Coherence Optimization and Its Limitations for Deformation Monitoring in Dynamic Agricultural Environments

Differential interferometry techniques are well known for its ability to provide centimeter to millimeter scale deformation measurements. However, in natural and agricultural areas, the presence of vegetation and the evolution of the land surface introduce a phase noise component which limits successful interferometric measurement. This paper aims to address the known limitations of traditional dInSAR in the presence of disturbances to reflected signals due to agricultural activities by testing the polInSAR technique for its ability to increase interferometric coherence and to detect surface movement in the areas of interest. Both fully polarimetric RADARSAT-2 and ALOS PALSAR data were subject to coherence optimization using the multiple scattering mechanism (MSM) approach. For C-band RADARSAT-2 data, coherence optimization resulted in a statistically significant increase in interferometric coherence. However, the spatial heterogeneity of the scattering process and how it changes over time caused random phase changes associated with temporal baseline effects and the evolution of the land surface. These effects could not be removed from C-band interferograms using the MSM approach. Therefore, coherence optimization resulted in an increase in the random speckle in interferograms reducing the ability to derive high confidence interferometric measurements, indicating a drawback in the MSM approach to coherence optimization. On the other hand, coherence optimization on L-band data demonstrated an increase in the spatial homogeneity of the speckle noise suggesting that the MSM approach to coherence optimization on L-band data may be more successful in enhancing the ability to extract deformation measurements in dynamic agricultural regions. In general, a good agreement in deformation measurements derived from dInSAR and polInSAR techniques was observed.