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Klees, R.; Massonnet, D.

doi:10.1023/a:1003594502801

Cited by 52 publications

(50 citation statements)

References 34 publications

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“…The coherence is a measure of the similarity between a pair of images (i.e., master and slave) [48][49][50][51]. Although the coherence is usually estimated on regular kernel windows [52], in this work we used the rock glacier outlines as boundaries to compute this value.…”

Section: Description Of the Proposed Methodsmentioning

confidence: 99%

“…Furthermore, in this way each rock glacier can be associated with a single SAR coherence value, representative of the entire area of the landform. Low coherence values indicate low or no similarity between the images, and this may be due to (i) the presence of vegetation, (ii) changes of the target properties (i.e., changes of the physical ground conditions), and (iii) changes of surface shape (i.e., displacement) [34,50,51,[53][54][55][56][57]. High coherence values indicate, instead, similarity between the images (i.e., no movement and no changes in the surface properties of the rock glacier).…”

Section: Description Of the Proposed Methodsmentioning

confidence: 99%

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An Unsupervised Method to Detect Rock Glacier Activity by Using Sentinel-1 SAR Interferometric Coherence: A Regional-Scale Study in the Eastern European Alps

et al. 2019

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Rock glaciers are widespread periglacial landforms in mountain regions like the European Alps. Depending on their ice content, they are characterized by slow downslope displacement due to permafrost creep. These landforms are usually mapped within inventories, but understand their activity is a very difficult task, which is frequently accomplished using geomorphological field evidences, direct measurements, or remote sensing approaches. In this work, a powerful method to analyze the rock glaciers’ activity was developed exploiting the synthetic aperture radar (SAR) satellite data. In detail, the interferometric coherence estimated from Sentinel-1 data was used as key indicator of displacement, developing an unsupervised classification method to distinguish moving (i.e., characterized by detectable displacement) from no-moving (i.e., without detectable displacement) rock glaciers. The original application of interferometric coherence, estimated here using the rock glacier outlines as boundaries instead of regular kernel windows, allows describing the activity of rock glaciers at a regional-scale. The method was developed and tested over a large mountainous area located in the Eastern European Alps (South Tyrol and western part of Trentino, Italy) and takes into account all the factors that may limit the effectiveness of the coherence in describing the rock glaciers’ activity. The activity status of more than 1600 rock glaciers was classified by our method, identifying more than 290 rock glaciers as moving. The method was validated using an independent set of rock glaciers whose activity is well-known, obtaining an accuracy of 88%. Our method is replicable over any large mountainous area where rock glaciers are already mapped and makes it possible to compensate for the drawbacks of time-consuming and subjective analysis based on geomorphological evidences or other SAR approaches.

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Section: Description Of the Proposed Methodsmentioning

confidence: 99%

Section: Description Of the Proposed Methodsmentioning

confidence: 99%

An Unsupervised Method to Detect Rock Glacier Activity by Using Sentinel-1 SAR Interferometric Coherence: A Regional-Scale Study in the Eastern European Alps

et al. 2019

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“…A general recommendation to mitigate temporal decorrelation is careful selection of image pairs based on short temporal baselines. However, in some cases, a strong correlation is observed for several years [Klees, Massonnet, 1999].…”

Section: Interpretation Of the Differential Sar Interferometry Datamentioning

confidence: 96%

Surface Deformations Near the Baikal–amur Railway From Differential Sar Interferometry Data

Lebedeva¹,

Sankov²,

Захаров³

et al. 2016

Geodin. tektonofiz.

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This paper presents SAR interferometric data obtained in the study of surface deformations of different origin within the Upper Angara-Muya interbasin link of the northeastern segment of the Baikal rift system, Russia. Differential SAR interferometry using images with small perpendicular baselines was applied in this geodynamical study. The potential of using ENVISAT/ASAR and ALOS/PALSAR data is discussed. New geodynamical data on recent strain patterns were obtained. The endogenous linear-localized and areal deformations were revealed in the influence zone of the active Muyakan fault. The origin of these deformations is discussed. The landslide that negatively affects the Baikal-Amur railway facilities is also studied. The use of SAR data for detailed study and monitoring of the landslide is discussed. It is confirmed that natural hazard in the study area is growing due to the ongoing landsliding.

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“…Geocoded interferometric coherence images were calculated from InSAR treatment processing based on the approach described in [25] and using open-source software, namely, DORIS (Delft Object-oriented Radar Interferometric) and ADORE (Automated DORIS Environment). Master and slave images were defined for each SAR mode (SM and SL) to calculate the coherence coefficients (γ) over the slave images, following Equation …”

Section: Bp a Cmentioning

confidence: 99%

Sensitivity of X-Band (σ0, γ) and Optical (NDVI) Satellite Data to Corn Biophysical Parameters

Baup¹,

Villa²,

Fieuzal³

et al. 2016

ARS

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The objective of this work was to evaluate the sensitivity of three different satellite signals (interferometric coherence (γ), backscattering coefficient (σ 0 ) and NDVI) to corn biophysical parameters (leaf area index, height, biomass and water content) throughout its entire vegetation cycle. All of the satellite and in situ data were collected during the Multi-spectral Crop Monitoring (MCM'10) experiment conducted in 2010 by the CESBIO Laboratory over eight different agricultural sites located in southwestern France. The results demonstrated that the NDVI is well adapted for leaf area index monitoring, whereas γ27.3° is much more suited to the estimation of the three other Biophysical Parameters throughout the entire crop cycle, with a coefficient of determination ranging from 0.83 to 0.99, using non-linear relationships. Moreover, contrary to the use of the NDVI or backscattering coefficients, the use of coherence exhibited a low sensitivity to the changes in vegetation and soil moisture occurring during senescence, offering interesting perspectives in the domain of applied remote sensing.

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Cited by 52 publications

References 34 publications

An Unsupervised Method to Detect Rock Glacier Activity by Using Sentinel-1 SAR Interferometric Coherence: A Regional-Scale Study in the Eastern European Alps

An Unsupervised Method to Detect Rock Glacier Activity by Using Sentinel-1 SAR Interferometric Coherence: A Regional-Scale Study in the Eastern European Alps

Surface Deformations Near the Baikal–amur Railway From Differential Sar Interferometry Data

Sensitivity of X-Band (<i>σ</i><sup>0</sup>, <i>γ</i>) and Optical (NDVI) Satellite Data to Corn Biophysical Parameters

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Untitled

Cited by 52 publications

References 34 publications

An Unsupervised Method to Detect Rock Glacier Activity by Using Sentinel-1 SAR Interferometric Coherence: A Regional-Scale Study in the Eastern European Alps

An Unsupervised Method to Detect Rock Glacier Activity by Using Sentinel-1 SAR Interferometric Coherence: A Regional-Scale Study in the Eastern European Alps

Surface Deformations Near the Baikal–amur Railway From Differential Sar Interferometry Data

Sensitivity of X-Band (&lt;i&gt;σ&lt;/i&gt;&lt;sup&gt;0&lt;/sup&gt;, &lt;i&gt;γ&lt;/i&gt;) and Optical (NDVI) Satellite Data to Corn Biophysical Parameters

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Sensitivity of X-Band (<i>σ</i><sup>0</sup>, <i>γ</i>) and Optical (NDVI) Satellite Data to Corn Biophysical Parameters