial simulation approaches, along with various socio-environmental factors offer an important tool for effective landscape management.
George Kefalas; Konstantinos Poirazidis; Panteleimon Xofis; Stamatis Kalogirou; Christos Chalkias. Landscape dynamics on insular environments of South-east mediterranean Europe. Geocarto International 2020, 1 -20.
AMA StyleGeorge Kefalas, Konstantinos Poirazidis, Panteleimon Xofis, Stamatis Kalogirou, Christos Chalkias. Landscape dynamics on insular environments of South-east mediterranean Europe. Geocarto International. 2020; ():1-20.
Chicago/Turabian StyleGeorge Kefalas; Konstantinos Poirazidis; Panteleimon Xofis; Stamatis Kalogirou; Christos Chalkias. 2020. "Landscape dynamics on insular environments of South-east mediterranean Europe." Geocarto International , no. : 1-20.
Mediterranean islands are widely recognized as biodiversity hotspots, with a long history of human activities shaping multi-functional landscapes. Socioeconomic and environmental factors are among the most important factors driving the creation of diverse landscapes, with a high supply of ecosystem services (ES). However, these factors, along with climate change, could also have irreversible consequences on local ecosystems. Thus, this study aimed to reveal the importance of socio-ecological factors in shaping ES bundles to manage natural resources efficiently and enhance human well-being. Using the Ionian Islands as a case study, we explored the relationships among multiple ES, including their supply and demand indicators. We identified bundles of ES to distinguish regions in which supply and demand exhibit different characteristics. An ensemble machine learning method (Random Forest - RF) was used to identify the most important socio-ecological variables out of 17 tested that contribute to ES bundles. Our results produced five bundles of ES supply and six bundles of ES demand. The most important variables for the distribution of ES supply bundles were landscape heterogeneity, elevation, slope, landscape connectivity, and population. In comparison, variables representing elevation, slope, and population were among the most important variables contributing to ES demand bundles. RF exhibited both good classification and predictability, which was supported by the accuracy measures. Our findings demonstrated that research on ES should account for underlying socio-ecological drivers that influence the supply and demand of ES to improve our understanding of the possible impacts of future management decisions regarding the diverse Mediterranean landscapes of the Ionian Islands.
Roxanne Suzette Lorilla; Konstantinos Poirazidis; Vassilis Detsis; Stamatis Kalogirou; Christos Chalkias. Socio-ecological determinants of multiple ecosystem services on the Mediterranean landscapes of the Ionian Islands (Greece). Ecological Modelling 2020, 422, 108994 .
AMA StyleRoxanne Suzette Lorilla, Konstantinos Poirazidis, Vassilis Detsis, Stamatis Kalogirou, Christos Chalkias. Socio-ecological determinants of multiple ecosystem services on the Mediterranean landscapes of the Ionian Islands (Greece). Ecological Modelling. 2020; 422 ():108994.
Chicago/Turabian StyleRoxanne Suzette Lorilla; Konstantinos Poirazidis; Vassilis Detsis; Stamatis Kalogirou; Christos Chalkias. 2020. "Socio-ecological determinants of multiple ecosystem services on the Mediterranean landscapes of the Ionian Islands (Greece)." Ecological Modelling 422, no. : 108994.
George Kefalas; Stamatis Kalogirou; Konstantinos Poirazidis; Roxanne Suzette Lorilla. Landscape transition in Mediterranean islands: The case of Ionian islands, Greece 1985–2015. Landscape and Urban Planning 2019, 191, 1 .
AMA StyleGeorge Kefalas, Stamatis Kalogirou, Konstantinos Poirazidis, Roxanne Suzette Lorilla. Landscape transition in Mediterranean islands: The case of Ionian islands, Greece 1985–2015. Landscape and Urban Planning. 2019; 191 ():1.
Chicago/Turabian StyleGeorge Kefalas; Stamatis Kalogirou; Konstantinos Poirazidis; Roxanne Suzette Lorilla. 2019. "Landscape transition in Mediterranean islands: The case of Ionian islands, Greece 1985–2015." Landscape and Urban Planning 191, no. : 1.
