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• W4313491172 startingPage "106852" @default.
• W4313491172 abstract "Material flow analysis (MFA) is a powerful tool to track and estimate material flows and stocks and evaluate the efficiency of the materials used in the modern infrastructure. 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 (20% of the total number of tracks) covering more than 9,000 km of track length (∼31% of the total), and the results were verified with the SNCF (Societe Nationale des Chemins de fer Francais) 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." @default.
• W4313491172 created "2023-01-06" @default.
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• W4313491172 date "2023-03-01" @default.
• W4313491172 modified "2023-10-02" @default.
• W4313491172 title "Potentiality of using Google Earth to extract material stock data from technosphere for Material Flow Analysis" @default.
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• W4313491172 doi "https://doi.org/10.1016/j.resconrec.2022.106852" @default.
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