scholarly journals A COMPARATIVE SPATIAL ANALYSIS OF THE POSSIBLE EFFECTS OF ECONOMIC CRISIS IN GREECE AND RUSSIA ON PROVINCES IN TURKEY

2016 ◽  
Vol 11 (1) ◽  
Author(s):  
Ilhan Korkmaz ◽  
Fatih Celebioglu
Keyword(s):  
Foreign Trade ◽  
Economic Crisis ◽  
Spatial Data ◽  
Global Financial Crisis ◽  
Spatial Data Analysis ◽  
Debt Burden ◽  
Spatial Dimensions ◽  
Choropleth Maps ◽  
Potential Risks ◽  
A Current

After 2008 global financial crisis some Europe countries which have excessive debt burden especially Greece, Iceland, Spain etc. effected negatively more than the others. On the other hand decrease in oil prices effected negatively some exporter countries for instance Russia, Venezuela etc. in this period. Greece and Russia are neighbor countries that has significant role on Turkey’s foreign trade. In this aspect, it has been occurred some potential risks for provinces in Turkey which exporting to Greece and Russia. This study aims to examine the possible effects of Greek and Russian economic crisis for provinces of Turkey by using spatial data and techniques. To identify risky areas first, it is created different choropleth maps of Turkey by using province based export data in particular Greece and Russia. Second, spatial dimensions of potential risks are discussed. To test spatial dimensions of the variables, we perform an exploratory spatial data analysis on export values for provinces of Turkey. While our choropleth maps indicate that the some part of the country is significantly more related to foreign trade of the countries than the others, the tools of spatial statistics reveal the presence of spatial dependence across provinces. The presence of heterogeneity is reflected in the distribution of LISA statistics. Overall, this paper is original in terms of analyzing spatial dimensions of a current economic issue for provinces across Turkey.

scholarly journals THE IMPACTS OF SOCIOECONOMIC FACTORS ON MIGRATION ACROSS TURKISH REGIONS: A SPATIAL DATA ANALYSIS

2016 ◽  
Vol 10 (2) ◽  
Author(s):  
Ilyas Oz ◽  
Fatih Celebioglu
Keyword(s):  
Data Analysis ◽  
Spatial Analysis ◽  
Unemployment Rate ◽  
Spatial Data ◽  
Spatial Data Analysis ◽  
Security Problem ◽  
Spatial Dimensions ◽  
Quality Health ◽  
Choropleth Maps ◽  
High Level

When examining the causes of migration in Turkey, it can be seen that low quality health and education services, imbalanced urbanization, security problem, high level unemployment rate have pivotal role on migration. In the 1950s Turkey, with intensified migration to big cities (mostly to West part of the country), urbanization process has accelerated. This process brought a number of problems with itself.Although many studies have been performed by researchers about migration in Turkey, there is no paper which includes spatial analysis. In this manner, this study purpose to examine the impacts of the factors as unemployment rate, Socio-economic Development Index on migration and their spatial analysis dimensions.To test spatial dimensions of the variables, we perform an exploratory spatial data analysis (ESDA) on migration and other variables among provinces of Turkey. While our choropleth maps indicate that the some part of the country is significantly more developed than the others, the tools of spatial statistics reveal the presence of spatial dependence across provinces. The presence of heterogeneity is reflected in the distribution of LISA statistics. Overall, our results shed new light on the distribution of migration and its relation with the others among provinces across Turkey.

scholarly journals Adaptive Choropleth Mapper: An Open-Source Web-Based Tool for Synchronous Exploration of Multiple Variables at Multiple Spatial Extents

2019 ◽  
Vol 8 (11) ◽  
pp. 509 ◽  
Author(s):  
Han ◽  
Rey ◽  
Knaap ◽  
Kang ◽  
Wolf
Keyword(s):  
Open Source ◽  
Spatial Data ◽  
Visual Analytics ◽  
Spatial Data Analysis ◽  
Dynamic Visualization ◽  
Web Based ◽  
Choropleth Mapping ◽  
Choropleth Maps ◽  
Multiple Variables ◽  
Choropleth Map

