Geographical Analysis of Foreign Immigration and Spatial Patterns in Urban Areas: Density Estimation and Spatial Segregation

2008 ◽  
pp. 459-474 ◽  
Author(s):  
Giuseppe Borruso
Keyword(s):  
Density Estimation ◽  
Spatial Patterns ◽  
Urban Areas ◽  
Spatial Segregation ◽  
Geographical Analysis

scholarly journals Back to the Countryside: Rural Development and the Spatial Patterns of Population Migration in Zhejiang, China

Agriculture ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 788
Author(s):  
Weiming Tong ◽  
Kevin Lo
Keyword(s):  
Rural Development ◽  
Spatial Patterns ◽  
Rural Areas ◽  
Return Migration ◽  
Urban Areas ◽  
Population Migration ◽  
Dominant Form ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Level Data

This study examines how rural development in China shapes new trends in population migration. Using first-hand, village-level data from Zhejiang—an economically developed province in China—we investigated the patterns and influencing factors of population migration between rural and urban areas. We conceptualized three types of migration in rural areas: rural out-migration, rural in-migration, and rural return-migration. First-hand data were collected from 347 villages. The results show that although rural out-migration remains the dominant form of migration, rural in-migration and return-migration are also common, and the latter two are positively correlated. Further, we found evidence to support the conclusion that rural economic, social, and spatial development encourages rural in-migration and return-migration but does not have a significant impact on rural out-migration. Therefore, it is foreseeable that rural in-migration and return-migration will become increasingly common in China.

scholarly journals Geovisualization and Spatial Analysis of Infant Mortality and Preterm Birth in Ohio, 2008-2015: Opportunities to Enhance Spatial Thinking

2020 ◽  
Vol 135 (4) ◽  
pp. 472-482
Author(s):  
Elisabeth Dowling Root ◽  
Emelie D. Bailey ◽  
Tyler Gorham ◽  
Christopher Browning ◽  
Chi Song ◽  
...  
Keyword(s):  
Public Health ◽  
Preterm Birth ◽  
Spatial Analysis ◽  
Infant Mortality ◽  
Spatial Patterns ◽  
Urban Areas ◽  
Vital Statistics ◽  
Infant Mortality Rate ◽  
Spatial Inequalities ◽  
Geographic Clustering

Objectives Geovisualization and spatial analysis are valuable tools for exploring and evaluating the complex social, economic, and environmental interactions that lead to spatial inequalities in health. The objective of this study was to describe spatial patterns of infant mortality and preterm birth in Ohio by using interactive mapping and spatial analysis. Methods We conducted a retrospective cohort study using Ohio vital statistics records from 2008-2015. We geocoded live births and infant deaths by using residential address at birth. We used multivariable logistic regression to adjust spatial and space–time cluster analyses that examined the geographic clustering of infant mortality and preterm birth and changes in spatial distribution over time. Results The overall infant mortality rate in Ohio during the study period was 6.55 per 1000 births; of 1 097 507 births, 10.3% (n = 112 552) were preterm. We found significant geographic clustering of both infant mortality and preterm birth centered on large urban areas. However, when known demographic risk factors were taken into account, urban clusters disappeared and, for preterm birth, new rural clusters appeared. Conclusions Although many public health agencies have the capacity to create maps of health outcomes, complex spatial analysis and geovisualization techniques are still challenging for public health practitioners to use and understand. We found that actively engaging policymakers in reviewing results of the cluster analysis improved understanding of the processes driving spatial patterns of birth outcomes in the state.

scholarly journals Impacts of Spatial Patterns of Rural and Exurban Residential Development on Agricultural Trends in the Intermountain West

SAGE Open ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 215824401987103
Author(s):  
Saleh Ahmed ◽  
Douglas Jackson-Smith
Keyword(s):  
Spatial Patterns ◽  
Urban Areas ◽  
Growth Management ◽  
Residential Development ◽  
Agricultural Activity ◽  
County Level ◽  
Intermountain West ◽  
Management Tools ◽  
Spatial Dependencies ◽  
Agricultural Trends

In recent years, counties in the Intermountain West (Colorado, Idaho, Montana, Wyoming, and Utah) have experienced rapid population growth and housing development, and much of this growth is occurring outside of urban areas. Residential development often has negative impacts on farmlands, farm viability, and environmental services provided by working landscapes. We used county-level data to identify the association between the intensity and spatial patterns of residential settlement and trends in selected farm outcomes between 1997 and 2012 in the region. Results demonstrate that accounting for the spatial pattern or degree of fragmentation and clustering of rural and exurban residential development improves our ability to explain variation in county-level agricultural trends. We also found evidence of significant spatial dependencies among the counties in this region, which suggests that trends in one county are affected by development and agricultural activity in neighboring counties. Findings suggest that efforts to protect farming using growth management tools can work, but should focus on separation of agriculture and potentially conflicting land uses.

scholarly journals A Study on the GIS Professional (GISP) Certification Program in the U.S.

