Estimation of Mining and Landfilling Activities with Associated Overburden through Satellite Data: Germany 2000–2010

Keisuke Yoshida, Keijiro Okuoka, Alessio Miatto, Liselotte Schebek and Hiroki Tanikawa
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Keisuke Yoshida: Railway Systems Business Unit, Hitachi, Tokyo 101-8608, Japan
Keijiro Okuoka: Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan
Alessio Miatto: School of Forestry & Environmental Studies, Yale University, New Haven, CT 06511, USA
Liselotte Schebek: Faculty of Civil and Environmental Engineering, Technical University of Darmstadt, Darmstadt 64287, Germany
Hiroki Tanikawa: Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan

Resources, 2019, vol. 8, issue 3, 1-17

Abstract: Despite ever-increasing material extraction on the global scale, very few studies have focused on the relationship between mining activities, overburden, and landfilling. This is mainly due to the lack of statistical data. Yet, large mining activities cause environmental strain to the natural environment, and are often cause of irreversible alterations to the natural landscape. To circumvent this problem, we develop a methodology that employs the digital elevation model and land cover to detect and analyze mining and landfilling site over time. We test our methodology with the case of Germany for the years 2000–2010. We then confront our results with statistically available data, to verify whether this methodology can be applied to other countries. Results from the analysis of satellite data give 15.3 Pg of extracted materials and 7.8 Pg of landfilled materials, while statistics report 29.4 Pg and 1.8 Pg, respectively. This large difference was likely due to the different frequency of recording, where satellite data was updated after 10 years, while statistics were reported yearly. The analysis of the anthropogenic disturbance with spatial information can effectively contribute to observe, analyze, and quantify mining activities, overburden, and landfills, and can thus provide policy makers with useful and practical information regarding resource usage and waste management.

Keywords: anthropogenic disturbance; digital elevation model (DEM); land cover; mining; overburden; remote sensing (search for similar items in EconPapers)
JEL-codes: Q1 Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2019
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