Univariate Spatial Autocorrelation Research Articles

Accessibility and Older and Foreign Populations: Exploring Local Spatial Heterogeneities across Italy

The interplay between accessibility and population change is a relatively new subject in Italian academic research. Along with social and economic factors such as regional economic prosperity, the ease of movement inside and outside an area can play a pivotal role in shaping population dynamics. This study seeks to explore the spatial distribution and spatial relationships of three indicators, including one related to real accessibility (RAI) and two others related, respectively, to the shares of the older population (SOP) and of the foreign population (SFP). An exploratory spatial data analysis is, therefore, conducted at the local level using Italian municipalities as the statistical units for the empirical analysis. Local univariate spatial autocorrelation analysis is used together with a regression analysis based on ordinary least squares (OLS) and geographically weighted regression (GWR) models. The results provide valuable insights into the local heterogeneity that characterizes the distribution of each indicator and the local relationship between them, highlighting the importance of thinking locally in quantitative social sciences.

Spatial autocorrelation and spatial heterogeneity of underground parking space development in Chinese megacities based on multisource open data

Underground parking is prevalent in high-density megacities. Understanding the use patterns of underground parking spaces (UPSs) is important for sustainable and resilient urban development. As such, in this study, we employed multisource open data to investigate the spatial autocorrelation and spatial heterogeneity of the UPSs in seven representative Chinese megacities, determining the spatial distribution pattern of and forces driving UPS development. We used the underground parking ratio (UPR) and underground parking density (UPD) at the subdistrict level as critical indicators of UPS use. We found that the UPSs tend to be centrally clustered, whereas the UPR is high in the urban periphery. Both UPR and UPD showed positive univariate spatial autocorrelation, with UPD being much more spatially autocorrelated. The results of univariate spatial autocorrelation revealed the spatial mismatch between UPR and UPD, being high-low in the urban periphery and low-high in the urban centre, respectively. The results of spatial heterogeneity analysis indicated that urban function and land development intensity are common drivers of both UPR and UPD, and socioeconomic conditions are the specific drivers of UPD. Although traffic factors did not have a predominant influence on UPSs, they substantially enhanced the effects when integrated with other factors.

Multi-scale spatial analysis of satellite-retrieved surface evapotranspiration in Beijing, a rapidly urbanizing region under continental monsoon climate.

As one of the important components of hydrological cycle, evapotranspiration spatial distribution is of great significance to regional water resources planning and rational utilization. This research used Surface Energy Balance System model to estimate the daily evapotranspiration (ET) in Beijing based on Landsat 8 observations. Results showed that the daily ET in Beijing ranged from 3.469 to 5.474mm/day. ET is known to decrease with the increase of land surface temperature (LST) and to increase with the increase of Normalized Difference Vegetation Index (NDVI). NDVI primarily decreased from the northwest to the southeast. When the NDVI value was 0.4-0.6, the average ET peaked at 4.88mm/day, and then slightly decreased by 3.7%. The coefficient of determination of NDVI (0.95) was much greater than that of LST (0.30) upon linear fitting, showing LST was not the main factor controlling ET in Beijing. In contrast to the linear fitting results, the spatial correlation between LST and ET is more significant than that between NDVI and ET in the global bivariate spatial analysis, where the absolute value of global bivariate Moran's I of LST (0.51) was higher than that of NDVI (0.21) at a resolution of 150m. And the univariate spatial autocorrelation indices of LST, ET, and NDVI equaled 0.84, 0.65, and 0.51, respectively. Furthermore, the complex spatial distribution pattern of variables could significantly affect the correlation analysis results. Local bivariate spatial analysis showed that over 60% of the Beijing area had a significant correlation, of which the negative correlation area of LST accounted for about 85%, and the positive correlation area of NDVI accounted for 74%. By improving the correlation analysis accuracy, the regional conditions for the establishment of correlation analysis results were clarified from the overall correlation analysis results.

