Generation of Global Backscatter Maps for Future SAR Missions Design

The generation of global backscatter maps allows for the exploitation of a priori knowledge of local synthetic aperture radar (SAR) backscatter statistics. SAR backscatter maps can be used for accurate performance prediction and for the optimization of instrument settings for present and future SAR systems. Also, many further SAR applications can benefit from the availability of backscatter maps in order to monitor the backscatter evolution in time and to investigate the radar reflectivity behaviour depending on sensor parameters and target properties. In this work, X-band backscatter maps are generated by mosaicking images acquired by the TerraSAR-X (TSM) and the TanDEM-X (TDM) missions at global scale. The correction models used for the characterization of backscatter behaviour are based on the database provided by Ulaby and are here presented for HH polarization and for any required reference incidence angle. As an example of application for future SAR missions design, a novel performance-optimized block-adaptive quantization (PO-BAQ), coming from the need of optimizing the resource allocation of the state-of-the-art quantization algorithms for SAR systems, is then considered. The methodology relies on global backscatter statistics for the generation of bitrate maps, which can provide a helpful information for performance budget definition and for optimizing resource allocation. strategie

Deep Learning-based Approaches for Forest Mapping with TanDEM-X Interferometric Data

Deep learning models trained in a fully supervised way have shown encouraging capabilities for mapping forests with TanDEM-X interferometric data, being able to generate time-tagged forest maps at large-scale over tropical forests. These maps have been generated at 50 m resolution to reduce the computation burden. In this work, we now aim to exploit the high-resolution capabilities of the TanDEM-X interferometric dataset, processed at only 6 m resolution, for forest mapping purposes. In order to cope with the lack of reliable reference data at such a high resolution, we focus on the investigation of self-supervised learning approaches. The availability of a reference map over Pennsylvania, USA, based on Lidar acquisitions at 1 m resolution, allows us to compare different deep learning approaches. The obtained results show the possibility to extend the proposed self-supervised learning approach over areas where the lack of reference data prevent us from using fully supervised deep learning methods

Characterization of the Amazon Rainforest Backscatter for X-Band SAR Calibration Using TanDEM-X Data

The radiometric calibration of spaceborne SAR products plays a key role for ensuring a good performance of the whole end-to-end system and requires a precise knowledge of both the radar system and the illuminated target. The shape of the antenna pattern in elevation can be directly estimated by analyzing SAR detected images in presence of a flat backscatter profile in the slant range dimension. This is typically accomplished by acquiring SAR data over homogeneous distributed targets, under the assumption of isotropic scattering. This is the case of tropical rainforests, such as the Amazon and Congo forests, which have been established by the SAR community as well-known test sites for SAR calibration, thanks to their homogeneous and almost isotropic signature. Nevertheless, several studies using X- and C-band sensors have shown a slight dependency of the rainforest backscatter on the incidence angle, as well as on ground target properties and meteorological conditions. The aim of this work is to present a statistical characterization of radar backscatter at X-band over the Amazon rainforest using TanDEM-X data, and to provide insights on how to best utilize radar backscatter data in this region for SAR calibration and modeling purposes

Relationship between Lidar-Derived Canopy Densities and the Scattering Phase Center of High-Resolution TanDEM-X Data

Abstract: The estimation of forestry parameters is essential to understanding the three-dimensional structure of forests. In this respect, the potential of X-band synthetic aperture radar (SAR) has been recognized for years. Many studies have been conducted on deriving tree heights with SAR data, but few have paid attention to the effects of the canopy structure. Canopy density plays an important role since it provides information about the vertical distribution of dominant scatterers in the forest. In this study, the position of the scattering phase center (SPC) of interferometric X-band SAR data is investigated with regard to the densest vegetation layer in a deciduous and coniferous forest in Germany by applying a canopy density index from high-resolution airborne laser scanning data. Two different methods defining the densest layer are introduced and compared with the position of the TanDEM-X SPC. The results indicate that the position of the SPC often coincides with the densest layer, with mean differences ranging from −1.6 m to +0.7 m in the deciduous forest and +1.9 m in the coniferous forest. Regarding relative tree heights, the SAR signal on average penetrates up to 15% (3.4 m) of the average tree height in the coniferous forest. In the deciduous forest, the difference increases to 18% (6.2 m) during summer and 24% (8.2 m) during winter. These findings highlight the importance of considering not only tree height but also canopy density when delineating SAR-based forest heights. The vertical structure of the canopy influences the position of the SPC, and incorporating canopy density can improve the accuracy of SAR-derived forest height estimations

