X-SAR Data Research Articles

Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit

The Geophysical Model Function (GMF) XMOD1 provides a linear algorithm for sea surface wind field retrievals for the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR). However, the relationship between the normalized radar cross section (NRCS) and the sea surface wind speed, wind direction and incidence angles is non-linear. Therefore, in this paper, XMOD1 is revisited using the full dataset of X-SAR acquired over the ocean. We analyze the detailed relationship between the X-SAR NRCS, incidence angle and sea surface wind speed. Based on the C-band GMF CMOD_IFR2, an updated empirical retrieval model of the sea surface wind field called SIRX-MOD is derived. In situ buoy measurements and the scatterometer data of ERS-1/SCAT are used to validate the retrieved sea surface wind speeds from the X-SAR data with SIRX-MOD, which respectively yield biases of 0.13 m/s and 0.16 m/s and root mean square (RMS) errors of 1.83 m/s and 1.63 m/s.

Influence of cell size on volume calculation using digital terrain models: A case of coastal dune fields

In this work, we analyze how variation in cell size influences the volume calculated from digital terrain models (DTMs) derived from a LiDAR (light detection and ranging) survey in two coastal Late Holocene dune fields in southern Brazil. Cell size varied from 1 to 100m. RMSE (root mean square error) of the resampled DTMs from the original LiDAR (with 0.5m resolution) increases linearly with cell size, while R2 (coefficient of determination) decreases following a second-order trend. The volume does not show simple linear or exponential behavior, but fluctuates with positive and negative deviations from the original DTM. This can be explained by a random factor in the position of the cell with regard to landforms and a relationship between cell and landform size, wherein a small change in cell size can lead to an under- or overestimation of volume. The ASTER GDEM (global digital elevation model) and X-SAR SRTM (Shuttle Radar Topography Mission) 1″ digital elevation models (DEMs) were not considered viable volume sources due to large deviations from the reference data, either as a consequence of noise in the SRTM X-SAR data or lack of bias elevation correction to a common reference base in the GDEM processing chain. Volumes from a 3-arcsec SIR-C SRTM deviated around ±5% from the reference data and are considered suitable input for numerical simulations of Quaternary dune field evolution models because these values should be within the expected range of sediment volume changes over hundreds to millions of years.

Characterization of atmospheric precipitation effects on spaceborne synthetic aperture radar response at X, Ku, Ka band

Space-borne X-band synthetic aperture radars (SARs) provide a unique opportunity to measure rainfall over land with unsurpassed spatial resolution of about few hundred meters. This work explores the potential of space-borne X-SARs to estimate rainfall over land from both a model and retrieval point of view. The main objective is to provide a framework for a physically-based inversion of SARs measurements at X (9.6 GHz), Ku (14 GHz) and Ka (30 GHz) band over land. A forward model of SAR response will be illustrated for X, Ku and Ka bands. We will present an inversion methodology, a quantitative application to XSAR data of the SIR-C mission in 1994, and a qualitative application to TerraSAR-X data over France, 2008.

Relief reconstruction from SAR stereo pairs: the "optimal gradient" matching method

The authors present a method for improving relief reconstruction from SAR stereo images, relying on preprocessing of input data with an optimal filter. This filter strongly reduces speckle noise and enhances relief structures, leading to better matching results. The method was tested using X-SAR data of a mountainous site whose DEM was available for control.

Calibration and performance analysis of the X-SAR system

In April 1994 the X-SAR was flown as part of the first SIR-C/X-SAR space radar laboratory mission on the Space Shuttle. Our institute is responsible for the calibration of all X-SAR data products. SAR calibration includes internal calibration of the sensor, measurement of the antenna pattern and determination of the absolute calibration factor. This paper includes a detailed description of the X-SAR calibration algorithms, procedures and preliminary results of the first mission.

