From the CFA result, five possible scenarios are drawn. Implementing
the first factor, Socio-Demographic, results in an HSR route
avoiding major population centers, highly occupied blocks, and jobconcentrated
centers. The second factor, Built-Environment, enables
the route to detour around highly developed areas, reducing
the probability of crossing major roads, and minimizing negative
noise effects from the HSR operation. The Ground-Resources factor
intends to preserve major aquifers, to find suitable geology types,
and to evade higher precipitation areas. The fourth factor, Water
Resources, is designed to preserve water resources as it reduces the
probability of crossing major streams, environmentally beneficial
wetlands, and areas at high risk to floods. The final factor, Green
Space, aids in conserving green infrastructure through minimizing a
route’s presence on productive farmlands, finding the most suitable
grades for HSR construction, and preserving natural vegetation
covers. Each factor indicates different priorities so that the resulting
HSR routes can vary accordingly. This is how the proposed SDSS
improves upon the first limitation identified in current practices. By
systematically grouping the input variables based on each variable’s
underlying characteristics, the limitations stemming from biased
variable categorization are mitigated to a great degree.
From the CFA result, five possible scenarios are drawn. Implementingthe first factor, Socio-Demographic, results in an HSR routeavoiding major population centers, highly occupied blocks, and jobconcentratedcenters. The second factor, Built-Environment, enablesthe route to detour around highly developed areas, reducingthe probability of crossing major roads, and minimizing negativenoise effects from the HSR operation. The Ground-Resources factorintends to preserve major aquifers, to find suitable geology types,and to evade higher precipitation areas. The fourth factor, WaterResources, is designed to preserve water resources as it reduces theprobability of crossing major streams, environmentally beneficialwetlands, and areas at high risk to floods. The final factor, GreenSpace, aids in conserving green infrastructure through minimizing aroute’s presence on productive farmlands, finding the most suitablegrades for HSR construction, and preserving natural vegetationcovers. Each factor indicates different priorities so that the resultingHSR routes can vary accordingly. This is how the proposed SDSSimproves upon the first limitation identified in current practices. Bysystematically grouping the input variables based on each variable’sunderlying characteristics, the limitations stemming from biasedvariable categorization are mitigated to a great degree.
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