SYNTHETIC APERTURE RADAR INTERFEROMETRY FOR DIGITAL ELEVATION MODEL OF KUWAIT DESERT – ANALYSIS OF ERRORS

Using different combinations of 29 Advanced Synthetic Aperture Radar (ASAR) images, 43 Digital Elevations Models (DEM) were generated adopting SAR Interferometry (InSAR) technique. Due to sand movement in desert terrain, there is a poor phase correlation between different SAR images. Therefore, suitable methodology for generating DEMs of Kuwait desert terrain using InSAR technique were worked out. Time series analysis was adopted to derive the best DEM out of 43 DEMs. The problems related to phase de-correlation over desert terrain are discussed. Various errors associated with the DEM generation are discussed which include atmospheric effects, penetration into soil medium, sand movement. The DEM of Shuttle Radar Topography Mission (SRTM) is used as a reference. The noise levels of DEM of SRTM are presented.


INTRODUCTION
DEMs are widely known for their applications in Civil Engineering, alignment of transport, power lines, drainage systems, communication networks etc.In Kuwait, it has great importance for the alignment of oil pipe lines.There are various techniques for generating DEM such as cartographic, satellite stereo-graphic and Synthetic Aperture Radar Interferometry (InSAR).During the recent years, InSAR technique has been considerably improved to generate accurate and high vertical/spatial resolutions DEMs (Zhang et al., 2005;Goncalves et al., 2008;Rao et al., 2006;Rodriguez et al., 2006;Hofton et al., 2006) .During the past 5 years, good amount of work is done in Kuwait ( Rao and Hala (2010a,b,c), Hala and Rao (2011)) using SAR Interferometry technique for generating DEM and also land subsidence.This paper summarizes our results so far obtained and published in referred journals.

STUDY AREA
The study are is Kuwait (see Figure 1).
Since SAR Interferometry has a decorrelation problem over open areas of the desert, the study area is confined to Oil fields of Kuwait.The main oil fields are Burgan, Managesh and Umgadir.Since Managesh and Umgadir oil fields are very close, in this paper, they are referred to as Managesh.The climate of Kuwait are given by Hala et al. (2006).

DATASETS AND SOFTWARE PACKAGES USED IN THIS STUDY
A variety of data sets are utilized in this study.

GENERATION DEMS USING INSAR TECHNIQUE
Generating DEMs using InSAR technique is well documented and published in our earlier publications.The flowchart is shown in Figure 4.The technique is specially tuned to suite to Kuwait desert environmental conditions.The major problem associated with the desert is the movement of sand which destroys the coherence between the pair of images required for generating Interferogram.Even a temporal base line of 35 days are enough to destroy the coherence.However, for the protected areas like oil fields, the coherence is preserved by the scant vegetation that was grown during the periods of rain fall.The multi-year scrubs acts as a barrier for the sand movement.In the open desert area, animal grazing destroys the vegetation cover, thus allowing the sand to move due to desert wind.Therefore, particularly in Kuwait desert, InSAR technique works only over oil fields, military sites and city area.Kuwait is covered by two major oil fields -Burgan and Managuish/Umgadir.The results presented here refers to these two oil fields.
Though a large number of pairs are possible with 29 ASAR scenes, only 43 pairs are considered in this study whose base line varies between 100 and 400 m. Figure 5 shows the temporal baseline (day-difference) vrs.Spatial baseline.For higher baselines, decorrelation of phase is a problem.For lower baselines, DEM sensitivity is an issue.Shorter the temporal baseline, better correlation and so reliability of the results.In time series analysis, less weightage is given for high temporal baseline pairs.B varies between 150 -400 m.The day-difference varies between 35 -770 except the case of one pair whose day-difference is 1225 days.

TIME SERIES GENERATION OF DEM OF KUWAIT AND RESULTS
Twenty nine ASAR scenes acquired during the time period 2005-2010 are used to generate 43 DEMs.All the generated DEMs are supposed to be same in elevations.However, there is not much correlation found among different DEMs of Kuwait oil fields.One possible reason is the effect of water vapor relative delays.Using MERIS water vapor data, corrections are incorporated which does not improve the accuracies.This is due to small quantity of residual water vapor and poor approximations in the model.Another reason was the temporal and spatial variation of soil moisture (see Figure 3).The more the soil moisture -less the penetration of microwaves.The uneven penetration of microwaves creates additional phases which are mistakenly interpreted as elevations.The third reason is the coherence between the pair of images used for generating Interferogram.Though the occasional correlation coefficient (CC) is as high as 0.9, the average of the scene is not more than 0.5.Therefore, this will cause additional errors in the DEMs.
To minimize the errors, time series analysis technique is applied.First-of-all, all the DEMs are registered to one another.The elevations of a particular pixel are extracted to find the mean and standard deviation (STD) of elevations.The data is filtered by setting the condition mean ± STD.All the elevations satisfying the above condition are collected and the new mean elevation is estimated.This process is repeated for all the pixels in the interferogram to generate the elevation image.This procedure considerably reduced the errors in the final DEM.The resultant DEM of Burgan oil field and Mamagesh oil field are shown in Figures 6,7.

Figure 1 .
Figure 1.ASAR intensity image of a part of Kuwait with major oil fields.Since the data is for Descending pass, East and West are interchanged.The low contrast area on the right side refers to open desert sand.The bright portion on the left is Burgan oil field.This image corresponds to March 2007.resolution, soil moisture data from AMSR-E are used in this study.The monthly average of soil moisture over Kuwait is shown in Figure 3. GAMMA interferometric software, ERDAS image processing software and EoliSA packages are used for the analysis of the data.Special software was developed by our group at Physics Department, Kuwait University for the analysis and presentation of the results.

Figure 4 .Figure 5 .
Figure 4. Flow chart for generating DEM through InSAR technique.The details of various steps are given in the text.

Figure 6 .
Figure 6.Colour coded and geocoded DEMs of Burgan oil field.The colour coding is at an interval of 5 m.(a) derived from SRTM, (b) derived from the pair with least STD error ( 2.8 m) corresponding to the pair December 2007 -July 2007.The day-difference in this case is 140 days and the ⊥ B is 280 m., (c) the weighted average image taking into account all the 43 DEMs.The values are in meters in the color coding.

Figure 7 .
Figure 7. (a) SRTM (b) Weighted average DEM (c) InSAR Pair Dec 07 -July 07.Comparison of DEMs of SRTM, Weighted average InSAR DEM and the DEM of one pair with lesser RMS error.There is a general agreement reflecting the topography of the study area.However, SRTM DEM shows more noise and InSAR DEMs are very smooth.
Figure 8.A small portion of the DEM of Figure 8 is enlarged and color coded at 2 m interval to enhance the noise levels.Center Coordinates are: -28° 52′ 30″ N and

Figure 9 .
Figure 9. Illustration of noise levels of SRTM DEM and the filtered smooth curve.The Standard Deviation is computed to be 0.99 m An example of water vapor image of Kuwait and its surrounding regions is shown in Figure 2. Topomaps of Kuwait, DEM of SRTM at 90 m spatial Twenty nine ASAR images acquired from EnviSat Satellite are used.An example of ASAR image of Kuwait is shown in figure 1.The protected areas (oil fields) are clearly separated from the open desert.Twenty seven water vapour images from MERIS onboard ENVISAT are used,