ScanSAR processing using standard high precision SAR algorithms

Processing ScanSAR or burst-mode SAR data by standard high precision algorithms (e.g., range/Doppler, wavenumber domain, or chirp scaling) is shown to be an interesting alternative to the normally used SPECAN (or deramp) algorithm. Long burst trains with zeroes inserted into the interburst intervals can be processed coherently. This kind of processing preserves the phase information of the data-an important aspect for ScanSAR interferometry. Due to the interference of the burst images the impulse response shows a periodic modulation that can be eliminated by a subsequent low-pass filtering of the detected image. This strategy allows an easy and safe adaptation of existing SAR processors to ScanSAR data if throughput is not an issue. The images are automatically consistent with regular SAR mode images both with respect to geometry and radiometry. The amount and diversity of the software for a multimode SAR processor are reduced. The impulse response and transfer functions of a burst-mode end-to-end system are derived. Special attention is drawn to the achievable image quality, the radiometric accuracy, and the effective number of looks. The scalloping effect known from burst-mode systems can be controlled by the spectral weighting of the processor transfer function. It is shown that the fact that the burst cycle period is in general not an integer multiple of the sampling grid distance does not complicate the algorithm. An image example using X-SAR data for simulation of a burst system is presented.

X-SAR radiometric calibration and data quality

In April and October, 1994 the X-SAR was flown as part of the SIR-C/X-SAR space radar laboratory missions (SRL-1/2) on the Space Shuttle. Amongst other activities DLR is responsible for the calibration of all X-SAR data products and is running the German Processing and Archiving Facility (D-PAF). Calibration activities included three major parts. Before the first mission, the authors performed a detailed analysis of the overall system to localize the main error sources and developed algorithms and procedures to correct these errors. During the missions they concentrated their efforts on calibration campaigns at the Oberpfaffenhofen super test site. Post mission activities included the determination of the antenna pattern and the absolute calibration factor as well as detailed performance analyses. This paper describes the overall approach to radiometrically calibrate the X-SAR and provides information on system performance and data quality to users in the different application fields. >

Estimation of forest biophysical characteristics in Northern Michigan with SIR-C/X-SAR

A three-step process is presented for estimation of forest biophysical properties from orbital polarimetric SAR data. Simple direct retrieval of total aboveground biomass is shown to be ill-posed unless the effects of forest structure are explicitly taken into account. The process first involves classification by (1) using SAR data to classify terrain on the basis of structural categories or (2) a priori classification of vegetation type on some other basis. Next, polarimetric SAR data at L- and C-bands are used to estimate basal area, height and dry crown biomass for forested areas. The estimation algorithms are empirically determined and are specific to each structural class. The last step uses a simple biophysical model to combine the estimates of basal area and height with ancillary information on trunk taper factor and wood density to estimate trunk biomass. Total biomass is estimated as the sum of crown and trunk biomass. The methodology is tested using SIR-C data obtained from the Raco Supersite in Northern Michigan on Apr. 15, 1994. This site is located at the ecotone between the boreal forest and northern temperate forests, and includes forest communities common to both. The results show that for the forest communities examined, biophysical attributes can be estimated with relatively small rms errors: (1) height (0-23 m) with rms error of 2.4 m, (2) basal area (0-72 m/sup 2//ha) with rms error of 3.5 m/sup 2//ha, (3) dry trunk biomass (0-19 kg/m/sup 2/) with rms error of 1.1 kg/m/sup 2/, (4) dry crown biomass (0-6 kg/m/sup 2/) with rms error of 0.5 kg/m/sup 2/, and (5) total aboveground biomass (0-25 kg/m/sup 2/) with rms error of 1.4 kg/m/sup 2/. The addition of X-SAR data to SIR-C was found to yield substantial further improvement in estimates of crown biomass in particular. However, due to a small sample size resulting from antenna misalignment between SIR-C and X-SAR, the statistical significance of this improvement cannot be reliably established until further data are analyzed. Finally, the results reported are for a small subset of the data acquired by SIR-C/X-SAR.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>