A comparison of the geographic patterns of HIV prevalence and hurricane events in the United States

ObjectivesPrevious research has documented the adverse association between hurricanes and HIV health outcomes; however, no research has been conducted to examine whether there is spatial overlap between hurricane events and the epidemiology of HIV in the United States. The objectives of this study were to assess the geographic distributions of and spatial autocorrelation between HIV prevalence and the occurrences of hurricanes in the US. Study designThis was a cross-sectional study. MethodsData on HIV prevalence rates were obtained from the Centers for Disease Control and Prevention, and data on US hurricane events were obtained from the National Oceanic and Atmospheric Administration. ArcGIS, version 10.6, was used for mapping HIV prevalence rates and occurrences of hurricane events, and GeoDa, version 1.12, was used to conduct all univariate and bivariate spatial autocorrelation analyses. ResultsHIV and hurricanes primarily affected states located in the south and along the Gulf Coast. Major hurricanes were reported among these regions also. States recording 20 or more hurricanes between 1851 and 2017 had an average HIV prevalence rate of 453.2 cases per 100,000 in 2016. States recording five or more major hurricanes between 1851 and 2017 had an average HIV prevalence rate of 421.8 cases per 100,000 in 2016. Regarding univariate spatial autocorrelation, HIV prevalence was clustered (Moran's I: 0.1913; pseudo P-value: 0.003). Hurricane events were also clustered (Moran's I: 0.2826; pseudo P-value: 0.004), as were major hurricanes (Moran's I: 0.1982; pseudo P-value: 0.009). There was statistically significant bivariate spatial autocorrelation between neither HIV and hurricanes nor HIV and major hurricanes. ConclusionThe epidemiology of HIV prevalence and hurricane events has overlapping geographic patterns. This may have implications for hurricane readiness and recovery planning with respect to people living with HIV.

Analysing Spatial and Statistical Dependencies of Deforestation Affected by Residential Growth: Gorganrood Basin, Northeast Iran

AbstractThis study aimed to examine deforestation and residential growth trends and their spatial dependencies from 1972 to 2010 in Northeast of Iran. First, change rates of forests and residential areas were mapped using Landsat satellite images in 1972–1987, 1987–2000 and 2000–2010. Then, the forest change patterns were interpreted using univariate local Moran's I (local univariate spatial autocorrelation), and the spatial autocorrelation between deforestation and residential growth was tested through bivariate local Moran's I (bivariate local spatial autocorrelation). Furthermore, the spatial relationships between deforestation and residential growth rates were quantified by ordinary least squares, spatial lag (SL) and geographically weighted regression. Results indicated that approximately 25% of forests have been converted to other land‐use types in the span of 38 years, since 1972. Local univariate spatial autocorrelation maps showed that significant values of high–high cluster scattered in all locations in the first span, in the east and south aspects in the second duration, and in the eastern part in the third span. Bivariate local spatial autocorrelation indicated a meaningful Moran's I values of −0·12, −0·26 and −0·20 between deforestation and residential growth, chronologically. Analyses of spatial regression models showed that geographically weighted regression performed better than SL and ordinary least squares in the first (R2 = 0·315, AIC = 6,160) and third periods (R2 = 0·27, AIC = 6,351), whereas, the validity of SL was the highest in the second period (R2 = 0·36, AIC = 6,288). However, the overall trends of deforestation and residential growth have decreased, but the rate of deforestation induced by residential growth is still significant. Spatial exploration of residential growth in deforestation leads to determine its influences in local scale for better conservation of these valuable natural resources. Copyright © 2017 John Wiley & Sons, Ltd.