Choropleth mapping is an essential visualization technique for exploratory spatial data analysis. Visualizing multiple choropleth maps is a technique that spatial analysts use to reveal spatiotemporal patterns of one variable or to compare the geographical distributions of multiple variables. Critical features for effective exploration of multiple choropleth maps are (1) automated computation of the same class intervals for shading different choropleth maps, (2) dynamic visualization of local variation in a variable, and (3) linking for synchronous exploration of multiple choropleth maps. Since the 1990s, these features have been developed and are now included in many commercial geographic information system (GIS) software packages. However, many choropleth mapping tools include only one or two of the three features described above. On the other hand, freely available mapping tools that support side-by-side multiple choropleth map visualizations are usually desktop software only. As a result, most existing tools supporting multiple choropleth-map visualizations cannot be easily integrated with Web-based and open-source data visualization libraries, which have become mainstream in visual analytics and geovisualization. To fill this gap, we introduce an open-source Web-based choropleth mapping tool called the Adaptive Choropleth Mapper (ACM), which combines the three critical features for flexible choropleth mapping.

scholarly journals Changes in Regional Economic Resilience after the 2008 Global Economic Crisis: The Case of Korea

2021 ◽  
Vol 13 (20) ◽  
pp. 11392
Author(s):  
Seoyoung Yu ◽  
Donghyun Kim
Keyword(s):  
Economic Crisis ◽  
Spatial Data ◽  
Data Model ◽  
Census Data ◽  
Metropolitan Areas ◽  
Spatial Data Analysis ◽  
Economic Resilience ◽  
Regional Economic ◽  
Administrative Units ◽  
Economic Regions

This study investigated Korea’s regional economic resilience after the 2008 economic crisis and analyzed the spatial patterns therein from the perspective of evolution and engineering. We analyzed the employee statistics of 229 si-gun-gu (city-county-district) administrative units for the 2002–2016 period sourced from Business Census data using shift-share analysis, a panel data model, and exploratory spatial data analysis (ESDA). According to the analysis, most regions showed resilience after the crisis, revealing various patterns within the economic regions. Regarding the capital area, there were more structural improvements in Gyeonggi-do than in Seoul. For other regions, there were also more structural improvements in and around metropolitan areas. When comparing the absolute levels of post-crisis employment, the capital area showed low employment resilience in the CBD, while areas where industries such as IT and finance were clustered showed great employment resilience. In addition, non-capital areas showed a significant recovery in the manufacturing areas. This means that regional inequalities in the process of responding to economic crises are likely to include both quantitative and qualitative aspects, and that policies that accompany more structural improvements should be implemented.

scholarly journals Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model

2021 ◽  
Vol 18 (3) ◽  
pp. 1056
Author(s):  
Yu Chen ◽  
Mengke Zhu ◽  
Qian Zhou ◽  
Yurong Qiao
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Correlation ◽  
Spatial Data ◽  
Central Area ◽  
Urban System ◽  
Entropy Method ◽  
Driving Factors ◽  
Spatial Data Analysis ◽  
Eastern Region ◽  
Urban Resilience

Urban resilience in the context of COVID-19 epidemic refers to the ability of an urban system to resist, absorb, adapt and recover from danger in time to hedge its impact when confronted with external shocks such as epidemic, which is also a capability that must be strengthened for urban development in the context of normal epidemic. Based on the multi-dimensional perspective, entropy method and exploratory spatial data analysis (ESDA) are used to analyze the spatiotemporal evolution characteristics of urban resilience of 281 cities of China from 2011 to 2018, and MGWR model is used to discuss the driving factors affecting the development of urban resilience. It is found that: (1) The urban resilience and sub-resilience show a continuous decline in time, with no obvious sign of convergence, while the spatial agglomeration effect shows an increasing trend year by year. (2) The spatial heterogeneity of urban resilience is significant, with obvious distribution characteristics of “high in east and low in west”. Urban resilience in the east, the central and the west are quite different in terms of development structure and spatial correlation. The eastern region is dominated by the “three-core driving mode”, and the urban resilience shows a significant positive spatial correlation; the central area is a “rectangular structure”, which is also spatially positively correlated; The western region is a “pyramid structure” with significant negative spatial correlation. (3) The spatial heterogeneity of the driving factors is significant, and they have different impact scales on the urban resilience development. The market capacity is the largest impact intensity, while the infrastructure investment is the least impact intensity. On this basis, this paper explores the ways to improve urban resilience in China from different aspects, such as market, technology, finance and government.

scholarly journals Spatial Agglomeration of China’s Forest Products Manufacturing Industry: Measurement, Characteristics and Determinants

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1006
Author(s):  
Zhenhuan Chen ◽  
Hongge Zhu ◽  
Wencheng Zhao ◽  
Menghan Zhao ◽  
Yutong Zhang
Keyword(s):  
Spatial Distribution ◽  
Spatial Data ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Economies Of Scale ◽  
Forest Products ◽  
Spatial Data Analysis ◽  
Forest Protection ◽  
Spatial Agglomeration ◽  
Continuous Space

China’s forest products manufacturing industry is experiencing the dual pressure of forest protection policies and wood scarcity and, therefore, it is of great significance to reveal the spatial agglomeration characteristics and evolution drivers of this industry to enhance its sustainable development. Based on the perspective of large-scale agglomeration in a continuous space, in this study, we used the spatial Gini coefficient and standard deviation ellipse method to investigate the spatial agglomeration degree and location distribution characteristics of China’s forest products manufacturing industry, and we used exploratory spatial data analysis to investigate its spatial agglomeration pattern. The results show that: (1) From 1988 to 2018, the degree of spatial agglomeration of China’s forest products manufacturing industry was relatively low, and the industry was characterized by a very pronounced imbalance in its spatial distribution. (2) The industry has a very clear core–periphery structure, the spatial distribution exhibits a “northeast-southwest” pattern, and the barycenter of the industrial distribution has tended to move south. (3) The industry mainly has a high–high and low–low spatial agglomeration pattern. The provinces with high–high agglomeration are few and concentrated in the southeast coastal area. (4) The spatial agglomeration and evolution characteristics of China’s forest products manufacturing industry may be simultaneously affected by forest protection policies, sources of raw materials, international trade and the degree of marketization. In the future, China’s forest products manufacturing industry should further increase the level of spatial agglomeration to fully realize the economies of scale.

scholarly journals A longitudinal study of e-commerce diversity in Europe

2021 ◽  
Author(s):  
Adam Sadowski ◽  
Karolina Lewandowska-Gwarda ◽  
Renata Pisarek-Bartoszewska ◽  
Per Engelseth
Keyword(s):  
Spatial Data ◽  
Online Shopping ◽  
Statistical Data ◽  
Spatial Diversity ◽  
Regional Level ◽  
Spatial Data Analysis ◽  
Household Preferences ◽  
Global And Local ◽  
Data Analysis Methods ◽  
Local Spatial Autocorrelation

AbstractOwing to increased access to the Internet and the development of electronic commerce, e-commerce has become a common method of shopping in all countries. The purpose of this study is more precisely to research e-commerce diversity in Europe at the regional level and develop the conception of “E-commerce Supply Chain Management”. Statistical data derived from the European Statistical Office were applied to analyse the spatial diversity of e-retailing. Assessments of the regional diversity of e-retailing applied geographic information systems and exploratory spatial data analysis methods such us global and local spatial autocorrelation statistics. Clusters of regions with similar household preferences related to online shopping were identified. A spatial visualisation of the e-retailing diversity phenomenon may be utilised for the reconfiguration of supply chains and to adapt them to actual household preferences related to shopping methods.

Regionální disparity ve voličském chování: Prostorová analýza voličské podpory České pirátské strany v krajských volbách

2021 ◽  
Author(s):  
Pavel Maškarinec
Keyword(s):  
Spatial Data ◽  
Regional Policy ◽  
Regional Governance ◽  
Regional Level ◽  
Capital City ◽  
Spatial Data Analysis ◽  
Regional Government ◽  
Regional Politics ◽  
Electoral Support ◽  
Regional Elections

The presented paper deals with the regionalization of the electoral support of the Czech Pirate Party (Pirates) in regional elections using methods and techniques of spatial data analysis. The aim is to answer the question whether the territorial distribution of Pirate electoral support allows this party to participate in governance at the regional level and thus influence the form of regional policy in individual regions. The results of the analysis show that the spatial distribution of Pirates’ electoral support in regional elections differed quite significantly not only from the pattern found in the elections to the Chamber of Deputies of the Czech Parliament and elections to the European Parliament, but also between individual regional elections. This suggests the current lack of anchorage of Pirates’ electoral support in regional politics, but at the same time, it may have its origins in the second-order character of regional elections and the candidacy of many local and regional entities in regional elections. On the other hand, the results of the regional elections in 2020 meant that the Pirates received seats in all regional councils, but especially in nine of the thirteen regions they joined the regional government (similarly to two years earlier when they joined government of capital city of Prague), gaining the opportunity to influence, with regard to its priorities, the form of regional governance in most Czech regions.

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