Difference between revisions of "SMT201 AY2019-20T1 EX2 Tan Zi Ying"

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== Part 1: Thematic Mapping ==
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== Building a national Communicable Disease Quarantine Centre ==
  
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[[File:Tanziyingschool.png |border|center|800x800px|]]
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# Economic Factor (study area and digital elevation)
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source: datagov.sg  
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# Accessibility Factor (study area and target roads)
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<br>
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# Health Risk Factor (study area and buildings)
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In order to classify the data, I categorized the different type of education by colours. I chose to use square shaped symbols as it provides greater readability. The schools are classified by – “Junior College/Centralised Institute” , “Mixed Level Schools” , “Primary Schools” and “Secondary Schools”.
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# Natural Conservation Factor (study area and natural)
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<br>
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<br/>
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[[ File:studyarea2.png|800px|center|Gombak Study Area]]
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Data source: Master Plan 2014 Subzone Boundary from URA from data.gov.sg.
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Roads, buildings and natural features data from OpenStreetMap (OSM) data sets from BBBike@Singapore.
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ASTER Global Digital Elevation Model (GDEM) dataset jointly prepared by NASA and METI, Japan from NASA’s EarthData Search site complied by Professor Kam
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<br/>
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=== Economic factor ===
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The selected site should avoid steep slope. This is because construction at steep slope tends to involve a lot of cut-and-fill and will lend to relatively higher development cost. The lowest point in Gombak, depicted in red is 8 meters above sea level while the highest point in Gombak, depicted in blue is 143 meters above sea level.
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<br/>
  
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[[File:tzyRoadnetwork.png |border|center|800x800px|]]
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=== Accessibility factor ===
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source: datagov.sg
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The selected site should be close to existing local roads, namely: service roads and tracks. This is to ensure easy transportation of building materials during the construction stage. As seen in the data, there is more service roads in the North-East of Gombak and the tracks are in the South-West of Gombak.
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I used calculator field function to categorize the different road network system according to “Expressway”, “Highway”, “Drive”, “Local Access”, “Major Road”, “Minor Road” and “Parkway” so that it would be more readable. Different categorised colours are used for the different types of road. A light background is used so that there will be contrast between the hue colours and the light-coloured map.
 
  
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[[File:TzyLanduse.png |border|center|800x800px|]]
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=== Health risk factor ===
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source: datagov.sg
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The selected site should be away from population i.e. housing areas and offices in order to avoid disease spreading to the nearby population. The buildings are mostly in the North and South part of Gombak.
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The different colours are used to represent the URA zone such as “Hotel”, “Sports & Recreation” and “Waterbody”. Categorized colours are used to differentiate the different area.
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<br/>
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== Part 2: Choropleth Mapping ==
 
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<br>
 
  
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[[File:tzyAboveandequal65(2010.png |border|center|800x800px|]]
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=== Natural conservation factor ===
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source: singstat.gov.sg
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The selected site should be away from forested land, park and water. The water body is depicted in blue, the park in green and the forest is in mustard yellow.
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<br/>
  
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<br>
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== Proximity Analysis ==
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[[File:tzyMorethan65('18').png |border|center|800x800px|]]
 
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source: singstat.gov.sg
 
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The number of aged population increased overall in 2018, as compared to 2010.
 
  
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<br>
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# the study area and proximity to target roads layer
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[[File:TzyProportion(2010).png |border|center|800x800px|]]
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# the study area and proximity to buildings layer
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source: singstat.gov.sg
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# the study area and proximity to target natural features layer
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# the study area and slope layer
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<br/>
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<br/>
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[[ File:proximity5.png|800px|center|Proximity Analysis]]
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Data source: Master Plan 2014 Subzone Boundary from URA from data.gov.sg.
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Roads, buildings and natural features data from OpenStreetMap (OSM) data sets from BBBike@Singapore.
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ASTER Global Digital Elevation Model (GDEM) dataset jointly prepared by NASA and METI, Japan from NASA’s EarthData Search site complied by Professor Kam
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===Proximity to Nature===
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The areas in black are closer to nature features and not as preferred as the areas in white that are further away from the natural features.
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The furthest distance away from natural in this map is 863.669 meters. The Quarantine Centre should be build as far away from natural features as possible.
  
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[[File:tzyProportion(2018).png |border|center|800x800px|]]
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===Proximity to Roads===
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source: singstat.gov.sg
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The areas in black are closer to the roads and hence it more preferred. The closer the Quarantine Centre to the Road, the more accessible it is. Therefore, it is more suited to build the Quarantine Centre in closer proximity to the service roads and tracks.
  
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===Proximity to Buildings===
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The areas in black are closer to the buildings. Hence it would be less suitable to build the Quarantine Centre in these areas as it is too close to the population in Gombak. The furthest distance from the buildings is 826.62 meters.
  
