Printer Friendly

Synthetic aperture radar interferometry coherence analysis.

1. INTRODUCTION

This study is basically focusing on coherence analysis. For a selected test area, namely Bucharest, a number of coherence maps are generated using data provided by different SAR sensors. The complex analysis is taking into account the temporal baseline, the perpendicular baseline, the wavelength of the SAR sensor and other elements that affect the coherence between each pair of available SAR data.

2. INTERFEROMETRY

Synthetic Aperture Radar (SAR) is an active microwave imaging system. Its advantages in comparison with the optical remote sensing sensors consist of: SAR has cloud-penetrating capabilities and it is operational during night and day. A complex SAR image is a bi-dimensional matrix of pixels that store in the form of a complex number the amplitude and the phase of the signal backscattered by the ground targets towards the sensor (Ferretti et al., 2007).

Interferometry is based on the following principle: the same area on the ground is viewed from slightly different positions. This interferometric acquisition geometry can be obtained either simultaneously--with two radar systems on the same platform--or at different moment in time--by repeated passes of the same satellite platform. The difference of phase between these two radar images can be used to measure differences or geometric distortions in the range direction (Massonnet & Souyris, 2008).

The products that can be derived using interferometry are: Digital Elevation Models (by conventional interferometry or simply interferometry--InSAR) or Displacement Maps (by differential interferometry--DInSAR).

A key parameter in interferometry is the perpendicular baseline (projection perpendicular to the slant range of the interferometer baseline). If the value of the perpendicular baseline is low, then the interferometric pair is more suitable for a DInSAR application; in this case, the phase sensitivity to ground displacements is much higher than the phase sensitivity to topography.

3. COHERENCE

Within a pixel, the difference in phase between two complex SAR images can be translated into a combination of contributing factors like topography, ground displacement, atmosphere and noise (Teleaga et al., 2009). According to (Massonnet & Souyris, 2008), the coherence is a self-validating indicator of the phase measurement which depends on the proportion of useful signal to non-useful signal.

Thus, the phase noise can be estimated by means of the local coherence [gamma] and it represents the cross-correlation coefficient of the SAR image pair estimated over a small window (usually between 16 to 40 independent pixels), once all the deterministic phase components are compensated for (Ferretti et al., 2007).

A method of coherence calculation is based on relation (1), where [absolute value of [u.sub.1]], [absolute value of [u.sub.2]] are the amplitudes of the two initial images and E is the expected value of the random variable x (Ferretti et al., 2007):

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (1)

Absolute values of coherence y varies from 0 to 1, where 0 means that the interferometric phase is completely affected by noise and 1 represents absence of noise.

4. SAR MISSIONS

4.1 ERS 1 / ERS 2

The first ERS satellite was launched by ESA (European Space Agency) in 1991 and the second one in 1995. The SAR sensor on board the ERS platform is operating in C-band (5.6 cm wavelength), on a sun synchronous orbit, at about 800 km altitude. The revisiting interval is 35 days. In 1995, the two satellites were linked in order to form the first ever Tandem mission which offered very good interferometric pairs for DEM generation due to the very short time interval of 24 hours between two acquisitions (http://www.esa.int).

4.2 ENVISAT

ENVISAT is also an ESA satellite that was launched in 2002. The ASAR (Advanced Synthetic Aperture Radar) sensor is designed to ensure continuity of the ERS SAR instrument. Both satellite platforms are using the same band for the SAR sensor and they operate on similar orbits, having the same repeat cycle of 35 days (http://www.esa.int).

4.3 TerraSAR-X

TerraSAR-X is a German SAR mission launched in 2007. It is a side-looking X band synthetic aperture radar equipped with an array antenna which is capable of acquiring data in different imaging modes. The platform's nominal orbit height at the equator is 514 km and the orbit repeat cycle is 11 days (Eineder et al., 2008).

5. METHODOLOGY AND RESULTS

5.1 Test site and available data

Test area is represented by the city of Bucharest, an urban area which offers a complex mixture of buildings, paved roads, vegetation, natural and artificial water bodies, etc. The surroundings of the city are mainly represented by agricultural fields and forested areas, the height interval ranging from 35 m to 143 m. The terrain is flat up to rolling. The interferometric SAR pairs (ERS Tandem, ENVISAT, TerraSAR-X Stripmap) used for this study are presented in Table 1.

