DEM GENERATION AND ANALYSIS ON RUGGED TERRAIN USING ENVISAT/ASAR ENVISAT/ASAR MULTI-ANGLE INSAR DATA

Similar documents
ERS-ENVISAT Cross-interferometry for Coastal DEM Construction

Measuring rock glacier surface deformation using SAR interferometry

LAND COVER CLASSIFICATION BASED ON SAR DATA IN SOUTHEAST CHINA

THREE DIMENSIONAL DETECTION OF VOLCANIC DEPOSIT ON MOUNT MAYON USING SAR INTERFEROMETRY

ERS-ENVISAT CROSS-INTERFEROMETRY SIGNATURES OVER DESERTS. Urs Wegmüller, Maurizio Santoro and Christian Mätzler

SAR Data Analysis: An Useful Tool for Urban Areas Applications

MODELING INTERFEROGRAM STACKS FOR SENTINEL - 1

Deformation measurement using SAR interferometry: quantitative aspects

MONITORING OF GLACIAL CHANGE IN THE HEAD OF THE YANGTZE RIVER FROM 1997 TO 2007 USING INSAR TECHNIQUE

GLOBAL FOREST CLASSIFICATION FROM TANDEM-X INTERFEROMETRIC DATA: POTENTIALS AND FIRST RESULTS

CHAPTER-7 INTERFEROMETRIC ANALYSIS OF SPACEBORNE ENVISAT-ASAR DATA FOR VEGETATION CLASSIFICATION

DETECTING ICE MOTION IN GROVE MOUNTAINS, EAST ANTARCTICA WITH ALOS/PALSAR AND ENVISAT/ASAR DATA

GEOMORPHOLOGICAL MAPPING WITH RESPECT TO AMPLITUDE, COHERENCEAND PHASE INFORMATION OF ERS SAR TANDEM PAIR

CLOSE FORMATION FLIGHT OF PASSIVE RECEIVING MICRO-SATELLITES

DIFFERENTIAL INSAR STUDIES IN THE BOREAL FOREST ZONE IN FINLAND

Snow Water Equivalent (SWE) of dry snow derived from InSAR -theory and results from ERS Tandem SAR data

Ground deformation monitoring in Pearl River Delta region with Stacking D-InSAR technique

APPEARANCE OF PERSISTENT SCATTERERS FOR DIFFERENT TERRASAR-X ACQUISITION MODES

MAPPING DEFORMATION OF MAN-MADE LINEAR FEATURES USING DINSAR TECHNIQUE

Dr. Simon Plank. German Remote Sensing Data Center (DFD), German Aerospace Center (DLR)

COAL MINE LAND SUBSIDENCE MONITORING BY USING SPACEBORNE INSAR DATA-A CASE STUDY IN FENGFENG, HEBEI PROVINCE, CHINA

ALOS PI Symposium 2009, 9-13 Nov 2009 Hawaii MOTION MONITORING FOR ETNA USING ALOS PALSAR TIME SERIES

INSAR DEM CALIBRATION FOR TOPOGRAPHIC MAPPING IN EASTERN UGANDA

Analysis of ERS Tandem SAR Coherence From Glaciers, Valleys, and Fjord Ice on Svalbard

RADAR Remote Sensing Application Examples

Journal of Geodynamics

On the Exploitation of Target Statistics for SAR Interferometry Applications

THE USE OF DIFFERENT REMOTE SENSING TECHNIQUES FOR LANDSLIDE CHARACTERIZATION

ERS Track 98 SAR Data and InSAR Pairs Used in the Analysis

The Potential of High Resolution Satellite Interferometry for Monitoring Enhanced Oil Recovery

Mitigation of Atmospheric Water-vapour Effects on Spaceborne Interferometric SAR Imaging through the MM5 Numerical Model