The Global Forest/Non-Forest Classification Map from TanDEM-X Interferometric Data

In this paper we present the global Forest/Non-Forest Map derived from TanDEM-X bistatic interferometric synthetic aperture radar (InSAR) data. The global TanDEM-X dataset has been acquired in stripmap single HH polarization mode and covers a time span from 2011 up to 2016. The volume correlation factor (or volume decorrelation), derived from the interferometric coherence, quantifies the coherence loss due to multiple scattering within a volume, a mechanism which typically occurs in presence of vegetation. For this reason, the volume correlation factor has been used as main indicator for the identification of forested areas. Quicklook images, a multi-looked version of the original full-resolution data at a ground resolution of 50 m x 50 m, have been used as input for the generation of the global product. The mosaicking process of multiple acquisitions is discussed as well, together with the identification of additional information layers, such as urban areas or water bodies. The resulting global forest/non-forest map has been validated using external reference information, as well as with other existing classification maps, and an overall agreement typically exceeding 90% is observed. The global product presented in this paper is intended to be released to the scientific community for free download and usage

The Global Water Body Layer from TanDEM-X Interferometric SAR Data

The interferometric synthetic aperture radar (InSAR) data set, acquired by the TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) mission (TDM), represents a unique data source to derive geo-information products at a global scale. The complete Earth's landmasses have been surveyed at least twice during the mission bistatic operation, which started at the end of 2010. Examples of the delivered global products are the TanDEM-X digital elevation model (DEM) (at a final independent posting of 12 m × 12 m) or the TanDEM-X global Forest/Non-Forest (FNF) map. The need for a reliable water product from TanDEM-X data was dictated by the limited accuracy and difficulty of use of the TDX Water Indication Mask (WAM), delivered as by-product of the global DEM, which jeopardizes its use for scientific applications, as well. Similarly as it has been done for the generation of the FNF map, in this work, we utilize the global data set of TanDEM-X quicklook images at 50 m × 50 m resolution, acquired between 2011 and 2016, to derive a new global water body layer (WBL), covering a range from -60° to +90° latitudes. The bistatic interferometric coherence is used as the primary input feature for performing water detection. We classify water surfaces in single TanDEM-X images, by considering the system's geometric configuration and exploiting a watershed-based segmentation algorithm. Subsequently, single overlapping acquisitions are mosaicked together in a two-step logically weighting process to derive the global TDM WBL product, which comprises a binary averaged water/non-water layer as well as a permanent/temporary water indication layer. The accuracy of the new TDM WBL has been assessed over Europe, through a comparison with the Copernicus water and wetness layer, provided by the European Space Agency (ESA), at a 20 m × 20 m resolution. The F-score ranges from 83%, when considering all geocells (of 1° latitudes × 1° longitudes) over Europe, up to 93%, when considering only the geocells with a water content higher than 1%. At global scale, the quality of the product has been evaluated, by intercomparison, with other existing global water maps, resulting in an overall agreement that often exceeds 85% (F-score) when the content in the geocell is higher than 1%. The global TDM WBL presented in this study will be made available to the scientific community for free download and usage

Database Interface Specification for SAR Verification Tools

Description of the required input tables for the SAR Verification Tool

TanDEM-X Water Body Layer Product Description

The purpose of this document is to describe the TanDEM-X Water Body Layer products and their formats

TanDEM-X Experimental Modes Characterization

This document summarizes the research carried out on the TanDEM-X experimental modes characterization. Possible beams, commanded PRF, processed and transmitted bandwidths, image characterization and performance analysis were investigated on a set of scientific acquisitions. The results fed into the public experimental product description TD-GS-PS-3028

Characterization of TanDEM-X Quad Polarization Products

This document summarizes the research analysis carried out on the TanDEM-X quad polarization acquistions in the pursuit monostatic constellation of the science phase. Main focus is given in the interferometric performance. The optimization of different instrument parameters, such as chirp bandwidth, PRF, or BAQ, in order to increase the coherence is presented and discuss. A SAR performance characterization of the quad polarization DTs, with the estimation of parameters like resolution, SLR, and NESZ, is also presented