SMT201 AY2019-20T1 EX1 Kok Su Yee

Part 1: Thematic Mapping

Distribution of Public Education Institutions in Singapore

This map depicts the distribution of public education institutions in Singapore. Different SVG markers are used to classify the different school types. I have segregated the maps into regions in Singapore, allowing us to have an overall picture of where the types of schools are in a quick glance. The number of Primary and Secondary Schools are evenly spread out in the five regions. There is only 1 central institute in Singapore as compared to the number of Junior Colleges. This could be due to the low demand as there is longer course of study in Central Institute.

Road Network Systems in Singapore

By making use of the LTA GIS Road Section Line data, the road network system of Singapore is classified in the hierarchy of:

1. Expressway
2. Major Road
3. Minor Road
4. Local Access Road

To further visualise the road network system clearly on the map, I increased the thickness of the road lines in terms of hierarchy basis. I have also segregated the areas in Singapore into regions. From here, this highlights the boundary and we can spot how closely connected Singapore is. I uses red colour to represent the expressway as this bright colour is able to bring out how the expressway is linked across the five regions.

2014 Master Plan Land Use in Singapore

In displaying the types of land use in Singapore, a new field called LU_CLASS is created to classify the different land use types into 14 broad categories. Such simple view enables us to recognise that a lot of land has been used as reserved site in Singapore for future land development purpose. Residential area is another land type that takes up most part of Singapore given that it is a highly densely populated country. The terminal land use is expected to expand with the opening of Terminal 5 in the future.

Part 2: Choropleth Mapping

Aged population (Above 65) in 2018

The above maps are classified with graduated symbology where the darker intensity of the red colour means the higher the area is populated with the aged. In comparing the two maps above that shows the aged population of over 65 years old in Singapore in 2010 and 2018, we can find that there is a trend of increasing aged population over the years. The areas that were highly populated with the aged before in 2010 remains in 2018, specifically in areas of Tampines and Bedok.

Proportion of Aged population in 2018

The choropleth maps of aged population proportion in 2010 and 2018 revealed that there is a growth in the proportion of aged populations over the eight years. There are more areas which become even highly populated with elderly in 2018. For instance, the areas are Lim Chu Kang, Bedok and Toa Payoh, just to name a few. This could signify that the ageing population challenge will get worse in years to come as people’s life span is expected to be longer. Thus, Singapore has to be prepared to handle the issue by providing greater support for the aged in the future.

Percentage change of Aged Population between 2010 and 2018

This map shows that there is a percentage increase in the aged population living in the areas of Yishun and Tampines over the eight years. The percentage increase is significant in the central region of Singapore. The mode of class in classifying the values of the percentage change is quantile (Equal count), this divides the distribution of the aged population into four equal parts. This ensures the extreme values of percentage change does not affect the visualisation.

Reasoning for classification choices, deriving new variables and handling of missing values

In designing the choropleth maps for the aged population, I have applied the graduated symbology in classifying the aged population count. Equal interval mode is set for maps of aged population and proportion of aged population. This is because there are no values that is below 0. On the other hand, quantile count mode is applied for percentage change of aged population map as I would need to split the distribution into equal count taking into consideration that there are negative values involved. In regards to the choice of colour, I have chosen red colour ramp as it is highly visible to identify the areas that is highly populated with the aged.

Before I start importing the downloaded Singapore Resident Population csv file from SingStats website into QGIS as a delimited text layer, I performed data cleaning to the dataset. Filtering is done to retrieve the data from only year 2010 and 2018. Besides, I capitalised the names of the subzone areas so that joining of this data with the 2014 Subzone region shapefile is possible. New columns are created for population count, total population count, population proportion and percentage change in 2010 and 2018. All null values detected are treated as zero. After the data cleaning process, the new csv file is imported as a delimited text layer into QGIS.

References

Singapore Resident Population Data [1]
2014 Master Plan Land Use Data [2]
2014 Master Plan Region Data [3]
2014 Master Planning Area Data [4]
Road Section Line Data [5]
Types of Schools in Singapore Data [6]
Understand Road Categories "Road Line Plan Explanatory Notes"
Understand Properties in Singapore [7]