Multivariate spatial analysis for the identification of criticalities and of the subtended causes in river ecosystems

2019 ◽  
Vol 27 (25) ◽  
pp. 30969-30976 ◽  
Author(s):  
Alessandro Bellino ◽  
Anna Alfani ◽  
Laura De Riso ◽  
Daniela Baldantoni
Keyword(s):  
Spatial Analysis ◽  
River Ecosystems ◽  
Multivariate Spatial Analysis

scholarly journals A multivariate spatial analysis of vowel formants in American English

2013 ◽  
Vol 1 (1) ◽  
pp. 31-51 ◽  
Author(s):  
Jack Grieve ◽  
Dirk Speelman ◽  
Dirk Geeraerts
Keyword(s):  
United States ◽  
Spatial Analysis ◽  
American English ◽  
Western United States ◽  
The West ◽  
Acoustic Data ◽  
Vowel Formant ◽  
Multivariate Spatial Analysis ◽  
Vowel Formants ◽  
Vowel Shift

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.

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

2013 ◽  
Vol 44 (2s) ◽  
Author(s):  
Marco Vizzari ◽  
Maurizia Sigura
Keyword(s):  
Spatial Analysis ◽  
Landscape Planning ◽  
Central Italy ◽  
Landscape Composition ◽  
Landscape Pattern Metrics ◽  
Multivariate Spatial Analysis ◽  
Urban Rural ◽  
Spatio Temporal ◽  
Landscape Gradient ◽  
Modern Landscape

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.

Crime Risk Maps: A Multivariate Spatial Analysis of Crime Data

2018 ◽  
Vol 51 (4) ◽  
pp. 475-499 ◽  
Author(s):  
Jihoon Chung ◽  
Heeyoung Kim
Keyword(s):  
Spatial Analysis ◽  
Crime Data ◽  
Multivariate Spatial Analysis ◽  
Risk Maps ◽  
Crime Risk ◽  
Spatial Analysis Of Crime
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