- freely available
Geosciences 2017, 7(2), 19; https://doi.org/10.3390/geosciences7020019
2. Materials, Methods, and Discussion
2.1. Sentinel-1 Archive Data
- Sentinels Scientific Data Hub (https://scihub.copernicus.eu/) operated by ESA, the most completed and updated (within 24 hours for systematically archived data) archive where SAR data are identified according to relative orbit and slice number. In 2015, alone, more than 1000 out of the 15,243 users registered from the UK .
- Alaska Satellite Facility , as part of an agreement between the U.S. State Department and the European Commission, where products are identified from their path and frame.
- Sentinel Data Access Service  operated by the Satellite Applications Catapult in association with the UK Space Agency where SLC IWS SAR data are identified according to the Absolute Orbit number.
2.2. Topographic Constraints
2.3. Land Cover Constraints
2.4. Kinematic and Geometrical Constraints to Monitor Geohazards
- The extension of the investigated phenomena must be over ~0.008 km2 which refers to the size of the smallest possible feature that can be detected by Sentinel-1 data accounting for the spatial resolution of its IW mode. Apart from dolines and sinkholes particular landslide typology (especially falls and topples), UK geohazards have an extension at the kilometric scale.
- Rather than providing 3-D components, ISBAS measurements are along the LOS direction and, therefore, insensitive to horizontal displacements in the along-track direction . To decompose the InSAR LOS signal into its vertical and horizontal components we, therefore, need sufficient acquisitions of both ascending and descending SAR data . In the absence of both geometries, quantification of the fraction of maximum motions measurable along the satellite LOS can be quantified by means of the R-Index for areas of good visibility or foreshortening. In this regard, most of the UK geohazards do not prevent InSAR analysis by being associated with predominant vertical deformation (see Section 1) and, specifically, this is true for dolines, sinkholes, collapsible ground, compressible ground, and shrink-swell terrains.
- Finally, a third limitation is represented by the incapability for resolving deformation ≥λ/4 between two SAR acquisitions  that constrains the measurable displacement velocity to ≤86 cm/year, or 1.4 cm for Sentinel-1 scenes six days apart. Such values are usually large enough to completely assess and monitor strain rates associated with rock and soil viscous, viscoelastic, or creep behaviour induced by human or natural-changes in stress conditions. At the same time, events partially detectable by SAR platforms represent an unlikely occurrence in the UK, temporally in the case of interseismic elastic deformation where an earthquake of ≥3.7 ML statistically hits every year, and spatially in the case of fall and topple landslides, whose recurrence is mainly limited to Western Scotland .
2.5. Test Site
3. Conclusions and Future Perspectives
- Provide information at regional and national scales to identify ground displacements that occur over hundreds or thousands of square kilometres and characterise areas prone to risk because they are affected by critical geohazards. With such information decision-makers (e.g., UK Oil and Gas Authority, Coal Authority, Environmental Agency, or Health and Safety Executive) can analyse and evaluate different scenarios and plan specific actions based on homogeneous and reliable measurements. Furthermore, InSAR data can be updated regularly as more Sentinel-1 images are acquired, and can provide new ways to design early warning systems covering entire nations, where satellite information can highlight areas where in situ sensors and continuous monitoring tools should be installed or field checks should be optimized.
- Realize an important database to encourage the sharing of methodologies, data, and results. In this regard the manual data analysis and interpretation of ~22 M ISBAS points makes the process cumbersome, operator-dependent, and time-consuming, while semi-automated methodologies can be particularly advantageous for analysing and classifying remote sensing data at the regional scale.
Conflicts of Interest
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|Area||Orbit||No. of Scenes||Dates||ISBAS Point||Surface Area (km2)|
|East Anglia||Asc||34||25 December 1014–29 June 2016||778,455||6730|
|East Midlands||Asc||39||12 March 2015–14 September 2016||402,829||3439|
|Hampshire||Asc||31||12 March 2015–17 May 2016||263,570||2510|
|Lancashire||Desc||36||8 May 2015–11 September 2016||353,703||3550|
|Yorkshire||Desc||36||7 March 2015—9 September 2016||447,564||4596|
|Southern Scotland||Asc||24||12 March 2015–18 January 2016||2,909,498||44,017|
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