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Analysis of building deformation in landslide area using multisensor PSInSAR ™ technique

View Article: PubMed Central - PubMed

ABSTRACT

We analyze ground deformation velocities of the buildings in San Fratello (Sicily, Italy).

We analyze satellite PSI data using different sensors, acquired from 1992 to 2012.

We performed a damages assessment map after the landslide occurred on the 14th February 2010.

The obtained data were compared to evaluate the residual risk.

The obtained data were compared to evaluate the residual risk.

No MeSH data available.


(a) Building deformation velocity map using both ascending and descending ENVISAT datasets. (b) ENVISAT PS dataset related to the 1922 landslide with two selected time series (c and d). (c) Corresponds to the yellow asterisk; (d) corresponds to the orange asterisk.
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fig0025: (a) Building deformation velocity map using both ascending and descending ENVISAT datasets. (b) ENVISAT PS dataset related to the 1922 landslide with two selected time series (c and d). (c) Corresponds to the yellow asterisk; (d) corresponds to the orange asterisk.

Mentions: The use of the ENVISAT datasets allowed the mapping of up to 279 (37.80%) of the town buildings. The related building deformation velocity map (Fig. 5a) is very similar to those obtained with ERS 1/2 datasets. Results highlight a substantial stability of the town. A very small amount of buildings is characterized by deformation velocities outside the stability range. Along the eastern slope, only one edifice shows an average velocity of −10 mm/y. On the western slope, along the 1922 landslide crown, the buildings affected by deformation are almost the same of those highlighted by the map obtained with ERS 1/2. The use of ENVISAT sensor increased the number of monitored buildings; however, these PS data were still not suitable to detect possible ground displacements to be considered as landslide precursors. Also in this case using the whole PS datasets it was possible to retrieve more information about slope instability (Fig. 5b). Along the western town sector the area affected by ground deformation could be better recognized using PS which highlighted the presence of a wide area affected by deformation, located along in the eastern sector of the 1922 landslide (Fig. 5b). The most interesting information obtained using the ENVISAT data concerns the ground deformation of the eastern slope (Fig. 6a). Here two areas, showing clusters of PS characterized by high ground deformation velocities, can be recognized. Even though both these areas are located inside the 2010 landslide body, including a very low number of buildings, the number of PS is sufficient to highlight ground deformation. The comparison between the PS and the damage assessment map shows a good agreement between the distribution of the PS having the highest velocities and the most damaged buildings by the 2010 landslide (Fig. 6b).


Analysis of building deformation in landslide area using multisensor PSInSAR ™ technique
(a) Building deformation velocity map using both ascending and descending ENVISAT datasets. (b) ENVISAT PS dataset related to the 1922 landslide with two selected time series (c and d). (c) Corresponds to the yellow asterisk; (d) corresponds to the orange asterisk.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5384476&req=5

fig0025: (a) Building deformation velocity map using both ascending and descending ENVISAT datasets. (b) ENVISAT PS dataset related to the 1922 landslide with two selected time series (c and d). (c) Corresponds to the yellow asterisk; (d) corresponds to the orange asterisk.
Mentions: The use of the ENVISAT datasets allowed the mapping of up to 279 (37.80%) of the town buildings. The related building deformation velocity map (Fig. 5a) is very similar to those obtained with ERS 1/2 datasets. Results highlight a substantial stability of the town. A very small amount of buildings is characterized by deformation velocities outside the stability range. Along the eastern slope, only one edifice shows an average velocity of −10 mm/y. On the western slope, along the 1922 landslide crown, the buildings affected by deformation are almost the same of those highlighted by the map obtained with ERS 1/2. The use of ENVISAT sensor increased the number of monitored buildings; however, these PS data were still not suitable to detect possible ground displacements to be considered as landslide precursors. Also in this case using the whole PS datasets it was possible to retrieve more information about slope instability (Fig. 5b). Along the western town sector the area affected by ground deformation could be better recognized using PS which highlighted the presence of a wide area affected by deformation, located along in the eastern sector of the 1922 landslide (Fig. 5b). The most interesting information obtained using the ENVISAT data concerns the ground deformation of the eastern slope (Fig. 6a). Here two areas, showing clusters of PS characterized by high ground deformation velocities, can be recognized. Even though both these areas are located inside the 2010 landslide body, including a very low number of buildings, the number of PS is sufficient to highlight ground deformation. The comparison between the PS and the damage assessment map shows a good agreement between the distribution of the PS having the highest velocities and the most damaged buildings by the 2010 landslide (Fig. 6b).

View Article: PubMed Central - PubMed

ABSTRACT

We analyze ground deformation velocities of the buildings in San Fratello (Sicily, Italy).

We analyze satellite PSI data using different sensors, acquired from 1992 to 2012.

We performed a damages assessment map after the landslide occurred on the 14th February 2010.

The obtained data were compared to evaluate the residual risk.

The obtained data were compared to evaluate the residual risk.

No MeSH data available.