Water level change time series extraction of Yellow River Delta based on small baseline subset approach

Abstract

The water level change has a great impact on the composition of plant species, the variety of the species and the succession of the colony of the Yellow River Delta wetland. However, due to the lack of enough hydrological sites, it is very difficult to obtain the water level change of the wetlands, especially those covered with vegetation. Synthetic aperture radar Interferometry (InSAR) has been proposed and used to solve the problem. However, with limited InSAR pairs, water level change time series cannot be obtained. In this paper, an InSAR time series analysis method called small baseline subset approach (SBAS) has been used to solve this problem. A total of 13 scenes of PALSAR L band SAR images are used for small baseline subset analysis. Only interferometric pairs with average coherence above 0.3 in the region of interest (wetlands with vegetation cover) are selected. Then small baseline subset approach was applied to interferograms after flattening, removal of the phase of terrain, filtering and phase unwrapping using minimum cost flow algorithm. Finally time series of relative water level change from June 28th, 2007 to December 31th, 2008 was obtained. Preliminary results on test sites showed an approximate linear-rate water level change. Our experiments showed the feasibility and potential of wetland water level change monitoring using SBAS.