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    ์‹œ๊ณ„์—ด InSAR ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ•˜์—ฌ ๋น„์ •์ƒ์  ํ•ด์ˆ˜๋ฉด ์ƒ์Šน ๊ธฐ๋ก์„ ๋ณด์ธ ์กฐ์œ„๊ด€์ธก์†Œ์˜ ์ˆ˜์ง์ง€๋ฐ˜๋ณ€์œ„ ํ‰๊ฐ€

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ์ง€๊ตฌํ™˜๊ฒฝ๊ณผํ•™๋ถ€, 2021.8. ๊น€๋•์ง„.Global sea level rise has been a serious threat to the low-lying coasts and islands around the world. It is important to understand the global and regional sea level changes for preventing the coastal zones. Tide gauges are installed around the world, which directly measures the change in sea level relative to the local datum. Sea level in the past three decades has risen to 1.8 mm/year compared to the sea level rise in the 20th century (3.35 mm/year), estimated by the Intergovernmental Panel on Climate Change (IPCC). However, along with the contributors of sea level rise, vertical land motion (VLM) is indeed an essential component for understanding the regional sea level change; however, its contribution remains still unclear. The VLM is referred to as change in elevation of land at tide gauge due to the regional and local processes by both natural and anthropogenic activities can deteriorate the sea level records and lead to spurious sea level acceleration. Assessing the vertical land motion at tide gauges with the accuracy of sub-millimeters is essential to reconstruct the global and regional sea level rise. Previous studies attempt to observe the vertical land movements at sparse locations through Global Positioning System (GPS). However, the VLM observed from the sparse GPS network makes the estimation uncertain. In this study, an alternative approach is proposed in this study to directly measure the relative vertical land motion including spatial and temporal variations through Synthetic Aperture Radar (SAR) data by using time-series SAR interferometric (InSAR) techniques. This work presents a contribution enhancing the estimation of VLM rates with high spatial resolution over large area using time-series InSAR analysis. First, the C-band Interferometric Wide-swath (IW) mode SAR data from the Sentinel-1 A/B satellite was used in this study to estimate the VLM rates of tide gauges. The Sentinel-1 A/B SAR data were obtained during the period between 2014/10 and 2020/12 (~ 6 years). Stanford Method for Persistent Scatterers โ€“ Persistent Scatterer Interferometry (StaMPS-PSI) time-series InSAR algorithm was initially applied to the case study: Pohang tide gauge in the Korean peninsula for monitoring the stability of tide gauge station and its VLM rates during 2014 ~ 2017. For the Pohang tide gauge site, SAR data acquired in both ascending and descending passes and derived the ground movement rates at tide gauge along the line-of-sight direction. The vertical movements from the collocated POHA GPS station were compared with the InSAR derived VLM rates for determining the correlation between the two methods. The VLM rates at the Pohang tide gauge site were -25.5 mm/year during 2014 ~ 2017. This VLM rate at Pohang tide gauge