Abstract
Pipeline is one of the premier means of transportation for petroleum products. Optimizing the cost, time of construction and environmental considerations for pipeline route, depends on the determination of optimal route for pipeline alignment. In this paper, an intelligent system capable of identifying optimal (based on cost, engineering criteria, and environmental issues) land corridor for alignment of natural gas pipeline from source to destination within onshore has been proposed. Accessing results by analyzing large datasets is achieved through spatial multi-criteria decision-making strategy. A preliminary implementation of the proposed system is being done to identify land corridor for alignment of gas pipeline from Shahdol (Latitude 23 18′ 07″ N and Longitude 81 21′ 24″ E in Madhya Pradesh, India) to Phulpur (Latitude 25 33′ 03″ N and Longitude 82 05′ 18″ E in Uttar Pradesh, India). Slope, crossings (road networks, rail tracks, rivers etc.), forests, vegetation and costs have been considered as criteria for identification of optimal land corridor. For implementation and analysis of the proposed work, Landsat 8 images, having spatial resolution 30 m, are used for analysis purpose. The study also made use of state boundary, road network, river network, elevation, and land cover type data. Data layers for analysis have been created using distance criteria. Finally, different layers of criteria have been merged using Analytical Hierarchical Process (AHP) algorithm to de ne two cost layers the Cost Distance Layer and Cost Direction Layer. Finally, depending on guiding criteria, the least cost path from source to destination station has been identified as the optimal land corridor for alignment of gas pipeline. To make the system more intelligent is the future scope of this work.
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Sawant, S., Kumar, R., Kumar, R. (2020). An Intelligent Gas Pipeline Route Alignment System. In: Ghosh, J., da Silva, I. (eds) Applications of Geomatics in Civil Engineering. Lecture Notes in Civil Engineering , vol 33. Springer, Singapore. https://doi.org/10.1007/978-981-13-7067-0_33
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DOI: https://doi.org/10.1007/978-981-13-7067-0_33
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