Machine learning algorithms such as Random Forest (RF) are being increasingly applied on traditionally geographical topics such as population estimation. Even though RF is a well performing and generalizable algorithm, the vast majority of its implementations are still ‘aspatial’ and may not address spatial heterogenous processes. At the same time, remote sensing (RS) data which are commonly used to model population can be highly spatially heterogeneous. From this scope, we present a novel geographical implementation of RF, named Geographical Random Forest (GRF) as both an predictive and exploratory tool to model population as a function of RS covariates. GRF is a disaggregation of RF into geographical space in the form of local sub-models. From the first empirical results, we conclude that GRF can be more predictive when an appropriate spatial scale is selected to model the data, with reduced residual autocorrelation and lower Root Mean Square Error and Mean Absolute Error values. Finally, and of equal importance, GRF can be used as an effective exploratory tool to visualize the relationship between dependent and independent variables, highlighting interesting local variations and allowing for a better understanding of the processes that may be causing the observed spatial heterogeneity.
Stefanos Georganos; Tais Grippa; Assane Niang Gadiaga; Catherine Linard; Moritz Lennert; Sabine VanHuysse; Nicholus Odhiambo Mboga; Eléonore Wolff; Stamatis Kalogirou. Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling. Geocarto International 2019, 36, 121 -136.
AMA StyleStefanos Georganos, Tais Grippa, Assane Niang Gadiaga, Catherine Linard, Moritz Lennert, Sabine VanHuysse, Nicholus Odhiambo Mboga, Eléonore Wolff, Stamatis Kalogirou. Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling. Geocarto International. 2019; 36 (2):121-136.
Chicago/Turabian StyleStefanos Georganos; Tais Grippa; Assane Niang Gadiaga; Catherine Linard; Moritz Lennert; Sabine VanHuysse; Nicholus Odhiambo Mboga; Eléonore Wolff; Stamatis Kalogirou. 2019. "Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling." Geocarto International 36, no. 2: 121-136.
In this paper we investigate a local implementation of Random Forest (RF), named Geographical Random Forest (GRF) to predict population density with Very-High-Resolution Remote Sensing (VHHRS) data. As an independent variable we use population density at the neighborhood level from the 2013 census of Dakar, while as explanatory features, the proportions of three different built-up types in each neighborhood derived from a VHHRS land cover classification. The results demonstrated, that by using an appropriate geographic scale to calibrate GRF, we can maximize prediction accuracy due to the incorporation of spatial heterogeneity in the estimates. Additionally, since GRF is an ensemble of local sub-models, the results can be mapped, highlighting local model performance and other interesting spatial variations. Consequently, GRF is suggested as an interesting exploratory and explanatory technique to model remotely-sensed spatially heterogeneous relationships.
Stefanos Georganos; Tais Grippa; Assane Gadiaga; Sabine VanHuysse; Stamatis Kalogirou; Moritz Lennert; Catherine Linard. An Application of Geographical Random Forests for Population Estimation in Dakar, Senegal using Very-High-Resolution Satellite Imagery. 2019 Joint Urban Remote Sensing Event (JURSE) 2019, 1 -4.
AMA StyleStefanos Georganos, Tais Grippa, Assane Gadiaga, Sabine VanHuysse, Stamatis Kalogirou, Moritz Lennert, Catherine Linard. An Application of Geographical Random Forests for Population Estimation in Dakar, Senegal using Very-High-Resolution Satellite Imagery. 2019 Joint Urban Remote Sensing Event (JURSE). 2019; ():1-4.
Chicago/Turabian StyleStefanos Georganos; Tais Grippa; Assane Gadiaga; Sabine VanHuysse; Stamatis Kalogirou; Moritz Lennert; Catherine Linard. 2019. "An Application of Geographical Random Forests for Population Estimation in Dakar, Senegal using Very-High-Resolution Satellite Imagery." 2019 Joint Urban Remote Sensing Event (JURSE) , no. : 1-4.