Spatial distribution of Canola culture in the State of Paraná (Brazil) between the agricultural years of 2005 and 2009

AbstractS.C. Wrublack, V.H.R. Prudente, E. Mercante, and S.R.M. Coelho. 2013. Spatial distribution of Canola culture in the State of Parana (Brazil) between the agricultural years of 2005 and 2009. Cien. Inv. Agr. 40(3): 513-521. There are a number of crops that are viable for small farms. To increase our knowledge of the occurrence of canola cultivation in the State of Parana, the present study aimed to identify the areas sown with canola (ha) and to examine canola production (t) during the growing seasons of 2005 to 2009. The methodology involved a literature review and analysis of spatial data from the Secretaria da Agricultura e do Abastecimento do Parana (SEAB/PR). We used the software ArcGis 9.3 for elaboration of thematic maps of variables as well as the free software GeoDa 0.9.5-i. The identification of spatial dependence was conducted through global univariate spatial autocorrelation using Moran’s Index ( I ) statistic and, at a local level, using Local Indicators of Spatial Association (LISA). Spatial correlation was detected in the data on the area sown (ha) and production (t) for the canola crop. The results also indicated the possibility of expansion of cultivated areas in the State of Parana, in addition to providing interesting options regarding the composition of systems of crop rotation and soil cover. The application of the spatial statistical area contributed to the recognition of the evolution of the canola crop in the State of Parana, based on the spatialization of production and sown areas in its municipalities. It is evident that most municipalities show no significant pattern, demonstrating the potential for the expansion of sown areas in the State. For the High-High standard, it was noted that the municipalities were grouped mainly in the western and south-central State of Parana.

Investigating the spatial pattern of mortality in Jordan-2008

Neighbourhood researches have been growing over the past two decades across the social sciences particularly in the area of public health. Many studies had examined the existence of spatial pattern of mortality in many developing and developed countries in improving the health status and reducing the variation in mortality between regions of such country. Some of these studies found spatial pattern for mortality and some were not using different statistical techniques and geographical mapping. Question was raised whether the spatial pattern of mortality was existed in Jordan? The objective was to investigate the spatial structure of mortality across different areas (governorates) of the country to provide implications for policy makers, investigating the hot spots of mortality, showing a visual picture of health status and reduce the variation in mortality as possible as can by showing the global clustering and local clusters for mortality. The data collected for 12 governorates based on census conducted in 2008. Mapping was used as a first step to conduct visual inspection based on the quantified gradients for mortality using quartiles. Two statistics of univariate spatial autocorrelation based on sharing boundary neighbours, known as global and local Moran's I, were carried out for examining the global clustering and local clusters respectively. All-cause standardized mortality ratios (SMR) have calculated for each governorate. Global Moran's I was found 0.18, z=1.73 with p value=0.08 and permutation p -value=0.02. Out of 12 governorates, three governorates were found as local clusters in mortality as shown from their local Moran's i I values 23 5 ( 0.71, 0.032 ; 0.18, 0.096 ; and 0.38, 0.023)

A Model of Cultural Evolution of Chaffinch Song Derived with the Meme Concept

The cultural evolution of song in populations of chaffinches from New Zealand was analyzed using the meme concept. Songs were broken down into their constituent memes (individual syllable types, their variants, or groups of linked syllables), and patterns of geographical variation for memes of different length were assessed. Multivariate spatial-autocorrelation analyses revealed a clinal pattern of variation, with close populations sharing more memes than would be expected at random and the inverse for populations that are far apart. Univariate spatial autocorrelation of syllable variants showed a random pattern attributable to high levels of mutation and random drift at this level. Syllable types, by contrast, are significantly correlated in their frequencies across populations and therefore have similar patterns. This is probably due to a major migrational event during colonization. Using Slatkin's method of rare alleles, we estimated that approximately 10 syllables per generation enter each population as a result of immigration. Rates of mutation vary for different units of cultural transmission, being highest for larger memes of sets of syllables and lowest for single syllable types. Approximately 20-30 new variants of syllables arise in a population each generation. Overall, the rate of cultural mutation and drift of apparently neutral song memes in New Zealand populations of chaffinches is high enough to swamp any homogenizing effect of meme flow, thus allowing the meme pools of these populations to diverge significantly in about the last 100 years. This is the first quantitative attempt to explain the process of cultural evolution of bird song in terms of the interaction of the mutation, flow, and random drift of memes within and among populations, and the task for the future is to assess the generality of this model in other species.