derived by StaMPS-PSI estimates were from the strong dominant scatterers along the coastal regions. Second, for the terrains, with few dominant scatterers and more distributed scatters, a short temporal InSAR pair selection approach was introduced, referred as Sequential StaMPS-Small baselines subset (StaMPS-SBAS) was proposed in this study. Sequential StaMPS-SBAS forms the interferograms of short temporal sequential order (n = 5) to increase the initial pixel candidates on the natural terrains in the vicinity of tide gauges. Sentinel-1 A/B SAR data over ten tide gauges in the Korean peninsula having different terrain conditions were acquired during 2014 ~ 2020; and employed with sequential StaMPS-SBAS to estimate the VLM rates and time-series displacements. The initial pixel density has been doubled and ~ 1.25 times the final coherent pixels identified over the conventional StaMPS-SBAS analysis. Third, the potential for the fully automatic estimation of time-series VLM rates by sequential StaMPS-SBAS analysis was investigated. A fully automatic processing module referred to as โ€˜Seq-TInSARโ€™, was developed which has three modules 1) automatically downloads Sentinel-1 Single look complex (SLC) data, precise orbit files, and Digital Elevation Model (DEM); 2) SLC pre-processor: extract bursts, fine Coregistration and stacking and, 3) Sequential StaMPS-SBAS processor: estimates the VLM rates and VLM time-series. Finally, the Seq-TInSAR module is applied to the 100 tide gauges that exhibit abnormal sea level trend with par global mean sea level average. For each tide gauge site, 60 ~ 70 Sentinel-1 A/B SLC scenes were acquired and 300 ~ 350 sequential interferograms were processed to estimate the VLM at tide gauge stations. The final quantitative VLM rates and time-series VLM are estimated for the selected tide gauges stations. Based on the VLM rates, the tide gauges investigated in this study are categorized into different VLM ranges. The in-situ GPS observations available at 12 tide gauge stations were compared with InSAR VLM rates and found strong agreement, which suggests the proposed approach more reliable in measuring the spatial and temporal variations of VLM at tide gauges.์ „ ์„ธ๊ณ„์ ์œผ๋กœ ๋ฐœ์ƒํ•˜๋Š” ํ•ด์ˆ˜๋ฉด ์ƒ์Šน์€ ์ €์ง€๋Œ€ ํ•ด์•ˆ๊ณผ ๋„์„œ ์ง€์—ญ์— ์‹ฌ๊ฐํ•œ ์œ„ํ˜‘์œผ๋กœ ์ž‘์šฉํ•œ๋‹ค. ํ•ด์•ˆ ์ง€์—ญ์„ ๋ณดํ˜ธํ•˜๊ธฐ ์œ„ํ•ด ์ „ ์ง€๊ตฌ ๋ฐ ํ•ด๋‹น ์ง€์—ญ์˜ ํ•ด์ˆ˜๋ฉด ๋ณ€ํ™”๋ฅผ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์€ ๋Œ€๋‹จํžˆ ์ค‘์š”ํ•˜๋‹ค. ์กฐ์œ„ ๊ด€์ธก์†Œ๋Š” ์ „ ์„ธ๊ณ„์— ์„ค์น˜๋˜์–ด ํ•ด๋‹น ์ง€์—ญ ๊ธฐ์ค€์— ๋”ฐ๋ฅธ ํ•ด์ˆ˜๋ฉด ๋ณ€ํ™”๋ฅผ ์ง์ ‘ ์ธก์ •ํ•œ๋‹ค. ์ง€๋‚œ 30 ๋…„๊ฐ„ ํ•ด์ˆ˜๋ฉด์€ IPCC (์ •๋ถ€ ๊ฐ„ ๊ธฐํ›„ ๋ณ€ํ™” ํŒจ๋„)๊ฐ€ ์ถ”์ •ํ•œ 20 ์„ธ๊ธฐ์˜ ํ•ด์ˆ˜๋ฉด ์ƒ์Šน (3.35mm / ๋…„)๋Œ€๋น„ 1.8mm / ๋…„ ๊ฐ€๊นŒ์ด ์ƒ์Šนํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ•ด์ˆ˜๋ฉด ์ƒ์Šน์˜ ์›์ธ๊ณผ ํ•จ๊ป˜ ์—ฐ์ง ์ง€๋ฐ˜ ์šด๋™ (VLM)์€ ์ง€์—ญ ํ•ด์ˆ˜๋ฉด ๋ณ€ํ™”๋ฅผ ์ดํ•ดํ•˜๋Š” ๋ฐ ํ•„์ˆ˜์ ์ธ ์š”์†Œ์ด์ง€๋งŒ ๊ทธ ๊ธฐ์—ฌ๋„๋Š” ์—ฌ์ „ํžˆ ๋ถˆ๋ถ„๋ช…ํ•˜๋‹ค. VLM์€ ์ž์—ฐ ํ™œ๋™๊ณผ ์ธ๊ฐ„ ํ™œ๋™ ๋ชจ๋‘์— ์˜ํ•œ ์ง€์—ญ์  ๋ณ€ํ™”๋กœ ์ธํ•ด ์กฐ์œ„ ๊ด€์ธก์†Œ์—์„œ ์ง€๋ฐ˜์˜ ๊ณ ๋„ ๋ณ€ํ™”๋กœ ์ •์˜๋˜๋ฉฐ ํ•ด์ˆ˜๋ฉด ๋ณ€ํ™” ์ •ํ™•๋„์„ ์•…ํ™”์‹œํ‚ค๊ณ  ์œ ์‚ฌ ํ•ด์ˆ˜๋ฉด ๋ณ€ํ™”์˜ ๊ฐ€์†์„ ์ดˆ๋ž˜ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ „ ์„ธ๊ณ„ ๋ฐ ์ง€์—ญ ํ•ด์ˆ˜๋ฉด ์ƒ์Šน์„ ์žฌ๊ตฌ์„ฑํ•˜๋ ค๋ฉด 1 ๋ฐ€๋ฆฌ๋ฏธํ„ฐ ๋ฏธ๋งŒ์˜ ์ •ํ™•๋„๋กœ ์กฐ์œ„ ๊ด€์ธก์†Œ์—์„œ VLM์„ ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ์ด ํ•„์ˆ˜์ ์ด๋‹ค. ์ด์ „ ์—ฐ๊ตฌ๋Š” GPS (Global Positioning System)๋ฅผ ํ†ตํ•ด ์ œํ•œ๋œ ์œ„์น˜์—์„œ VLM ์„ ๊ด€์ธกํ•˜๋ ค๊ณ  ์‹œ๋„ํ•˜์˜€์œผ๋‚˜ ๊ตญ์†Œ์ ์ธ GPS ์‹ ํ˜ธ๋“ค๋กœ๋ถ€ํ„ฐ ๊ด€์ธก๋œ VLM์œผ๋กœ๋Š” ๊ทธ ์ถ”์ •์ด ๋ถˆํ™•์‹คํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์‹œ๊ณ„์—ด SAR ๊ฐ„์„ญ๊ณ„ (InSAR) ๊ธฐ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ SAR (Synthetic Aperture Radar) ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ๊ณต๊ฐ„์ , ์‹œ๊ฐ„์  ๋ณ€ํ™”๋ฅผ ํฌํ•จํ•œ ์ƒ๋Œ€์  VLM์„ ์ง์ ‘ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•œ ๋Œ€์•ˆ์  ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ์ด ์ž‘์—…์€ ์‹œ๊ณ„์—ด InSAR ๋ถ„์„์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ด‘๋Œ€์—ญ์— ๊ฑธ์ณ ๋†’์€ ๊ณต๊ฐ„ ํ•ด์ƒ๋„๋กœ VLM ์†๋„์˜ ์ถ”์ •์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๋ฐ ๊ธฐ์—ฌํ•œ๋‹ค. ์ฒซ์งธ๋กœ, Sentinel-1 A / B ์œ„์„ฑ์˜ C-band Interferometric Wide-swath (IW) ๋ชจ๋“œ SAR ์˜์ƒ์ด ๋ณธ ์—ฐ๊ตฌ์—์„œ ์กฐ์œ„ ๊ด€์ธก์†Œ์˜ VLM ์†๋„๋ฅผ ์ถ”์ •ํ•˜๋Š” ๋ฐ ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. Sentinel-1 A / B SAR ์˜์ƒ์€ 2014 ๋…„ 10 ์›”๋ถ€ํ„ฐ 2020 ๋…„ 12 ์›”๊นŒ์ง€ (~ 6 ๋…„) ๊ธฐ๊ฐ„ ๋™์•ˆ ์ˆ˜์ง‘๋˜์—ˆ๋‹ค. ๊ณ ์ • ์‚ฐ๋ž€์ฒด๋ฅผ ์œ„ํ•œ ์Šคํƒ ํฌ๋“œ ๊ธฐ๋ฒ• โ€“ ๊ณ ์ • ์‚ฐ๋ž€ ๊ฐ„์„ญ๊ณ„ (StaMPS-PSI) ์‹œ๊ณ„์—ด InSAR ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ํ•œ๋ฐ˜๋„ ํฌํ•ญ ์กฐ์œ„ ๊ด€์ธก์†Œ์˜ 2014 ~ 2017 ๋…„ ๋™์•ˆ์˜ ์กฐ์œ„ ๊ด€์ธก์†Œ์˜ ์•ˆ์ •์„ฑ๊ณผ VLM ์†๋„๋ฅผ ๋ชจ๋‹ˆํ„ฐ๋งํ•˜๊ธฐ ์œ„ํ•ด ์ ์šฉ๋˜์—ˆ๋‹ค. ํฌํ•ญ ์กฐ์œ„ ๊ด€์ธก์†Œ ๋ถ€์ง€์˜ ๊ฒฝ์šฐ, ์œ„์„ฑ๊ถค๋„์˜ ์ƒ์Šน ๋ฐ ํ•˜๊ฐ• ๊ฒฝ๋กœ๋กœ ํš๋“ํ•œ SAR ์˜์ƒ์„ ํ†ตํ•ด ์‹œ์„  ๋ฐฉํ–ฅ์„ ๋”ฐ๋ผ ์กฐ์œ„ ๊ด€์ธก์†Œ์—์„œ์˜ ์ง€๋ฉด ์ด๋™ ์†๋„๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. ํฌํ•ญ GPS ๊ด€์ธก์†Œ์˜ ์—ฐ์ง ์ด๋™์€ ๋‘ ๊ธฐ๋ฒ• ๊ฐ„์˜ ์ƒ๊ด€์„ฑ๋ฅผ ํŒ๋‹จํ•˜๊ธฐ ์œ„ํ•ด InSAR๊ธฐ๋ฒ•์œผ๋กœ๋ถ€ํ„ฐ ์ถ”์ •๋œ VLM ์†๋„์™€ ๋น„๊ต๋˜์—ˆ๋‹ค. ํฌํ•ญ ์กฐ์œ„ ๊ด€์ธก์†Œ์˜ VLM ์†๋„๋Š” 2014 ~ 2017 ๋…„์˜ ๊ธฐ๊ฐ„ ๋™์•ˆ -25.5mm / ๋…„์œผ๋กœ ๊ด€์ธก๋˜์—ˆ๋‹ค. StaMPS-PSI ์ถ”์ •์— ์˜ํ•ด ๋„์ถœ ๋œ ํฌํ•ญ ์กฐ์œ„ ๊ด€์ธก์†Œ์˜ VLM ์†๋„์€ ํ•ด์•ˆ ์ง€์—ญ์˜ ๊ฐ•ํ•œ ์‚ฐ๋ž€ ์ฒด์—์„œ ๊ธฐ์ธํ•œ๋‹ค. ๋‘˜์งธ๋กœ, ๊ฐ•ํ•œ ์‚ฐ๋ž€์ฒด๊ฐ€ ์ˆ˜๊ฐ€ ์ ๊ณ  ๋ถ„์‚ฐ๋œ ์‚ฐ๋ž€์ฒด๊ฐ€ ๋” ๋งŽ์€ ์ง€ํ˜•์˜ ๊ฒฝ์šฐ, ๋ณธ ์—ฐ๊ตฌ์—์„œ Sequential StaMPS-Small baselines (StaMPS-SBAS)์ด๋ผ๋Š” ํ•˜๋Š” ๋‹จ๊ธฐ InSAR ์Œ์˜ ์„ ํƒ์— ์˜ํ•œ ์ ‘๊ทผ ๋ฐฉ์‹์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. Sequential StaMPS-SBAS๋Š” ์งง์€ ์‹œ๊ฐ„ ๋ฒ”์œ„(n = 5)์˜ ๊ฐ„์„ญ๊ณ„ ์˜์ƒ์„ ํ˜•์„ฑํ•˜์—ฌ ์กฐ์œ„ ๊ด€์ธก์†Œ ๋ถ€๊ทผ์˜ ์ž์—ฐ ์ง€ํ˜•์—์„œ ๋ณ€ํ™”๊ฐ€ ์ ์€ ํ™”์†Œ ์„ ํƒ์„ ์ฆ๊ฐ€์‹œํ‚จ๋‹ค. Sentinel-1 A / B SAR ์˜์ƒ์€ 2014 ๋…„ ~ 2020 ๋…„ ์‚ฌ์ด์— ์„œ๋กœ ๋‹ค๋ฅธ ์ง€ํ˜• ์กฐ๊ฑด์„ ๊ฐ€์ง„ ํ•œ๋ฐ˜๋„์˜ 10 ๊ฐœ ์กฐ์œ„ ๊ด€์ธก์†Œ์—์„œ ์ˆ˜์ง‘๋˜์—ˆ์œผ๋ฉฐ, VLM ์†๋„ ๋ฐ ์‹œ๊ณ„์—ด ๋ณ€์œ„๋ฅผ ์ถ”์ •ํ•˜๊ธฐ ์œ„ํ•ด Sequential StaMPS-SBAS์™€ ํ•จ๊ป˜ ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ์ดˆ๊ธฐ ํ™”์†Œ ๋ฐ€๋„๋Š” ๊ธฐ์กด StaMPS-SBAS ๋ถ„์„์„ ํ†ตํ•ด ํ™•์ธ ๋œ ์ตœ์ข…์ ์ธ ๋ถˆ๋ณ€ํ™”์†Œ ๋ฐ€๋„์˜ ์•ฝ 1.25 ๋ฐฐ์™€ ๋‘ ๋ฐฐ๋กœ ๋„์ถœ๋˜์—ˆ๋‹ค. ์…‹์งธ๋กœ, Sequential StaMPS-SBAS ๋ถ„์„์— ์˜ํ•œ ์‹œ๊ณ„์—ด VLM ๋น„์œจ์˜ ์™„์ „ํ•œ ์ž๋™ ์ถ”์ • ๊ฐ€๋Šฅ์„ฑ์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. Seq-TInSAR๋ผ๊ณ ํ•˜๋Š” ์™„์ „ํ•œ ์ž๋™ ์ฒ˜๋ฆฌ ๋ชจ๋“ˆ์ด ๊ฐœ๋ฐœ๋˜์—ˆ์œผ๋ฉฐ, 3 ๊ฐœ์˜ ํ•˜์œ„ ๋ชจ๋“ˆ๋กœ ๊ตฌ์„ฑ๋˜์–ด์žˆ๋‹ค. 1) Sentinel-1 SLC (Single Look Complex) ์˜์ƒ, ์ •๋ฐ€ํ•œ ๊ถค๋„ ์ •๋ณด ๋ฐ DEM (Digital Elevation Model)์˜ ์ž๋™ ๋‹ค์šด๋กœ๋“œ 2) SLC ์ „ ์ฒ˜๋ฆฌ๊ธฐ : ์˜์ƒ ๋ณ„ Burst ์ถ”์ถœ, ์ •๋ฐ€ํ•œ ํ†ตํ•ฉ ๋ฐ Stacking, 3) Sequential StaMPS-SBAS ํ”„๋กœ์„ธ์„œ : VLM ์†๋„ ๋ฐ VLM ์‹œ๊ณ„์—ด ๋ณ€์œ„์˜ ์ถ”์ • ๋งˆ์ง€๋ง‰์œผ๋กœ, Seq-TInSAR ๋ชจ๋“ˆ์€ ๋™์œ„ ํ‰๊ท  ํ•ด์ˆ˜๋ฉด ํ‰๊ท ์œผ๋กœ ๋น„์ •์ƒ์ ์ธ ํ•ด์ˆ˜๋ฉด ์ถ”์„ธ๋ฅผ ๋ณด์ด๋Š” 100 ๊ฐœ์˜ ์กฐ์œ„ ๊ด€์ธก์†Œ์— ์ ์šฉ๋œ๋‹ค. ์กฐ์œ„ ๊ด€์ธก์†Œ ์ง€์ ๋ณ„๋กœ 60 ~ 70 ๊ฐœ์˜ Sentinel-1 A / B SLC ์˜์ƒ์„ ํš๋“ํ•˜๊ณ  300 ~ 350 ๊ฐœ์˜ ์‹œ๊ณ„์—ด ๊ฐ„์„ญ๊ณ„ ์˜์ƒ์„ ์ฒ˜๋ฆฌํ•˜์—ฌ ์กฐ์œ„ ๊ด€์ธก์†Œ์—์„œ VLM์„ ์ถ”์ •ํ•˜์˜€๋‹ค. ์ •๋Ÿ‰์ ์ธ VLM ์†๋„์™€ ์‹œ๊ณ„์—ด VLM์€ ์„ ์ •ํ•œ ์กฐ์œ„ ๊ด€์ธก์†Œ์— ๋Œ€ํ•ด ์ถ”์ •ํ•˜์˜€๋‹ค. VLM ์†๋„์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋„์ถœํ•œ ์กฐ์œ„ ๊ด€์ธก์†Œ๋Š” ๋‹ค์–‘ํ•œ VLM ๋ฒ”์œ„๋กœ ๋ถ„๋ฅ˜๋œ๋‹ค. 12 ๊ฐœ์˜ ์กฐ์œ„ ๊ด€์ธก์†Œ์—์„œ ์ทจ๋“ํ•œ ํ˜„์žฅ GPS ๊ด€์ธก ์ž๋ฃŒ๋ฅผ InSAR๋กœ๋ถ€ํ„ฐ ์ถ”์ •ํ•œ VLM ๋น„์œจ๊ณผ ๋น„๊ตํ•˜์—ฌ ๊ฐ•๋ ฅํ•œ ์ƒ๊ด€์„ฑ์„ ์ฐพ์•˜๊ณ , ์ด๋Š” ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆํ•œ ์ ‘๊ทผ ๋ฐฉ์‹์ด ์กฐ์œ„ ๊ด€์ธก์†Œ์—์„œ VLM์˜ ๊ณต๊ฐ„์  ๋ฐ ์‹œ๊ฐ„์  ๋ณ€ํ™”๋ฅผ ์ธก์ •ํ•˜๋Š”๋ฐ ์‹ ๋ขฐํ•  ์ˆ˜ ์žˆ๋Š” ์ž๋ฃŒ๋กœ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค.Chapter 1. Introduction 1 1.1. Brief overview of sea-level rise 1 1.2. Motivations 4 1.3. Purpose of Research 9 1.4. Outline 12 Chapter 2. Sea Level variations and Estimation of Vertical land motion 14 2.1. Sea level variations 14 2.2. Sea level observations 14 2.3. Long term sea level estimation 19 2.4. Factors contributing tide gauge records: Vertical Land Motion 19 2.5. Brief overview of InSAR and Time-series SAR Interferometry 24 Chapter 3. Vertical Land Motion estimation at Tide gauge using Time-series PS-InSAR technique: A case study for Pohang tide gauge 36 3.1. Background 36 3.2. VLM estimation at Pohang tide gauge using StaMPS-PSI analysis 38 3.3. Development of StaMPS-SBAS InSAR using Sequential InSAR pair selection suitable for coastal environments 55 3.4. Discussion 80 Chapter 4. Application of time-series Sequential-SBAS InSAR for Vertical Land Motion estimation at selected tide gauges around the world using Sentinel-1 SAR data 85 4.1. Description of PSMSL tide gauge data 87 4.2. Sentinel-1 A/B SAR data acquisitions 92 4.3. Automatic Time-series InSAR processing module โ€Seq-TInSARโ€ 93 4.4. Results: Estimation of vertical land motions at selected tide gauges 97 4.5. Comparison of InSAR results with GNSS observations 112 4.6. Discussion 125 Chapter 5. Conclusions and Future Perspectives 128 Abstract in Korean 133 Appendix โ€“ A 136 Appendix โ€“ B 146 Bibliography 151๋ฐ•

