Figure 6 - available via license: Creative Commons Attribution 4.0 International
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Histograms of the rasters of coherence between consecutive SAR images in the study area of the eastern slopes. The numbers of the histograms identify the rasters chronologically. See dates in Table A1 and the location and extent of the study area in Figure 2: (a) Camar; (b) Socaire; (c) eastern slopes. Some histograms (framed in red) clearly differ from the general pattern, hypothetically due to fluvial sediment transport events.
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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 thes...
Contexts in source publication
Context 1
... the results are not exactly the same from one area to the other. However, they are consistent: in the classification of the histograms (Figure 6), a general pattern consisting of unimodal distributions with low dispersion and a mode shifted to high values is observed in all three zones. For example, for the eastern slopes, the standard deviation is 24 ± 4 and the mode ranges from 210 to 230 (the coherence is normalised to the range [0,254]). ...
Context 2
... the same way, this general pattern is altered on specific dates that are coincident in all three zones, in which the dispersion increases and the mode adopts lower values. These are the dates classified as potential events of fluvial sediment transport (red-framed histograms in Figure 6). In this sense, PLS-DA corroborates that, in all three study areas, there are two sets of histograms ("events" or "positives" and "non-events" or "negatives") that are clearly distinguishable (Figure 7). ...
Context 3
... the results are not exactly the same from one area to the other. However, they are consistent: in the classification of the histograms (Figure 6), a general pattern consisting of unimodal distributions with low dispersion and a mode shifted to high values is observed in all three zones. For example, for the eastern slopes, the standard deviation is 24 ± 4 and the mode ranges from 210 to 230 (the coherence is normalised to the range [0,254]). ...
Context 4
... the same way, this general pattern is altered on specific dates that are coincident in all three zones, in which the dispersion increases and the mode adopts lower values. These are the dates classified as potential events of fluvial sediment transport (red-framed histograms in Figure 6). In this sense, PLS-DA corroborates that, in all three study areas, there are two sets of histograms ("events" or "positives" and "non-events" or "negatives") that are clearly distinguishable (Figure 7). ...
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The extraction of underground minerals in hilly regions is highly susceptible to landslides, which requires the application of InSAR techniques to monitor the surface displacement. However, repeated mining for multiple coal seams can cause a large displacement beyond the detectable gradient of the traditional InSAR technique, making it difficult to...
Citations
... In order to design a sediment-detention basin, it is necessary to know the volume knowledge [1,4,9,10,15,25,26]. However, although previous studies confirm the ability of CCD to detect surface changes [27], none of the mentioned approaches have yet resolved how to map surface changes using CCD with certainty [1]. ...
... The methods and the procedure explained in the next sections are applied to events that were already detected and located in time in a previous study [27]. In short, the events were detected based on the analysis of the histograms of the rasters of coherence between consecutive SAR images. ...
... The geometric decorrelation depends on the perpendicular baseline and the local slope of the surface, so it is not correlated with time but its distribution in space is constant. On the other hand, the soil moisture decorrelation, in arid environments, is relevant only during and after rain-and snowfall events (for a few months at most), so it can be located in time [4,19,27]. Regarding the spatial dimension, it has been found that the quantity of precipitation only affects the duration of the soil moisture decorrelation, not its magnitude [16]. Therefore, the spatial distribution of the soil moisture decorrelation is probably similar from one rain-or snowfall event to another and is probably related to: (i) the topographic relief because the increase in soil moisture caused by rain-or snowfall lasts longer in areas that are protected from the action of the wind; (ii) the lithology because the more porous the soil is, the more water from rain-or snowfall penetrates into the soil, so the evaporation of soil moisture lasts longer; and (iii) the geographical distribution of the precipitation as the cause of the increased soil moisture. ...
InSAR coherence-change detection (CCD) is a promising remote sensing technique that is able to map areas affected by torrential sediment transport triggered by flash floods in arid environments. CCD maps the changes in the interferometric coherence between synthetic aperture radar images (InSAR coherence), a parameter that measures the stability of the radar signal between two different SAR images, i.e., data acquisitions. In arid environments, such changes are mainly due to changes in the surface. However, the residual effect of other factors on the InSAR coherence cannot be completely excluded. Therefore, CCD-based maps contain the uncertainty of whether the detected changes are actual changes in the observed surface or just errors related to those residual effects. Thus, in this paper, the results of four CCD mapping methods, with different degrees of complexity and sensitivity to the different factors affecting the InSAR coherence, are compared in order to evaluate the existence of the errors and their importance. The obtained CCD maps are also compared with changes in satellite optical images and a field campaign. The results lead to the conclusion that CCD maps are reliable in the identification of the zones affected by sediment transport, although the precision in the delimitation of the affected area remains an open issue. However, highly rugged relief areas still require a thorough analysis of the results in order to discard the geometric effects related to the perpendicular baseline.
