The Use of InSAR Phase Coherence Analyses for the Monitoring of Aeolian Erosion

Abstract

Aeolian erosion occurring in sand deserts causes significant socio-economical threats over extensive areas through mineral dust storm generation and soil degradation. To monitor a sequence of aeolian erosion in a sand desert area, we developed an approach fusing a set of remote sensing data. Vegetation index and Interferometric Synthetic Aperture Radar (InSAR) phase coherence derived from space-borne optical/SAR remote sensing data were used. This scheme was applied to Kubuqi Desert in Inner Mongolia where the effects of activity to combat desertification could be used to verify the outcome of the approach. We first established time series phase coherence and conducted a functional operation based on principal component analysis (PCA) to remove uncorrelated noise. Then, through decomposition of vegetation effect, where a regression model together with the Enhanced Vegetation Index (EVI) was employed, we estimated surface migration caused by aeolian interaction, that is, the aeolian erosion rate (AER). AER metrics were normalized and validated by additional satellite and ground data. As a result, the spatiotemporal migration of the target environment, which certainly induced dust storm generation, was traced and analyzed based on the correlations among surface characteristics. It was revealed that the derived AER successfully monitored the surface changes that occurred before and after the activities to combat desertification in the target area. Employing the established observation scheme, we expect a better understanding of the aeolian process in sand deserts with enhanced spatio-temporal resolution. In addition, the scheme will be beneficial for the evaluation of combating desertification activities and early warning of dust storm generations.

Keywords

• aeolian process
• desertification
• multi-sensor fusion
• interferometric SAR
• time-series analysis