    A general framework and related procedures for multiscale analyses of DInSAR data in subsiding urban areas

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    In the last decade Differential Synthetic Aperture Radar (DInSAR) data were successfully tested in a number of case studies for the detection, mapping and monitoring of ground displacements associated with natural or anthropogenic phenomena. More recently, several national and regional projects all around the world provided rich data archives whose confident use, however, should rely on multidisciplinary experts in order to avoid misleading interpretations. To this aim, the present work first introduces a general framework for the use of DInSAR data; then, focusing on the analysis of subsidence phenomena and the related consequences to the exposed facilities, a set of original procedures is proposed. By drawing a multiscale approach the study highlights the different goals to be pursued at different scales of analysis via high/very high resolution SAR sensors and presents the results with reference to the case study of the Campania region (southern Italy) where widespread ground displacements occurred and damages of different severity were recorded

    Elevation change of Bhasan Char measured by persistent scatterer interferometry using Sentinel-1 data in a humanitarian context

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    This study investigates the elevation changes for the island of Bhasan Char, located in the Bay of Bengal, which was selected for the relocation of around 100,000 refugees of the Rohingya minority which were forced to leave their homes in Myanmar. Eighty-nine Sentinel-1 products were analysed using persistent scatterer interferometry (PSI) beginning August 2016 through September 2019, divided into three periods of one year to reduce the impact of temporal decorrelation. The findings indicate that the island is a recent landform which underlies naturally induced surface changes with velocities of up to ยฑ20 mm per year. Additional displacement is probably caused by heavy construction loads since early 2018, although we found no statistical evidence for this. The main built-up area shows stable behaviour during the analysed period, but there are significant changes along the coasts and artificial embankments of the island, and within one separate settlement in the north. The moist surface conditions and strong monsoonal rains complicated the proper retrieval of stable trends, but the sum of findings supports the assumption that the island underlies strong morphologic dynamics which put the people to be relocated at additional risk. Its suitability for construction has to be investigated in further studies

    Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

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    This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

    Analisi di dati DInSAR in aree urbane affette da subsidenza o frane a cinematica lenta

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    2012 - 2013Subsidence and slow-moving landslides systematically cause social, economic and environmental impacts all over the world. For this reason studies aimed at both the characterization of subsidence and slow-moving landslides and the analysis of the consequences on the exposed elements interacting with them are of great interest for the scientific and the technical community. These studies, to be useful in land use planning and management, need a huge number of displacement measurements within and on the boundary of the affected areas. Recently the scientific community has shownan increasing interest in the potential of using satellite observation techniques and, in particular, interferometric methods of Synthetic Aperture Radar (DInSAR)image processing. The literature review on DInSAR applications highlights the possibility of further researches pursuing the exploitation of DInSAR potentiality in studies at different scales and the development of procedures for the proper use of interferometric data and their validation with reference to well documented case studies. To this end, this PhD Thesis is aimed at developing original procedures for the analysis of the interferometric measurements specifically devotedto pursue two main objectives: the characterization of the phenomena of interest and the prediction of consequences to buildings interacting with them. The conceived procedures were tested, in sample areas of the Campania region (southern Italy)following a multi-scale approach. With reference to subsidence phenomena, the studies at small-scale involved the entire region and were mainly aimedatdetecting subsiding macro-areas; within these latter, more detailed studies at medium scale were carried out and the most affected municipalities were individuated. At large scale,focusing on one of these municipalities, studies dealing with the analysis of parameters whose variation leadsto the generation of the damage were carried out. Finally, at the scale of the single building the interferometric data were interpretedaccording todamageability criteria adopted in engineering practice. As forslow-moving landslides, the joint use of interferometric measurements and damage surveysallowed the updating of landslide inventory maps at medium scale and the analysis of the consequencesthrough the generation of fragility and vulnerability curves within a test area including 21 municipalities of BeneventoProvince. At large-scale studies were performed on a landslide-affected area within the municipality of Ascea(Salerno Province) in order to follow the evolution - in space and time - of the analyzed phenomenon as well as to deepen its kinematic behavior, in turn useful for zoning purposes. The obtained results highlight that the conceived procedures can valuably integrate the current practice for land use planning and as well as for the selection of the most suitablemanagement strategy.XII n.s

    Vulnerability analysis of buildings in areas affected by slow-moving landslides and subsidence phenomena

