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On combining persistent and distributed scatterers using StaMPS/MTIтезисы доклада
- Авторы: Kiseleva E., Mikhailov V., Cherepantsev A., Smolianinova E., Dmitriev P.
- Сборник: Living Planet Symposium, 2019
- Тезисы
- Год издания: 2019
- Место издания: Милан, Италия
- Аннотация: In recent years InSAR methods of estimation of surface displacements find ever-widening applications. Different techniques were developed to identify persistent scatterers (PSInSAR) in time series of SAR images (e.g., Feretti, 2001). However, density of PS in rural areas is usually low (<10-20 PS/sq.km). Along with PS techniques, methods for estimation of displacements of both coherent and decorrelated pixels have been developed. One of the possible approaches to reduce decorrelation is to analyze only interferometric pairs with small temporal or spatial baselines (e.g. SBAS, Berardino et al., 2002). The scatterers identified in such a way were called distributed scatterers (DS). The A. Hooper’s method (implemented in the StaMPS /MTI software) integrates advantages of both approaches/ It is based on assumption of phase stability of scatterers as criterion for identification of persistent scatterers, thus, often increasing number of PS in rural areas.. Next step was development of techniques allowing to identify both PS and DS (e.g., SqueeSAR, ILS SM-phase estimation, see Monti, Guarnieri, Tebaldini, 2008; Ferretti et al.,2011; Lanari et al., 2013; Samiei-Esfahany et al. 2016; Wang et al., 2016, and others) employing all possible interferograms. This substantially increases spatial density of scatterers, thus, improving unwrapping procedure and accuracy of estimation of displacement fields. Our approach is based on the following. Scatterers on natural terrains are often identified in areas with low (for some periods of time) phase coherence. However, many neighboring pixels show similar reflectivity because they belong to the same natural object. Thus, similar to SqueeSAR (Ferretti et al.,2011) we first reveal spatially connected clusters of statistically homogeneous pixels (SHP). To estimate statistical homogeneity we employed the two sample Kolmogorov–Smirnov test. Then SHP range for a certain pixel is determined on the assumption of constant phase within the whole SHP range and expected phase consistency condition. After all phase filtering is performed using the Integer Least Squares (ILS) method (Samiei-Esfahany et al. 2016). The algorithm is implemented as a module compatible with StaMPS/MTI. We applied the proposed approach to landslide investigation in the Caucasus (ALOS PALSAR и ENVISAT images) and seismic and volcanic events of the Kuril-Kamchatka subduction zone. (ENVISAT images). Total number of PS+DS for 18 ALOS PALSAR was nearly the same as for interferograms without phase filtering while for the Envisat stack of images phase filtering provided the doubled number of distributed and persistent scatterers. Authors are grateful to ESA for the ENVISAT images. This study was supported by grant of the Russian Ministry of Education and Science under contract №14.W03.31.0033.
- Добавил в систему: Михайлов Валентин Олегович