Geocoding of fast-delivery ERS-l SAR image mode product using DEM data

Johnsen, Harald; Lauknes, L.; Guneriussen, T.

doi:10.1080/01431169508954532

Cited by 44 publications

(24 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The scenes were processed according to [29] and [30] to produce geocoded calibrated backscatter images. No corner reflectors were used to geolocate the SAR images.…”

Section: Gpr Data and Processingmentioning

confidence: 99%

“…Instead, we performed a careful geocoding and calibration of the scene using a high-resolution digital elevation model and cross correlation with a reference image which has been adjusted using tie points and coast line. This gives a relative coregistration accuracy that is better than 0.2 pixels and a subpixel absolute accuracy [29], [30]. The processing results in images with a resolution of 30 m in both range and azimuth.…”

Section: Gpr Data and Processingmentioning

confidence: 99%

See 1 more Smart Citation

From Glacier Facies to SAR Backscatter Zones via GPR

Langley

Hamran

Høgda

et al. 2008

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

Abstract-We present a comparison between data acquired with frequency-modulated ground-penetrating radar (GPR) and satellite synthetic aperture radar (SAR). Both radars are polarimetric and operate at a center frequency of 5.3 GHz. The field site is the polythermal glacier Kongsvegen, Svalbard. Along glacier GPR profiles cover the ablation area and the accumulation area, where the latter consists of superimposed ice (SI) and firn. The glacier facies are clearly identifiable on the GPR profiles, although we show that the copolarized response is better for distinguishing different ice zones, whereas the SI-firn boundary is most obvious in the cross-polarized response. A calibrated backscatter coefficient is calculated for the GPR data and compared with the SAR backscatter coefficient. The SAR zones are in very good agreement with the GPR-derived glacier facies. We show that, in the ablation area, the SAR response is dominated by backscatter from the previous summer surface. In the SI and firn areas, it is dominated by sources below the previous summer surface.

show abstract

“…The scenes were processed according to [29] and [30] to produce geocoded calibrated backscatter images. No corner reflectors were used to geolocate the SAR images.…”

Section: Gpr Data and Processingmentioning

confidence: 99%

Section: Gpr Data and Processingmentioning

confidence: 99%

From Glacier Facies to SAR Backscatter Zones via GPR

Langley

Hamran

Høgda

et al. 2008

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Surface undulations with wavelengths at least twice as large as the resolution cell cause signature variations from cell to cell due to changes of the local incidence angles. The local incidence angle for each resolution cell can be estimated from a digital elevation model (DEM) [49] or from SAR interferograms [50]. A SAR scene usually covers several types of scattering media, which reveal different functional dependencies of the scattering intensity on the incidence angle, so that the removal of intensity variations due to the topography is difficult and in certain cases not appropriate.…”

Section: E Influence Of Large-scale Topographymentioning

confidence: 99%

Quantitative roughness characterization of geological surfaces and implications for radar signature analysis

Dierking

1999

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

show abstract

“…ERS-1 SAR PRI datasets from 29 March, 6 June, 11 July and 12 July have been calibrated and processed into terrain corrected images in Universal Transverse Mercator (UTM) map projection by applying high resolution (5m x5m) DEM data and geocoding software [4]. The DEM is derived from airphoto.…”

Section: Ers Datamentioning

confidence: 99%

Discussion and Conclusions

Pollitt¹

2012

New Perspectives on Public Services

View full text Add to dashboard Cite

Area 3 was used for investigation of the classification results. The results are shown in Table 2. The table shows that clustering of VV data gave the best results with an error rate of 7.2%. The least good results were obtained for crosspolarization with an error rate of 12.2%. ERS DATAERS-1 SAR PRI datasets from 29 March, 6 June, 11 July and 12 July have been calibrated and processed into terrain corrected images in Universal Transverse Mercator (UTM) map projection by applying high resolution (5m x5m) DEM data and geocoding software [4]. The DEM is derived from airphoto. A 3x3 Lee filter was applied to the data before conversion to dB. In Fig. 3 the mean ERS-1 SAR backscattering coefficient for from, 29 March, 6 June, 11 July and 12 July, respectively, are shown for two areas close to the previously defined areas are used. A decrease of 4 dB in backscattering coefficient is observed for the high mountainous area between 29 March to 6 July. This change is related to the change in snow properties. In 29 March the area is covered with dry snow while in June the area is covered with wet snow. We clearly observe a change between the ascending 11 July and descending 12 July ERS pass. This is caused by the difference in viewing geometry giving rise to different local incidence angle. DISCUSSION AND CONCLUSIONSThe backscatter statistics of two areas with an elevation difference of about 450 m was studied. The difference of the mean of the class snow between the two areas were largest for co-polarization with about 4.4 dB. Correspondingly, it was 1.8 dB for cross-polarization. For bare ground, the corresponding numbers were less than 1.0 and 1.3 dB. Since the ground conditions for snow were very similar in the two areas, the main reason for the change of the backscatter level is probably the incidence angle. For the purpose of classification, a preliminary conclusion is that local classstatistics must be applied. If the reason for variation is mainly due to the incidence angle parametrized class models may be designed. A classification test using K-means clustering showed best results with an error rate of 7.2% for VV polarization. All error rates were between 7.2 and 12.2. An investigation of a larger area is necessary in order to draw more clear conclusions.EMISAR C-band polarization responses from wet snow correspond to theoretical responses from smooth surfaces. The polarization response at L-band show a higher degree of diffuse scattering than C-band. The ground measurements include measurements of snow density, snow grain size, snow liquid water content and surface roughness. Air-and snow temperature data are also available. Several trihedral corner reflectors were deployed within the field for calibration and georeferencing purposes. The field measurements are georeferenced using GPS. One aerial photo of the test site was taken July 14. The field was completely covered with snow on March 22 and on May 1-3, while in July the field was nearly snowfree. REFERENCESThe calibration of the EMISAR data have been verif...

show abstract

Geocoding of fast-delivery ERS-l SAR image mode product using DEM data

Cited by 44 publications

References 4 publications

From Glacier Facies to SAR Backscatter Zones via GPR

From Glacier Facies to SAR Backscatter Zones via GPR

Quantitative roughness characterization of geological surfaces and implications for radar signature analysis

Discussion and Conclusions

Contact Info

Product

Resources

About