4.7 Article

Parameters Affecting Interferometric Coherence-The Case of a Dynamic Agricultural Region

Journal

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 52, Issue 3, Pages 1572-1582

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2013.2252620

Keywords

Coherence estimation; interferometry; subsidence monitoring

Funding

  1. South African Council for Geoscience
  2. South African Department of Science and Technology

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In South Africa, the need exists for a long-term monitoring system to detect deformation because of mining. Differential radar interferometry (dInSAR) is recognized for its ability to detect deformation without the need for extensive field observations. However, phase noise (assessed by interferometric coherence) is known to adversely affect interferometric measurements. In this paper, 12 polarimetric RADARSAT-2 SAR images are used to statistically analyze the sensitivity of coherence to perpendicular baseline, Doppler centroid (DC) difference, temporal baseline, land surface evolution, and polarization. The results suggest that the average scene coherence for HH and VV polarizations is most sensitive to the effects of temporal baseline if RADARSAT-2 data with small perpendicular baselines and DC differences are considered. However, an increase in the sensitivity to dc difference and perpendicular baseline is observed after analysis of ERS-2 data for which higher values of these parameters are available. The choice of optimal polarization is seasonally dependent, with VV polarization data being more suitable at the end of the growing season after harvesting, while HH polarization is more suitable during the peak of the growing season. Image pairs with at most 24-day temporal baselines are required during the peak of the growing season while successful interferogram generation is possible with temporal baselines of up to 120 days after the peak of the growing season. Subsidence basins are successfully detected, demonstrating that the dInSAR techniques would be suitable for the long-term monitoring of surface subsidence in this dynamic commercial agricultural environment.

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