DEM REGISTRATION, ALIGNMENT AND EVALUATION FOR SAR INTERFEROMETRY

Maximum Likelihood Multi-Baseline SAR Interferometry

EasyChair Preprint. Height Accuracy and Data Coverage for the Final Global TanDEM-X DEM Data

Modeling of Atmospheric Effects on InSAR Measurements With the Method of Stochastic Simulation

Surface Deformation Measurements Scientific Requirements & Challenges

Slow Deformation of Mt. Baekdu Stratovolcano Observed by Satellite Radar Interferometry

Urban land and infrastructure deformation monitoring by satellite radar interferometry

sensors ISSN

VALIDATION OF THE PERMANENT SCATTERERS TECHNIQUE IN URBAN AREAS

SNOW MASS RETRIEVAL BY MEANS OF SAR INTERFEROMETRY

GPS and GIS Assisted Radar Interferometry

Interferometers of synthetic aperture radar (InSAR) relevance in generation of digital elevation model (DEM) for real world solutions

ERS1/2 interferometry on Erta Ale volcano: the study of a proto-ocean ridge using SAR

Observation of Surface Displacements on Glaciers, Sea Ice, and Ice Shelves Around Canisteo Peninsula, West Antarctica Using 4-Pass DInSAR

[1] Integrated Global Observing Strategy, Theme Report 2003 Monitoring of our Environment from Earth and Space.

Fusion of Optical and InSAR DEMs: Improving the Quality of Free Data

TEMPORAL VARIABILITY OF ICE FLOW ON HOFSJÖKULL, ICELAND, OBSERVED BY ERS SAR INTERFEROMETRY

Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry

InSAR measurements of volcanic deformation at Etna forward modelling of atmospheric errors for interferogram correction

Application of differential SAR interferometry for studying eruptive event of 22 July 1998 at Mt. Etna. Abstract

Constructing high-resolution, absolute maps of atmospheric water vapor by combining InSAR and GNSS observations

PERSISTENT SCATTERER INTERFEROMETRY: POTENTIAL AND LIMITS

Fusion of high-resolution DEMs derived from COSMO-SkyMed and TerraSAR-X InSAR datasets

SLOPE STABILITY MONITORING USING SPACE-BORNE REPEAT- PASS SAR INTERFEROMETRY

Improved PSI Performance for Landslide Monitoring Applications. J. Duro, R. Iglesias, P. Blanco-Sánchez, F. Sánchez and D. Albiol

Estimation of Velocity of the Polar Record Glacier, Antarctica Using Synthetic Aperture Radar (SAR)

GEOGRAPHICAL DATABASES FOR THE USE OF RADIO NETWORK PLANNING

Terrafirma Persistent Scatterer Processing Validation

P079 First Results from Spaceborne Radar Interferometry for the Study of Ground Displacements in Urban Areas SUMMARY

MOST synthetic aperture radar (SAR) satellites operate in

PHASE UNWRAPPING. Sept. 3, 2007 Lecture D1Lb4 Interferometry: Phase unwrapping Rocca

Generation and Validation of Digital Elevation Model using ERS - SAR Interferometry Remote Sensing Data

ACHIEVING THE ERS-2 ENVISAT INTER-SATELLITE INTERFEROMETRY TANDEM CONSTELLATION.

Spatiotemporal analysis of ground deformation at Campi Flegrei and Mt Vesuvius, Italy, observed by Envisat and Radarsat-2 InSAR during

Available online at GHGT-9. Detection of surface deformation related with CO 2 injection by DInSAR at In Salah, Algeria

Zhong Lu, Member, IEEE, Eric Fielding, Matthew R. Patrick, and Charles M. Trautwein

Subsidence-induced fault

The financial and communal impact of a catastrophe instantiated by. volcanoes endlessly impact on lives and damage expensive infrastructure every

Two-pass DInSAR uses an interferometric image pair and an external digital elevation model (DEM). Among the two singlelook complex (SLC) images, one i

DEMONSTRATION OF TERRASAR-X SCANSAR PERSISTENT SCATTERER INTERFEROMETRY

Evaluation of subsidence from DinSAR techniques using Envisat-ASAR data at Toluca Valley Basin, Mexico.

