Land subsidence can be a major problem where there are large-scale underground activities such as oil extraction. This paper addresses the spatial variability of land subsidence over Minagish and Umm Gudair oil fields of Kuwait. Synthetic aperture radar interferometry (InSAR) with multiple reference scenes using a persistent scatterer InSAR toolchain was employed in this study. Twenty-nine scenes of advanced synthetic aperture radar data (for the period January 2005 to August 2009) were used to make 20 pairs of interferograms (with high coherence and low noise) of stable point-like reflectors. The output of this study is the land subsidence maps of Minagish and Umm Gudair oil fields with a spatial resolution of 40 m. The results indicate that there is land subsidence of 29.9 mm/year in the southern part of the oil field (Umm Gudair). This is the first detailed assessment of land subsidence in the Minagish–Umm Gudair oil fields; therefore, no ground-truth data are available to compare the subsidence results. The results were consistent, indicating their validity.
Forty-three digital elevation models (DEMs) of the Managesh oil field, Kuwait desert study area, are derived from 28 advanced synthetic aperture radar (ASAR) images using radar interferometry (InSAR) technique. Weighted-average technique is used to reduce the noise in the integrated DEM. The final DEM is compared with DEM of Shuttle Radar Topography Mission (SRTM) and found to have a general agreement. The standard deviation (STD) of individual DEMs with reference to DEM of SRTM is in the range 10 to 40 m. The results indicate that the 90 m spatial resolution DEM of SRTM is noisier over the Managesh oil field as it shows drastic changes in elevations of neighboring pixels which is not expected for a plain desert like the Managesh oil field. Using mean filter, the noise level is estimated as one meter. The reasons for high noise in the DEM of SRTM may be due to uneven distribution of soil moisture leading to uneven penetration of microwaves. The results are in confirmation with the earlier investigators as explained in the text.
The aim of this paper is to analyze the errors in the Digital Elevation Models (DEMs) derived through repeat pass SAR interferometry (InSAR). Out of 29 ASAR images available to us, 8 are selected for this study which has unique data set forming 7 InSAR pairs with single master image. The perpendicular component of baseline (B) varies between 200 to 400 m to generate good quality DEMs. The Temporal baseline (T) varies from 35 days to 525 days to see the effect of temporal decorrelation. It is expected that all the DEMs be similar to each other spatially with in the noise limits. However, they differ very much with one another. The 7 DEMs are compared with the DEM of SRTM for the estimation of errors. The spatial and temporal distribution of errors in the DEM is analyzed by considering several case studies. Spatial and temporal variability of precipitable water vapour is analysed. Precipitable water vapour (PWV) corrections to the DEMs are implemented and found to have no significant effect. The reasons are explained. Temporal decorrelation of phases and soil moisture variations seem to have influence on the accuracy of the derived DEM. It is suggested that installing a number of corner reflectors (CRs) and the use of Permanent Scatter approach may improve the accuracy of the results in desert test sites.
Twenty five ASAR scenes are analyzed to find the suitable pairs for generating DEM of Kuwait desert area. About 40
pairs are suitable for generating DEMs. A unique combination of seven DEM are possible with a single master image
whose perpendicular baseline component varies between 233 to 393m. GAMMA inerferometric package coupled with
ERDAS image processing package are used in the analysis. The seven DEMs are compared with the 90 m DEM
derived from SRTM. It has been found that the RMS error varies from 1.9 m to 15.3 m. The highest RMS error refers to
day-difference of 525 days with average coherence value of 0.71 (lowest of all). Therefore, correlation will be the cause
of higher errors. However, 35 days day-difference pair gave RMS error of 5.5 m with highest coherence value (0.93)
which is supposed to produce the lowest RMS error. For the study of spatial distribution of errors, Interferometric
DEMs are subtracted from DEM of SRTM. From this analysis, it is observed that the atmospheric affects are aligned
and varies systematically. It can give an error in elevation as high as 15 m. Therefore, one should be very careful in
using SAR interfoermetry technology for DEM generation even for desert regions.
Seven scenes of ASAR images acquired by ENVISAT satellite during the time period April 2004 - June 2005 have been analyzed to assess the geo-coding accuracy of the data. Eighty ground control points (GCPs) spread all over Kuwait were measured using Trimble 5700 GPS which are mainly the road intersections. The same road intersections were identified in the ASAR image and its geo-locations were measured using BEST software package provided by the European Space Agency. The GPS and BEST results were compared to estimate the geo-location accuracy of ASAR data. The average accuracy in geo-coding is estimated to be 54 m in both azimuth and range directions. These results are in agreement with the results reported in the literature. Twenty well-defined targets (built-up areas, grass lands, airports, agricultural plots, desert soils, etc.) were considered for the backscattering signature study. The size of each target varies from 50,000 to 100,000 Single Look Complex (SLC) pixels for good statistical accuracy. It has been estimated that the Standard Deviation (Std) of backscatter signature is 1.3% (after speckle filtering) of the mean value. The temporal / spatial variability of the signatures are within the Std. During the study period, the soil moisture varied from 6% to 10% as estimated from AMSR-E on board Acqua satellite.
The utility of ASAR data will be greately enhanced if the Radiometric and Geometric quality of the data satisfies the requirements of applications. 7 secenes of ASAR data acquired during April 2004 - June 2005 have been processed to assess the Geo-location accuracy and also temporal / spatial variability of backscattered signatures. Ground Crontrol Points (GPS) approach was used for Geometric accuracy assessment. 80 GCPs spread all through the image were measured using Trimble 5700. It is estimated that the geometric accuracy of the data is within 55 m. This is in agreement with the reported accuracies in the literature. About 20 well defined targets were considered for the backscattering signature study. The size of each target varies from 1000 to 5000 SLC pixels for good statistical stability of the signature. It has been estimated that the Standard Deviation (STD) of the sitgnature is 1.3% and the temporal / spatial variability of the signatures ( considering all varieties of targets such as built-up area, grass lands, airports, agricultureal plots, desert soils, etc) are within its STD. During this study period the soil moisture varied from 10% to 6% as recorded from AMSR-E on board Acqua satellite.The ASAR data has been filtered for speckle noise.
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