Difference between revisions of "SMT201 AY2019-20G2 Ex1 Ng Poh Yeng"

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<big>Part one thematic mapping
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== Part One: Thematic Mapping ==
</big>
 
  
  
1) level of schools
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=== 2014 Master Plan Landuse ===
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Data provided was discrete in nature, so categorized symbology where different uses of land had different colours were used.
 +
Depending on the land use functions and appearances, different groups of colours were used. For example, parks and agriculture were assigned green, while business and commercial land uses were assigned red and orange. Transport and utility functions were assigned shades of yellow, while residential areas were given light and white-ish blue shades.
 +
This type of grouping where similar functions are of different shades of the same colour allows the map to visualise how different areas of Singapore are being used.
  
[[File:Level of school.jpg|thumb]]
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=== Level of Schools ===
 +
As the classification data of each school was discrete in nature, categorized symbology was used to visualise the distribution of public educational institutes. For each category of educational institutes, different symbols and colours were used such that they could be easily told apart from each other. Some python code was used in order to geocode the educational institutes onto QGIS as only their ZIP codes were provided in the dataset.
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[[File:Py geocode scr.png|thumb]]
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Subzone data provided by data.gov.sg was used as the backdrop such that the reader would be able see the distribution of schools across Singapore.
 +
 
 +
=== Road Network System ===
 +
An assumption used was that the road prefixes were indicators of hierarchy, as road classification data was not directly available. By calculating a new field on the attribute table of the road data layer found on data.gov.sg, each road was assigned one of 3 groups. Based on this grouping, categorized symbology was used to visualise the hierarchy.
 +
 
 +
From this, roads were given different colouring and thickness based on their hierarchy, with expressways and highways being the thickest. This was done to show the branching out of each group of roads from the group of roads that are higher in hierarchy.

Revision as of 01:10, 15 September 2019

Part One: Thematic Mapping

2014 Master Plan Landuse

Data provided was discrete in nature, so categorized symbology where different uses of land had different colours were used. Depending on the land use functions and appearances, different groups of colours were used. For example, parks and agriculture were assigned green, while business and commercial land uses were assigned red and orange. Transport and utility functions were assigned shades of yellow, while residential areas were given light and white-ish blue shades. This type of grouping where similar functions are of different shades of the same colour allows the map to visualise how different areas of Singapore are being used.

Level of Schools

As the classification data of each school was discrete in nature, categorized symbology was used to visualise the distribution of public educational institutes. For each category of educational institutes, different symbols and colours were used such that they could be easily told apart from each other. Some python code was used in order to geocode the educational institutes onto QGIS as only their ZIP codes were provided in the dataset.

Py geocode scr.png

Subzone data provided by data.gov.sg was used as the backdrop such that the reader would be able see the distribution of schools across Singapore.

Road Network System

An assumption used was that the road prefixes were indicators of hierarchy, as road classification data was not directly available. By calculating a new field on the attribute table of the road data layer found on data.gov.sg, each road was assigned one of 3 groups. Based on this grouping, categorized symbology was used to visualise the hierarchy.

From this, roads were given different colouring and thickness based on their hierarchy, with expressways and highways being the thickest. This was done to show the branching out of each group of roads from the group of roads that are higher in hierarchy.