Assignment Task:
Task:
Introduction
The Toronto district is a massive and dense city that has a growing population of 2.93 million people. Based on the data in the past 3 years numbers have showed that crime is moderately increasing even though this number is not high it is very useful to learn where and why does crime take place. This research will explore the spatial distribution of police-reported crime in the city of Toronto and its purpose will be to find relationships between neighbourhoods characterises and crime rates. In this research we will look Toronto neighbourhood Crime rates and see which locations are more prone of having a crime. Based on that information then we will conduct research on the social structure of those specific neighbourhoods. This research will look at how social processes such as poverty, racial discrimination, issued with families, drop out of school can lead an individual to commit crime. It will be beneficial to understand factors that contribute to these crimes.
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The objective of this project is to provide appropriate solutions given data on areas prone to crime related to youth. We will be looking at data acquired by the city of Toronto Police Service through last decade to help identify how the numbers of homicide can be reduce in the city. Primary beneficiaries include the city of Toronto should they enact our proposal as they will benefit from reduced deaths of denizens and safer streets. While the scope of the skills used in this project are largely rudimentary GIS functions. In addition, while the geographic scope of our project was just Toronto, our analysis can also be applied to other cities across the world.
Methods:
From the help of R-code, goal would be to detect both patterns and possible anomalies based on available data. Just to explain, I can use calculate_ density to see if there are crimes happening in an area. Next, we can use few
QGIS tools such as:
Grass-GIS
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