Research on efficient statistical method of surface coverage data along the pipeline

Qiuxia Tan; Ming Liu; Huiqing Zhu; Mingming Kou; Feige Zheng

doi:10.1117/12.2656604

20 October 2022 Research on efficient statistical method of surface coverage data along the pipeline

Qiuxia Tan, Ming Liu, Huiqing Zhu, Mingming Kou, Feige Zheng

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 124510Z (2022) https://doi.org/10.1117/12.2656604
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

In order to improve the reliability of pipeline design, a large amount of rich spatial data is required in the early stage of the project. Usually, the project in this stage does not require high data accuracy, but requires a large spatial coverage. At the same time, the construction period is usually very tight, and it is inconvenient to carry out a large number of field data collection works. This paper proposes to convert the route to SHP format through the FME tool, cut out the corresponding part of the TIF data, convert the raster data into vector data and perform area calculation, and then classify and output the statistical area. Through this process of FME, the surface coverage within 2 kilometres along the pipeline can be quickly and effectively calculated, and the vector data of the corresponding area can be output at the same time. It provides an important data basis for optimizing the route selection scheme and calculating the restoration of soil and water conservation plants and the compensation of surface economic crops.

Citation Download Citation

Qiuxia Tan, Ming Liu, Huiqing Zhu, Mingming Kou, and Feige Zheng "Research on efficient statistical method of surface coverage data along the pipeline", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 124510Z (20 October 2022); https://doi.org/10.1117/12.2656604

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