• Title of article

    A prototype for pipeline routing using remotely sensed data and geographic information system analysis

  • Author/Authors

    Feldman، نويسنده , , Sandra C. and Pelletier، نويسنده , , Ramona E. and Walser، نويسنده , , Ed and Smoot، نويسنده , , James C. and Ahl، نويسنده , , Douglas، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 1995
  • Pages
    9
  • From page
    123
  • To page
    131
  • Abstract
    A prototype least cost analysis was performed for pipeline routing using remotely sensed data and GIS analysis. A small section of the proposed Caspian oil pipeline was chosen for development of the prototype. The entire proposed 700-km Caspian pipeline would connect with existing pipelines and carry oil from the Tengiz oil field in Kazakhstan, on the Caspian Sea, to Novorossiysk in Russia, on the Black Sea. A model was developed incorporating pipeline length, topography, geology, land use, and stream, wetland, road, and railroad crossings to identify a least cost pathway. Satellite remote sensing imagery was used as a base to display results and to define the land cover. Geographic Information System (GIS) analysis was used for spatial modeling and data overlay. Costs associated with terrain conditions, geology, and land use were calculated from actual costs on a recent Bechtel pipeline project. The length and cost associated with a straight line path between four predetermined points along a section of the pipeline were compared with the length and cost of the least cost pathway. The straight line path was 42 km long, and the least cost pathway was 51 km long. Although longer in length, the least cost pathway (in the area considered) is 14% less expensive to construct than the straight line path. The least cost pathway realizes savings principally by avoiding higher cost urban and industrial cells on the straight line route. The results of this analysis demonstrate the benefits of integrating remotely sensed data with GIS analysis as a first look for pipeline routing.
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    1995
  • Journal title
    Remote Sensing of Environment
  • Record number

    1571933