SMT201 AY2019-20G2 Ex2 JerryTohvan

Part 1: Study Area Map Components

FIGURE I

Study Area Map Components

Firstly, the above summarises an overview of the study area and its map components we want to consider in this suitability land analysis for the Communicable Disease Quarantine Centre in Bukit Gombak.

FIGURE II

Target Road Map

Figure II shows Bukit Gombak's Road Network that will be accounted in as an Accesibility factor in weighing the location suitability.

FIGURE III

Target Building Map

Figure III shows Bukit Gombak's Buildings that will be accounted in as an Health Risk factor in weighing the location suitability. We want the Disease Quarantine Centre to be further away from residential in order to ensure safe-zone. Health Risk factor will be prioritised as for the very fact that a Quarantine Centre exists, to ensure no further disease spreading. Bukit Gombak has mostly residential areas in its'subzone.

FIGURE III

Target Natural Features Map

FIGURE IV

Incomplete Waterway Target Inclusion. Applying buffering and merging of polygons in QGIS.

Figure IV shows Bukit Gombak's Natural Features that will be accounted in as an Natural Conservation factor in weighing the location suitability. The Natural features includes forest, park, water, and also waterway(canal, drain, stream). Waterway polygon was merged into the natural features in order to account in medium of disease transmission that could potentially cause disease spreading. We account this as risk factor that needed to be considered.

FIGURE V

Digital Elevation Map

Figure V shows Bukit Gombak's Elevation Map that will be accounted in as an Economical factor in weighing the location suitability. Most projects will always assess its cost in building. In estimation, slope inclination of about 15 degrees and beyond could add further costs to increase significantly as the risks become greater and the work becomes more difficult to build.

Part 2: Study Area Proximity Maps

FIGURE VI

Accessibility Factor: Road Proximity Map

After target map elements have been rasterised. We perform the raster proximity distance on its layer and apply binary model classification on all the factor layers. The legend of Proximity map layer indicates that the furthest distance from the roads is 796.304 metres.

FIGURE VII

Health Risk Factor: Building Proximity Map

Applying the same methods used on road proximity map, The legend of Proximity map layer indicates that the furthest distance from the buildings is 910 metres.

FIGURE VIII

Natural Conservation Factor: Natural Features Proximity Map

Next, the Figure VIII shows the Natural Features Proximity Map where the legend of Proximity map layer indicates that the furthest distance from the natural features is 948.117 metres.

FIGURE IX

Economic Factor: Slope Layer

Lastly, Figure IX shows the slope layer. The legend of Slope layer shows that the minimum and maximum values of the slope values are 0 and 34.5339 degrees respectively.

Criterion Scores for Map Components

FIGURE X

Accesibility Factor: Road Binary & Criteria Score

Figure X includes the accesibility binary model, where we prefer location under 200 m.

FIGURE XI

Health Risk Factor: Building Binary & Criteria Score

The Figure XI includes the health risk binary model where we prefer that buildings are 250 meters away from the Disease Quarantine Centre.

FIGURE XII

Natural Conservation Factor: Natural Features Binary & Criteria Score

Next, Figure XII includes the natural conservation risk binary model, where we prefer public natural features and waterways are 200 meters away from the centre.

FIGURE XIII

Economical Factor: Slope Binary & Criteria Score

Lastly, Figure XIII includes the economical factor binary model,where we locations where slope inclination is below or equal to 15 degrees.

Analytical Hierarchical Process Input Matrix & Approach

FIGURE XIV

SCB Associates' AHP Scoring Framework

FIGURE XV

AHP Scoring Framework for Accounting Factors

FIGURE XVI

AHP Results

FIGURE XVII

Weighing AHP Scores into QGIS Raster Calculator

FIGURE XVIII

Reclassifying Raster Values using SAGA's Plugin for Degrees of Suitability

Recommendation

FIGURE XIX

Suitability Map Overview

FIGURE XX

Qualitative Analysis: Zooming into Possible Region Using Google's Satelitte

FIGURE XXI

Making Recommendation based on Availibity of Land