To manage multiple ecosystem services (ES) effectively, it is essential to understand how the dynamics of ES maintain healthy ecosystems to avoid potential negative impacts on human well-being in the context of sustainable development. In particular, the Ionian Islands in the central Mediterranean are characterized by high natural, ecological, and recreational value; however, the intensification of human activities over time has resulted in the loss of natural ecosystems, which might have negatively impacted ES. Here, we aimed to assess and understand the spatiotemporal dynamics of ES supply and how these components interact across the Ionian Islands to optimize future ES provision and mitigate current trade-offs. We quantified multiple ecosystem services and analyzed their interactions at a temporal scale across the four prefectures of the Ionian Islands. Seven ES were quantified covering all three ES sections (provisioning, regulating and maintenance, and cultural) of the Common International Classification of Ecosystem Services (CICES). ES interactions were investigated by analyzing ES relationships, identifying ES bundles (sets of ES that repeatedly occur together across space and time), and specifying ES occurrence within bundles. The three ES groups exhibited similar patterns on some islands, but differed on islands with areas of high recreation in parallel to low provisioning and regulating ES. Temporal variations showed both stability and changes to the supply of ES, as well as in the interactions among them. Different patterns among the islands were caused by the degree of mixing between natural vegetation and olive orchards. This study identified seven ES bundles that had distinct compositions and magnitudes, with both unique and common bundles being found among the islands. The olive grove bundle delivered the most ES, while the non-vegetated bundle delivered negligible amounts of ES. Spatial and temporal variation in ES appear to be determined by agriculture, land abandonment, and increasing tourism, as well as the occurrence of fires. Knowledge about the spatial dynamics and interactions among ES could provide information for stakeholders and decision-making processes to develop appropriate sustainable management of the ecosystems on the Ionian Islands to secure ecological, social, and economic resilience.
Roxanne Lorilla; Kostas Poirazidis; Stamatis Kalogirou; Vassilis Detsis; Aristotelis Martinis. Assessment of the Spatial Dynamics and Interactions among Multiple Ecosystem Services to Promote Effective Policy Making across Mediterranean Island Landscapes. Sustainability 2018, 10, 3285 .
AMA StyleRoxanne Lorilla, Kostas Poirazidis, Stamatis Kalogirou, Vassilis Detsis, Aristotelis Martinis. Assessment of the Spatial Dynamics and Interactions among Multiple Ecosystem Services to Promote Effective Policy Making across Mediterranean Island Landscapes. Sustainability. 2018; 10 (9):3285.
Chicago/Turabian StyleRoxanne Lorilla; Kostas Poirazidis; Stamatis Kalogirou; Vassilis Detsis; Aristotelis Martinis. 2018. "Assessment of the Spatial Dynamics and Interactions among Multiple Ecosystem Services to Promote Effective Policy Making across Mediterranean Island Landscapes." Sustainability 10, no. 9: 3285.
Mediterranean islands contain heterogeneous landscapes, resulting from the complex interactions between natural and anthropogenic processes, and have significant ecological and conservation importance. They are vulnerable systems to global change and the monitoring of changes, induced by the interacting environmental drivers, is of particular importance for applying a sustainable management regime. The aim of this study was to detect and analyze the landscape dynamics and changes in landscape composition over a 30-year period on the Ionian Islands of Western Greece. State-of-the-art object-oriented image analysis on freely available remote sensing data such as Landsat images was employed achieving final mapping products with high spatial and thematic accuracy (over than 85%), and a transferable classification scheme. The main drivers of environmental change are tourism and associated activities, wildfires and livestock breeding which act in different ways and intensities within and between the islands. The repopulation of those islands, after a period of significant depopulation from the 1940s to the 1980s, and the boom of tourism since the mid-1970s prevented further land abandonment and the recultivation of abandoned land which indicates that tourism and agriculture can be complementary rather than competing economic sectors. Despite the significant increase of tourism, a general trend was observed towards increasing cover of high-density vegetation formations, such as shrublands and forests. At the same time, wildfires, which are in some cases associated with livestock breeding, continue to be an important vegetation degradation factor preventing further ecosystem recovery on the study islands.
George Kefalas; Konstantinos Poirazidis; Panteleimon Xofis; Stamatis Kalogirou. Mapping and Understanding the Dynamics of Landscape Changes on Heterogeneous Mediterranean Islands with the Use of OBIA: The Case of Ionian Region, Greece. Sustainability 2018, 10, 2986 .
AMA StyleGeorge Kefalas, Konstantinos Poirazidis, Panteleimon Xofis, Stamatis Kalogirou. Mapping and Understanding the Dynamics of Landscape Changes on Heterogeneous Mediterranean Islands with the Use of OBIA: The Case of Ionian Region, Greece. Sustainability. 2018; 10 (9):2986.
Chicago/Turabian StyleGeorge Kefalas; Konstantinos Poirazidis; Panteleimon Xofis; Stamatis Kalogirou. 2018. "Mapping and Understanding the Dynamics of Landscape Changes on Heterogeneous Mediterranean Islands with the Use of OBIA: The Case of Ionian Region, Greece." Sustainability 10, no. 9: 2986.