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    2015 - 2016Slow-moving landslides and subsidence phenomena yearly induce huge damages both direct (on structures and/or infrastructures with them interacting) and indirect (corresponding to the associated economic losses). For this reason, studies aimed at analyzing and predicting the aforementioned damages are of great interest for Scientific Community and Authorities in charge of identifying the most suitable strategies for the land-use planning and management of urban areas affected by slowmoving landslides and subsidence phenomena. However, carrying out the activities related to the pursuit of those goals is not straightforward since it usually requires high costs due to the great amount of data to be collected for setting up reliable forecasting models as well as the development of proper procedures that take into account i) the identification and quantification of the exposed elements; ii) the definition and estimation of an intensity parameter; iii) the prediction of the damage severity level (generally associated with the attainment of a certain limit state). In this PhD Thesis some original procedures are proposed. In particular, on the basis of empirical and numerical methods, fragility and vulnerability curves are generated in order to predict the damage to buildings in subsidence- and slow-moving landslide-affected areas. The proposed empirical procedures, based on the joint use of DInSAR data (provided from the processing of images acquired by Synthetic Aperture Radar via Differential Interferometric techniques) and information on damages suffered by buildings (recorded and classified during in situ surveys), were tested on case studies in The Netherlands, affected by subsidence phenomena, and in Calabria Region (southern Italy) for slow-moving landslide-affected areas. The procedure based on the adoption of a numerical method was applied on a structural model representative of a single building. With reference to subsidence phenomena, the analyses were carried out for a densely urbanized municipality following a multi-scale approach. In particular, at medium scale, the subsiding areas that are most prone to ground surface settlements along with their spatial distribution and rates, were preliminarily detected. The above ground surface settlements (here considered as subsidence intensity parameter) combined with the results of an extensive damage survey on masonry buildings, allowed first retrieving, at large-scale (on building aggregates) and at detailed scale (on single buildings), the relationships between cause (settlements/differential settlements) and effect (damage severity level); then, empirical fragility curves were generated for structurally independent single buildings. These latter were validated via their comparison with fragility curves generated, with reference to two others densely urbanized municipalities, for buildings with similar structural typology (masonry) and foundation type (shallow or deep). Finally, fragility and vulnerability curves for masonry buildings were generated by using the entire database of damages. As for slow-moving landslides, the analyses were carried out at large scale. In particular, the joint use of DInSAR and damage surveys data allowed analyzing the consequences induced on the buildings (either of masonry or reinforced concrete) with shallow foundations by retrieving the causeeffect relationships and generating empirical fragility and vulnerability curves. Finally, the numerical analyses carried out on a structural model representative of a single masonry building, allowed to go in-depth in the different aspects contributing to the onset and development of building damages as well as to quantify the uncertainties inherent to the addressed issue. The obtained results highlight the huge potential of the fragility and vulnerability curves generated according to the proposed procedures that, once further calibrated/validated and jointly used with a continuous monitoring of the intensity parameter via conventional (e.g., inclinometers, GPS, topographic leveling) and/or innovative (e.g., SAR images processed via DInSAR techniques) systems, can be valuably used as tools for the analysis and prediction of the damage to buildings for land-use planning and urban management purposes in subsidence- and slow-moving landslide-affected areas. [edited by author]Le frane a cinematica lenta e i fenomeni di subsidenza causano annualmente ingenti danni sia diretti (su strutture e/o infrastrutture con essi interagenti) che indiretti (quali si configurano le associate perdite di natura economica). Per tale ragione, gli studi volti ad analizzare e a prevedere i predetti danni sono di indubbio interesse per le Comunitร  e gli Enti impegnati nella individuazione delle piรน idonee strategie di pianificazione e di gestione delle aree urbanizzate affette dai suddetti fenomeni. Tuttavia, lo svolgimento delle attivitร  connesse al perseguimento dei predetti obiettivi รจ tuttโ€™altro che agevole in quanto richiede costi elevati, dovuti alla grande quantitร  di dati da acquisire per la generazione di modelli previsionali affidabili, nonchรฉ lo sviluppo di procedure che contemplino i) lโ€™identificazione e la quantificazione degli elementi esposti, ii) la definizione e la stima di un parametro di intensitร  e iii) la previsione del livello di severitร  del danno (generalmente associato al raggiungimento di uno stato limite). La presente Tesi di Dottorato propone alcune procedure originali che, sulla base di metodi empirici e numerici, conducono alla generazione di curve di fragilitร  e vulnerabilitร  quali strumenti di previsione del danno a edifici in aree affette da frane a cinematica lenta e fenomeni di subsidenza. Le procedure empiriche proposte, basate sullโ€™integrazione congiunta di dati DInSAR (ovvero derivanti dalla elaborazione di immagini acquisite da radar ad apertura sintetica montati su piattaforme satellitari mediante tecniche interferometriche differenziali) e sul danno subito da edifici (a sua volta classificato sulla base degli esiti di rilievi in sito dei quadri fessurativi esibiti dalle facciate), sono state testate con riferimento a casi di studio dei Paesi Bassi, affetti da fenomeni di subsidenza, e della Regione Calabria (Italia meridionale), interessati da frane a cinematica lenta. La procedura basata sullโ€™impiego di metodi numerici รจ stata, invece, applicata su un modello strutturale rappresentativo di un edificio singolo. Con riferimento ai fenomeni di subsidenza, le attivitร  svolte con un approccio multi-scalare hanno consentito preliminarmente di rilevare (a media scala) le aree che risultano essere maggiormente predisposte a cedimenti dovuti a fenomeni di subsidenza. La conoscenza della distribuzione spaziale e della entitร  di tali cedimenti รจ stata, poi, combinata con i risultati di un esteso rilievo del danno agli edifici in muratura di unโ€™area comunale in modo da i) risalire โ€“ sia a grande scala (su aggregati di edifici) che a scala di dettaglio (singoli edifici) โ€“ alle relazioni funzionali che si stabiliscono tra causa (cedimenti assoluti/differenziali) ed effetti (livello di severitร  del danno) e ii) generare per singoli edifici strutturalmente indipendenti curve di fragilitร  su base empirica. Le curve di fragilitร  cosรฌ calibrate sono state, poi, validate operandone un confronto con curve di fragilitร  generate, con la medesima procedura, per altre due aree comunali caratterizzate dalla presenza di edifici con la stessa tipologia strutturale e fondale (superficiale o profonda). Si รจ, infine, provveduto alla generazione di curve di fragilitร  e di vulnerabilitร  di edifici in muratura utilizzando lโ€™intero campione di dati a disposizione. Per quanto riguarda le frane a cinematica lenta, le analisi sono state svolte esclusivamente a grande scala, dove lโ€™uso congiunto dei dati DInSAR e del rilievo del danno a edifici in cemento armato e in muratura con fondazioni superficiali ha consentito, ancora una volta, di risalire alle relazioni causa-effetto e di generare curve di fragilitร  e di vulnerabilitร  su base empirica. Infine, lโ€™analisi numerica effettuata su un modello strutturale rappresentativo di un singolo edificio in muratura con fondazioni superficiali ha consentito di approfondire il ruolo esercitato da alcuni fattori nella generazione e nello sviluppo del danno nonchรฉ di quantificare le incertezze che intervengono nel problema esaminato. I risultati ottenuti evidenziano lโ€™enorme potenzialitร  delle curve di fragilitร  e vulnerabilitร  ottenute che, laddove ulteriormente calibrate e validate, possono essere impiegate congiuntamente con tecniche di monitoraggio in continuo dei parametri dโ€™intensitร  โ€“ sia di tipo convenzionale (quali, ad esempio, inclinometri, GPS, livellazione topografica) che innovative (come quelle derivanti dallโ€™elaborazione di immagini satellitari mediante tecniche DInSAR) โ€“ per la messa a punto di modelli previsionali utili alla pianificazione territoriale e alla gestione di aree urbane affette da frane a cinematica lenta e fenomeni di subsidenza. [a cura dell'autore]XV n.s

