Multiple-aperture SAR interferometry (MAI) has demonstrated outstanding measurement accuracy of along-track displacement when compared to pixel-offset-tracking methods; however, measuring slow-moving (cm/year) surface displacement remains a challenge. Stacking of multi-temporal observations is a potential approach to reducing noise and increasing measurement accuracy, but it is difficult to achieve a significant improvement by applying traditional stacking methods to multi-temporal MAI interferograms. This paper proposes an efficient MAI stacking method, where multi-temporal forward- and backward-looking residual interferograms are individually stacked before the MAI interferogram is generated. We tested the performance of this method using ENVISAT data from Kīlauea Volcano, Hawai‘i, where displacement on the order of several centimeters per year is common. By comparing results from the proposed stacking methods with displacements from GPS data, we documented measurement accuracies of about 1.03 and 1.07 cm/year for the descending and ascending tracks, respectively—an improvement of about a factor of two when compared with that from the conventional stacking approach. Three-dimensional surface-displacement maps can be constructed by combining stacked InSAR and MAI observations, which will contribute to a better understanding of a variety of geological phenomena.
Bibliographical noteFunding Information:
The research described in this paper was carried out with financial support from the Space Core Technology Development Program through the National Research Foundation of Korea, funded by the ministry of education, science and technology (2012M1A3A3A02033465). This study also supported by the MSIP (Ministry of Science, ICT and Future Planning) and NRF (National Research Foundation of Korea) under the Space Core Technology Development Program (project id: 2013M1A3A3A02042314). The Hawai‘i GPS network is supported by grants from the USGS, NSF, and NASA, and is operated in collaboration by the USGS, Stanford University, and Pacific GPS Facility at the University of Hawai’i. GPS RINEX data are archived at UNAVCO.
© 2015, Springer-Verlag Berlin Heidelberg.
All Science Journal Classification (ASJC) codes
- Geochemistry and Petrology
- Computers in Earth Sciences