This study evaluates the impact of four feature selection (FS) algorithms in an object-based image analysis framework for very-high-resolution land use-land cover classification. The selected FS algorithms, correlation-based feature selection, mean decrease in accuracy, random forest (RF) based recursive feature elimination, and variable selection using random forest, were tested on the extreme gradient boosting, support vector machine, K-nearest neighbor, RF, and recursive partitioningclassifiers, respectively. The results demonstrate that the selection of an appropriate FS method can be crucial to the performance of a machine learning classifier in terms of accuracy but also parsimony. In this scope, we propose a new metric to perform model selection named classification optimization score (COS) that rewards model simplicity and indirectly penalizes for increased computational time and processing requirements using the number of features for a given classification model as a surrogate. Our findings suggest that applying rigorous FS along with utilizing the COS metric may significantly reduce the processing time and the storage space while at the same time producing higher classification accuracy than using the initial dataset.
Stefanos Georganos; Tais Grippa; Sabine VanHuysse; Moritz Lennert; Michal Shimoni; Stamatis Kalogirou; Eleonore Wolff. Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application. GIScience & Remote Sensing 2017, 55, 221 -242.
AMA StyleStefanos Georganos, Tais Grippa, Sabine VanHuysse, Moritz Lennert, Michal Shimoni, Stamatis Kalogirou, Eleonore Wolff. Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application. GIScience & Remote Sensing. 2017; 55 (2):221-242.
Chicago/Turabian StyleStefanos Georganos; Tais Grippa; Sabine VanHuysse; Moritz Lennert; Michal Shimoni; Stamatis Kalogirou; Eleonore Wolff. 2017. "Less is more: optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application." GIScience & Remote Sensing 55, no. 2: 221-242.
Stefanos Georganos; Abdulhakim M. Abdi; David E. Tenenbaum; Stamatis Kalogirou. Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression. Journal of Arid Environments 2017, 146, 64 -74.
AMA StyleStefanos Georganos, Abdulhakim M. Abdi, David E. Tenenbaum, Stamatis Kalogirou. Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression. Journal of Arid Environments. 2017; 146 ():64-74.
Chicago/Turabian StyleStefanos Georganos; Abdulhakim M. Abdi; David E. Tenenbaum; Stamatis Kalogirou. 2017. "Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression." Journal of Arid Environments 146, no. : 64-74.
The aim of this paper is to measure the spatial accessibility to public health care facilities in Greece. We look at population groups disaggregated by age and socioeconomic characteristics. The purpose of the analysis is to identify potential spatial inequalities in the accessibility to public hospitals among population groups or service areas. The data refer to the accessibility of all residents to public hospitals in Greece. The spatial datasets include the location of settlements (communities), the administrative boundaries of municipalities and the location of public hospitals. The methodology stems from spatial analysis theory (gravity models), economics theory (inequalities) and geocomputation practice (GIS and programming). Several accessibility measures have been calculated using the newly developed R package SpatialAcc, which is available in CRAN. The results are interesting and tend to show an urban-rural and social class divide: younger, working age population as well as people with the highest educational attainment have better accessibility to public hospitals compared to older or low educated residents. This finding has serious policy making implications and should be taken into account in the future spatial (re)organisation of hospitals in Greece.
S. Kalogirou. SPATIAL INEQUALITY IN THE ACCESSIBILITY TO HOSPITALS IN GREECE. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2017, XLII-4/W2, 91 -94.
AMA StyleS. Kalogirou. SPATIAL INEQUALITY IN THE ACCESSIBILITY TO HOSPITALS IN GREECE. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2017; XLII-4/W2 ():91-94.
Chicago/Turabian StyleS. Kalogirou. 2017. "SPATIAL INEQUALITY IN THE ACCESSIBILITY TO HOSPITALS IN GREECE." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W2, no. : 91-94.
The main aim of this article is to combine recent developments in spatial interaction modeling to better model and explain spatial decisions. The empirical study refers to migration decisions made by internal migrants from Athens, Greece. To achieve this, geographically weighted versions of standard and zero inflated Poisson (ZIP) spatial interaction models are defined and fit. In the absence of empirical studies for the effect of potential determinants on internal migration decisions in Greece and the presence of an excessive number of zero migration flows among municipalities in Greece, this article provides empirical evidence for the power of the proposed Geographically Weighted ZIP regression method to better explain destination choices of Athenian internal migrants. We also discuss statistical inference issues in relation to the application of the proposed regression techniques.
