Comparison of L-band and X-band differential interferometric synthetic aperture radar for mine subsidence monitoring in central Utah

Wempen, Jessica M.; McCarter, M. K.

doi:10.1016/j.ijmst.2016.11.012

Cited by 35 publications

(19 citation statements)

References 13 publications

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“…However, this was expected, since UAVSAR L-band images exploited in [26], having higher penetration depth, are less sensitive to land cover (e.g., vegetation) compared to the X-band COSMO-SkyMed data used for this study. This means that the correlation between different images is expected to be higher in the first case [41] and, in turn, the displacement estimation is more precise.…”

Section: Discussionmentioning

confidence: 99%

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

Amitrano

Guida

Dell'Aglio³

et al. 2019

Remote Sensing

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Kinematic characterization of a landslide at large, small, and detailed scale is today still rare and challenging, especially for long periods, due to the difficulty in implementing demanding ground surveys with adequate spatiotemporal coverage. In this work, the suitability of space-borne synthetic aperture radar sub-pixel offset tracking for the long-term monitoring of the Slumgullion landslide in Colorado (US) is investigated. This landslide is classified as a debris slide and has so far been monitored through ground surveys and, more recently, airborne remote sensing, while satellite images are scarcely exploited. The peculiarity of this landslide is that it is subject to displacements of several meters per year. Therefore, it cannot be monitored with traditional synthetic aperture radar differential interferometry, as this technique has limitations related to the loss of interferometric coherence and to the maximum observable displacement gradient/rate. In order to overcome these limitations, space-borne synthetic aperture radar sub-pixel offset tracking is applied to pairs of images acquired with a time span of one year between August 2011 and August 2013. The obtained results are compared with those available in the literature, both at landslide scale, retrieved through field surveys, and at point scale, using airborne synthetic aperture radar imaging and GPS. The comparison showed full congruence with the past literature. A consistency check covering the full observation period is also implemented to confirm the reliability of the technique, which results in a cheap and effective methodology for the long-term monitoring of large landslide-induced movements.

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Section: Discussionmentioning

confidence: 99%

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

Amitrano

Guida

Dell'Aglio³

et al. 2019

Remote Sensing

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“…Using InSAR technique, for each study area, a DEM was extracted from Sentinel-1 data. Because of low coherence, vegetated areas typically will produce poor elevation value in C-band [ 44 , 71 ]. Our results also showed that DEM from L-band (ALOSPALSAR) is more suitable than DEM from C- band (Sentinel-1).…”

Section: Resultsmentioning

confidence: 99%

“…Typically, X-band signals backscatter from the top of the trees canopy, while C-band signals penetrate deeper into the canopy [ 98 ]. In contrast, L-band signals provide a greater penetration rate than X- and C-bands [ 71 , 99 , 100 , 101 ]. The estimated interferometric phase and the coherence between two images (master and slave) is generally an indicator for assessing the phase information quality, which have direct influences on DEM generation.…”

Section: Discussionmentioning

confidence: 99%

“…When SAR signals could not penetrate vegetation, then coherence will be poor (dark) [ 104 ]. Therefore, coherence loss causes poor interferometric results [ 45 , 71 ], which result in a low quality DEM. Short wavelength SAR sensors of C- and X-bands (because of low penetration rate) have poor coherence (dark) in vegetation areas (this differs based on the density of vegetation); while having a slightly higher coherence (bright) in township areas.…”

Section: Discussionmentioning

confidence: 99%

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A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models

Mohammadi

Karimzadeh

Jalal

et al. 2020

Sensors

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Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs’ performance, such as 90-meters’ TanDEM-X and 30-meters’ SRTM, are better than Sentinel-1 DEM (with a better spatial resolution).

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“…In this context, one of the techniques commonly used for this type of study in different parts of the world is differential interferometry (DInSAR), which is a technique based on synthetic aperture radar satellites that can be used to measure surface displacement in large regions with high spatial resolution. Under good conditions, displacements can be measured with centimeter to subcentimeter accuracy [4]. By monitoring the subsidence in the El Teniente mine in central Chile using the DInSAR technique during 2010 and 2015, subsidence was estimated in some sectors of up to −5 cm with TerraSAR-X and COSMO-SkyMED (X band) images [5].…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Mining Subsidence in a Sector of Central Chile through the Processing of a Time Series of Sentinel 1 Images Using Differential Interferometry Techniques (DInSAR)

Vidal-Páez

Derauw

Fernández-Sarría

et al. 2019

The II Geomatics Engineering Conference

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The objective of this work is to monitor the mining subsidence in a mountain range sector of central Chile between 2014 and 2018 through the processing of a time series of Sentinel 1 images using differential interferometry techniques (DInSAR). As a pretest, nine interferometric pairs were considered and processed using SNAP and SNAPHU software. Coherence levels obtained in complex topography sectors were low, due to both temporal and geometrical decorrelation. However, it is proposed that data from the PAZ project (X-band) and the Argentinean SAOCOM satellite (L-band) be used in the future.

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Comparison of L-band and X-band differential interferometric synthetic aperture radar for mine subsidence monitoring in central Utah

Cited by 35 publications

References 13 publications

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models

Monitoring of Mining Subsidence in a Sector of Central Chile through the Processing of a Time Series of Sentinel 1 Images Using Differential Interferometry Techniques (DInSAR)

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