    An investigation of ongoing displacements of active faults in the Gobi desert using persistent scatterer interferometric synthetic aperture radar technique to support the permanent disposal of high-level waste in Beishan, China

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    This research demonstrated the application of PSInSAR method in identifying and characterising the micro-displacements along active faults in Beishan to support the selection of GDF host rock. This research first distinguishes and separates the tectonic induced and non-tectonic induced deformation within three study areas at Suanjingzi, Jiujing and Xinchang. Through the application of coherence change detection, it found the granite outcrop areas characterised by high coherence provide more robust results of tectonic activity. The Quaternary sediments covered areas which are characterised by low coherence usually show higher deformation rates due to the impacts of erosion and deposition. The tectonic induced displacements generally range from -0.4 to 0.4 mma-1 and are dominated by fault bound tectonic movements. As a part of wrench faut zone, Beishan is impacted by a NE-SW trended maximum in situ compressive stress field (ฯƒ1). To correlate the visible valleys, gullies, or cracks in Google Earth imagery with the SAR image deformation discontinuities, this study mapped and characterised more than 40 active faults in the three study areas, these include (1) the NE-SW trended sinistral strike-slip faults triggered by extension and (2) the NW-SE/W-E trended reverse faults triggered by maximum compression. The fault activity is characterised by subtle (minor) displacement rate value difference between the two sides of the fault plane. This research successfully improved the understanding of local structural geology and provided moderate guidance for the selection of HLW disposal sites in China. It was indicated that Xinchang has the highest tectonic stability, and this is then followed by Jiujing and Suanjingzi. This kind of displacement rate difference is possible due to the angle difference towards the Sanweishan Fault Zone. To trace and characterise the undiscovered active fault planes, the PSInSAR approach also benefits the prediction of earthquake by improving the positioning of the potential epicentres.Open Acces

    Technology and Management for Sustainable Buildings and Infrastructures

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    A total of 30 articles have been published in this special issue, and it consists of 27 research papers, 2 technical notes, and 1 review paper. A total of 104 authors from 9 countries including Korea, Spain, Taiwan, USA, Finland, China, Slovenia, the Netherlands, and Germany participated in writing and submitting very excellent papers that were finally published after the review process had been conducted according to very strict standards. Among the published papers, 13 papers directly addressed words such as sustainable, life cycle assessment (LCA) and CO2, and 17 papers indirectly dealt with energy and CO2 reduction effects. Among the published papers, there are 6 papers dealing with construction technology, but a majority, 24 papers deal with management techniques. The authors of the published papers used various analysis techniques to obtain the suggested solutions for each topic. Listed by key techniques, various techniques such as Analytic Hierarchy Process (AHP), the Taguchi method, machine learning including Artificial Neural Networks (ANNs), Life Cycle Assessment (LCA), regression analysis, Strengthโ€“Weaknessโ€“Opportunityโ€“Threat (SWOT), system dynamics, simulation and modeling, Building Information Model (BIM) with schedule, and graph and data analysis after experiments and observations are identified

