6th International Workshop on Retrieval of Bio- & Geo-physical Parameters from SAR Data for Land Applications

Multi-temporal Sentinel-1 SAR data processing for thematic applications over land

17 Nov 2015, 11:10

20m

Harwell, UK

General Land-use and Classification I - General Land-Use and Classification

Speaker

Dr Urs Wegmuller (Gamma Remote Sensing AG)

Description

The Sentinel-1 SARs are designed to achieve global coverage with short repeat intervals. Using a constellation of two satellites and operating these in a special ScanSAR mode permits providing excellent multi-temporal data. Therefore, multi-temporal processing techniques are becoming very relevant. In our processing and retrieval concept we are using a two stage approach. The first stage deals with elements as calibration, co-registration, filtering, coherence estimation, estimation of multi-temporal signatures and geocoding. As a result standardized multi-temporal signatures are derived which are then used as input to the second stage, the retrieval algorithms. In our work presented we focus on the first stage considering specifically Sentinel-1 IWS data. For applications based on SAR backscatter speckle reduction is one important aspect of the processing. We use a multi-image filtering approach (Wegmüller et al., 2013) that builds upon multi-image filtering methodologies proposed by Quegan et al. 2001, and structural spatial filtering proposed by Lee et al., 1999. In the multi-image filtering, an assumption used is that the spatial patterns remain unchanged over time. This is often almost perfectly the case for agricultural fields, built up structures as houses, roads, power lines, dams and alike also meet this criteria. As a consequence, the filter performs well over these targets with a significant increase of the Equivalent Number of Looks (ENL) over homogeneous areas such as fields while maintaining individual scatterers and field boundaries sharp. The filtering methodology is described and results generated using substantial multi-temporal Sentinel-1 stacks are discussed. Speckle filtering is also relevant in the estimation of multi-temporal parameters as the temporal variability of the backscattering. Over land Sentinel-1 acquires data most of the time in dual polarization mode. As a consequence cross-polarization backscattering and combined parameters as the cross- to like-polarization ratio are available. Furthermore, Sentinel-1 coherence is estimated at both like and cross-polarization. References: Lee J-S., M.R. Grunes, and G. de Grandi, Polarimetric SAR Speckle Filtering and Its Implication for Classificantion, IEEE TGRS, Vol.. 37, No. 5, pp. 2363-2373, 1999. Quegan and Yu, Filtering of multichannel SAR images, IEEE Trans Geosci. and Remote Sensing, vol. 39, no. 11, 2001. Wegmüller, U., M. Santoro, and C. Werner, "Multi-temporal SAR data filtering for land applications," ESA Living Planet Symp., Edinburgh, UK, 9-13 Sep., SP-722, 2013.

Summary

A multi-temporal processing concept for Sentinel-1 SAR data is presented. One focus is on the use of multi-temporal filtering to reduce speckle noise and improve the estimation of multi-temporal parameters as the temporal variability. Furthermore, cross-polarization backscatter, cross-polarization to like-polarization ratio, and coherence are considered.