Least-Cost Pipeline using Geographic Information System: The Limit to Technicalities

Least-Cost Pipeline using Geographic Information System: The Limit to Technicalities

Matthew Biniyam Kursah (Geography Department, University of Education Winneba, Winneba, Ghana)
Copyright: © 2017 |Pages: 15
DOI: 10.4018/ijagr.2017070101
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Abstract

Increasing demand for water in Wapuli and its environ led to a proposal to construct a pipeline to link the town to an existing water plant. This paper developed a geospatial model incorporating multi-criteria analysis involving technical factors such as slope, landcover, watercourses, distance to roads and soil types to determine a least-cost path for the pipeline. However, the first least-cost path passes through a tiny sacred grove near Moadani dam, necessitating the generation of a second least-cost path by considering sacred groves as constraint. The result showed that the least-cost path avoided steep slopes, and runs through relatively levelled grounds. This analysis showed the importance of cultural factors in route planning. It is recommended that in route planning attention be given to cultural factors much in the same way as the technical factors.
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Literature Review

Least-cost path is referred with different names; best path, shortest path, optimal path and cheapest path. In all its usages, it means the route with the lowest cost of construction after factoring all the necessary varying criteria which influence route construction and maintenance (Atkinson, Deadman, Dudycha, & Traynor, 2005; Choi, Park, Sunwoo, & Clarke, 2008; Ismail & Jusoff, 2009; Saha et al., 2005; Yu, Lee, & Munro-Stasiuk, 2003). The least-cost path analysis requires multi-criteria evaluation (MCA) to determine the relative importance or weights of multiple factors (Atkinson et al., 2005). Thus, least-cost path is generated from cost dataset or thematic cost surface. This is a raster map where value at each cell gives the estimated cost of passing through the pixel (Saha et al., 2005). The cost here represents the difficulty, resistance or friction in crossing the cell (Collischonn & Pilar, 2000). Thus, the thematic cost layer or cost dataset provides an estimate of the cost of route construction and maintenance over an area (Saha et al., 2005).

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