2020 ◽  
Vol 9 (9) ◽  
pp. 523
Author(s):  
Dapeng Li ◽  
Yingru Li ◽  
Quynh C. Nguyen ◽  
Laura K. Siebeneck
Keyword(s):  
New York ◽  
Spatial Patterns ◽  
Urban Areas ◽  
The United States ◽  
Washington Dc ◽  
Certification Program ◽  
Managerial Role ◽  
Current State ◽  
Shed Light ◽  
The U.S

This study examines the characteristics of the members in the most popular Geographic Information Systems (GIS) Professional (GISP) certification program in the United States as well as the spatial patterns of the certified GISPs. The results show that the majority of GISPs (97.3%) are located in urban areas. About 75% of the GISPs are male. Among all the GISPs, 3971 GISPs (43.3%) play a managerial role, while 4983 individuals (54.5%) assume a non-administrative role. Among the GISPs with a non-administrative role, 348 GISPs (7%) fall within the GIS Developer group, 3392 GISPs (68%) belong to the GIS Analyst group, and 1243 GISPs (25%) play other roles. Additionally, in our analysis of spatial patterns, we identified two hotspots and two coldspots. The first hotspot is centered around Idaho and Wyoming, while the second hotspot includes Virginia, Washington DC, and Maryland. One coldspot is along Iowa, Missouri, Arkansas, and Louisiana in the central U.S., while the other coldspot includes states such as Connecticut, New Jersey, and New York on the east coast. The information presented in this study can help GIS educators and practitioners develop a better understanding of the current state of this certification program in the U.S and shed light on how to further improve the GISP certification program.

scholarly journals Catchment Area of Park-and-Ride and Kiss-and-Ride nearby Citayam and Bojonggede Railway Station

2021 ◽  
Vol 940 (1) ◽  
pp. 012009
Author(s):  
M H Bassayev ◽  
W Sumadio
Keyword(s):  
Spatial Patterns ◽  
Urban Areas ◽  
Catchment Area ◽  
Road Network ◽  
Vehicle Speed ◽  
Network Characteristics ◽  
Park And Ride ◽  
The Difference ◽  
The Cost ◽  
Local Road

Abstract Rail-based transportation, namely trains, has an important role for communities in sub-urban areas. By using the train, communities no longer need to use their vehicles. They can change modes with two choice of ways to get to the station, park their personal vehicle or by using shuttle transportation. The concepts of the two-ways is a form of implementation of park-and-ride and kiss-and-ride. This study aims to identify the reasons why KRL users choose park-and-ride or kiss-and-ride facilities and the user spatial patterns of these facilities. The analysis uses the E2-SFCA (Enhanced 2-Step Floating Catchment Area) method by calculating the distance and ratio of station users and then produces an accessibility value. The results of the analysis that have been carried out indicate that the majority of park-and-ride users are spread out in zone 2 and kiss-and-ride users are spread out in zone 1. The catchment area from both stations are predominantly from areas with local road network characteristics. This road network has a high density but limited vehicle speed. The cost and origin of the distance from the place of residence affect the difference in the catchment area of the KRL station.

scholarly journals Are Metropolitan Areas Primed for Success? A Prosperity Risk Index for Evaluating Economic Development Patterns

2020 ◽  
Vol 5 (3) ◽  
pp. 323-337
Author(s):  
Richard Sadler ◽  
Dayne Walling ◽  
Zac Buchalski ◽  
Alan Harris
Keyword(s):  
Economic Development ◽  
Spatial Patterns ◽  
Urban Areas ◽  
Regional Differences ◽  
Metropolitan Areas ◽  
Local Economic Development ◽  
Risk Index ◽  
Population Characteristics ◽  
Development Theory ◽  
Regional Dynamics

Urban areas differ greatly in their exposure to economic change, their trajectory toward recovery and growth, and the extent to which development and equity are paired. Some of this differentiation can be explained by regional dynamics, policies, and migration flows that influence the composition of economic activity, land use, and population characteristics. Simultaneously, the fortunes of center cities are known to often correlate with metropolitan characteristics, yet the interaction of socio-spatial conditions with multi-level governance and development processes—particularly with respect to how prosperity is shared across municipal lines and is distributed among communities—is under-researched. In this article, we use a GIS-based and quantitative approach to characterize such patterns and evaluate regional differences among 117 mid-sized metropolitan areas in the Eastern US with a population between 250,000 and 2,500,000. Our analysis rests on initial GIS-based inquiries to define city, urbanized area, county, and core-based statistical area-level measures of municipal fragmentation, geographic sprawl, racial segregation, economic inequality, and overall poverty. These five characteristics are combined to propose a prosperity risk index for each region. Further, indicators of economic performance such as job and population growth are inverted to create an economic vulnerability index. An interaction model is run to determine relationships among the indices to highlight both the regional differences in these characteristics that became noticeably significant in the analysis and the linkages of spatial patterns of economic growth and social equity. Analyzing these multi-scalar regional dynamics illuminates the socio-spatial patterns that deserve attention in urban economic development theory and, subsequently, offers a framework for evaluating public policy and development practices. We likewise offer two comparisons of outliers as a means of illustrating potential directions urban areas can take toward economic development. These findings are valuable for local economic development practitioners who may be seeking further contextual/comparative information on urban regions, or for others interested in understanding the dynamics behind urban planning that may drive regional competitiveness and prosperity.

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