TOPOPHILIA-EXPOSURE CENTRAL SPACE CONCEPT MODEL
- 1Bicol University, Geodetic Engineering Faculty, Legazpi City, Philippines
- 2Bicol University, Research Faculty, Legazpi City, Philippines
Keywords: Topophilia-Exposure, Central Space, Tessellated Bin, Philia-Binning, safety, comfort, origin
Abstract. This study proposes how a hexagon object (rather than a perfect circle) is a better representation of a data bin to visualize weighted spatial information, in analysing location (space center), and sorted local knowledge on ‘topophilia-exposure’. This approach which depicts the topographic features sorted in a tessellated bin, correlated with the origin (space center), and geographic knowledge on love of a place (tessellated space), was sought to understand the relationships of ‘topo’(topography), ‘philia’ (love of), and exposure data, sorted in a hexagonal lattice shaped cell or bin as spatial objects, where each hexagon has an area of 100 hectares (tessellated bin mapping unit) at a 1 kilometer continuous interval between centroids (central space of hexagon). The ‘topophilia-exposure’ central space concept model is designed to look at the ‘Phila’ factors influencing selected exposed residents situated in spaces at risk. This paper shows the effect of ‘Philia’ elements in the exposed sample Barangays (villages) in Daraga, and Guinobatan towns, Albay, Philippines. These factors dissuade residents from permanently relocating to safer areas, despite the obvious risks involved with staying. Undesired development and sprawling in vulnerable landscapes and danger zones make reducing disaster risk difficult to accomplish; and relocation is often the required option for some areas. Undoubtedly, the factors of Topophilia complicate even the most logical and scientific options for disaster risk reduction and mitigation. This paper finally concludes that the topophilia-exposure model is a model that reflects the phenomena of disaster risk, Exposure complicated by the “love of land” will prevail, and may increase; surely causing complexities in Disaster Risk Reduction and Management.