The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W13
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1951–1957, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1951-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1951–1957, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1951-2019

  05 Jun 2019

05 Jun 2019

WORKABLE MONITORING SYSTEM BASED ON SPACEBORNE SAR IMAGES FOR MINING AREAS - STINGS DEVELOPMENT PROJECT

C. H. Yang1, A. Müterthies1, and U. Soergel2 C. H. Yang et al.
  • 1EFTAS Remote Sensing Transfer of Technology, Münster, Germany
  • 2Institute for Photogrammetry, University of Stuttgart, Stuttgart, Germany

Keywords: Differential Interferometric Synthetic Aperture Radar (DInSAR), Persistent Scatterer Interferometry (PSI), Small Baseline Subset (SBAS), Mining Monitoring, Sentinel-1, Disaster Prevention

Abstract. Nowadays monitoring of mining areas, e.g., regarding dam stability, has become increasingly important with rising awareness of safety and environmental protection. An appropriate monitoring scheme is necessitated to legally activate, reactivate, or terminate mining operations. Usually such monitoring relies on in situ surveys, which are unrealistic to cover an extensive mining area. Alternatively, remote sensing based on spaceborne data offers efficient and cost-effective solutions for regular surveillance of large areas. Spaceborne SAR sensors provide images captured rapidly over vast areas at fine spatiotemporal resolution. These sensors are characterized by weather independent and day-and-night vision, which guarantees intensive image series without cloud occlusion. Using multi-temporal SAR images, advanced DInSAR such as PSI and SBAS is a mature technique to evaluate surface deformation at best millimetre level. This technique has been commercialized as a standard service in many Geoinformation companies. Nevertheless, experts from other fields like mining engineers often doubt the information about movement derived from DInSAR. Our duty in industry is to solve these doubts and tailor our techniques for various applications. With the support of STINGS project, we have developed an initial prototype of our monitoring system. The final goal is to launch an interactive GIS-based platform as an early warning system to the public. In this paper, we demonstrate our initial test result using Sentinel-1 images at a mining site in Chile. We also propose the strategies to solve the problems in real applications and discuss how to improve the overall quality.