SMT201 AY2019-20T1 EX2 Kong Yi Ru Kaelyn

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Background of Study Area

Gombak Planning Subzone, or Bukit Gombak, is located in Bukit Batok Planning Area, in the central-west part of Singapore. In order to identify the most suitable location for building a national Communicable Disease Quarantine Centre, we will be studying both natural and man-made features present and weighing each feature’s importance in deciding where is most suitable.

Initial Analysis of Study Area

We will be analyzing four features, the buildings, roads, natural features, and elevation of the subzone. Each of these features contribute as a decision factor in the following ways.

Decision Factor Feature Analysed
1. Health Risk Factor Buildings
2. Accessibility Factor Roads
3. Natural Conservation Factor Natural Features
4. Economic Factor Slope

[[File:Takehome2.png|1000px|frameless|center]

1. Health Risk Factor (Buildings)

Due to the nature of a Disease Quarantine Centre, it is important that the selected site should be away from residential and working areas, i.e. located away from buildings. In the Buildings data from OpenStreetMap, it was null for most of the values in attribute ‘Type’. Therefore, I clipped the 2014 Masterplan Landuse layer with the buildings layer, to get a better idea of the type of buildings. This shows that the buildings in Gombak Planning Subzone consist of mostly special use and residential buildings. Therefore, the selected site should be situated far away from any of these buildings.

2. Accessibility Factor (Roads)

In order for ease of construction and transportation of goods, the selected site should be near service roads and tracks. The Roads layer from OpenStreetMap also contained information on other types of roads, such as residential roads or footways. Therefore, service roads and tracks were selected, and categorized as shown, using different colours to represent the different roads.

3. Natural Conservation Factor (Natural Features)

The selected site should be away from natural features, namely forests, parks and water. Several of these natural features can be found in Gombak Planning Subzone, as shown, where several parks, forests and water features are found. They are categorized into those respective categories, and represented by using colours representing the nature of the feature, for easy differentiation between features. Dark green is used to represent parks, light green for forests, and light blue for water features.

4. Economic Factor (Slope)

The selected site should avoid steep slope due to the high cost of construction on such areas. To study the slope in Gombak Planning Subzone, ASTER GDEM raster data was imported, clipped, and categorized as shown. A graduated model is used, to show the range of elevation above sea level in the subzone. The elevation ranges from 8 to 145 metres above sea level. The greatest elevation in the subzone is situated near the centre to southern area of the Subzone, and the areas near the subzone boundary have lower elevations.

Proximity and Slope Analysis

To study the proximity to the different features, the different vector layers were rasterized before carrying out proximity analysis. This was done by first creating a new column, POI code, then converting it using to a raster layer, using georeferenced units as the output raster size units. For ease of comparison, the largest distance studied was from 0 – 100 metres for the 3 target features. The proximity to the features is represented as shown, where the darker the areas, the closer they are to the target features.

Takehome2.2.png

1. Proximity to Buildings

The furthest distance from the buildings is 100m, represented by the black areas.

2. Proximity to Target Roads

The furthest distance from service roads and tracks is 100m, represented by the black areas.

3. Proximity to Target Natural Features

The furthest distance from the forests, parks and water is 100m, represented by the black areas.

4.Analysis of Slope

The legend shows that the minimum and maximum values of the slope values are 0 and 34.8148 degrees, represented by the colours black and white respectively. Dark grey areas on the map are indicative of a gentle slope, while light grey areas are indicative of a steeper slope.

Criterion Score

To come up with the criterion score for the different features, the SAGA raster standardization feature was used to standardize the values of the features to a range of 0 to 1. This allows the different features to be compared on the same scale, such as distance measures (metres) and slope (degrees) can be fairly compared against each other. The same colour ramp was also used for easier comparison.

Takehome2 3.png

1. Criterion Score for Buildings

2. Criterion Score for Target Roads

3. Criterion Score for Target Natural Features

4. Criterion Score for Slope Analysis

AHP Analysis

The Analytical Hierarchical Process (AHP) helps us to make fair decisions when deciding amongst multiple factors. The pair-wise comparison matrix is used to calculate the relative costs between the different factors.

Reasons for Ranking of Decision Factors

I believe that the Health Risk Factor is the most important factor. Prior analysis of the study area has shown that there are many residential buildings in the area, and has many people staying in the subzone. Preventing disease from spreading to the nearby population should be the top priority, as there is a high chance that a large number of people might be infected, and might eventually lead to an epidemic.

The second most important factor is the Economic Factor, to avoid steep slope. A steep slope would cause the government to incur much higher costs to construct the quarantine centre, as a lot of cut-and-fill would be required to level the land. Research has also shown that it could even cost multiple times the original cost, and hence, makes it an important consideration.

Thirdly, Accessibility is important, in order for ease of transportation of construction materials to the site of construction. Without having such accessibility, it would be costly and inconvenient to transport the materials, as no local roads are available.

Lastly, the Natural Conservation Factor is the least important of the four, as there are very few natural features in Gombak Planning Subzone, and those features are unlikely to be heavily affected by being close to the selected site.

Computation of AHP Scores

Using the AHP Template provided by SCB Associates, I computed the weights of each decision factor as shown.

AHP TAKE HOME 2.jpg
Relative Importance (Decreasing) Decision Factor Weight
1 Health Risk Factor 0.552
2 Economic Factor 0.255
3 Accessibility Factor 0.128
4 Natural Conservation Factor 0.065

As the consistency was 8%, which is below 10%, this AHP matrix can be used.

Using the weights of each factor, the final land suitability layer was computed using the raster calculator with the following formula, such that the relative importance of each factor was taken into consideration to give the final suitability of the land.

Formula Used:

0.255*"Standardised Slope@1" + 0.128*"Standardised Roads@1" + 0.552*"Standardised Buildings@1" + 0.065*"Standardised Natural@1"

Land Suitability Analysis

Takehome2.3 4.png

The map shown is the output after considering the weights of each factor, with the score of land suitability given in the legend.

land suitability categorised

I then reclassified the AHP Analysis layer using ‘Reclassify by Table’ to give a map showing the suitability on a scale of 1 – 10.

Takehome2.3 6.png

From this, I defined ‘Suitable Locations’ as plots of land with suitability > 5, converted the layer into a vector layer, and selected the plots of land that have an area of at least 10,000m2. The following plots of land were identified as possible areas to build the quarantine centre.

Recommendations

Area of land.jpg

Data

Dataset Source
Subzone Data https://data.gov.sg/dataset/master-plan-2014-subzone-boundary-no-sea
Master Plan 2014 Land Use Data https://data.gov.sg/dataset/master-plan-2014-land-use
Buildings, Road, Natural Features https://www.bbbike.org/Singapore/
ASTER Global Digital Elevation Model (GDEM) dataset https://search.earthdata.nasa.gov/search?m=-7.175!25.59375!1!1!0!0%2C2
Analytical Hierarchical Process Template https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=17&ved=2ahUKEwi198HV87_lAhXhjuYKHWn1AnEQFjAQegQICRAC&url=http%3A%2F%2Fwww.scbuk.com%2FAHP%2520Template%2520SCBUK.xls&usg=AOvVaw002J8QfYIxOE_I9PYqrH8_