5.2 Methodology

The processing chain is composed of the following steps: data input (read master and slave data, crop, precise orbits, master timing), azimuth common band filtering, co-registration (coarse and fine), slave resampling, optimal spectral shift filtering, interferogram generation, differential interferogram computation and coherence estimation.

5.3 Results

High coherence values are obtained over the urban area, especially in the case of TerraSAR-X and ENVISAT. Usually, high coherence values are expected in areas with lack of vegetation like built-up areas or exposed rocks (Ferretti et al., 2007). Contrary, the ERS Tandem coherence map shows lower coherence values for the urban area than it was expected. One possible explanation might be given by the fact that coherence values are strongly affected by the local weather.

All coherence maps show very low coherence values for the forested areas and also for the areas covered by water (the dark pixels correspond to low coherence). Even in the case of ERS Tandem (one day time interval between the acquisitions), the coherence is very low because the surface of the water and the leaves of the trees are constantly moving.

Agricultural fields present good coherence values in case of ERS Tandem due to the very short acquisition interval. In case of TerraSAR-X and ENVISAT the corresponding coherence values are lower. ENVISAT coherence values are low due to the very large time interval and also the season of acquisitions (summer). In order to obtain high coherence values, it is recommended to choose images rather from the same season (but one or more years apart) than from different seasons (Ferretti et al., 2007). Also, the recommended season is winter.

[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

6. CONCLUSIONS

The main causes for coherence loss are represented by the large time interval between the interferometric acquisitions and the value of the perpendicular baseline. These disadvantages will be overcome by the future SAR missions: TanDEM-X (second TerraSAR-X satellite, operating in tandem mode with the first one) and CosmoSkyMed (constellation of four SAR satellites). These new missions will offer very short revisiting times (few hours) and optimal interferometric baselines that will enable the generation of high quality coherence maps.

The ERS and ENVISAT data used in this study were kindly provided by ESA under the ESA Category-1 Proposal ID 6050.

The TerraSAR-X images were acquired under the German Aerospace Center (DLR) TerraSAR-X Project, pre-launch proposal ID LAN_0130.

7. REFERENCES

Eineder, M.; Fritz, T.; Mittermayer, J.; Roth, A.; Borner, E. & Breit, H. (2008). TerraSAR-X Ground Segment Basic Product Specification Document, Available from: http://sss.terrasar-x.dlr.de/ Accessed: 2009-06-12

Ferretti, A.; Monti-Guarnieri, A.; Prati, C.; Rocca, F. & Massonnet, D. (2007). InSAR Principles: Guidelines for SAR Interferometry Processing and Interpretation, ESA Publications, ISBN 92-9092-233-8, ESTEC, The Netherlands

Massonnet, D. & Souyris, J. C. (2008). Imaging with Synthetic Aperture Radar, CRC Press, ISBN 978-0-8493-8239-0 (CRC Press), USA

Teleaga, D.; Poncos, V.; Dana, I. F.; Nedelcu, I. & Olteanu, V. G. (2009). Urban Infrastructure Monitoring Using Spaceborne Interferometric Synthetic Aperture Radar Techniques, Proceedings of the 1st International Conference on Space Technology, August 2009, Thessaloniki, Greece

*** (2008) http://www.esa.int--European Space Agency, Observing the Earth, ESA's Earth Observation Missions, Accessed on: 2009-06-12
Tab. 1. Interferometric SAR data for coherence analysis

 Perpendicular Time
Satellite Date baseline interval

ERS 08.10.1999 [approximately 1 day
 09.10.1999 equal to]= 229 m

ENVISAT 09.06.2007 [approximately 385 days
 28.06.2008 equal to]= 165 m

TerraSAR-X 12.02.2008 [approximately 44 days
 27.03.2008 equal to]= 555 m
COPYRIGHT 2009 DAAAM International Vienna
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2009 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Dana, Iulia Florentina; Badea, Alexandru; Moise, Cristian; Olteanu, Vlad Gabriel; Jivanescu, Iulia E
Publication:Annals of DAAAM & Proceedings
Article Type:Report
Geographic Code:4EUAU
Date:Jan 1, 2009
Words:1379
Previous Article:Psychological and behavior aspects regarding internet addiction.
Next Article:Career management in school organisations: case study.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |