scholarly journals Testando a hipótese de dependência espacial na taxa de crime dos municípios da Região Sul do Brasil / Testing the space dependence hypothesis on crime rate of the municipalities of the south region of Brazil

2018 ◽  
Vol 8 (1) ◽  
pp. 118-141
Author(s):  
Otoniel Rodrigues dos Anjos Júnior ◽  
Stélio Coêlho Lombardi Filho ◽  
Juliane Da Silva Ciríaco ◽  
Magno Vamberto Batista da Silva
Keyword(s):  
Spatial Data ◽  
Spatial Model ◽  
Crime Rate ◽  
Behavioral Pattern ◽  
Spatial Data Analysis ◽  
The South ◽  
Show Evidence ◽  
Classical Linear Regression ◽  
Space Dependence ◽  
Global And Local

Este artigo tem como objetivo testar a hipótese de dependência espacial na taxa de criminalidade dos municípios da região Sul do Brasil. Para tanto, utilizou-se dados relativos aos homicídios provenientes do Sistema de Informação de Mortalidade (SIM-DATASUS), pertencente ao Ministério da Saúde, e variáveis do DATASUS e do Censo Demográfico. As análises descritivas revelaram que a criminalidade segue um determinado padrão comportamental quanto à escolha dos municípios em que a mesma ocorre. Com base na Análise Exploratória de Dados Espaciais (AEDE), observou-se que tanto o indicador de associação global quanto o local apontam indícios de não aleatoriedade do crime no espaço. A partir desse resultado, estimou-se o Modelo Clássico de Regressão Linear, visando constatar tal dependência e, em seguida, o modelo econométrico-espacial SAR-MQ2E para a obtenção de estimativas mais precisas e robustas. Os resultados do modelo espacial mostraram que a criminalidade sulista está correlacionada ao crime passado, ao desemprego, à densidade demográfica, ao Índice de Desenvolvimento Humano e às diferenças individuais de cada Estado (captadas pela dummies de Estado). AbstractThis paper aims to test the spatial dependence hypothesis on crime rate of the municipalities of the south region of Brazil in the year 2012. To this end, it were collected data from the Mortality Information System (SIM-DATASUS), belonging to the Ministry of Health, together with variables from DATASUS and the Demographic Census. Descriptive analyzes revealed that crime follows a certain behavioral pattern regarding the choice of the municipalities in which it occurs. Based on the Exploratory Spatial Data Analysis (ESDA), it was observed that both the indicator of global and local association show evidence of the non-randomness of crime in space. From this result, it was estimated the Classical Linear Regression Model, aiming to verify such dependency, and then the SAR-MQ2E econometric-spatial model to obtain more accurate and robust estimates. The results of the spatial model showed that southern crime correlates with past crime, unemployment, demographic density, Human Development Index and individual differences in each state (captured by the state dummies).

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.

scholarly journals Analysis on spatial distribution pattern of football fields: A case study in Wuhan, China

2021 ◽  
Vol 293 ◽  
pp. 02051
Author(s):  
Yuwei Wang ◽  
Kaicheng Wu ◽  
Wang Gao
Keyword(s):  
Spatial Data ◽  
Global Scale ◽  
Spatial Data Analysis ◽  
Wuhan City ◽  
The Sustainable Development ◽  
Aggregation Pattern ◽  
Per Capita ◽  
Football Field ◽  
Global And Local

In order to promote the sustainable development of sports facilities, the statistical data of football fields in 13 districts of Wuhan city were selected. Based on geographic information system (GIS) and exploratory spatial data analysis (ESDA) technology, this paper analyzed the global and local autocorrelation of the number of football fields per capita in Wuhan city. The results indicate that: (1) Comparing to the new districts in Wuhan, the number of football fields per capita in the central districts was relatively few. (2) In the global scale, the number of football fields per capita in Wuhan presented a spatial aggregation pattern. (3) In the local scale, the regional discrepancy and spatial clusters were confirmed in the local spatial autocorrelation analysis for football fields in Wuhan. At the same time, the research results could provide reasonable references for the planning of football field facilities.

scholarly journals Assessment of Temperature Variability Effect on Rice Production in Nasarawa State, Nigeria

2020 ◽  
pp. 91-100
Author(s):  
Oladeinde Stephen Olufemi ◽  
Magaji I. Joshua ◽  
Ekpo Abraham Salamatu
Keyword(s):  
Spatial Data ◽  
Negative Impact ◽  
Temperature Variability ◽  
Rice Production ◽  
Spatial Data Analysis ◽  
Effect Of Temperature ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
The South ◽  
Governmental Institutions

The output of cereal farmlands is imperative for sustainable global food security. Quantity of production from cereal croplands are partly a function of climatic elements and are connected to the pulses of climatic variation. Hence, this paper assessed temperature variability effect on rice production in Nasarawa State, Nigeria. Daily maximum and minimum temperature data were obtained from the Nigerian Meteorological Agency and converted into monthly averages while annual rice production data was obtained from the office of Nasarawa State’s Agricultural Development Programme. Acquired data were analysed using Linear Multiple Regression Model, coefficient of variation and spatial data analysis techniques. Although rice production in the State is being affected by the fluctuations in both minimum and maximum monthly temperature, the later poses grave concern for sustainability of rice production with a negative effect size of -3.145 and a coefficient value of -191,324.30 metric tons. This negative impact of maximum temperature fluctuations on rice production indicates that rice production in Nasarawa State is vulnerable to climate variability with increasing maximum temperature. LGAs in the south senatorial district has more favourable locations for rice production in comparison to those in the North and West districts given that less temperature fluctuation was observed in the former. Government and non-governmental institutions as well as individuals planning to establish rice farm project(s) in the study area should consider doing so in the South Senatorial District in order to avoid the adverse effect of temperature variability.

scholarly journals Dependencia espacial de la tasa municipal de desempleo en Andalucía. Un análisis espacial exploratorio

2021 ◽  
Author(s):  
Antonio Jesús Acevedo Blanco ◽  
Violante Martínez Quintana
Keyword(s):  
Data Analysis ◽  
Spatial Data ◽  
Spatial Dependence ◽  
Hot Spots ◽  
Spatial Context ◽  
Spatial Data Analysis ◽  
Exploratory Spatial Data Analysis ◽  
Sociological Research ◽  
Para Determinar ◽  
Global And Local

El presente trabajo examina la dependencia espacial, global y local, de la Tasa Municipal de Desempleo en Andalucía. Aplicando el software Geoda realizamos en primer lugar un ejercicio exploratorio encaminado a identificar los valores atípicos superiores del indicador. Posteriormente se implementan estadísticos propios del Análisis Espacial Exploratorio para determinar la dependencia espacial del desempleo en Andalucía. En la última sección de resultados se identifican los puntos calientes (Hot Spots) de mayor incidencia en la construcción del indicador de autocorrelación espacial. Se concluye tras el examen de resultados en la necesidad de añadir el territorio entre las variables de análisis para el estudio sociológico del paro.The current paper examines the spatial, global and local autocorrelation of the Municipal Unemployment Rate in Andalusia. Applying the Geoda software, firstly, we carried out an exploratory exercise aimed at identifying the superior outliers of the indicator. Later, statistics of the Exploratory Spatial Data Analysis are implemented to determine the spatial dependence of unemployment in Andalusia. In the last section of results, the hot spots with the highest incidence in the construction of the spatial autocorrelation indicator are identified. After examining the results it’s concluded on the need to add the spatial context among the analysis variables for the sociological research of unemployment.

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.

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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