Share Email Print

Journal of Applied Remote Sensing

Integrating the probability integral method for subsidence prediction and differential synthetic aperture radar interferometry for monitoring mining subsidence in Fengfeng, China
Author(s): Xinpeng Diao; Kan Wu; Dawei Zhou; Liang Li
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Differential synthetic aperture radar interferometry (D-InSAR) is characterized mainly by high spatial resolution and high accuracy over a wide coverage range. Because of its unique advantages, the technology is widely used for monitoring ground surface deformations. However, in coal mining areas, the ground surface can suffer large-scale collapses in short periods of time, leading to inaccuracies in D-InSAR results and limiting its use for monitoring mining subsidence. We propose a data-processing method that overcomes these disadvantages by combining D-InSAR with the probability integral method used for predicting mining subsidence. Five RadarSat-2 images over Fengfeng coal mine, China, were used to demonstrate the proposed method and assess its effectiveness. Using this method, surface deformation could be monitored over an area of thousands of square kilometers, and more than 50 regions affected by subsidence were identified. For Jiulong mine, nonlinear subsidence cumulative results were obtained for a time period from January 2011 to April 2011, and the maximum subsidence value reached up to 299 mm. Finally, the efficiency and applicability of the proposed method were verified by comparing with data from leveling surveying.

Paper Details

Date Published: 21 March 2016
PDF: 15 pages
J. Appl. Rem. Sens. 10(1) 016028 doi: 10.1117/1.JRS.10.016028
Published in: Journal of Applied Remote Sensing Volume 10, Issue 1
Show Author Affiliations
Xinpeng Diao, China Univ. of Mining and Technology (China)
Kan Wu, China Univ. of Mining and Technology (China)
Dawei Zhou, China Univ. of Mining and Technology (China)
Rwth Aachen University (Germany)
Liang Li, China Univ. of Mining and Technology (China)

© SPIE. Terms of Use
Back to Top