MONITORING MODERATE SLOPE MOVEMENTS (LANDSLIDES) IN THE SOUTHERN FRENCH ALPS USING DIFFERENTIAL SAR INTERFEROMETRY. Jan Vietmeier and Wolfgang Wagner

APPLICABILITY OF PSINSAR FOR BUILDING HAZARD IDENTIFICATION

On the use of COSMO/SkyMed data and Weather Models for interferometric DEM generation

Impact of the Envisat Mission Extension on SAR data

Innovative InSAR approach to tackle strong nonlinear time lapse ground motion

Forest mapping and monitoring with interferometric. Synthetic Aperture Radar (InSAR)

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 1, NO. 2, APRIL

SURFACE DEFORMATION OF ALPINE TERRAIN DERIVED BY PS-INSAR TECHNIQUE ON THE SIACHEN GLACIER

DAMAGE DETECTION OF THE 2008 SICHUAN, CHINA EARTHQUAKE FROM ALOS OPTICAL IMAGES

Model based forest height estimation with ALOS/PalSAR: A first study.

Analysis of the Temporal Behavior of Coherent Scatterers (CSs) in ALOS PalSAR Data

SAR interferometry Status and future directions. Rüdiger Gens

PERSISTENT SCATTERER SAR INTERFEROMETRY APPLICATIONS ON LANDSLIDES IN CARPATHIANS (SOUTHERN POLAND)

Radar Remote Sensing: Monitoring Ground Deformations and Geohazards from Space

MODELS TO PREDICT PERSISTENT SCATTERERS DATA DISTRIBUTION AND THEIR CAPACITY TO REGISTER MOVEMENT ALONG THE SLOPE

ERAD Water vapor observations with SAR, microwave radiometer and GPS: comparison of scaling characteristics

Haiti Earthquake (12-Jan-2010) co-seismic motion using ALOS PALSAR

ATMOSPHERIC EFFECTS REMOVAL OF ASAR-DERIVED INSAR PRODUCTS USING MERIS DATA AND GPS

InSAR, structural analyses and dating of Paka volcanic products, Northern Kenya Rift

SAR INTERFEROMETRIC ANALYSIS OF GROUND DEFORMATION AT SANTORINI VOLCANO (GREECE)

Monitoring Earth Surface Deformations with InSAR Technology: Principle and Some critical Issues

InSAR techniques and applications for monitoring landslides and subsidence

USE OF INTERFEROMETRIC SATELLITE SAR FOR EARTHQUAKE DAMAGE DETECTION ABSTRACT

Retrieving 3D deformation pattern of a landslide with hiresolution InSAR and in-situ measurements: Just landslide case-study

Integration of InSAR and GIS for Monitoring of Subsidence Induced by Block Caving Mining

Advanced Analysis of Differences between C and X Bands using SRTM Data for Mountainous Topography

Atmospheric Effects on InSAR Measurements in Southern China and Australia: A Comparative Study

Università di Roma La Sapienza, Facoltà d Ingegneria, Dipartimento di Idraulica,Trasporti e Strade (D.I.T.S.) 00185, Roma, Italy

Transcription:

DEM GENERATION AND ANALYSIS ON RUGGED TERRAIN USING ENVISAT/ASAR ENVISAT/ASAR MULTI-ANGLE INSAR DATA Li xinwu Guo Huadong Li Zhen State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Application,Chinese Academy of Sciences, P.O.Box 9718, Datun 3, Beijing, 100101, China, Email:xinwuli@irsa.ac.cn ABSTRACT The suitable incidence angle is one of the important parameters on DEM mapping precision when interferometric SAR used to generate DEM on mountainous terrain. In this paper, from real ENVISAT/ASAR multiple angle interferometric data, SRTM DEM with 90m horizontal resolution and 1:50000 digital topographic DEM, the concrete impact of incidence angle on DEM accuracy has been analysed and discussed from qualitative and quantitative views The result indicates: (1)For ASAR multi-incidence angle interferometric data, the effects of the layover and foreshortening on DEM precision are significantly at lower incidence angle, and difference of DEM accuracy is large, for example, the accuracy difference between IS2 and IS4 ASAR DEM is more than 6m. So, the incidence angle must be selected rigidly when InSAR are used for rugged terrain mapping. (2) Temporal decorrelation is serious with 35 days time interval, the overall evaluation of DEM precision are difficult. If the InSAR data that have wider incidence range and have not temporal decorrelation can be obtained, the further and overall evaluation and analysis that radar layover, shadow and foreshortening are how to affect the DEM precision can be investigated. Key Words: InSAR, Multi-angle, DEM, Layover, foreshortening 1. INTRODUCTION With the implementation of ERS-1/2 tandem project and Global Shutter Radar Topographic Mapping project (SRTM), InSAR has been wildly used to map topography[1-8]; At the same time, TanDEM-X project launched by Germany is in process[9]. The DEM precision obtained from InSAR technique determined by incidence angle, frequency, interferometric geometry such as spatial baseline, temporal baseline and surface terrain situation (Such as vegetation and topographic relief) etc.. In the mountainous area with large terrain relief, suitable incidence angle is one of important factors for high precision DEM generation from InSAR technique. According to the geometric characteristics of SAR imaging, at lower incidence angle[10], radar layover and Proc. Envisat Symposium 2007, Montreux, Switzerland 23 27 April 2007 (ESA SP-636, July 2007) foreshortening are very serious, and have significantly impact on DEM precision. But, limited by real multi-angle InSAR data sources, the most of research that layover and foreshortening are how to affect the DEM precision is based on simulation SAR data. In March, 2003, ENVISAT/ASAR has been launched by ESA, and it provides interferometric data with seven incidence angle from 15 degree to 45 degree, the multi-angle imaging mode of ASAR provide the real data sources for rugged terrain DEM generation. From multi-angle ASAR InSAR data and the other DEM data, for different incidence case, the effects of layover and foreshortening on DEM precision is preliminary discussed. Being the range of incidence angle of ASAR is from 15 degree to 45 degree, the effects of shadow on DEM precision is not discussed here[11]. 2 THE THEORY ANALYSIS OF INCIDENCE ANGLE ON DEM PRECISION FROM INSAR DATA The effects of foreshortening and layover on DEM precision is discussed for different incidence angle as following. (1) Foreshortening. In general, foreshortening is not change the position relations of targets, so the phase of targets are not superposition, but the position of targets are lean to direction of radar illumination. At lower incidence angle, foreshortening is very serious, it has significantly impact on horizontal resolution, with the increasing of incidence angle, the effect of foreshortening is become lower, horizontal resolution is gradually improving. (2) Layover. It has two cases: displacement between top and bottom of target, and the superposition of multi-targets. The displacement between top and bottom of target means the top of target locates at front of bottom of target in the range direction in SAR image. The superposition of multi-targets means these targets

have same position because of the same slant range. for first case, the position relations of targets are changed, and the phase of target in the top superposed with the phase of one target at some place, so the height of this resolution cell is the mean of height of target in the top and surface target, at the same time, being the displacement between top and bottom of target, the position relations is changed, it will cause significantly DEM errors. For second case, being many targets belong to one resolution cell with different height, so the phase of this resolution cell is the value of phase center formed by several targets. It means that the DEM height of this resolution cell represented by the phase center value, and it will cause significantly DEM errors. The most complicated case is that all cases are existed and lead to more serious DEM error. 3 STUDY AREA AND DATA RESOURCES In general, temporal decorrelation is serious for the most of terrain surface within 35 days repeat cycle. To guarantee adequate high coherence for DEM generation, the Langshan test site located at Linghe county of Ningxia province is selected. The center of test site is E106 33,N41 11. Test site locates the north part of Langshan Mountain, this test site has little cloud and mist, little rain, dry weather, and sparse vegetation. Generally, the terrain surface can maintain stability for a long time. At this study, research group collected four pair of multi-angle InSAR data, they are IS2, IS3, IS4 and IS6 respectively. Being the baseline for IS6 is very long, the spatial decorrelation is serious, and it has not enough coherence for DEM generation. So we use other three pairs InSAR data to generate DEM. To compensate the shortage of data acquisition, SRTM DEM with 90m horizontal resolution is collected. To validate the results, research group also bought the 1:50000 digital topographic DEM. Table 1 InSAR data parameters of descending IS2, IS3 and IS4 of ENVISAT/ASAR IS No. Orbit No. Incidence angle Date (day/month/year) perpendicular baseline(m) temporal baseline(day) IS2 13370/13871 19.2-26.7 20/09/ 2004; 25/10/2004-197.55 35 IS3 12325/12826 26.0-31.4 09/07/ 2004; 13/08/ 2004-124.26 35 IS4 11552/12503 31.0-36.3 16/05/ 2004; 20/06/ 2004 201.18 35 Fig.1 shows two study area image extracted from IS2 SAR image, the test site shown by Fig.1(a) is selected by considering detailed surface situations before data acquisition, from the figure, we can see that layover, shadow and foreshortening caused by topographic relief and interferometric geometry are very significant. But, after the data analysis, it indicates that the temporal decorrelation is very serious at this test site and have significantly impacts on next data processing and analysis, so we rejected this test site. By comparison and analysis of coherence, the another study area shown by Fig.1(b) is selected. From Fig.1(b), the relief of terrain of this test site is lower than that shown by Fig.1(a), so the effects of layover, shadow and foreshortening is not obvious than that shown by Fig.1(a), Although the difference between two study area have some impact on (a)

(b) Figure.1 SAR amplitude images of descending IS2 of ENVISAT/ASAR for two study area result analysis and interpretation, the final result still indicate that incidence angle have important impact on DEM precision. 4 DATA PROCESSING AND ANALYSIS It includes two parts for data processing: (1) InSAR data processing for multi-angle ENVISAT/ASAR data; (2) high precision registration for different incidence angle, different sensor and different sources DEM. For ENVISAT/ASAR InSAR data processing, EvInSAR software developed by Atlantis Company is used. After data processing, the geocoded DEM of IS2, IS3 and IS4 are obtained. But, two points should be take care for data processing: (1) Selecting the same area as an reference area for flatten phase removal; (2) the same control points group had better be used when transforming phase to elevation. To compare and analyse for different DEM, the high precision registration must be implemented. PCI software developed by Apollo company is used to carry out high precision registration. At here, 1:50000 digital DEM, IS2, IS3 DEM generated from ASAR data and SRTM DEM are all co-registrated to IS4 DEM because of IS4 DEM has highest horizontal resolution(about 20m 20m) Some data processing result are discussed and analysed as following. Fig.2 is the zoom image of left-bottom region of Fig.1(b). To convenient for observation, fig.2 has been rotated and the illumination direction is from up to down. From the figure, we can see that, at lower incidence angle, the layover and foreshortening are very serious and with the increasing of incidence angle, the image distortion caused by layover and foreshortening is decreasing. (a) (b) (c) Figure.2 SAR amplitude images of IS2, IS3 and IS4 of ASAR at the left-bottom region of Fig 1(b) Fig.3 shows the coherence coefficient images of descending IS2, IS3 and IS4 of ASAR, from the figure, we can see that some area have very low coherence, two possible reasons for this low coherence: one is temporal decorrelation caused by surface change within 35 days repeat cycle, another is that decorrelation caused by layover and shadow because of terrain relief. In general, with the increasing of incidence angle, the effect of layover is decreasing, coherence is improving. At the same time, shadow area is increasing and then will lead to useful information lost, and then low coherence in the shadow area. It is very obvious in the upper-left part of images. So, it had better avoid these low coherence area when precision evaluation is implemented. (a) (b) (c) Figure.3 Coherence coefficient images of IS2, IS3 and IS4 of ASAR for study area Fig.4 is the interferograms of IS2,IS3,and IS4 after flattened phase removals. From the figure, at low terrain relief area, the quality of interferometric pattern is vary well, but, the interferometric pattern become bad with the increasing of terrain relief, especially for right-bottom part. (a) (b) (c) Figure.4 Interferogram of IS2,IS3 and IS4 of ASAR after flattened phase removal for study area

