Difference between revisions of "SMT201 AY2019-20G2 Ex1 Soh Bai He"

From Geospatial Analytics for Urban Planning
Jump to navigation Jump to search
Line 21: Line 21:
 
=== Road Network System ===
 
=== Road Network System ===
  
[[File:P1b-roadnetwork.jpg|700px|thumb|left|Data Source: mytransport.sg / File: RoadSectionLine.shp]]
+
[[File:P1b-roadnetwork.jpg|700px|thumb|left|Data Source: mytransport.sg / File: RoadSectionLine.shp]]<br>
 +
'''Data Handling & Choice of Classification:''' RoadSectionLine.shp is exported into .csv format and new columns RD_CAT_NO, RD_MAIN_CAT, RD_SUB_CAT are added on excel (road-section-category-sorted.csv). Roads are then categorised with reference to [https://www.ura.gov.sg/-/media/Corporate/Resources/Publications/Streets-and-Building-Names/SBNB_handbook_streets.pdf?la=en Urban Redevelopment Authority’s Handbook on Guidelines] for Naming of Streets. Thereafter, I analysed the remaining roads (that do not include the street name descriptors in Table 1) on the OpenStreetMap and grouped them into Arterial/Primary Access as they are minor roads that provide access to developments.<br><br>
 +
 
 +
'''Visual Variable:''' Line symbols with different colours are used to represent each road type. A warm colour scheme (red > orange > yellow > white) is chosen to highlight the hierarchy of road types. Expressway is given the thickest width as they form the primary network.<br><br>
 +
 
  
 
=== 2014 Master Plan Landuse ===
 
=== 2014 Master Plan Landuse ===

Revision as of 17:35, 15 September 2019

Part One: Thematic Mapping


Public Education Institutions

Data Source: data.gov.sg / File: general-information-of-schools.csv


Data Handling: general-information-of-schools.csv is geocoded into school_information.shp

Choice of Classification:
1) Categorisation by school type. Junior College and Centralised Institute are grouped together as both offers pre-university courses and lead to the ‘A’ Level examinations.
2) Categorisation by region to facilitate easier visualisation of the distribution of schools by region.

Visual Variable: An SVG marker of a book is used as the symbol. Different colours are used for each school type/region for easier identification.

Feature count: Total (344), Primary (181), Secondary (138), Mixed Level (14), Junior College/Centralised Institute (11)

Observation: Of all school types, Junior College/Centralised Institute has the least number. However, the existing ones are well distributed across Singapore with every region covered.


Road Network System

Data Source: mytransport.sg / File: RoadSectionLine.shp


Data Handling & Choice of Classification: RoadSectionLine.shp is exported into .csv format and new columns RD_CAT_NO, RD_MAIN_CAT, RD_SUB_CAT are added on excel (road-section-category-sorted.csv). Roads are then categorised with reference to Urban Redevelopment Authority’s Handbook on Guidelines for Naming of Streets. Thereafter, I analysed the remaining roads (that do not include the street name descriptors in Table 1) on the OpenStreetMap and grouped them into Arterial/Primary Access as they are minor roads that provide access to developments.

Visual Variable: Line symbols with different colours are used to represent each road type. A warm colour scheme (red > orange > yellow > white) is chosen to highlight the hierarchy of road types. Expressway is given the thickest width as they form the primary network.


2014 Master Plan Landuse

Data Source: data.gov.sg / File: G_MP14_LAND_USE_PL.shp

Part Two: Choropleth Mapping

Aged population (+65) in 2010 and 2018

Data Source: data.gov.sg / File: SUBZONE_AGE_GENDER_2010.shp
Data Source: singstat.gov.sg / File: SGResidentPopulationAgeGroupSex_2018.csv

Proportional of aged population in 2010 and 2018

P2b-2010.jpg
P2b-2018.jpg

Percentage change of aged population between 2010 and 2018

P2c.jpg

References & Acknowledgements