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<br>
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=== Slopes ===
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[[File:TzyProportion(2010).png |border|center|800x800px|]]
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The areas in darker blue are used to shade the areas with slopes higher than 30 degrees. Hence, it would be less suited to build the Quarantine Centre in the areas of darker shades as is too steep to build the Quarantine Centre. The steepest area in Gombak is 36.43 degrees.
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source: singstat.gov.sg
 
  
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The proportion in 2010 is obtained by using (Agedpopulation2010)/(Totalpopulation2010) whereas the proportion in 2018 is obtained through the formula (Agedpopulation2018)/(Totalpopulation2018). The proportion of the aged population increased in 2018, as compared to 2010. Additionally, it can be observed that the north-east part of Singapore holds a higher proportion of aged population than the rest of Singapore subzones.  
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== Criterion Scores of each Factor Layers ==
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In order to compare the criterion scores of the respective factor layers, I standardized the proximity analysis result as shown.
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[[ File:standard1.png|500px|center|AHP_input_maxtrix]]
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<br/>
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For the road and natural factor layer I used the formula (1-(proximity)/(max(proximity)-min(proximity)))
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[[ File:standard2.png|500px|center|AHP_input_maxtrix]]
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For the slope and building factor layer I used the formula (proximity)/(max(proximity)-min(proximity))
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<br/>
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[[ File:criteria_tzy.png|900px|center|AHP_criterion]]
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<br/>
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The criterion score ranges from 0 to 1, the darker areas represent area with a higher criterion score while the lighter areas represent area with a lower criterion score.
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<br/>
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===Accessibility Score===
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The accessibility score is determined by the proximity to the service roads and tracks. Hence, the areas closer to the roads would obtained a higher criterion score.  
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<br/>
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===Health Risk Score===
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The health risk score is determined by the proximity away from the buildings. The risk of infection is higher when the population is closer to the Quarantine centre. Hence, the areas further away from the buildings would obtained a higher criterion score.
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<br/>
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===Natural Conservation Score===
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The Natural Conservation score is determined by the proximity away from natural. The area further from the natural is preferred and hence given a higher criterion score.
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<br/>
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===Economic Score===
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The economic score is determined by the steepness of the slope. A gentle slope is preferred as it requires less cost to build the Quarantine Centre and hence is preferred and given a higher criterion score.
  
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<br>
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== Analytical Hierarchical Process Input Matrix and Result Report ==
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[[File:tzy_change.png |border|center|800x800px|]]
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[[ File:AHP1_tanziying.png|900px|center|AHP_input_maxtrix]]
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source:singsta.gov.sg
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Data Source: AHP Template from SCBUK
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The percentage change is obtained through the formula (Agedpopulation2018-Agedpopulation2010)/Agedpopulation2010. Through this choropleth map, we observed that there more than half of the subzone experienced a positive change in aged population.  
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[[ File:AHP2_tanziying.png|300px|center|AHP_consistency]]
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Data Source: AHP Template from SCBUK
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[[ File:AHP3_tanziying.png|300px|center|AHP_tzy]]
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Data Source: AHP Template from SCBUK
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<br/>
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[[ File:AHP4_tanziying.png|300px|center|AHP_tzy1]]
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Data Source: AHP Template from SCBUK
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As seen in the AHP matrix, the level of importance is as such: 1. Health Risk 2. Accessibility 3. Economic 4. Natural Conservation. The AHP is as such: Health Risk: 0.572, Accessibility: 0.218 3. Economic: 0.140 4. Natural Conservation: 0.070. The consistency level is 10% indicating that it is consistent.
  
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== Comments on the Suitable Land Lot(s) Identified ==
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<br>
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[[ File:suitable_tzy.png|500px|center|steps]]
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[[ File:suitability2.png|600px|center|suitability]]
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Discussion
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According to the map shown, the areas that are more suitable for building a Quarantine Center is the South side of Gombak. The larger area would be more suitable for building a Quarantine center to accommodate for more people.
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In order to see the difference between the quantitative data, graduated colours were used to differentiate the quantity in the subzones. I obtained the data file from Singstat and summed the population aged 65 and above by using the calculator field function.
 
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For the Aged population (+65) in 2010 and 2018, the 2010.cvs file and the 2018.cvs file is added into the map respectively. The value is used wholesale from the summed total.  
 
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<br>
 
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Whereas, for the Proportion of Aged Population in 2010 and 2018, the value is obtained through the formula: (Agedpopulation2010)/(Totalpopulation2010) whereas the proportion in 2018 is obtained through the formula: (Agedpopulation2018)/(Totalpopulation2018).
 
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<br>
 
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Finally, the percentage change is obtained through the formula (Agedpopulation2018-Agedpopulation2010)/Agedpopulation2010.
 
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I choose Natural Breaks (Jenks) for the different map as it shows the greatest differentiation between each category. I manually added a 0 class for each of the map to observe the absence of aged population in that subzone.
 