5 RESULT ANALYSIS AND VALIDATION 5.1 Qualitative analysis Fig.5 shows the ASAR DEM of IS2, IS3 and IS4, SRTM DEM and 1:50000 digital DEM. From qualitative aspects, the DEM quality is gradually improving with the increasing of incidence angle. To compare with 1:50000 digital DEM, the SRTM DEM(incidence angle from 30degree-60degree) have almost same visual result, the only difference is that detail information is relatively bad because of 90m horizontal resolution for SRTM DEM(the resolution of IS4 DEM is 20m). At the same time, from fig.5, the DEM quality at right-bottom part is very bad, there have three possible reasons: (1) radar layover lead to distortion and then bad DEM quality because of large terrain relief; (2) temporal decorrelation within 35 days data acquisition interval; (3) phase unwrapping errors. Figure.5 The DEM of IS2, IS3, IS4 of ENVISAT/ASAR, SRTM DEM of 1Km grid and digital DEM of 1:50000 topographic map from left to right and up to bottom respectively for study area Figure.6 The zoom images of yellow region of Fig.5, the DEM of IS2,IS3,IS4, SRTM DEM with 90m resolution, and digital DEM of 1:50000 topographic map respectively for left to right, up to bottom for study area Fig.6 shows the zoom images for yellow region of Fig.5. They represent the ASAR DEM of IS2,IS3,IS4, SRTM DEM, 1:50000 digital DEM from left to right, and up to bottom. These figures show clearly the effects of foreshortening on DEM mapping. From the figure, we can see that the effects of foreshortening are decreasing and horizontal resolution are improving with the increasing of incidence angle for ASAR DEM of IS2, IS3 and IS4. Because of 90m horizontal resolution for SRTM DEM, the detail information is not as clear as ASAR DEM of IS4. 5.2 Quantitative analysis and validation Fig.7 shows the comparison result of five DEM along yellow horizontal profile line. Fig.8 shows the comparison result of five DEM along vertical profile line. From the figure, we can see that the DEM precision of ASAR IS4 is best compared with 1:50000 digital DEM, and then is IS3, and the last is IS2. The RMS errors are 8.991m, 13.077m, 15.384m, 9.863m for IS4, IS3, IS2 and SRTM DEM respectively compared with 1:50000 digital DEM. Generally, DEM mapping precision is significantly improved with the increasing of incidence angle, and clearly indicate incidence angle has significant impact on DEM precision when InSAR technique use to generate DEM for rugged terrain. In addition, from the figure, we can see that the precision of IS3 DEM has not significant improving compared with that of IS2 DEM, the most probable reason is that the spatial baseline of IS3 interferometric pair is shorter than that of IS2 interferometric pair(see table 1), and the height sensitive is lower than that of IS2 interferometric pair. The DEM precision of SRTM is not as good as that of IS4 DEM, the main reason is SRTM DEM mainly shows the change of height trends and not sensitive to detail information because of 90m horizontal resolution. Certainly, from the result, we can see that there have relative large errors for other four DEM compared with 1:50000 digital DEM. The main reasons is that (1) the temporal decorrelation caused by 35 days repeat cycles(only for ASAR DEM); (2) The high precision control points are shortage when change relative height

