How can we make Polarimetry Analysis Ready?

Abstract

Today, several SAR missions provide valuable and extensive information for monitoring the Earth’s surface, for assessing the current state and to improve the understanding of ongoing changes. In the last decades the capabilities for data reception and storage have been continuously extended to allow routine operations of the growing amount of SAR data. Additional, significant effort has been put into the development of processing techniques to gain the full range of information being inherent in SAR data. However, the increase of data volume and processing complexity requires appropriate resources for storage and processing to convert the SAR image content into geoinformation. Therefore, new strategies are needed for data management and provision. The Committee on Earth Observation Satellites (CEOS) has set up the CEOS Analysis Ready Data for Land initiative (CARD4L) that aims for the standardization of such products. One example is the radiometrically calibrated and orthorectified Normalized Radar Backscatter (NRB) Analysis Ready Data (ARD) product for single-polarized SAR data. In contrast, ARD for polarimetric SAR data is not that straight forward, as the information is in the complex scattering matrix and usually each application performs special filtering and decomposition methods for a specific data preparation. For the time being, the processing still starts from the basic Single Look Complex products. CEOS proposes several polarimetric ARDs that ease the utilization. However, these products are not really ready for use as they still require further pre-processing. Here, we propose a polarimetric ARD product based on a Kennaugh element framework [1,2], that doesn’t require any further pre-processing. The idea is to produce ready to use layers for image analyzation e.g. deep learning applications. The product avoids complex data format to ease the user handling, radiometric calibration and orthorectification are applied as well as a normalization of the data in order to reduce their storage demand. A big advantage of the Kennaugh elements is their applicability to all polarimetric combinations (dual, quad, and even compact pol). Finally, even further polarimetric decomposition (e.g. Freeman-Durden, Yamaguchi) are possible. The technique for generating the proposed polarimetric ARD is already implemented in DLR’s Multi-SAR System and was applied in several projects and international collaborations (e.g. [3,4]). It supports TerraSAR-X, PAZ, RADARSAT-1/2, ALOS-PALSAR, Sentinel-1, ERS-1/2, ENVISAT-ASAR and newly the RADARSAT Constellation Mission (RCM). The proposed presentation shall introduce the Kennaugh framework, the ARD product layout and highlight the applicability with examples.