SMT201 AY2019-20T1 EX1 Eddie Leow Kian Giap

Part 1: Thematic Mapping

Using school information from data.gov.sg, prepare a thematic map showing the distribution of public education institution by school types such as primary, secondary, etc.

I have categorized the data set according to the school type such as Primary, Secondary, Mixed Level, Junior College and Centralised Institution. My cartographic technique is to use an icon which represents the school type. For example, I used an icon that states "ABC" to indicate a primary school. The icon is given a width and height of 4 so that it can display clearly on the map without overlapping other nearby school types.

Using road GIS data of LTA, prepare a thematic map showing the hierarchy of road network system of Singapore such as expressway, major road, minor road, etc.

For this data set, I have categorized them according to the road network system such as expressway, expressway slip road, main road and minor road. My cartographic technique is to use different line colours to represent each system or hierarchy. This gives a clear view of expressway, expressway slip road, major road and minor road to users.
Using master plan landuse GIS data from data.gov.sg, prepare a thematic map showing 2014 Master Plan Landuse.

As there are many different usage of land, I have grouped some of them together then categorized them with icons or colours to represent the type. One of the groupings I have done is all the business-related type is grouped into business. The icons selected for each type represents the purpose of it. For example, open space is defined by green colour and park is defined by a tree icon.

Part 2: Choropleth Mapping

Using planning subzone GIS data from data.gov.sg and Singapore residents by age group and gender, prepare the following choropleth maps:

• Aged population (+65) in 2010 and 2018.
• Proportional of aged population in 2010 and 2018.
• Percentage change of aged population between 2010 and 2018.

In separate text describe the spatial patterns, if any, reveals by each of the choropleth maps prepared.
Explain the reasoning behind your classification choices, how you derived the new variables and handled missing values, and any other relevant judgments and assumptions. Please limit this discussion to a maximum of not more than 500 words.

In order to derive the missing values of the aged population (65 years old and above) in 2018, I calculated the percentage of each subzone based on the data set found in 2017 on data.gov. With the percentage, I multiplty it with another data set which compromises of aged population in 2018 found on data.gov to derive the value for each subzone in 2018. The missing values found in the data set are ignored because it does not affect the outcome of the mapping.