scholarly journals Spatial and Temporal Evaluation of Ecological Footprint Intensity of Jiangsu Province at the County-Level Scale

2020 ◽  
Vol 17 (21) ◽  
pp. 7833
Author(s):  
Decun Wu ◽  
Jinping Liu
Keyword(s):  
Spatial Data ◽  
Ecological Footprint ◽  
Temporal Trends ◽  
Spatial Association ◽  
Jiangsu Province ◽  
Control Measures ◽  
Spatial Data Analysis ◽  
Spatial Distributions ◽  
County Level ◽  
Over Time

Due to the high ecological pressure that exists in the process of rapid economic development in Jiangsu Province, it is necessary to evaluate its ecological footprint intensity (EFI). This article focuses on ecological footprint intensity analysis at the county scale. We used county-level data to evaluate the spatial distributions and temporal trends of the ecological footprint intensity in Jiangsu’s counties from 1995 to 2015. The temporal trends of counties are divided into five types: linear declining type, N-shape type, inverted-N type, U-shape type and inverted-U shape type. It was discovered that the proportions of the carbon footprint intensity were maintained or increased in most counties. Exploratory spatial data analysis shows that there was a certain regularity of the EFI spatial distributions, i.e., a gradient decrease from north to south, and there was a decline in the spatial heterogeneity of EFI in Jiangsu’s counties over time. The global Moran’s index (Moran’s I) and local spatial association index (LISA) are used to analyze both the global and local spatial correlation of EFIs among counties of Jiangsu Province. The high-high and low-low agglomeration effects were the most common, and there were assimilation impacts of counties with strong agglomeration on adjacent units over time. The results implied the utility of differentiated EFI reduction control measures and promotion of low-low agglomeration and suppression of high-high agglomeration in EFI-related ecology policy.

scholarly journals How Far Has China’s Urbanization Gone?

2018 ◽  
Vol 10 (8) ◽  
pp. 2953 ◽  
Author(s):  
Yiping Xiao ◽  
Yan Song ◽  
Xiaodong Wu
Keyword(s):  
Urban Development ◽  
Spatial Autocorrelation ◽  
Spatial Data ◽  
Spatial Association ◽  
Early Years ◽  
Spatial Data Analysis ◽  
Rapid Urbanization ◽  
Urban Rural ◽  
Global Spatial Autocorrelation ◽  
Over Time

China’s rapid urbanization has attracted wide international attention. However, it may not be sustainable. In order to assess it objectively and put forward recommendations for future development, this paper first develops a four-dimensional Urbanization Quality Index using weights calculated by the Deviation Maximization Method for a comprehensive assessment and then reveals the spatial association of China’s urbanization by Exploratory Spatial Data Analysis. The study leads to three major findings. First, the urbanization quality in China has gradually increased over time, but there have been significant differences between regions. Second, the four aspects of urbanization quality have shown the following trends: (i) the quality of urban development has steadily increased; (ii) the sustainability of urban development has shown a downward trend in recent years; (iii) the efficiency of urbanization improved before 2006 but then declined slightly due to capital, land use, and resource efficiency constraints; (IV) the urban–rural integration deteriorated in the early years but then improved over time. Third, although the urbanization quality has a significantly positive global spatial autocorrelation, the local spatial autocorrelation varies between eastern and western regions. Based on these findings, this paper concludes with policy recommendations for improving urbanization quality and its sustainability in China.

scholarly journals SPATIAL STUDY OF INCIDENCE RATES OF OCCUPATIONAL ACCIDENTS IN BRAZIL FROM 2002 TO 2012

2018 ◽  
Vol 36 (4) ◽  
pp. 927
Author(s):  
André Luis Santiago MAIA ◽  
Gecynalda Soares da Silva GOMES ◽  
Isabelle Galdino de ALMEIDA
Keyword(s):  
Spatial Data ◽  
Spatial Association ◽  
Job Creation ◽  
Incidence Rates ◽  
Spatial Data Analysis ◽  
Occupational Accidents ◽  
Exploratory Spatial Data Analysis ◽  
High Incidence ◽  
Random Manner ◽  
Critical Regions

The intensive process of economic growth and job creation in Brazil in the last years is often associated an important dimension where this process is far drop satisfactory: the high incidence rates of occupational accidents. Important instruments can be constructed from the quantitative study considering possible changes caused by economic dynamics over the years. We conducted exploratory spatial data analysis  (ESDA) and Local Indicators of Spatial Association (LISA) to analyze the spatial distribution of this rate in order to identify critical regions in Brazil. Data were extracted from the Brazilian Ministry of Labor and Employment (MTE) and from the Brazilian Ministry of Social Security websites for the years from 2002 to 2012. Results show that the incidence rate of occupational accidents in Brazil is distributed in a geographically non-random manner and municipalities with high rates tends to cluster.

