Spatial–Temporal Characteristics and Determinants of Digital Divide in China: A Multivariate Spatial Analysis

The digital divide has loomed as a sustainable development issue for over two decades and there has been much research in terms of efforts to measure the digital divide from different dimensions and scales. Drawing on spatial agglomeration analysis and multiple linear regression, this paper aims to reveal the spatiotemporal pattern of the prefectural digital divide in China and its determinants. The results show that there is a significant prefectural digital divide in China that is characterized by a decline of ICT development index (IDI) values from the east to the west as well as from core cities to more peripheral ones. Cities with high IDI values are mainly concentrated in large metropolitan areas in eastern China, whereas cities with low values tend to concentrate in poverty stricken regions in central and western China. However, the digital divide has been characterized by a reduction from 2001 to 2015. The results also show that both economic and educational factors have significant influences on the prefectural digital divide in China. During the early stages, the percentage of university students, urban residential income, and the urbanization rate were key factors. However, after 2010, the adult literacy rate and rural residential income determined the digital divide.

Urban-rural gradient detection using multivariate spatial analysis and landscape metrics

The gradient approach allows for an innovative representation of landscape composition and configuration not presupposing spatial discontinuities typical of the conventional methods of analysis. Also the urban-rural dichotomy can be better understood through a continuous landscape gradient whose characterization changes accordingly to natural and anthropic variables taken into account and to the spatio-temporal scale adopted for the study. The research was aimed at the analysis of an urban-rural gradient within a study area located in central Italy, using spatial indicators associated with urbanization, agriculture and natural elements. A multivariate spatial analysis (MSA) of such indicators enabled the identification of urban, agricultural and natural dominated areas, as well as specific landscape transitions where the most relevant relationships between agriculture and other landscape components were detected. Landscapes derived from MSA were studied by a set of key landscape pattern metrics within a framework oriented to the structural characterization of the whole urban-rural gradient. The results showed two distinct sub-gradients: one urban-agricultural and one agricultural-natural, both characterized by different fringe areas. This application highlighted how the proposed methodology can represent a reliable approach supporting modern landscape planning and management.

A multivariate spatial analysis of vowel formants in American English

This paper presents the results of a multivariate spatial analysis of thirty-eight vowel formant variables measured in 236 cities from across the contiguous United States, based on the acoustic data from the Atlas of North American English. The results of the analysis both confirm and challenge the results of the Atlas. Most notably, while the analysis identifies similar patterns as the Atlas in the West and the Southeast, the analysis finds that the Midwest and the Northeast are distinct dialect regions that are considerably stronger than the traditional Midland dialect region identified in the Atlas. The analysis also finds evidence that a vowel shift is actively shaping the language of the Western United States.