Journal
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
Volume -, Issue -, Pages 1103-1106Publisher
IEEE
DOI: 10.1109/IGARSS46834.2022.9884443
Keywords
DInSAR; P-SBAS; deformation time series; HPC; GPU; infrastructure monitoring; CSK; CSG; Sentinel-1
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Funding
- Presidency of the Council of Ministers-Department of Civil Protection, through the IREA-DPC
- EU EPOS-SP [871121]
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This work presents an advanced implementation of the P-SBAS DInSAR processing chain, which effectively and automatically generates DInSAR products related to buildings and infrastructures in Italy. The proposed pipeline utilizes GPU-based parallel technologies to efficiently process large amounts of DInSAR data, achieving high scalability. The results demonstrate the effectiveness of the solution in terms of computing time and efficiency.
In this work, we present an advanced implementation of the full resolution Parallel Small BAseline Subset (P-SBAS) DInSAR processing chain, aimed to effectively and automatically generate DInSAR products (displacement time series and corresponding velocity maps) related to single buildings and infrastructures over the whole Italian territory. The proposed full resolution P-SBAS pipeline exploits innovative hardware and software parallel technologies based on GPUs, which are able to efficiently process large amounts of full resolution DInSAR data stacks in reasonable time frames and with high scalability. The presented results, achieved by processing very large archives of full resolution X-band first and second generation COSMO-SkyMed data and C-band Sentinel-1 images, demonstrate the effectiveness of the proposed solution in terms of computing time and computational efficiency.
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