ABSTRACT
India has proven to be one of the most diverse and dynamic economic regions in the world. Its industry focuses predominantly on the service sector and immediate economic growth seems to steer India into the economic superpower. India's unique business landscape is felt at a regional level, where massive urbanization has become an unavoidable consequence of population growth and spatial allocation to the economic hubs of metropolitan cities. Mumbai, one of the world's largest cities, represents a unique combination of a diverse economic landscape and the growth of a megacity. The role of Mumbai in India's growth is of crucial importance for India's business landscape. This paper explores the massive urbanization processes of Mumbai's peri-urban areas and compares urban sprawl with the location of its business landscape. A spatial accounting methodology based on the proximity of Mumbai's different economic hubs will be used to measure the underlying pattern of the Mumbai region, concerning past and present urbanization, and the effect of this urbanization process has on the possible location of businesses. This business-urban ecosystem perspective will be implemented by a spatial analysis on the correlation between urban compactness and urban footprints, in relation to business concentration and its spatiotemporal evolution over the last hundred years.
ABSTRACT
Injuries have become devastating and often under-recognized public health concerns. In Canada, injuries are the leading cause of potential years of life lost before the age of 65. The geographical patterns of injury, however, are evident both over space and time, suggesting the possibility of spatial optimization of policies at the neighborhood scale to mitigate injury risk, foster prevention, and control within metropolitan regions. In this paper, Canada's National Ambulatory Care Reporting System is used to assess unintentional and intentional injuries for Toronto between 2004 and 2010, exploring the spatial relations of injury throughout the city, together with Wellbeing Toronto data. Corroborating with these findings, spatial autocorrelations at global and local levels are performed for the reported over 1.7 million injuries. The sub-categorization for Toronto's neighborhood further distills the most vulnerable communities throughout the city, registering a robust spatial profile throughout. Individual neighborhoods pave the need for distinct policy profiles for injury prevention. This brings one of the main novelties of this contribution. A comparison of the three regression models is carried out. The findings suggest that the performance of spatial regression models is significantly stronger, showing evidence that spatial regressions should be used for injury research. Wellbeing Toronto data performs reasonably well in assessing unintentional injuries, morbidity, and falls. Less so to understand the dynamics of intentional injuries. The results enable a framework to allow tailor-made injury prevention initiatives at the neighborhood level as a vital source for planning and participatory decision making in the medical field in developed cities such as Toronto.
Subject(s)
Databases, Factual , Machine Learning , Urban Health , Wounds and Injuries/epidemiology , Canada/epidemiology , Cities/epidemiology , HumansABSTRACT
This study has developed a GIS framework that uses spatial environmental and climate data to better understand areas on Earth that share the most environmental similarities to Mars. The purpose of developing this framework is to determine which vegetation is most likely to survive in closed bioregenerative life support systems on Mars, using as many in-situ materials and environmental elements as possible. Using remotely sensed climate data, digital elevation models, and vegetation occurrence data sourced from the Global Biodiversity Information Facility, three Mars-like study areas on Earth were analysed (the Antarctic Peninsula, Ellesmere Island, and Devon Island). This study found that plants that are part of the Bryophyte and Tracheophyta phyla are worthy of further research in regard to possible vegetation candidates that could be brought to Mars. In addition, the most promising candidate of the entire study is the genus Poa, which is found in the phylum Tracheophyta.
