Difference between revisions of "EX2 Lim Zhong Zhen Timothy"

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[[SMT201_AY2018-19T1_EX2_Lim_Zhong_Zhen_Timothy| <font color="#FFFFFF"> About </font>]]
 
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[[EX2_Lim_Zhong_Zhen_Timothy| <font color="#FFFFFF"> Analysis </font>]]
 
[[EX2_Lim_Zhong_Zhen_Timothy| <font color="#FFFFFF"> Analysis </font>]]
  
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Revision as of 00:34, 11 November 2019

About

Analysis

AHP / Criterion

Criterion Maps

Overview of all components
Overview of all components
Overview of all components
Overview of all components


Data preparation

In order to do a ranked analysis, the layer data have to be normalised as the data now vary in scale. To that, Min-Max normalisation was used.
For example, To normalise road proximity, we take the (current_data - min_of given layer)/(max_of given layer - min_of given layer):" "Prox_road@1" - 0 / (703.28" - 0)
Another thing to note, is that the results for roads and steepness needs to be inversed. As the closer the roads or less steep the land the better! Thus, I took (1 - normalised data) to get the correct comparison.

Next step

Factor Priority Reason AHP Scoring



Health Risk 1 CDQC's top priority is to keep the diseased away from the general population, this is prevent the virus from spreading and causing an epidemic. Thus, this factor is highest

priority

9
Accessibility 2 Transportation is the key issue in swiftly getting the patient away from the masses. Thus, accessibility is also given a very high priority. 7
Natural Conservation 3 Although important, Parks and water beds and forests is not as populated as the buildings. 3
Economic 4 Singapore has limited land space, and do not have a lot of non-steep land. Thus, I believe it is worth investing on a place which poses less health risk, has good transportation and further away from natural conservation. 1

Using the AHP template given by prof Kam, I performed a PairWise Comparison matrix to calculate weightage comparison of each factor.

AHP template


AHP template


The results show the weightage of each Factor, with 4.7% assigned to Economic, 36.6% to Accessibility, 47.9% to Health Risk and 10.9% to Natural Conservation

Suitability Map

Data prepartion

Using the data from the AHPmatrix, I created a ranked model for the suitability of the land for CDQC. To do so, I had to take the each factor multiplied by its percentage weightage.

About

Analysis