Stamatis Kalogirou. Destination Choice of Athenians: An Application of Geographically Weighted Versions of Standard and Zero Inflated Poisson Spatial Interaction Models. Geographical Analysis 2015, 48, 191 -230.
AMA StyleStamatis Kalogirou. Destination Choice of Athenians: An Application of Geographically Weighted Versions of Standard and Zero Inflated Poisson Spatial Interaction Models. Geographical Analysis. 2015; 48 (2):191-230.
Chicago/Turabian StyleStamatis Kalogirou. 2015. "Destination Choice of Athenians: An Application of Geographically Weighted Versions of Standard and Zero Inflated Poisson Spatial Interaction Models." Geographical Analysis 48, no. 2: 191-230.
In recent years, there has been a growing application of advanced methods and techniques such as geographical information systems (GIS), remote sensing and spatial analysis methods in research aimed at understanding, analyzing and visualizing environmental risks. Areas of interest are particularly focused around climate change: the increase in the frequency of extreme weather conditions; the impact of natural disasters; the change to human development make the latter even more relevant. Progress in computer hardware and software allows the application of mathematically complex and computationally intensive methods over relatively small timescales. This special issue of the Journal of Maps is devoted to recent innovations and techniques in the exploitation of mapping and geoinformatics in the field of Environmental Risk Assessment.
Stamatis Kalogirou; Christos Chalkias. Mapping environmental risks: Quantitative and spatial modeling approaches. Journal of Maps 2014, 10, 183 -185.
AMA StyleStamatis Kalogirou, Christos Chalkias. Mapping environmental risks: Quantitative and spatial modeling approaches. Journal of Maps. 2014; 10 (2):183-185.
Chicago/Turabian StyleStamatis Kalogirou; Christos Chalkias. 2014. "Mapping environmental risks: Quantitative and spatial modeling approaches." Journal of Maps 10, no. 2: 183-185.
C. Chalkias; Stamatis Kalogirou; Maria Ferentinou. Landslide susceptibility, Peloponnese Peninsula in South Greece. Journal of Maps 2014, 10, 211 -222.
AMA StyleC. Chalkias, Stamatis Kalogirou, Maria Ferentinou. Landslide susceptibility, Peloponnese Peninsula in South Greece. Journal of Maps. 2014; 10 (2):211-222.
Chicago/Turabian StyleC. Chalkias; Stamatis Kalogirou; Maria Ferentinou. 2014. "Landslide susceptibility, Peloponnese Peninsula in South Greece." Journal of Maps 10, no. 2: 211-222.
The aims of this paper are to estimate, for the first time for Greece, life expectancy at birth by gender at local authority level and to explore spatial patterns. The data used in the analysis come from the vital registration system of Greece and the 2001 population census. For areas with male/female population 5,000 or more, representing 97% of the total, abridged life tables are constructed by employing the Chiang methodology. For local areas of less than 5,000, estimates of expectation of life at birth are obtained by employing regression models. Standard errors of life expectancy are estimated using the Chiang approximation as well as the Scherbov–Ediev reference tables. The results are presented in thematic as well as cluster maps; the latter are based on local Moran's I spatial autocorrelation statistics. Local populations are ranked by level of deprivation in three groups, low, medium, and high, and differences in mean life expectancies are assessed. The findings indicate that across localities, life expectancy ranges from 70.7 to 79.6 for men (8.9-year difference) and from 76.1 to 82.5 for women (6.4-year difference). More deprived areas exhibit lower life expectancy but greater sex difference. Comparatively high life expectancy is found in Crete, the Aegean and Ionian Islands, the Peloponnese, Central-Western Greece and in Athens and Thessaloniki metropolitan areas; conditions are unfavourable in North-Eastern Greece (particularly Thrace). Life expectancy standard errors, based on the two aforementioned procedures, are close, but Chiang approximation tends to underestimate to some extend standard errors particularly for populations 5,000–10,000. Copyright © 2013 John Wiley & Sons, Ltd.
Cleon Tsimbos; Stamatis Kalogirou; Georgia Verropoulou. Estimating Spatial Differentials in Life Expectancy in Greece at Local Authority Level. Population, Space and Place 2013, 20, 646 -663.
AMA StyleCleon Tsimbos, Stamatis Kalogirou, Georgia Verropoulou. Estimating Spatial Differentials in Life Expectancy in Greece at Local Authority Level. Population, Space and Place. 2013; 20 (7):646-663.
