Hsing-Chung Chang

Mine subsidence monitoring using multi-source satellite SAR images

Ground subsidence due to underground mining has posed a constant threat to the safety of surface infrastructure such as motorways, railways, power lines, and telecommunications cables. Traditional monitoring techniques like using levels, total stations and GPS can only measure on a point-by-point basis and hence are costly and time-consuming. Differential interferometric synthetic aperture radar (DINSAR) together with GPS and GIS have been studied as a complementary alternative by exploiting multi-source satellite SAR images over a mining site southwest of Sydney. Digital elevation models (DEMs) derived from ERS-1 and ERS-2 tandem images, photogrammetry, airborne laser scanning, and the Shuttle Radar Topography Mission were assessed based on ground survey data using levelling as well as GPS-RTK. The identified high quality DEM was then used in the DINSAR analysis. Repeat-pass acquisitions by the ERS-1, ERS-2, JERS-1, RADARSAT-1 and ENVISAT satellites were used to monitor mine subsidence in the region with seven active mine collieries. Sub-centimeter accuracy has been demonstrated by comparing DINSAR results against ground survey profiles. The ERS tandem DINSAR results revealed mm-level resolution.

Assessment of Radar Interferometry Performance for Ground Subsidence Monitoring due to Underground Mining

This paper describes the results from the recently launched SAR satellites for the purpose of subsidence monitoring over underground coal mine sites in the state of New South Wales, Australia, using differential interferometric synthetic aperture radar (DInSAR) technique. The quality of the mine subsidence monitoring results is mainly constrained by 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. Simulations were carried out prior to real data analyses. SAR data acquired using different operating frequencies, for example, X-, C- and L-band, from the TerraSAR-X, ERS-1/2, ENVISAT, JERS-1 and ALOS satellite missions, were examined. The simulation results showed that the new satellites ALOS, TerraSAR-X and COSMO-SkyMed perform much better than the satellites launched before 2006. ALOS and ENVISAT satellite SAR images with similar temporal coverage were searched for the test site. The ALOS PALSAR DInSAR results have been compared to DInSAR results obtained from ENVISAT ASAR data to investigate the performance of both satellites for ground subsidence monitoring. Strong phase discontinuities and decorrelation have been observed in almost all ENVISAT interferograms and hence it is not possible to generate the displacement maps without errors. However these problems are minimal in ALOS PALSAR interferograms due to its spatial resolution and longer wavelength. Hence ALOS PALSAR is preferred for ground subsidence monitoring in areas covered by vegetation and where there is a high rate ground deformation.

Deformation mapping in three dimensions for underground mining using InSAR – Southern highland coalfield in New South Wales, Australia

This article presents 3D surface deformation mapping results derived from satellite synthetic aperture radar (SAR) data acquired over underground coal mines. Both ENVISAT Advanced Synthetic Aperture Radar (ASAR) and Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data were used in this study. The quality of the 3D deformation mapping results due to underground mining is mainly limited by two factors. (1) Differential interferometric synthetic aperture radar (DInSAR) is less sensitive to displacement along the north–south direction in the case of the current SAR satellite configurations. (2) The mining-induced displacement is continuous and nonlinear; and the accuracy of the 3D DInSAR measurement is severely affected by the similar but non-identical temporal overlaps of the InSAR pairs. The simulation and real data analyzes have shown that it would be more practical to use DInSAR pairs with the assumption of negligible northing displacement to derive the displacements in the easting and vertical directions. The northing displacement could then be estimated from the residuals. This limitation could be overcome in the future with the launch of more radar satellites, which would provide better viewing geometry.

Preliminary Results of Satellite Radar Differential Interferometry for the Co-seismic Deformation of the 12 May 2008 Ms8.0 Wenchuan Earthquake

Abstract Satellite differential SAR interferometry has been widely accepted as a powerful tool to map co-, post- and inter-seismic deformation since its successful application to the 1992 Landers Earthquake. As soon as the Ms8.0 Wenchuan Earthquake occurred on 12 May 2008 in the Sichuan Province of southwestern China, the Japan Aerospace Exploration Agency tasked its Advanced Land Observing Satellite (ALOS) to respond to the disaster by collecting images. This paper presents the preliminary DInSAR results of co-seismic deformation of the quake observed from two satellite paths of the onboard ALOS/PALSAR sensor with post-seismic images acquired on 19 and 24 May. Results from pixel offset analysis and difference of coherence will also be discussed. The radar mapping is still ongoing because the ruptured seismic fault is more than 300km in length. Each swath of the PALSAR fine beam covers only about a 75km segment of the fault, and it takes 46 days for ALOS to revisit the same site.

