Multitemporal InSAR Coherence Analysis and Methods for Sand Mitigation

Manzoni, Marco; Molinari, Monia Elisa; Guarnieri, Andrea Monti

doi:10.3390/rs13071362

Cited by 8 publications

(11 citation statements)

References 31 publications

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“…We used multitemporal spatial coherence (MSC) as a proxy for stagnant areas delineation, similar to the method used by Manzoni et al (2021). The spatial distribution of the MSC is displayed in Supplementary Figure S2.…”

Section: Multitemporal Spatial Coherence From Sar Imagesmentioning

confidence: 99%

“…The development of remote sensing techniques, including optical and radar imagery and digital elevation models (DEMs), allows the investigation of geomorphological changes with dense spatiotemporal measurements. The majority of studies addressing the evolution of dune dynamics have been conducted using optical imagery (Manzoni et al, 2021). Compared to the optical imageries, the dependency on synthetic-aperture radar (SAR) imagery to monitor dune migration is not extensive.…”

Section: Introductionmentioning

confidence: 99%

“…Compared to the optical imageries, the dependency on synthetic-aperture radar (SAR) imagery to monitor dune migration is not extensive. Previous studies that employed SAR imagery (e.g., Rozenstein et al, 2016;Gaber et al, 2018;Ullmann et al, 2019;Manzoni et al, 2021) mainly depended on interferometric coherence as an indicator of dune and sand sheet instability. Notably, these coherence-based techniques do not provide any quantitative representation of dune dynamics, however, can be used as a proxy for the fine movements of dunes and sand sheets.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Aeolian Activity in the Bodélé Depression, Chad: A Dense Spatiotemporal Time Series From Landsat-8 and Sentinel-2 Data

Ali

Xie

et al. 2022

Front. Environ. Sci.

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There are several hotspots of dust production in the central Sahara, the Bodélé Depression (BD) in northern Chad is considered the largest source of aerosol dust worldwide, with the fastest Barchan dunes that migrate southwesterly. Less is known about the complex patterns of dune movement in the BD, especially on a short time scale. Time-series inversion of optical image cross-correlation (TSI-OICC) proved to be a valuable method for monitoring historical movements with low uncertainties, high spatial coverage, and dense temporal coverage. We leveraged ∼8 years of Landsat-8 and ∼6 years of Sentinel-2 data to capture the dune migration patterns at BD. We used TSI-OICC, creating four independent networks of offset maps from Landsat-8 and Sentinel-2 images, and forming three networks by fusing data from the two sensors. We depended on the multi spatial coherence estimated from Sentinel-1 interferograms to automatically discriminate between the active and stagnant regions, which is important for the postprocessing steps. We combined the data from the two sensors in areas of overlap to assess the performance of the fusion between two sensors in increasing the temporal scale of the observations. Our results suggest that dune migration at BD is subject to seasonal and multiyear variations that differed spatially across the dune field. Seasonal variations were observed with migration slowing during the summer months. We estimated the median for velocities belonging to the same season and calculated the seasonal sliding coefficient (SSC) representing the ratio between seasonal velocities. The median SSC reached a maximum value of ∼2 for winter/summer, while the ratios were ∼1.10 and ∼1.35 for winter/spring and winter/autumn, respectively. The seasonal variability of the temporal patterns was strongly supported by the wind observations. Between (1984–1998 and 1998–2007) and (1998–2007 and 2013–2021), decelerations in dune velocities were observed with percentages of ∼4 and ∼28%, respectively, and these decelerations were supported by a deceleration in wind velocities. Inversion of time series provides dense spatiotemporal monitoring of the dune activity. The fusion between two sensors allows condensing the temporal sampling up to a weekly scale especially for locations exposed to contamination of high cloud cover or dust.

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Section: Multitemporal Spatial Coherence From Sar Imagesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of Aeolian Activity in the Bodélé Depression, Chad: A Dense Spatiotemporal Time Series From Landsat-8 and Sentinel-2 Data

Ali

Xie

et al. 2022

Front. Environ. Sci.

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“…CCD is a highly sensitive radar technique used to remotely detect and map changes in the observed scene. Because coherence integrates information from both the amplitude and phase, it is sensitive to slight changes in the dielectrical and geometrical characteristics of the observed surface on the subpixel scale [4][5][6][7]. Thus, CCD is a promising complement to field campaigns and optical remote sensing techniques: it is suitable to monitor large and remote areas where field campaigns are costly and difficult, and it is more sensitive to surface changes than optical techniques without being constrained by cloud cover [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…In another study of dunes' motion, Ref. [7] explored the potential of InSAR coherence in supporting sand mitigation measures and used Sentinel-1 SAR data from 2015 to 2018 to detect and track the motion of sand accumulations in desert areas in the United Arab Emirates (UAE) and Egypt. Migrating dunes were detected with the average coherence ("mean short-term coherence", MSTC) and a novel index called the Temporal Stability Index (TSI), conceived to characterise the percentage of stability of a target over time.…”

Section: Introductionmentioning

confidence: 99%

SAR Coherence in Detecting Fluvial Sediment Transport Events in Arid Environments

et al. 2023

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Coherence change detection (CCD) is a remote sensing technique used to map phenomena that, under certain conditions, can be directly related to changes in Interferometric SAR (InSAR) coherence. Mapping the areas affected by sediment transport events in arid environments is one of the most common applications of CCD. However, the reliability of these maps remains an unsolved issue. This paper focuses on verifying that InSAR coherence is indeed able to detect all the fluvial sediment transport events that have actually mobilised sediments in arid environments by building a classification model and validating its results. The proposed methodology is tested in three study areas in Salar de Atacama, Chile, using three years of Sentinel data plus a fourth year for validation, and meteorological records of rainfall, the relative humidity of the air and snow cover. The results prove that InSAR coherence can be used to remotely detect sediment transport events related to flash floods in arid environments, that it might have a greater detection ability than meteorological records and that the perpendicular baseline does have a relevant effect on the InSAR coherence that needs to be considered. All these findings will increase the reliability of maps based on InSAR coherence. In addition, the proposed method will allow focusing the mapping tasks only on the relevant dates and, once calibrated, the classification model will enable the automatised remote detection of new events.

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Assessing complex aeolian dune field morphology and evolution with Sentinel-1 SAR imagery – Possibilities and limitations

et al. 2023

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Multitemporal InSAR Coherence Analysis and Methods for Sand Mitigation

Cited by 8 publications

References 31 publications

Assessment of Aeolian Activity in the Bodélé Depression, Chad: A Dense Spatiotemporal Time Series From Landsat-8 and Sentinel-2 Data

Assessment of Aeolian Activity in the Bodélé Depression, Chad: A Dense Spatiotemporal Time Series From Landsat-8 and Sentinel-2 Data

SAR Coherence in Detecting Fluvial Sediment Transport Events in Arid Environments

Assessing complex aeolian dune field morphology and evolution with Sentinel-1 SAR imagery – Possibilities and limitations

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