SAR Interferometry for DEM Generation

Geometric registration
Registration of SAR images (both intensity and phase) is generally carried out at sub-pixel level for accurate results. At the first instance, the registration at pixel level is accomplished by a simple two-dimensional transformation using a limited number of Ground Control Points identified in the two images. This is followed with a sub-pixel registration using a large number of GCPs (of the order of 40 to 50). In the first attempt, two images are divided into sub-areas. Then, the coordinates of each sub-area are determined according to one of the following correlation method (Rao and Rao, 1999):
  • Cross correlation of pixel intensities,
  • Maximum value of the coherence coefficient,
  • Evaluation of the maximum intensity, and
  • Minimum of the average fluctuation of the phase difference image.
Interferogram generation
Two SAR images are combined to produce a SAR Interferogram to reveal information about the third dimension (elevation) of the object and to measure small displacements of objects between the two image acquisitions. An interferogram is an image acquired by making the phases of two SAR images of the same terrain to interfere. 

Thus, after registration, the complex interferograms are formed by multiplying each complex pixel of the first image by the complex conjugate of the same pixel in the second image. The interferogram thus generated is a complex image itself. The intensity of the interferogram is a measure of cross correlation of the images. A careful observation of the fringes in Fig. 2 reveals that closer are the fringes, more are the topographical changes or height variations.

Phase unwrapping
As the height of the terrain increases, the phase also increases steadily. Since phase values are periodic functions of 2p, they automatically get wrapped after reaching 2p, which is not a desirable situation. Phase unwrapping is a technique that permits retrieving the unwrapped phase from the wrapped phase, which for the InSAR, is a necessary step for the generation of DEM (Fornaro et al., 1996). There are many methods of phase unwrapping. 

Phase to height conversion
As a final step, the terrain height may be determined using several methods which convert phases into terrain heights (Bilrgmann et al., 1999). Some of them are:
  • Normal baseline method
  • Integrated incidence angle method
  • Baseline rotation method.
Normal baseline method operates on unwrapped phase where change in the height of the terrain is related to change in the phase using the following equation (Rao and Rao, 1999):

Dh = (lr1 sinq / 4pB') Dj    (3)

where r1 is the range in the first image,
B' is the normal baseline,
l is the wavelength, 
Dj is change in phase, and
q is the incident angle.

Thus, utilising the above-mentioned steps, the relationship between the heights and the phase differences can be determined. These heights determined for each pixel of the SAR image form the necessary DEM in raster form. The steps, though they look, simple require complex mathematical algorithms at each step and therefore, it is desirable that the processing be done using some software. In the next section, some of the softwares for InSAR have been listed.

Software for InSAR
A number of software packages have been developed to process and analyse SAR interferometric data. The early days of InSAR saw the development of packages by many research institutes. Later, a few commercial packages have also become available. The salient features of some of the commercial and non-commercial packages have been given in Table 1. It provides information about the supported sensors and formats as well as the other generated products as mentioned before. It can be seen that most of the supported sensors are from space borne systems. Among them ERS-1 and 2 imageries are supported by all the packages. It may also be noticed that most of the packages can be used for the generation of the DEM. To represent the DEM as a final interferogram product, additional information about map projection, grid size, etc. may also be required. A log file can also be generated from most of these software packages that contains a large amount of information about the parameters used for processing as well as its performance.

Conclusions
An overview of various aspects related to InSAR such as the concepts, the data acquisition and processing steps, and the availability of software to perform InSAR are described for DEM generation.

Following general conclusions can be drawn:
  • In less than ten years, InSAR has demonstrated its capabilities for quantitative measurements of surface topography.
  • InSAR has the potential of providing DEM at an accuracy of 1-10 cm, which can further be improved to millimeter level from Differential InSAR.
  • SRTM and ENVISAT are the dedicated missions for providing necessary data for InSAR. However, the ERS-1, ERS-2, JERS-1 and RADARSAT can also be used for interferometric purposes.
  • Though many softwares have been developed, some aspects regarding data format and data quality need to be standardised in them to get uniform end products.
  • By and large, InSAR can effectively be applied in many areas that are concerned with mapping and monitoring of earth’s surface at higher accuracy.
References
Asdorf, D. and Smith L. C., 1999, Interformetric SAR observations of ice topography and velocity changes related to the 1996 Gjalp sub-glacial eruption Iceland, International Journal of Remote Sensing, 20, 3031-3050.
  • Bilrgmann R., Rosen P. A., and Fielding E. J., 1999, SAR Interferometry to measure earth’s surface topography and its deformation, 1-57.
  • Fornaro G., Franceschetti G., and Lanari R., 1996, Interferometric SAR phase unwrapping using Green’s formulation, IEEE Transactions on Geoscience and Remote Sensing, 34, 720-727.
  • Gens R., 1999, SAR Interferometry: software, data format and data quality, Photogrammetric Engineering and Remote Sensing, 65, 1375-1378. http://www.asf.alaska.edu/, 2000, SAR frequently asked questions, http://earth.esa.int/, 1995, SAR Interferometry with ERS
  • Kimura H., and Yamaguchi, Y., 2000, Detection of landslide areas using satellite radar interferometry, Photogrammetric Engineering and Remote Sensing, 66, 337-344.
  • Massonnet D., Feigl K. L., Rossi M., and Vadon H., 1996, Co seismic deformation field of the M 6.7 Northridge, California Earthquake of January 17, (1994), Recorded by Two Radar Satellites using Interferometry”, Geophysical Reaserch Letters, Vol. 23, No. 9, 969-972.
  • Rao K. S. and Rao Y. S., (1999), “Seminar on Recent Developments in Differential SAR INTERFEROMETRY and its Applications”, Lecture Notes, IIT Bombay, 1-11.

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