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Stockpile Monitoring Using Linear Shape-From-Shading on Planetscope Imagery

  • Marie D'AUTUME*
  • , Alexandra PERRY
  • , Jean-Michel MOREL
  • , Enric MEINHARDT-LLOPIS
  • , Gabriele FACCIOLO
  • *Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

The storage and management of stockpiles of materials is a fundamental process in large scale activities such as mining, civil engineering, and in the management of waste landfill sites. Following the evolution of stocks has always been important, and advancements in remote sensing technology are not only facilitating this, but also making it possible in near real-time. Nowadays, this monitoring appears to be performed almost exclusively using UAV based techniques. This paper proposes to apply a simple Shape-from-Shading method on low resolution satellite images provided by PlanetScope to monitor the evolution of the volume of stockpiles. The proposed Shape-from-Shading formulation makes it possible to handle occluding objects in the scene. The loss in accuracy due to the low resolution of PlanetScope images is well compensated by the daily revisit frequency and by the fact that spaceborne acquisitions require no human supervision. With satellites it is also easy to follow simultaneously several stocking sites all over the world. We test our method on two coal storage sites and demonstrate that the stockpiles are well detected.
Original languageEnglish
Pages (from-to)427-434
Number of pages8
JournalISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume5
Issue number2
DOIs
Publication statusPublished - 3 Aug 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 Copernicus GmbH. All rights reserved.

Funding

Work partly financed by the Office of Naval Research grant N00014-17-1-2552, CNES MISS project, DGA Astrid project ≪filmer la Terre≫ no ANR-17-ASTR-0013-01.

Keywords

  • Shape-from-Shading
  • time series
  • satellite imagery
  • stockpiles monitoring

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