350 research outputs found
Calibration of a Ground-Based Array Radar for Tomographic Imaging of Natural Media
Ground-based tomographic radar measurements provide valuable knowledge about the electromagnetic scattering mechanisms and temporal variations of an observed scene and are essential in preparation for space-borne tomographic synthetic aperture radar (SAR) missions. Due to the short range between the radar antennas and a scene being observed, the tomographic radar observations are affected by several systematic errors. This article deals with the modelling and calibration of three systematic errors: mutual antenna coupling, magnitude and phase errors and the pixel-variant impulse response of the tomographic image. These errors must be compensated for so that the tomographic images represent an undistorted rendering of the scene reflectivity. New calibration methods were described, modelled and validated using experimental data. The proposed methods will be useful for future ground-based tomographic radar experiments in preparation for space-borne SAR missions
Sensitivity of P- and L-Band SAR Tomography to Above-Ground Biomass in a Hilly Temperate Forest
Tomographic synthetic aperture radar (TomoSAR) is a promising technique for the estimation of forest above-ground biomass (AGB), but knowledge gaps still remain concerning the effects of forest type and ground topography. This article presents new results at P- and L-bands based on data acquired during the TomoSense campaign. The study area is a temperate forest, predominantly beech and spruce, with ground slopes ranging up to 40°. Analysis of vertical reflectivity profiles shows distinct differences for spruce and beech. Three AGB retrieval methods are analyzed, i.e., total vertical backscatter I tot, canopy backscatter from a height layer Ic, and the ratio Icr= Ic/Itot. All three methods show sensitivity to AGB for spruce, whereas for beech, this is only true for the two latter methods. For the P-band, a significant ground slope effect is observed, while less so for the L-band. The highest R2 is obtained for spruce with HV polarization, Ic and ground slopes less than 10°, i.e., R2 = 0.86 and RMSE =15.6% for P-band and R2 = 0.75 and RMSE =12.5% for L-band. Corresponding results by including all forest types are R2 = 0.77 and RMSE =11.4% for P-band and R2 = 0.54 and RMSE =12.0% for the L-band. Moreover, the performance of using I cr is similar to that of Ic. The ratio I cr can be determined without absolute radiometric calibration which relaxes system requirements. This article reinforces the potential of TomoSAR for forest AGB estimation and draws attention to important effects of tree species and ground slope
MODEL-BASED ESTIMATION OF TROPICAL FOREST BIOMASS FROM NOTCH FILTERED P-BAND SAR BACKSCATTER
This paper presents a new algorithm for forest biomass estimation from P-band synthetic-aperture radar (SAR) backscatter data, notch-filtered at ground-level. A semi-empirical model is fitted to spatial and polarization trends in the backscatter data and no reference biomass data are needed for training. An evaluation on airborne P-band SAR data from a tropical test site in Gabon results in a root-mean-square error lower than 20% and a correlation better than 90%
Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
P-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground topography, forest structure, and soil moisture. Tomographic processing of multiple SAR images Tomographic SAR (TomoSAR) provides information about the vertical backscatter distribution. This article evaluates the use of P-band TomoSAR data to improve AGB retrievals from backscattered intensity by suppressing the backscattered signal from the ground. This approach can be used even when the tomographic resolution is insufficient to resolve the vertical backscatter profile. The analysis is based on P-band data from two campaigns: BioSAR-1 (2007) in Remingstorp, southern Sweden, and BioSAR-2 (2008) in Krycklan (KR), northern Sweden. BioSAR airborne data were also processed to correspond as closely as possible to future BIOMASS TomoSAR acquisitions, with BioSAR-2-based results shown. A power law AGB model using volumetric HV polarized backscatter performs best in KR, with training residual root mean-squared error (RMSE) of 30%-36% (27-33 t/ha) for airborne data and 38%-39% for simulated BIOMASS data. Airborne TomoSAR data suggest that both vertical and horizontal tomographic resolution are of importance and that it is possible to greatly reduce AGB retrieval bias when compared with airborne P-band SAR backscatter intensity-based retrievals. A lack of significant ground slopes in Remningstorp reduces the benefit of using TomoSAR data which performs similar to retrievals based solely on P-band SAR backscatter intensity
Mapping above-ground biomass in tropical forests with ground-cancelled P-band SAR and limited reference data