Assessing Spatial Equity: An Evaluation of Measures of Accessibility to Public Playgrounds

1998 ◽  
Vol 30 (4) ◽  
pp. 595-613 ◽  
Author(s):  
E Talen ◽  
L Anselin
Keyword(s):  
Spatial Data ◽  
Empirical Studies ◽  
Spatial Association ◽  
Spatial Data Analysis ◽  
Socioeconomic Indicators ◽  
Model Average ◽  
Urban Service ◽  
Spatial Equity ◽  
Analytical Perspective

Geographical and political research on urban service delivery—who benefits and why—has proliferated during the past two decades. Overall, this literature is not characterized by a particular attention to the importance of method in drawing conclusions about spatial equity based on empirical studies. Specifically, there has been scant interest in the effect of geographic methodology on assessing the relationship between access and socioeconomic characteristics that are spatially defined. In this paper we take a spatial analytical perspective to evaluate the importance of methodology in assessing whether or not, or to what degree the distribution of urban public services is equitable. We approach this issue by means of an empirical case study of the spatial distribution of playgrounds in Tulsa, Oklahoma, relative to that of the targeted constituencies (children) and other socioeconomic indicators. In addition to the ‘traditional’ measure (count of facilities in an areal unit), we consider a potential measure (based on the gravity model), average travel distance, and distance to the nearest playground as indicators of accessibility. We find significant differences between the spatial patterns in these measures that are suggested by local indicators of spatial association and other techniques of exploratory spatial data analysis. The choice of access measure not only implies a particular treatment of spatial externalities but also affects conclusions about the existence of spatial mismatch and inequity.

Analysis on Spatial Difference of the Rural Resident’s per Capita Net Income in Qinhuangdao City Based on ESDA

2014 ◽  
Vol 955-959 ◽  
pp. 3893-3898
Author(s):  
Yu Hong Wu
Keyword(s):  
Spatial Data ◽  
Rural Economy ◽  
Spatial Association ◽  
Spatial Data Analysis ◽  
Moran’S I ◽  
Net Income ◽  
Gis Technology ◽  
Moran's I ◽  
Per Capita ◽  
Global Moran’S I

Based on the exploratory spatial data analysis (ESDA) and GIS technology, the spatial differences of the rural economic development level of Qinhuangdao city was investigated by adopting the rural resident’s per capita net income data at town level in Qinhuangdao city from 2007 to 2011. The results of global Moran’s I value for rural resident’s per capita net income at town level showed that there existed significant positive spatial autocorrelation and significant spatial aggregation in the spatial distribution of rural resident’s per capita net income. However, the global Moran’s I value showed a decreasing trend during 2007 to 2011, indicating an enlarged spatial disparity of rural economy at the town level. The results of the Moran scatter plots and LISA cluster maps of 2007 and 2011 showed that most of towns were characterized by positive local spatial association , ie. They were located in the HH or the LL quadrant. The significant HH towns were mostly to be found in the south of Qinhuangdao city, Haigang district, Changli county, Lulong county. The significant LL towns were mostly to be found in the Qinglong county, north of Qinhuangdao city.

scholarly journals Metropolitan urban hotspots of chronic sleep deprivation: evidence from a community health survey in Gyeongbuk Province, South Korea

2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Sun-Bi Um ◽  
Jung-Sup Um
Keyword(s):  
South Korea ◽  
Sleep Deprivation ◽  
Community Health ◽  
Health Survey ◽  
Spatial Data ◽  
Spatial Association ◽  
Spatial Data Analysis ◽  
Community Health Survey ◽  
Chronic Sleep Deprivation ◽  
Chronic Sleep

The geographic concentration of chronic sleep deprivation (CSD) remains largely unexplored. This paper examined the community-specific spatial pattern of the prevalence of CSD and the presence of clustered spatial hotspots among the Korean elderly population in Gyeongbuk Province, South Korea, revealing CSD hotspots and underscoring the importance of geography-focused prevention strategies. The study analysed cross-sectional data collected from 9847 elderly individuals aged 60 years and older who participated in a Korean Community Health Survey conducted in 2012. To assess the level of spatial dependence, an exploratory spatial data analysis was conducted using Global Moran’s I statistic and the local indicator of spatial association. The results revealed marked geographic variations in CSD prevalence ranging from 33.4 to 73.4%, with higher values in the metropolitan urban areas and lower in the rural areas. Almost half of the community residents [both men (44.1%) and women (53.5%)] slept 6 h or less per 24 h. The average CSD prevalence (53.6% men and 65.1% women) in the hotspots was about 13.0% higher than that in other areas (42.6% for men and 51.1% for women). To our knowledge, this is the first study to generate a CSD hotspot map that includes data on sleep deprivation across metropolitan district levels. This study demonstrates that not only is sleep deprivation distributed differentially across communities but these differences may be explained by urbanisation.

