Detail publikace

Surface Classification Above Gas Pipeline Facilities

Originální název

Surface Classification Above Gas Pipeline Facilities

Anglický název

Surface Classification Above Gas Pipeline Facilities

Jazyk

en

Originální abstrakt

The article discusses a surface classification above the stored gas facilities in the territory under the administration of the RWE Company in the Czech Republic (CR). The aim of the project was to determine reproductive values of these facilities and a reasonable estimate of the costs that would be spent on a construction of new pipelines. The classification uses a raster dataset of orthophoto with the resolution of 25 cm/1 pixel, a vector dataset of the Fundamental Base of Geographic Data (ZABAGED) and vector datasets of the route of underground utilities. As part of the assignment, it was necessary to classify a surface from two perspectives: from the object standpoint (the surface above gas facilities) and the spatial standpoint (administrative division of the territory of the CR). The authors have succeeded in creating a technological line (workflow) with a high degree of automation. The core of this workflow is a geographic information system (GIS). The technology has been implemented within a special application developed in Python language with a support of the ESRI libraries and ArcGIS 10.0. It is massive task given the territorial coverage of almost the whole of the CR with the area of 64,350 km2 with a data volume of the order of 500 GB. The results demonstrated the effectiveness of proposed procedure to achieve low error rate in the range of 2% - 3% across the modeled area.

Anglický abstrakt

The article discusses a surface classification above the stored gas facilities in the territory under the administration of the RWE Company in the Czech Republic (CR). The aim of the project was to determine reproductive values of these facilities and a reasonable estimate of the costs that would be spent on a construction of new pipelines. The classification uses a raster dataset of orthophoto with the resolution of 25 cm/1 pixel, a vector dataset of the Fundamental Base of Geographic Data (ZABAGED) and vector datasets of the route of underground utilities. As part of the assignment, it was necessary to classify a surface from two perspectives: from the object standpoint (the surface above gas facilities) and the spatial standpoint (administrative division of the territory of the CR). The authors have succeeded in creating a technological line (workflow) with a high degree of automation. The core of this workflow is a geographic information system (GIS). The technology has been implemented within a special application developed in Python language with a support of the ESRI libraries and ArcGIS 10.0. It is massive task given the territorial coverage of almost the whole of the CR with the area of 64,350 km2 with a data volume of the order of 500 GB. The results demonstrated the effectiveness of proposed procedure to achieve low error rate in the range of 2% - 3% across the modeled area.

BibTex


@inbook{BUT114699,
  author="Dalibor {Bartoněk} and Jiří {Bureš} and Irena {Opatřilová}",
  title="Surface Classification Above Gas Pipeline Facilities",
  annote="The article discusses a surface classification above the stored gas facilities in the territory under the administration of the RWE Company in the Czech Republic (CR). The aim of the project was to determine reproductive values of these facilities and a reasonable estimate of the costs that would be spent on a construction of new pipelines. The classification uses a raster dataset of orthophoto with the resolution of 25 cm/1 pixel, a vector dataset of the Fundamental Base of Geographic Data (ZABAGED) and vector datasets of the route of underground utilities. As part of the assignment, it was necessary to classify a surface from two perspectives: from the object standpoint (the surface above gas facilities) and the spatial standpoint (administrative division of the territory of the CR). The authors have succeeded in creating a technological line (workflow) with a high degree of automation. The core of this workflow is a geographic information system (GIS). The technology has been implemented within a special application developed in Python language with a support of the ESRI libraries and ArcGIS 10.0. It is massive task given the territorial coverage of almost the whole of the CR with the area of 64,350 km2 with a data volume of the order of 500 GB. The results demonstrated the effectiveness of proposed procedure to achieve low error rate in the range of 2% - 3% across the modeled area.",
  address="Springer",
  booktitle="Surface models for Geosciences",
  chapter="114699",
  doi="10.1007/978-3-319-18407-4_3",
  edition="Lecture Notes in Geoinformation and Cartography",
  howpublished="online",
  institution="Springer",
  year="2015",
  month="june",
  pages="27--36",
  publisher="Springer",
  type="book chapter"
}