Chicago/Turabian StyleCleon Tsimbos; Stamatis Kalogirou; Georgia Verropoulou. 2013. "Estimating Spatial Differentials in Life Expectancy in Greece at Local Authority Level." Population, Space and Place 20, no. 7: 646-663.
Deaths due to neoplasms and diseases of the circulatory and the respiratory system represent 80% of all deaths in Greece. In the context of dearth of statistical analysis of spatial patterns of cause-specific mortality in Greece, this paper aims at studying the distribution and structure of appropriate mortality measures for the above mentioned causes of death at prefecture level. To achieve this, official statistics on deaths (2006–2008) and population (2007) are employed and Standardized Mortality Ratios (SMRs) by gender and cause of death are estimated using as ‘standard’ mortality schedule the national age-sex and cause-specific death rates. Estimation of Moran's I statistic revealed the existence of significant positive spatial autocorrelation for neoplasms and circulatory diseases. Empirical Bayes procedures were employed to adjust SMR values which, although show less dispersion, were close to the original estimates. The thematic maps depict regions with relatively high (SMRs > 100) or low (SMRs < 100) mortality and their significance levels, indicating that spatial patterns exhibit many similarities between sexes for each cause of death. SMRs for neoplasms and circulatory diseases show a roughly similar tendency; lower mortality compared to the country's average in southern and western Greece and the islands, and higher mortality in northern Greece, especially in the Region of East Macedonia and Thrace. Patterns due to respiratory diseases, on the other hand, differ somewhat but the corresponding relative risks are not as significant. Thorough observation and analysis of the conditions prevailing in northern Greece is needed to identify factors exacerbating ill health.
Stamatis Kalogirou; Cleon Tsimbos; Georgia Verropoulou; George Kotsifakis. Regional mortality differentials in Greece by selected causes of death: 2006–2008. Journal of Maps 2012, 8, 354 -360.
AMA StyleStamatis Kalogirou, Cleon Tsimbos, Georgia Verropoulou, George Kotsifakis. Regional mortality differentials in Greece by selected causes of death: 2006–2008. Journal of Maps. 2012; 8 (4):354-360.
Chicago/Turabian StyleStamatis Kalogirou; Cleon Tsimbos; Georgia Verropoulou; George Kotsifakis. 2012. "Regional mortality differentials in Greece by selected causes of death: 2006–2008." Journal of Maps 8, no. 4: 354-360.
A gridded dataset representing near surface atmospheric fields has been developed to allow spatial analysis of long-term weather patterns over an area with significant climate spatiotemporal variability, Greece. The atmospheric elements considered are means of near surface temperature, means of relative humidity, as well as monthly and annual accumulated precipitation. The extracted patterns are based on the gridded European Centre for Medium-Range Weather Forecast (ECMWF) daily analyses interpolated on a regular 0.25° × 0.25° grid. Long-term means on annual and monthly bases for an 18-year reference period (1990–2007), are estimated for the continuous fields. Monthly and annual averages of accumulated precipitation for the period of 1980–2001 have also been created from near to analysis ECMWF forecasts and records gathered from surface meteorological stations. The extracted dataset has been accordingly formatted in order to allow visualization of the long-term atmospheric variables using a geographic information system.
Petros Katsafados; Stamatis Kalogirou; Anastasios Papadopoulos; Gerasimos Korres. Mapping long-term atmospheric variables over Greece. Journal of Maps 2012, 8, 181 -184.
AMA StylePetros Katsafados, Stamatis Kalogirou, Anastasios Papadopoulos, Gerasimos Korres. Mapping long-term atmospheric variables over Greece. Journal of Maps. 2012; 8 (2):181-184.
Chicago/Turabian StylePetros Katsafados; Stamatis Kalogirou; Anastasios Papadopoulos; Gerasimos Korres. 2012. "Mapping long-term atmospheric variables over Greece." Journal of Maps 8, no. 2: 181-184.
