scholarly journals Lockout, Lockdown and Land Use: Exploring the Spatio-Temporal Evolution Patterns of Licensed Venues in Sydney, Australia between 2012 and 2021 in the Context of NSW Public Policy

Buildings ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 35
Author(s):  
Jayden Mitchell Perry ◽  
Sara Shirowzhan ◽  
Christopher James Pettit
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Spatial Clustering ◽  
Hot Spot ◽  
Temporal Analysis ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Spatio Temporal ◽  
Over Time ◽  
Sydney Australia

The hospitality industry in Sydney, Australia, has been subject to several regulatory interventions in the last decade, including lockout laws, COVID-19 lockdowns and land use planning restrictions. This study has sought to explore the spatial implications of these policies in Inner Sydney between 2012 to 2021. Methods based in spatial analysis were applied to a database of over 40,000 licensed venues. Point pattern analysis and spatial autocorrelation methods were used to identify spatially significant venue clusters. Space-time cube and emerging-hot-spot methods were used to explore clusters over time. The results indicate that most venues are located in the Sydney CBD on business-zoned land and show a high degree of spatial clustering. Spatio-temporal analysis reveals this clustering to be consistent over time, with variations between venue types. Venue numbers declined following the introduction of the lockout laws, with numbers steadily recovering in the following years. There was no discernible change in the number of venues following the COVID-19 lockdowns; however, economic data suggest that there has been a decline in revenue. Some venues were identified as having temporarily ceased trading, with these clustered in the Sydney CBD. The findings of this study provide a data-driven approach to assist policymakers and industry bodies in better understanding the spatial implications of policies targeting the hospitality sector and will assist with recovery following the COVID-19 pandemic. Further research utilising similar methods could assess the impacts of further COVID-19 lockdowns as experienced in Sydney in 2021.

scholarly journals Spatial and temporal drivers of wildfire occurrence in the context of rural development in northern Wisconsin, USA

2012 ◽  
Vol 21 (2) ◽  
pp. 141 ◽  
Author(s):  
Brian R. Miranda ◽  
Brian R. Sturtevant ◽  
Susan I. Stewart ◽  
Roger B. Hammer
Keyword(s):  
Linear Regression ◽  
Land Use Planning ◽  
Temporal Trends ◽  
Point Pattern Analysis ◽  
Annual Number ◽  
Point Pattern ◽  
Linear Regression Models ◽  
Housing Density ◽  
Spatial And Temporal Scales ◽  
Wildfire Occurrence

Most drivers underlying wildfire are dynamic, but at different spatial and temporal scales. We quantified temporal and spatial trends in wildfire patterns over two spatial extents in northern Wisconsin to identify drivers and their change through time. We used spatial point pattern analysis to quantify the spatial pattern of wildfire occurrences, and linear regression to quantify the influence of drought and temporal trends in annual number and mean size of wildfires. Analyses confirmed drought as an important driver of both occurrences and fire size. When both drought and time were incorporated in linear regression models, the number of wildfires showed a declining trend across the full study area, despite housing density increasing in magnitude and spatial extent. Fires caused by campfires and debris-burning did not show any temporal trends. Comparison of spatial models representing biophysical, anthropogenic and combined factors demonstrated human influences on wildfire occurrences, especially human activity, infrastructure and property values. We also identified a non-linear relationship between housing density and wildfire occurrence. Large wildfire occurrence was predicted by similar variables to all occurrences, except the direction of influence changed. Understanding these spatial and temporal drivers of wildfire occurrence has implications for land-use planning, wildfire suppression strategies and ecological goals.

scholarly journals Spatial and spatio-temporal analysis of Salmonella infection in dairy herds in England and Wales

2008 ◽  
Vol 137 (6) ◽  
pp. 847-857 ◽  
Author(s):  
S. E. FENTON ◽  
H. E. CLOUGH ◽  
P. J. DIGGLE ◽  
S. J. EVANS ◽  
H. C. DAVISON ◽  
...  
Keyword(s):  
Transition Probabilities ◽  
Spatial Clustering ◽  
Markov Chain Model ◽  
Temporal Analysis ◽  
Dairy Herds ◽  
Chain Model ◽  
Time Period ◽  
Spatio Temporal ◽  
Using Data ◽  
Residual Deviance

SUMMARYUsing data from a cohort study conducted by the Veterinary Laboratories Agency (VLA), evidence of spatial clustering at distances up to 30 km was found for S. Agama and S. Dublin (P values of 0·001) and borderline evidence was found for spatial clustering of S. Typhimurium (P=0·077). The evolution of infection status of study farms over time was modelled using a Markov Chain model with transition probabilities describing changes in status at each of four visits, allowing for the effect of sampling visit. The degree of geographical clustering of infection, having allowed for temporal effects, was assessed by comparing the residual deviance from a model including a measure of recent neighbourhood infection levels with one excluding this variable. The number of cases arising within a defined distance and time period of an index case was higher than expected. This provides evidence for spatial and spatio-temporal clustering, which suggests either a contagious process (e.g. through direct or indirect farm-to-farm transmission) or geographically localized environmental and/or farm factors which increase the risk of infection. The results emphasize the different epidemiology of the three Salmonella serovars investigated.

Spatio-temporal analysis of land use/cover changes in the Pra River Basin, Ghana

2019 ◽  
Vol 12 (1) ◽  
pp. 83-93 ◽  
Author(s):  
Ebenezer Boakye ◽  
F. O. K. Anyemedu ◽  
Jonathan A. Quaye-Ballard ◽  
Emmanuel A. Donkor
Keyword(s):  
Land Use ◽  
River Basin ◽  
Temporal Analysis ◽  
Spatio Temporal ◽  
Pra River

A Spatio-Temporal Storage Method for Land-Use Change

2014 ◽  
Vol 687-691 ◽  
pp. 3078-3082
Author(s):  
Ning Pan ◽  
Ke Wang ◽  
Jing Jing Tan
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Land Use ◽  
Land Use Change ◽  
Land Use Planning ◽  
Historical Data ◽  
Land Use Changes ◽  
Storage Method ◽  
Temporal Aspect ◽  
Spatio Temporal

Frequent land-use changes might produce a large amount of historical data which are valuable for data mining and decision-making. Based on the traditional Whole-state-recording Mode, the Special-state-recording Mode was proposed, focusing on the temporal aspect. This mode could optimize the land use database and reduce redundant change record. It could also improve data rollback and historical backtracking functions. The mode was successfully applied to land use planning in Zhejiang Province.

On the absurdity of rapid urbanization: Spatio-temporal analysis of land-use changes in Morogoro, Tanzania

Cities ◽  
2020 ◽  
Vol 107 ◽  
pp. 102876
Author(s):  
Neema Simon Sumari ◽  
Patrick Brandful Cobbinah ◽  
Fanan Ujoh ◽  
Gang Xu
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Temporal Analysis ◽  
Rapid Urbanization ◽  
Spatio Temporal
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