Radar Interferometry for Ground Subsidence Monitoring Using Alos Palsar Data

This paper describes the results using data from ALOS and ENVISAT satellites for the purpose of subsidence monitoring over underground coal mine sites in the state of New South Wales, Australia, using the differential interferometric synthetic aperture radar (DInSAR) technique. The quality of the mine subsidence monitoring results is mainly constrained by the noise due to the spatial and temporal decorrelation between the interferometric pair and the phase discontinuities in the interferogram. This paper reports on the analysis of the impact of these two factors on the performance of DInSAR for monitoring ground deformation. The ALOS L-band PALSAR DInSAR results have been compared to DInSAR results obtained from ENVISAT C-band ASAR data to investigate the performance of ALOS PALSAR for ground subsidence monitoring. Differential interferograms from SAR data acquired using different operating frequencies, for example, X-, Cand L-band, from the TerraSAR-X, ERS-1/2, ENVISAT, JERS-1 and ALOS satellite missions, were simulated. The simulation results showed that the new satellites ALOS, TerraSAR-X and COSMO-SkyMed perform much better than the others. ALOS PALSAR and ENVISAT ASAR images with similar temporal coverage were searched. The two-pass DInSAR technique with a 25m DEM was used to measure the location and amplitude of ground deformation. Strong phase discontinuities and decorrelation have been observed in almost all ENVISAT interferograms and hence it is not possible to generate the displacement maps. However these problems are minimal in ALOS PALSAR interferograms due to its spatial resolution and longer wavelength. Six successive subsidence maps are generated with eight ALOS PALSAR images from both ascending and descending orbits. The results are compared with ground survey data at two sites with RMS error of 1.7cm and 0.6cm being achieved. The accumulated subsidence can be estimated by adding up all subsidence maps; however the error in each DInSAR result, such as the geocoding error between each result, will also accumulate. An approach for minimising geocoding error in order to calculate the accumulated subsidence from a series of SAR images is described.