Exploring regional and urban clusters and patterns in Europe using satellite observed lighting

2018 ◽  
Vol 47 (4) ◽  
pp. 553-568 ◽  
Author(s):  
Vassilis Tselios ◽  
Demetris Stathakis
Keyword(s):  
Spatial Data ◽  
Economic Activity ◽  
Urban Areas ◽  
Regional Analysis ◽  
Spatial Association ◽  
Cell System ◽  
Spatial Data Analysis ◽  
Urban Structure ◽  
Activity Levels ◽  
Nighttime Lights

We explore regional and urban clusters and patterns in Europe by using satellite images of nighttime lights and by employing Exploratory Spatial Data Analysis. We map Defense Meteorological Satellite Program nighttime lights data onto the nomenclature of territorial units for statistics III, Local Administrative Units II and pixel (i.e. 1 km2 grid cell system of Europe) level and apply global and local statistics of spatial association. Under the assumption that nighttime light data are a good proxy for economic activity, the analysis at regional level shows that the regions of global cities and megacities and their surrounding areas are hot spots of high economic activity levels. The regional analysis also reveals the polycentric hierarchical structure of Europe. Using the case studies of the regions of London and Île -de -France, the analysis at the urban level reveals the different urban structure of these two global regions and identifies the functional urban areas of London and Paris.

A Spatial Analysis of Breastfeeding and Breastfeeding Support in the United States: The Leaders and Laggards Landscape

2019 ◽  
Vol 35 (4) ◽  
pp. 790-800 ◽  
Author(s):  
Tony H. Grubesic ◽  
Kelly M. Durbin
Keyword(s):  
United States ◽  
Geographic Variation ◽  
Spatial Data ◽  
Spatial Association ◽  
The United States ◽  
Spatial Data Analysis ◽  
Breastfeeding Initiation ◽  
Breastfeeding Support ◽  
Geographic Variations ◽  
Breastfeeding Practices

Background: To better track progress in achieving the Healthy People 2020 goals, the Centers for Disease Control and Prevention (CDC) publishes an annual Breastfeeding Report Card (BRC) that represents a compilation of data on breastfeeding practices in all states. With data drawn from the CDC National Immunization Survey, the BRC provides an especially valuable source of information about geographic trends in breastfeeding and related support activities. Research aim: This study aimed to identify important geographic trends in both breastfeeding practices and support structures in the United States, highlighting their spatial disparities. Methods: Exploratory spatial data analysis, including local indicators of spatial association, is combined with spatial regression models to highlight geographic variations in breastfeeding practices and support. Results: Geographic variation in both breastfeeding practices and allied support exists within the United States. Geographic hot spots of breastfeeding are found in the western and northeastern sections of the United States, and cool spots are located primarily in the Southeast. Regression results suggested that unemployment and demographic diversity are negatively associated with breastfeeding rates, whereas higher education and the presence of International Board Certified Lactation Consultants® (IBCLCs®) are positively connected to persistent breastfeeding practices. Further, although the availability of professional support (IBCLC) strengthened nationwide between 2011 and 2016, the availability of mother-to-mother support (La Leche League) softened. Conclusion: Although breastfeeding initiation rates continue to increase in the United States, rates of exclusive breastfeeding at 3 and 6 months remain low, displaying significant geographic variation. The ability to pinpoint lagging regions can help to efficiently allocate additional breastfeeding support resources and interventions.

scholarly journals Spatial Spillovers and Innovation Activity in European Regions

2005 ◽  
Vol 37 (10) ◽  
pp. 1793-1812 ◽  
Author(s):  
Rosina Moreno ◽  
Raffaele Paci ◽  
Stefano Usai
Keyword(s):  
Spatial Econometrics ◽  
Spatial Data ◽  
Spatial Association ◽  
Innovative Activity ◽  
Spatial Data Analysis ◽  
Innovation Activity ◽  
European Patent ◽  
European Regions ◽  
Spatial Spillovers ◽  
Set Up

This paper explores the spatial distribution of innovative activity and the role of technological spillovers in the process of knowledge creation and diffusion across 175 regions of seventeen countries in Europe (the fifteen members of the pre-2004 European Union plus Switzerland and Norway). The analysis is based on a databank set up by CRENoS on regional patenting at the European Patent Office, spanning 1978–2001 and classified by ISIC sectors. The first step is an exploratory spatial data analysis of the dissemination of innovative activity in Europe. The goal of the rest of the paper is to analyse to what extent externalities that cross regional boundaries can explain the spatial association process detected in the distribution of innovative activity in the European regions. The framework given by the knowledge-production function together with the use of spatial econometrics techniques allow us to look for insights on the mechanics of knowledge interdependences across regions, which are shown to exist. Empirical results point to the relevance of internal regional factors (R&D expenditure and agglomeration economies). Moreover, the production of knowledge appears also to be affected by spatial spillovers due to innovative activity (both patenting and R&D) performed in other regions. Additional results show that spillovers are mostly constrained by national borders within less than 250 km, and that technological similarity between regions also matters.

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