JeromeQuah Ex2 CriterionScores

OVERVIEW	PROXIMITY	CRITERION SCORES	AHP	SUITABILITY

Gombak Study Area with Criterion Scores of:
- Economic Factor (Top Left)
- Health Risk Factor (Top Right)
- Natural Conservation Factor (Bottom Left)
- Accessibility Factor (Bottom Right)

In order to come up with a standardized Criterion Score, we would have to ensure that the scale used across all four maps would have to be uniformed as well as the raster values of all four maps denoting the same value meaning at both ends of the scale. To further understand this better, the following was considered: 1. Necessity to Standardise a Scale to Use Across All Four Factors Apart from the Proximity Map of Roads, Buildings and Natural Features having different minimum and maximum values in their respective scales, the Slope Layer measures degrees as its units of measurement for its scale. Therefore, we would need to standardize the scale for the criterion score so that this scale can be applied across all four maps and thus all four factors. 2. Necessity to Invert Raster Pixel Value of Certain Map Views Take the Health Risk Factor (Buildings) and Accessibility Factor (Roads) for example. For the Health Risk Factor, an area would be deemed favorable if the area was located away from the buildings. In the case the Accessibility Factor, an area would be deemed favourable if the area was instead located closer to the target roads. This means that their respective scales for their own views would be opposite with each other. From this, the following steps were carried out in the digitization of each of the views for this map: 1. Standardization: Normalization of all four Proximity Layers of the respective factors via the Minimum-Maximum Formula using the Raster Calculator Criteria Standardization Technique: The Minimum-Maximum Formula Example of Formula in Raster Calculator: (Proximity Map of Feature − Minimum Value of Proximity Map of Feature) ÷ (Maximum Value of Proximity Map of Feature − Minimum Value of Proximity Map of Feature) 2. Uniformity: Inversion of Raster Values of the Buildings and Natural Features Layer using the Raster Calculator Example of Formula in Raster Calculator: (1 − Normalized Proximity Map of Roads) 3. Symbology: Band Rendering of each of the Normalized Proximity Layers with a Linear Interpolation and Continuous Mode, providing the Criterion Score Scale of 0 to 1 for all four layers. 0 Represents the FAVOURABLE pixel value 1 Represents the UNFAVOURABLE pixel value

ECONOMIC FACTOR (SLOPE)

From the Economic Factor View (Top Left), the suitable site for the building of the CDQC would preferably be located within the green areas of the Gombak Boundary in this view. The red areas indicate unfavorable locations for the CDQC, which in turn indicates a high slope terrain in these locations.

HEALTH RISK FACTOR (BUILDINGS)

From the Health Risk Factor View (Top Right), the suitable site for the building of the CDQC would preferably be located within the green areas of the Gombak Boundary in this view, which cover the bottom area of Gombak. The red areas indicate unfavorable locations for the CDQC, in which these areas are in close proximity to the buildings.

NATURAL CONSERVATION FACTOR (NATURAL FEATURES)

From the Natural Conservation Factor (Bottom Left), the suitable site for the building of the CDQC would preferably be located within the green areas of the Gombak Boundary in this view, which cover a small Southern-East area of Gombak. The red areas indicate unfavorable locations for the CDQC, in which these areas are in close proximity to the natural features alike the Health Risk Factor View.

ACCESSIBILITY FACTOR (ROADS)

From the Accessibility Factor (Bottom Right), the suitable site for the building of the CDQC would preferably be located within the green areas of the Gombak Boundary in this view, which cover a huge portion of the areas in Gombak. The red areas indicate unfavorable locations for the CDQC, in which these areas are far from the roads.

REFERENCES

Lesson09_GIS Modelling for Urban Planning Support_v1.2.0, Page 8 of 13, Dr. Kam Tin Seong, Accessed 8th November 2019