    La variabilitรฉ rรฉgionale du niveau de la mer

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    Au cours du XXรจme siรจcle, les mesures marรฉgraphiques ont permis d'estimer la hausse du niveau de la mer global ร  1.7 mm.a-1. Depuis deux dรฉcennies, les observations faites par les satellites altimรฉtriques indiquent une hausse du niveau de la mer plus rapide, de 3.2 mm. a-1 sur la pรฉriode 1993-2011. Grรขce ร  leur couverture quasi-globale, les observations spatiales ont aussi rรฉvรฉlรฉ une forte variabilitรฉ rรฉgionale dans la hausse du niveau de la mer qui dรฉpasse de beaucoup la hausse moyenne globale dans de nombreuses rรฉgions du globe. Cette composante rรฉgionale qui s'ajoute ร  la hausse globale pour donner le niveau de la mer total local, est essentielle dans l'รฉtude des impacts de la hausse du niveau de la mer sur les rรฉgions cรดtiรจres et les รฎles basses. Dans cette thรจse, nous analysons les observations de la variabilitรฉ rรฉgionale de la hausse du niveau de la mer, nous proposons une reconstruction de cette variabilitรฉ rรฉgionale depuis 1950 (i.e. avant l'avรจnement de l'altimรฉtrie spatiale) et nous รฉtudions ses causes et ses origines. Tout d'abord, nous proposons une reconstruction de la variabilitรฉ rรฉgionale du niveau de la mer dans le passรฉ (avant la pรฉriode altimรฉtrique) en combinant des donnรฉes marรฉgraphiques avec les structures spatiales propres de l'ocรฉan dรฉduites des modรจles d'ocรฉan. Cette mรฉthode permet de reconstruire le niveau de la mer en 2 dimensions depuis 1950, sur la majeure partie du globe, avec une rรฉsolution proche de celle de l'altimรฉtrie spatiale. Ensuite, nous appliquons la mรฉthode de reconstruction pour estimer la variabilitรฉ rรฉgionale de la hausse du niveau de la mer passรฉe dans trois rรฉgions sensibles au rรฉchauffement climatique : le Pacifique tropical, la mer Mรฉditerranรฉe et l'ocรฉan Arctique. Nous en dรฉduisons pour ces rรฉgions la hausse totale ( rรฉgionale plus moyenne globale) du niveau de la mer local au cours des derniรจres dรฉcennies. Pour les sites oรน l'on dispose de mesures du mouvement de la croรปte terrestre, nous รฉvaluons la hausse local du niveau de la mer relatif (i.e. hausse du niveau de la mer totale plus mouvement de la croรปte local) depuis 1950. Le but est de permettre les รฉtudes de l'impact local de la hausse du niveau de la mer aux รฉchelles climatiques. Enfin, nous analysons l'origine de la variabilitรฉ rรฉgionale de la hausse du niveau de la mer pour dรฉterminer si elle est due ร  l'activitรฉ anthropique ou si elle rรฉsulte de la variabilitรฉ naturelle du systรจme climatique. Nous nous focalisons sur le Pacifque tropical qui est marquรฉ par une trรจs forte variabilitรฉ rรฉgionale de la hausse du niveau de la mer depuis 1993. Grรขce a la reconstruction du niveau de la mer depuis 1950, nous montrons que cette variabilitรฉ rรฉgionale rรฉcente (17 derniรจres annรฉes) n'est pas stationnaire dans le temps mais qu'elle fluctue en lien avec une basse frรฉquence du mode de variabilitรฉ ENSO. Avec les modรจles de climat du projet CMIP3, nous montrons de plus que cette variabilitรฉ rรฉgionale est essentiellement d'origine naturelle (variabilitรฉ interne du systรจme climatique) et que l'impact anthropique y est trop faible pour l'instant pour y รชtre dรฉtectรฉ.Over the XXth century, tide gauge records indicate a rise in global sea level of 1.7 mm.a-1. For the past two decades, satellite altimetry data indicate a faster sea level rise of 3.2 mm.a-1 (period 1993-2011). Thanks to its global coverage, they also reveal a strong regional variability in sea level rise that is several times bigger than the global rise in many regions of the world. This regional signal, which must be added to the global sea level rise to compute the total sea level signal, is essential when assessing the potential impacts of sea level rise in coastal areas and low lying islands. In this thesis, we analyse the observed regional variability in sea level rise from satellite altimetry (since 1993), we propose a reconstruction of the past regional variability since 1950 (i.e. prior to altimetry) and we discuss its causes (thermal expansion of the ocean plus land ice loss) and origins (from natural or anthropogenic origin). First, we propose a reconstruction of the sea level variations for the past decades (before the altimetry era) by combining tide gauge records with the principal spatial structures of the ocean deduced from ocean general circulation models. This method enables to reconstruct the 2 dimensional sea level variations since 1950 with a spatial coverage and resolution similar to the satellite altimetry ones. In the second part of this thesis, the reconstruction method is applied to estimate the past regional variability in three regions which are particularly vulnerable to sea level rise: the tropical Pacific, the Mediterranean sea and the Arctic ocean. For each region, the reconstruction gives an estimation of the total (regional component plus global mean) 2-dimensional sea level rise over the past decades. For the sites where vertical crustal motion monitoring is available, we compute as well the total relative sea level (i.e. total sea level rise plus the local vertical crustal motion) since 1950. The objective is to provide estimates of the relative local sea level rise at climatic time scales to allow further studies on the coastal impacts of sea level rise. In the last part of this thesis, the question of the origins of the regional variability in sea level rise is addressed. We examine whether the regional variability in observed sea level rise since 1993 is a consequence of the anthropogenic activity or if it results essentially from the natural variability of the climate system. We focus on the Tropical Pacific where the regional variability in sea level rise is particularly strong since 1993. On the basis of the reconstruction of the sea level variations since 1950, we show that the recent regional variability in sea level rise observed by satellite (over the last 17 years) in this region is not stationnary. It fluctuates with time, following some low frequency of the ENSO climate mode of variability. With the CMIP3 climate models, we show that this regional variability is dominated by the natural variability of the climate system (essentially by the internal variability of the climate system) and that the signature of the anthropogenic activity is still too weak in this region to be detected
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