Abstract Theoretical relationships with crime across cities are explicitly or implicitly assumed to be the same in all places: a one-unit change X leads β Y. But why would we assume impact of unemployment, for example, is wealthy and impoverished neighborhoods? We use local statistical technique, geographically weighted regression, identify property crime. find that theoretical vary city, most ...

Models designed to capture spatially varying processes are now employed extensively in the social and environmental sciences. The main strength of such models is their ability represent relationships that vary across locations through locally parameter estimates. However, local spatial also provide information on nature these estimation a ‘bandwidth’ parameter. This paper examines bandwidth at ...

Poverty is a multidimensional problem faced by all countries in the world. inability of individual or group to meet their basic needs terms expenditure. In poverty problem, there tendency that poor will locations with certain characteristics. This spatial clustering indicates diversity making global regression analysis inappropriate for application. Therefore, purpose this research model percen...

The existence of nonstationarity, or spatial variability in geographical relationships, is a topic that has received some attention in the geographical literature in recent years. Its effect in regression-based spatial interpolation methods, however, remains an open research question. In order to explore this question, the paper describes a general regression model which can be used to derive a...

The air quality in China, particularly the PM2.5 (particles less than 2.5 μm in aerodynamic diameter) level, has become an increasing public concern because of its relation to health risks. The distribution of PM2.5 concentrations has a close relationship with multiple geographic and socioeconomic factors, but the lack of reliable data has been the main obstacle to studying this topic. Based on...

Housing is among the most pressing issues in urban China and has received considerable scholarly attention. Researchers have primarily concentrated on identifying the factors that influence residential property prices and how such mechanisms function. However, few studies have examined the potential factors that influence housing prices from a big data perspective. In this article, we use a big...

BACKGROUND The present research evaluates the possibility of spatial heterogeneity in the effects on neighborhood crime rates of both traditional demographic indicators—immigrant concentration, racial composition, socioeconomic disadvantage, and residential instability—and a contemporary aspect of housing transition—foreclosure—that has garnered significant attention in recent scholarship. OBJE...

BACKGROUND Drug-resistant tuberculosis (DR-TB) is a major public health problem caused by various factors. It is essential to systematically investigate the epidemiological and, in particular, the ecological factors of DR-TB for its prevention and control. Studies of the ecological factors can provide information on etiology, and assist in the effective prevention and control of disease. So it ...

OBJECTIVES Numerous studies have revealed the adverse health effects of acute and chronic exposure to particulate matter less than 10 μm in aerodynamic diameter (PM10). The aim of the present study was to examine the spatial distribution of PM10 concentrations and cardiovascular mortality and to investigate the spatial correlation between PM10 and cardiovascular mortality using spatial scan sta...

Previous studies consistently indicate measurable local associations between alcohol and drug usage and the incidence of violence, which reveal the importance of spatial analysis in the study of alcohol, drugs, and violence. While studies increasingly incorporate spatial correlation among model residuals to improve model performance, many analyses assume associations that are constant across a ...