Latest revision as of 22:45, 10 November 2019

Building a national Communicable Disease Quarantine Centre

  1. Economic Factor (study area and digital elevation)
  2. Accessibility Factor (study area and target roads)
  3. Health Risk Factor (study area and buildings)
  4. Natural Conservation Factor (study area and natural)



Gombak Study Area

Data source: Master Plan 2014 Subzone Boundary from URA from data.gov.sg. Roads, buildings and natural features data from OpenStreetMap (OSM) data sets from BBBike@Singapore. ASTER Global Digital Elevation Model (GDEM) dataset jointly prepared by NASA and METI, Japan from NASA’s EarthData Search site complied by Professor Kam

Economic factor

The selected site should avoid steep slope. This is because construction at steep slope tends to involve a lot of cut-and-fill and will lend to relatively higher development cost. The lowest point in Gombak, depicted in red is 8 meters above sea level while the highest point in Gombak, depicted in blue is 143 meters above sea level.

Accessibility factor

The selected site should be close to existing local roads, namely: service roads and tracks. This is to ensure easy transportation of building materials during the construction stage. As seen in the data, there is more service roads in the North-East of Gombak and the tracks are in the South-West of Gombak.

Health risk factor

The selected site should be away from population i.e. housing areas and offices in order to avoid disease spreading to the nearby population. The buildings are mostly in the North and South part of Gombak.

Natural conservation factor

The selected site should be away from forested land, park and water. The water body is depicted in blue, the park in green and the forest is in mustard yellow.

Proximity Analysis

  1. the study area and proximity to target roads layer
  2. the study area and proximity to buildings layer
  3. the study area and proximity to target natural features layer
  4. the study area and slope layer



Proximity Analysis

Data source: Master Plan 2014 Subzone Boundary from URA from data.gov.sg. Roads, buildings and natural features data from OpenStreetMap (OSM) data sets from BBBike@Singapore. ASTER Global Digital Elevation Model (GDEM) dataset jointly prepared by NASA and METI, Japan from NASA’s EarthData Search site complied by Professor Kam

Proximity to Nature

The areas in black are closer to nature features and not as preferred as the areas in white that are further away from the natural features. The furthest distance away from natural in this map is 863.669 meters. The Quarantine Centre should be build as far away from natural features as possible.

Proximity to Roads

The areas in black are closer to the roads and hence it more preferred. The closer the Quarantine Centre to the Road, the more accessible it is. Therefore, it is more suited to build the Quarantine Centre in closer proximity to the service roads and tracks.

Proximity to Buildings

The areas in black are closer to the buildings. Hence it would be less suitable to build the Quarantine Centre in these areas as it is too close to the population in Gombak. The furthest distance from the buildings is 826.62 meters.

Slopes

The areas in darker blue are used to shade the areas with slopes higher than 30 degrees. Hence, it would be less suited to build the Quarantine Centre in the areas of darker shades as is too steep to build the Quarantine Centre. The steepest area in Gombak is 36.43 degrees.

Criterion Scores of each Factor Layers

In order to compare the criterion scores of the respective factor layers, I standardized the proximity analysis result as shown.

AHP_input_maxtrix


For the road and natural factor layer I used the formula (1-(proximity)/(max(proximity)-min(proximity)))

AHP_input_maxtrix

For the slope and building factor layer I used the formula (proximity)/(max(proximity)-min(proximity))

AHP_criterion


The criterion score ranges from 0 to 1, the darker areas represent area with a higher criterion score while the lighter areas represent area with a lower criterion score.

Accessibility Score

The accessibility score is determined by the proximity to the service roads and tracks. Hence, the areas closer to the roads would obtained a higher criterion score.

Health Risk Score

The health risk score is determined by the proximity away from the buildings. The risk of infection is higher when the population is closer to the Quarantine centre. Hence, the areas further away from the buildings would obtained a higher criterion score.

Natural Conservation Score

The Natural Conservation score is determined by the proximity away from natural. The area further from the natural is preferred and hence given a higher criterion score.

Economic Score

The economic score is determined by the steepness of the slope. A gentle slope is preferred as it requires less cost to build the Quarantine Centre and hence is preferred and given a higher criterion score.

Analytical Hierarchical Process Input Matrix and Result Report

AHP_input_maxtrix

Data Source: AHP Template from SCBUK

AHP_consistency

Data Source: AHP Template from SCBUK

AHP_tzy

Data Source: AHP Template from SCBUK

AHP_tzy1

Data Source: AHP Template from SCBUK
As seen in the AHP matrix, the level of importance is as such: 1. Health Risk 2. Accessibility 3. Economic 4. Natural Conservation. The AHP is as such: Health Risk: 0.572, Accessibility: 0.218 3. Economic: 0.140 4. Natural Conservation: 0.070. The consistency level is 10% indicating that it is consistent.

Comments on the Suitable Land Lot(s) Identified

steps


suitability

According to the map shown, the areas that are more suitable for building a Quarantine Center is the South side of Gombak. The larger area would be more suitable for building a Quarantine center to accommodate for more people.

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