(a) to absolute elevation; (3) registration error caused by difficult control point selection. 6 CONCLUSION AND DISCUSSION From the comparison and analysis above, the following conclusions are conclude: (1) For ASAR multi-incidence angle interferometric data, the effects of the layover and foreshortening are significantly at lower incidence angle on DEM, and the difference of accuracy is large, for example, the accuracy difference between IS2 and IS4 DEM is more than 6m. So, the incidence angle must be selected rigidly when InSAR are used for rugged terrain mapping; (2) temporal decorrelation is serious within 35 days time interval, the overall evaluation of DEM are difficulty. If the InSAR data that has wider incidence range and have not temporal decorrelation can be obtained, the further and overall evaluation and analysis that radar layover, shadow and foreshorten are how to affect the DEM precision can be implemented. (b) Figure.7 The comparison result of five DEM along yellow horizontal line. The DEM accurate of IS4 is best, and then IS3, and last IS2 (a) (b) Figure.8 The comparison result of five DEM along yellow vertical line. The DEM accurate of IS4 is best, and then IS3, and last IS2 ACKNOWLEDGEMENT: This work was sponsored by National Natural Science Funding Committee (40501050), the civil project of Commission of Science Technology and Industry for National Defense(KGW), and by ESA project (AO 711) REFERENCES: 1. Alessandro Ferretti, Claudio Prati, and Fabio Rocca, Multibase InSAR DEM Reconstruction: The Wavelet Approach, IEEE Transactions Geoscience and Remote Sensing, 1999, 37(2):705-715. 2. Andrea Monti Guarnieri, SAR interferoemtry and Statistical Topography, IEEE Transactions Geoscience and Remote Sensing, 2002,40(12):2567-2581. 3. Riadh Abdelfattah, and Jean Marie Nicolas, Topographic SAR interferoemtry Formulation for High-Precision DEM generation, IEEE Transactions Geoscience and Remote Sensing, 2002, 40(11):2415-2426. 4. L. Riccardo, G. Fornaro, D. Riccio, M. Migliaccio, K. P. Papathanassiou, R. Moreira, M. Schwabisch, L. Durta, G. Puglisi, G. Franceschetti and M. Coltelli, Generation of Digital Elevation Models by Using SIR-C/X-SAR Multifrequency Two-Pass Interferometry: The Etna Case Study, IEEE Transactions on Geoscience and Remote Sensing, 1996, 34(5):1097-1114. 5. G.Rufino, A. Moccia, S. E., DEM Generation by Means of ERS Tandem Data, IEEE Transactions Geoscience and Remote Sensing, 1998, 36(6):905-1912 6. H. A Zebker, R M Goldstein, Topographic mapping from interferometry synthetic aperture radar

observations, Journal of Geophysical Research, 1986, 91: 4993-4999, 7. M. Crosetto, Calibration and Validation of SAR interferometry for DEM generation, ISPRS Journal of Photogrammetry & Remote Sensing, 2002, 57:213-227 8. H. A.Zebker, C. L. Werner, P. Rosen, S. Hensky, Accuracy of Topographic Maps Derived from ERS-1 Interferometric Radar, IEEE Transactions Geoscience and Remote Sensing, 1994, 32(4):823-836, 9. Gerhard Krieger, Hauke Fiedler, Irena Hajnsek, Michael Eineder, Marian Werner, Alberto Moreira, TanDEM-X: Mission Concept and Performance Analysis, IGARSS 05 10. Guo Huadong Editor in Chief, Radar Image Analysis and Geologic Applications, Science Press, 1991, 88-93 11. http://www.ipi.uni-hannover.de/html/aktivitaeten/e ARSeL-Workshop2005_Paper/Eineder.pdf 12. Zebker H. A. and J. Villasenor, Decorrelation in interferometric radar echoes. IEEE Trans. Geosci. Remote Sensing, 1992, 30(5):950-959