Quantifying Relationships Between Subsidence and Longwall Face Advance Using DInSAR

Society for Mining, Metallurgy & Exploration
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Society for Mining, Metallurgy & Exploration
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5
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1625 KB
Publication Date:
Jan 7, 2020

Abstract

Surface subsidence that results from longwall mining can be large magnitude and can affect significant areas. Conventional methods for subsidence monitoring include leveling, global positioning system (GPS), and photogrammetric surveys. Remote sensing techniques, including aerial LiDAR, terrestrial laser scanning, and satellite-based differential interferometric synthetic aperture radar (DInSAR), are also used to measure deformation associated with subsidence. DInSAR data are different than data from conventional subsidence surveys. Images capture data over large areas (hundreds of kilometers), and each pixel (data point) in an image quantifies the average displacement over an area of square meters. DInSAR data can have fairly high time resolution; imaging periods typically range from weeks to months.
Citation

APA:  (2020)  Quantifying Relationships Between Subsidence and Longwall Face Advance Using DInSAR

MLA: Quantifying Relationships Between Subsidence and Longwall Face Advance Using DInSAR. Society for Mining, Metallurgy & Exploration, 2020.

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