APPLICATION OF VARIOUS OPEN SOURCE VISUALIZATION TOOLS FOR EFFECTIVE MINING OF INFORMATION FROM GEOSPATIAL PETROLEUM DATA

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Babu, A.^1¹  Gholba, N. D.^1² 

[1] Geoinformatics Department, Indian Institute of Remote Sensing, Dehradun, Uttrakhand, India^2;M. Tech Students, Indian Institute of Remote Sensing, Dehradun, Uttrakhand, India^1

关键词: Open Source Geodata Visualization;    Data Mining;    Global Petroleum Statistics;    QGIS;    R;    Sankey Maps;   

DOI  :  10.5194/isprs-archives-XLII-5-167-2018

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

This study emphasizes the use of various tools for visualizing geospatial data for facilitating information mining of the global petroleum reserves. In this paper, open-source data on global oil trade, from 1996 to 2016, published by British Petroleum was used. It was analysed using the shapefile of the countries of the world in the open-source software like StatPlanet, R and QGIS. Visualizations were created using different maps with combinations of graphics and plots, like choropleth, dot density, graduated symbols, 3D maps, Sankey diagrams, hybrid maps, animations, etc. to depict the global petroleum trade. Certain inferences could be quickly made like, Venezuela and Iran are rapidly rising as the producers of crude oil. The strong-hold is shifting from the Gulf countries since China, Sudan and Kazakhstan have shown a high rate of positive growth in crude reserves. It was seen that the global oil consumption is not driven only by population but by lifestyle also, since Saudi Arabia has a very high rate of per-capita consumption of petroleum, despite very low population. India and China have very limited oil reserves, yet have to cater to a large population. These visualizations help to understand the likely sources of crude and refined petroleum products and to judge the flux in the global oil reserves. The results show that geodata visualization increases the understanding, breaks down the complexity of data and enables the viewer to quickly digest the high volumes of data through visual association.

【 授权许可】

CC BY