Bachelor Thesis Co-Relator - Giovanni Pagnozzi

Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2022

Thesis title: Analysis of large strategic structures using the PyGMTSAR tool on Sentinel-1 data


Geo-hazards include geological and natural aspects, such as earthquakes, landslides, subsidence, and tsunamis, which can cause devastating effects on populations, their territories, and their economies. This process in its entirety can affect, in the long or short term, the affected territories in a significant way, at local and regional level. Understanding the evolution of each phenomenon can be an important first step in risk mitigation, such as in the case of slow landslides or subsidence, or in the case of sudden catastrophic events, such as the collapse of the dam structure, the consequences of which are catastrophic. .

With reference to this last example, traditionally the monitoring of a dam is carried out by keeping under control the surface displacements, measured with geodetic techniques [collimation, high precision leveling and Global Positioning System (GPS)]. The main drawback of traditional surveys is represented by the reduced number of monitoring stations, which cannot ensure the desired spatial density in the required information, unless a long data processing is activated with prohibitive operating costs. It should be emphasized that changes in a dam are slow and appreciable (if any) only over long periods, from months to decades. This means that monitoring through traditional instrumentation can only be performed through the collection of an enormous amount of data, which must be suitably treated to extract useful information over time.

Alternatively, in addition to geodetic techniques, other survey techniques can be used, such as those based on the measurement of the coordinates of surface points, through the use of electronic distance measurement devices (Total Product Stations-TPS and / or specific GPS devices), allowing automatic operation and continuous monitoring. To overcome the limitations associated with traditional measures, satellite data acquisitions can be effectively used for dam monitoring, as they allow to cover the monitoring area, in a spatially distributed way and over long periods of time. It should be added that in extreme cases, for example in the occurrence of a major earthquake, traditional monitoring stations could stop their operation and take some time to be replaced or reactivated. In this intermediate stage, remote sensing can prove to be extremely useful as it becomes the only source of information on the stability of the dam. In this case, the techniques that can be used are many, such as the InSAR (Interferometry Synthetic Aperture Radar) processing based on the use of SAR data from the ESA (European Space Agency) Sentinel-1 satellite and the tools made available by ‘ESA as free tools, such as SNAP (Sentinel Application Platform) and others.

Having said that, starting from this basic knowledge, I wrote my thesis work. Using Sentinel-1 satellite data, I performed an interferometric analysis on the Campolattaro dam. Thanks to the use of software, such as Alaska Satellite Facility (ASF) and Geojson, I was able to visualize the orbital scenes of Sentinel-1 on this dam in a period ranging from 8/11/2016 to 15/11/2016. Finally, thanks to the use of a new Toolbox PyGMTSAR (Python GMTSAR) I have greatly simplified the interferometric analysis, in order to be able to calculate many interferograms with little processing and with a not high computational honor, as the tool is available on the cloud. (Google Colab). The final part of my thesis concerned the comparison of the results obtained with the SNAP software and with this PyGMTSAR Toolbox using the Case study presented in the paper that referred to the Campolattaro Dam.

The PyGMTSAR Toolbox was created by Professor Alexey Pechnikov to quickly and easily build interferograms from Sentinel-1 data, and is an open source project that includes various modules including a Python package and GMTSAR tools. The latter is an open source system (GNU General Public License) for performing InSAR processing, designed for users familiar with Generic Mapping Tools (GMT). The use of the PyGMTSAR Toolbox allowed me on the one hand to make comparisons with the results obtained through the use of interferometric techniques based on the use of SNAP and ESA tools, on the other hand to interact with Professor Pechnikov on some problems arose during the use of his Toolbox which, having been released recently, inevitably still has some small things to fix.