Suchergebnisse

A large body of research has found that highways and airports have played important roles in promoting development and population growth (or decline). However, little attention has been paid to the possible spatial variation of their effects on population change. This study uses data related to population change in 1980–90 at the minor civil division level in Wisconsin to investigate the effects of highway and airport accessibility and accessibility improvements on population change across rural, suburban and urban areas. The results show that the effects vary across the three area types. In rural areas, highway improvement and airport accessibility promote population growth; in suburban areas, airport accessibility promotes population growth but highway accessibility facilitates population flows; and in urban areas, neither highways nor airports have a statistically significant effect on population change. The findings have important implications for local transport planning, as highways and airports play different roles along the rural–urban continuum.

Introduction -- Exploratory spatial data analysis -- Models dealing with spatial dependence -- Advanced models dealing with spatial dependence -- Models dealing with spatial heterogeneity -- Models dealing with both spatial dependence and spatial heterogeneity -- Advanced spatial regression models -- Practical considerations for spatial data analysis.

Population projection is essential to governments, businesses, and research communities for many purposes. Although projection performance is often evaluated, we know very little about what factors affect projection accuracy. It is important to understand these factors in order to utilize the projections knowledgeably. This study fills this gap in the literature by comprehensively investigating the possible factors associated with population projection accuracy in 2010 for the continental US counties. The results indicate that the counties whose populations are more predictable tend to be desirable places—places with abundant employment opportunities, reliable public transportation infrastructure, easy access to work, and/or high land development potential; their neighboring counties tend to have a well-educated population and a higher income level. Also, projection accuracy is highly spatially associated. The findings provide important insights for population projection users to understand the characteristics of counties and their neighboring counties associated with their projection accuracy.

The past century has witnessed rapidly increasing population-land conflicts due to exponential population growth and its many consequences. Although the measures of population-land conflicts are many, there lacks a model that appropriately considers both the social and physical contexts of population-land conflicts. In this study we introduce the concept of population stress, which identifies areas with populations growing faster than the lands available for sustainable development. Specifically, population stress areas are identified by comparing population growth and land development as measured by land developability in the contiguous United States from 2001 to 2011. Our approach is based on a combination of spatial multicriteria analysis, zonal statistics, and spatiotemporal modeling. We found that the population growth of a county is associated with the decrease of land developability, along with the spatial influences of surrounding counties. The Midwest and the traditional "Deep South" counties would have less population stress with future land development, whereas the Southeast Coast, Washington State, Northern Texas, and the Southwest would face more stress due to population growth that is faster than the loss of suitable lands for development. The factors contributing to population stress may differ from place to place. Our population stress concept is useful and innovative for understanding population stress due to land development and can be applied to other regions as well as global research. It can act as a basis towards developing coherent sustainable land use policies. Coordination among local governments and across different levels of governments in the twenty-first century is a must for effective land use planning.

Population growth (or decline) is influenced by many factors that fall into the broad realms of demographic characteristics, socioeconomic conditions, transportation infrastructure, natural amenities, and land use and development across space and time. This paper adopts an integrated spatial regression approach to investigate the spatial and temporal variations of these factors' effects on population change. Specifically, we conduct the analysis at the minor civil division level in Wisconsin, USA, from 1970 to 2000. The results suggest that the factors have varying effects on population change over time and across rural, suburban, and urban areas. Their effects depend upon the general trend of population redistribution processes, local dynamics, and areal characteristics. Overall, a systematic examination of population change should consider a variety of factors, temporal and spatial variation of their effects, and spatial spillover effects. The examination should have the flexibility to identify and incorporate influential factors at a given point in time and space, not to adhere to a single set of drivers in all circumstances. The findings have important implications for population predictions used for local and regional planning.