Validation of DEMs derived from radar interferometry, airborne laser scanning and photogrammetry by using GPS-RTK

A high resolution digital elevation model (DEM) enables easy derivation of subsequent information for various applications. This work uses real-time kinematic (RTK) GPS to examine the quality of some DEMs generated by such means as radar interferometry (InSAR), airborne laser scanning (ALS) and photogrammetry. The preliminary results show that a DEM generated from ALS has the highest accuracy with a RMS error of 0.09 /spl sim/ 0.3 m. The RMS errors of DEMs derived by photogrammetric and radar interferometric techniques are 1.03 /spl sim/ 3.75m and 4.26 /spl sim/ 27.81 m respectively.

DInSAR for mine subsidence monitoring using multi-source satellite SAR images

This paper demonstrates the use of differential interferometric synthetic aperture radar (DInSAR) for mine subsidence monitoring in Australia. The C-band SAR imagery acquired by ERS-1/2 and Radarsat-1 and L-band data acquired by JERS-1 were tested. As the satellites have different re-visit periods so that the mine subsidence occurred during the intervals of 1, 24, 35 and 44 days can be observed. The C-band InSAR results generally have lower coherence over vegetated areas, but the Radarsat-1 fine-beam mode data demonstrated that decorrelation can be reduced by having finer imaging resolution and shorter temporal separation. Another difficulty of DInSAR for mine subsidence monitoring is to resolve the phase ambiguity in interferogram. The L-band SAR data with comparatively longer wavelength than C-band showed it is more suitable for mining subsidence monitoring where large displacement over a small spatial extent occurs.

Estimating the greatest dust storm in eastern Australia with MODIS satellite images

On the 23rd of September 2009, Sydney encountered its most severe dust storm in 70 years. The dusts were originated from the Lake Eyre Basin and elevated and swept across the Australian Capital Territory, New South Wales, and Queensland by gusty winds. Ground air quality observation indicated that the dust particle density was 70 times higher than the normal when the dusts struck Sydney. The authors have researched MODIS satellite optical imagery in order to monitor this severe dust storm, and have extracted the information from the satellite images through computing the brightness temperature difference of two thermal infrared channels of MODIS imagery. This method is effective in separating dust and clouds. The mass of the dust plume, therefore, has been estimated using a retrieval model. However, the result of the mass is believed to be under-estimated because the extent of dusts was too great to be covered by a single MODIS image.

Impact of ground subsidence on the Beijing-Tianjin high-speed railway as mapped by radar interferometry

The construction of the Beijing–Tianjin high-speed railway line started in July 2005. The railway has been completed and opened to traffic in August 2008, just before the Beijing Olympic Games. The 113 km railway costing 13.3 billion Yuan (US

Remote Sensing Analysis Techniques and Sensor Requirements to Support the Mapping of Illegal Domestic Waste Disposal Sites in Queensland, Australia

1.5 billion) is the countrys first high-standard passenger rail. It is also believed to be the pilot project of a massive high-speed rail network in China. The train shuttles passengers between the cities in just half an hour, 45 minutes shorter than the usual travel time. The train is designed to go 200 km/h, but can reach speeds of 350 km/h. The current railway is under pressure, handling 25.55 million passengers each year. The new passenger rail line is expected to handle 32 million passengers from 2008 and 54 million passengers in 2015. Both Tianjin and Beijing have been suffering from ground subsidence due to groundwater extraction. This study focuses on mapping the impact of such subsidence on the Beijing–Tianjin high-speed railway using differential radar interferometry. Both persistent scatterer interferometric synthetic aperture radar (PSInSAR) and differential InSAR (DInSAR) techniques are used to analyse SAR data collected by ENVISAT ASAR and ALOS PALSAR sensors. The results are further analysed in GIS and compared with reported ground survey results.

Mapping illegal domestic waste disposal potential to support waste management efforts in Queensland, Australia

Illegal disposal of waste is a significant management issue for contemporary governments with waste posing an economic, social, and environmental risk. An improved understanding of the distribution of illegal waste disposal sites is critical to enhance the cost-effectiveness and efficiency of waste management efforts. Remotely sensed data has the potential to address this knowledge gap. However, the literature regarding the use of remote sensing to map illegal waste disposal sites is incomplete. This paper aims to analyze existing remote sensing methods and sensors used to monitor and map illegal waste disposal sites. The purpose of this paper is to support the evaluation of existing remote sensing methods for mapping illegal domestic waste sites in Queensland, Australia. Recent advances in technology and the acquisition of very high-resolution remote sensing imagery provide an important opportunity to (1) revisit established analysis techniques for identifying illegal waste disposal sites, (2) examine the applicability of different remote sensors for illegal waste disposal detection, and (3) identify opportunities for future research to increase the accuracy of any illegal waste disposal mapping products.