Quezon City soil profile reference

• Main Authors: Galupino, Joenel G., Dungca, Jonathan R.
• Format: text
• Published: Animo Repository 2019
• Subjects: Soils > Philippines > Quezon City—Analysis; oil profiles > Philippines > Quezon City; Machine learning; Civil and Environmental Engineering; Civil Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2361; https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=3360&context=faculty_research
• Institution: De La Salle University

The City of Quezon City is one of the highly urbanized cities and one of the fastest growing metropolitan areas in the Philippines, many local and foreign investors are discovering it as a cost-effective business location; many infrastructures were built to serve these growing business hub. Every infrastructure project constructed rests on the ground, without knowing the soil interaction underground, safety is at risk. Thus, this study aims to generate the soil profile of Quezon City using machine learning, specifically, k-Nearest Neighbor (k-NN) algorithm; k-Nearest Neighbor (k-NN) measured the similarity of soil types in terms of distance. The soil profile generated by the model was delineated using computer-aided design (CAD); it was discovered that the underground of the Quezon City is usually dominated by tuff. The generated soil profile will not only serve engineers to decide what type of foundations to be used for a particular site but will also be used for Disaster Risk Reduction (DRR) planning to mitigate ground related disasters; government zoning and policymakers for land use purposes; for real estate industry as their initial reference before investing. The nearest neighbor algorithm model used in the generation of the soil profiles was cross-validated to ensure the predictions are adequate. © Int. J. of GEOMATE.