This paper introduces the CASINO (CAnopy backscatter estimation, Subsampling, and Inhibited Nonlinear Optimisation) algorithm for above-ground biomass (AGB) estimation in tropical forests using P-band (435 MHz) synthetic aperture radar (SAR) data. The algorithm has been implemented in a prototype processor for European Space Agency\u27s (ESA\u27s) 7th Earth Explorer Mission BIOMASS, scheduled for launch in late 2022. CASINO employs an interferometric ground cancellation technique to estimate canopy backscatter (CB) intensity. A power law model (PLM) is then used to model the dependence of CB on AGB for a large number of systematically distributed SAR data samples and a small number of calibration areas with a known AGB. The PLM parameters and AGB for the samples are estimated simultaneously within pre-defined intervals using nonlinear minimisation of a cost function. The performance of CASINO is assessed over six tropical forest sites on two continents: two in French Guiana, South America and four in Gabon, Africa, using SAR data acquired during airborne ESA campaigns and processed to simulate BIOMASS acquisitions. Multiple tests with only two randomly selected calibration areas with AGB > 100 t/ha are conducted to assess AGB estimation performance given limited reference data. At 2.25 ha scale and using a single flight heading, the root-mean-square difference (RMSD) is ≤ 27% for at least 50% of all tests in each test site and using as reference AGB maps derived from airborne laser scanning data. An improvement is observed when two flight headings are used in combination. The most consistent AGB estimation (lowest RMSD variation across different calibration sets) is observed for test sites with a large AGB interval and average AGB around 200–250 t/ha. The most challenging conditions are in areas with AGB < 200 t/ha and large topographic variations. A comparison with 142 1 ha plots distributed across all six test sites and with AGB estimated from in situ measurements gives an RMSD of 20% (66 t/ha)
Evaluating spaceborne L-band pol tomo SAR for forest biomass retrieval based on airborne SAR data
This paper presents an evaluation of L-band tomographic synthetic-aperture radar (TomoSAR) data for forest biomass retrievals. Tomograms are processed from multiple synthetic-aperture radar (SAR) data sets from the Krycklan forest site, located in the north and south of Sweden. Tomographic performance is matched to possible future spaceborne SAR configurations such as SAOCOM-CS. Ivol, the integrated volumetric backscatter between 10 m and 30 m, is found to result in improved biomass retrievals compared to those based on slope corrected SAR intensity γ0from the original airborne E-SAR system
Interferometric Ground Notching of SAR Images for Estimating Forest Above Ground Biomass
The effectiveness of SAR tomography in estimating forest Above Ground Biomass (AGB) has been repeatedly demonstrated in the recent years. For tropical rain-forests, analysis from the Paracou test site reveals that the best results are achieved when the backscattered power coming from 30m above the ground is considered. As suggested in previous papers, the most likely reason is that ground scattering acts as a disturbing factor for forest biomass retrieval, as it depends on a number of parameters (like topography, moisture), that do not relate to forest biomass. In this paper we further test this hypothesis by proposing the concept of interferometric ground notching. By taking the difference between two phase calibrated, ground-steered, SAR SLC images a third image is obtained where ground scattering contributions are canceled out, hence the name ground-notched SLC. Results indicate that ground-notched data can effectively retain the features of vegetation-only scattering, including its polarimetric signature and correlation with AGB
Impulse response function for ultra-wideband SAR
A new impulse response function (IRF) for ultra-wideband synthetic-aperture radar (SAR) is derived based on an analytical Fourier transform pair. The latter corresponds in 2D frequency domain to a triangular area with con-stant amplitude, zero amplitude otherwise, which is used to model the SAR IRF. We show that the IRF reduces to a 2D sinc function for small aperture angles and that it is a good approximation for SAR up to about 10\ub0 of aperture angle. This IRF also generates the characteristic crossed sidelobe arms of ultra-wideband SAR from two rotated and interfering sinc functions. For aperture angles greater than about 10\ub0, the IRF is constructed by su-perposition of adjacent triangles next to each other in frequency domain. The IRF for ultra-wideband SAR corresponding to an annulus sector is thus given by an infinite series of such triangular regions, but only a few terms are necessary for typical ultra-wideband SAR systems. About one term per 10\ub0 of aperture angle gives an accurate result
- …
