Material Stock Data Extraction Method Using Geographical Imagery Information in Material Flow Analysis for Railway Infrastructure

Abstract

Several industries, such as raw materials, construction, energy, and transportation, have extensively employed the MFA method and approach. However, the use of MFA is mainly limited due to the lack of regional data, uncertainty in the available data, and lack of input data in some cases. Data limitation for MFA is addressed but with limited success, particularly for building infrastructure. This study has addressed this issue by employing Google Earth as a secondary method that can potentially extract data applicable to MFA. This data collection approach is applied to the French Railway Infrastructure by systematically selecting 95 railway tracks covering more than 9,000 km of track length, and the results were verified with the SNCF statistical data based upon the developed parameters. This study contributes to overcoming data issues of MFA and accelerates the application of MFA on a broader scale.

Keywords: region, resource, material flow analysis, geographical information, railway, infrastructure