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Methodologies in Identification, Analysis, and Measurement of Visual Pollution: The Case Study of Intramuros

Stanley Don Barroga, Nappy L. Navarra, Honorio T. Palarca
Published: 1 April 2021
Jurnal Lanskap Indonesia , Volume 13, pp 19-26; doi:10.29244/jli.v13i1.33322

Abstract: The problem of visual pollution in the Philippines has been increasingly evident, and people are becoming aware of it. But to create effective solutions, a deep understanding of the problem should first be established. This paper was aimed to identify, analyze, and measure the visual pollution present in Intramuros, a heritage city in the Philippines that encapsulates the Philippine colonial architecture in the 1890s. The site is known for its preservation of its city image but also modern landscape changes. To achieve the goal, the application of the Indirect and Direct Method of Landscape Evaluation was executed. These methods led to two results: (1) the identification of components— which are landscape attributes and indicators, that make up a visual landscape; and (2) the understanding of how it is perceived by the observer through a survey and interviews, which are quantified by ratings. To further understand the relationship of indicators and ratings with each other, a series of correlational studies was done. This resulted to the establishment of Disturbance, Stewardship, and Image Rating as the primary descriptors of visual pollution. A weighted average formula was then established, which quantified the visual pollution of Intramuros through indicator values and response ratings. It was concluded that visual pollution in Intramuros, through research-based methodology, can be identified, analyzed, and measured. Specific viewpoints in the district were identified as unacceptably visually-polluted. Magallanes St. cor. Victoria St. in Intramuros had the highest VP Score at -4.886. Elements that contributed to visual pollution were also identified.
Keywords: survey / landscape / identification / Philippines / visual pollution / Intramuros / quantified

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