The aim of this paper is to define and test local versions of standard correlation coefficients in statistical analysis. This research is motivated by the increasing number of applications using local versions of explanatory spatial data analysis methods such as local regression. Local statistical methods should be applied together with local measures of statistical inference in order to check their performance and to provide an indication of the quality of their results. One example of local explanatory data analysis method is the Geographically Weighted Regression, the application of which allows the researcher to check for the existence of spatial nonstationarity in the relationships between a geographic phenomenon and its determinants. In this paper, a local version of Pearson correlation coefficient is defined and applied to internal migration data in Sweden. The results suggest that globally independent variables are not necessarily independent locally, thus the independence criterion may be violated when local regression analysis is performed. Thus, the results of local regression analysis should be presented in light of the local statistical inference and their interpretation should be made with care.
Stamatis Kalogirou. Testing local versions of correlation coefficients. Review of Regional Research 2011, 32, 45 -61.
AMA StyleStamatis Kalogirou. Testing local versions of correlation coefficients. Review of Regional Research. 2011; 32 (1):45-61.
Chicago/Turabian StyleStamatis Kalogirou. 2011. "Testing local versions of correlation coefficients." Review of Regional Research 32, no. 1: 45-61.
Cleon Tsimbos; George Kotsifakis; Georgia Verropoulou; Stamatis Kalogirou. Life expectancy in Greece 1991–2007: regional variations and spatial clustering. Journal of Maps 2011, 7, 280 -290.
AMA StyleCleon Tsimbos, George Kotsifakis, Georgia Verropoulou, Stamatis Kalogirou. Life expectancy in Greece 1991–2007: regional variations and spatial clustering. Journal of Maps. 2011; 7 (1):280-290.
Chicago/Turabian StyleCleon Tsimbos; George Kotsifakis; Georgia Verropoulou; Stamatis Kalogirou. 2011. "Life expectancy in Greece 1991–2007: regional variations and spatial clustering." Journal of Maps 7, no. 1: 280-290.
Cultural events such as festivals are emerging worldwide as a dynamic sector of the tourism and leisure industries with significant economic, social, cultural and political impacts on the destination area. Their economic importance stems from the expenditure of the attendants that filters through the local economy of the host community. This paper seeks to explore the degree to which economic benefits generated by film festivals are spread out evenly around the festival venues within the host community. The paper uses a business survey technique to assess the direct economic impact of a film festival on the local leisure business sector. The 2008 Thessaloniki International Film Festival is used as a case study in order to provide empirical evidence for an uneven economic impact over space. The paper makes use of primary data to determine the spatial extent of the festival's economic benefits within the Thessaloniki Metropolitan Area.
Stella Kostopoulou; Stamatis Kalogirou. The spatial-economic impact of cultural events. International Journal of Sustainable Development 2011, 14, 309 .
AMA StyleStella Kostopoulou, Stamatis Kalogirou. The spatial-economic impact of cultural events. International Journal of Sustainable Development. 2011; 14 (3/4):309.
Chicago/Turabian StyleStella Kostopoulou; Stamatis Kalogirou. 2011. "The spatial-economic impact of cultural events." International Journal of Sustainable Development 14, no. 3/4: 309.
Please click here to download the map associated with this article. This paper looks at the spatial inequalities of income and post-graduate educational attainment for Local Authorities in Greece. It also introduces a composite variable that is defined as the average of the standardized values of mean household income and high level of educational attainment (post-graduate degree holders). The explanatory analysis of these variables contributes to the literature of applied spatial analysis of socio-economic indicators at the local authority level in Greece. The latter has so far attracted little attention in the literature even though it is important for informed policy making decisions related to the local economic development in Greece. Another aim for creating the suggested composite variable, is for it to be used as an indicator for explaining spatial phenomena such as internal migration. Maps, and the corresponding exploratory analysis of the composite variable and its components, are shown in different sections of the main map. It is apparent that the Local Authorities in Greece, especially the affluent suburbs of the two metropolitan areas located within the prefectures of Attiki and Thessaloniki, exhibit the highest values of the composite variable. There is a strong North/South, Urban/Rural and Attica/Rest-of-the-country divide. However, smaller peripheral cities and some rural areas seem to perform relatively well compared with the country's average not fully following this divide, an unexpected finding.
Stamatis Kalogirou. Spatial inequalities in income and post-graduate educational attainment in Greece. Journal of Maps 2010, 6, 393 -400.
AMA StyleStamatis Kalogirou. Spatial inequalities in income and post-graduate educational attainment in Greece. Journal of Maps. 2010; 6 (1):393-400.
Chicago/Turabian StyleStamatis Kalogirou. 2010. "Spatial inequalities in income and post-graduate educational attainment in Greece." Journal of Maps 6, no. 1: 393-400.