Deformation analysis and visualization from GNSS observations in Python 3 and QGIS 3

Geodynamic research
UDC: 
528.3
DOI: 
10.22389/0016-7126-2023-1002-12-17-26
1 Manevich A.I.
2 Shevchuk R.V.
3 Losev I.V.
4 Kaftan V.I.
5 Urmanov D.I.
6 Shakirov A.I.
Year: 
2023
№: 
12
1002
Pages: 
17-26

RAS Geophysical Center

1, 
2, 
3, 
4, 
5, 
6, 
Abstract:
The authors present the results of developing a library designed for GNSS deformation measurement upshot analysis in the Python 3 environment and their visualization in the QGIS 3 geographic information system. Development of global navigation satellite systems (permanent networks, data publications, creation of software for processing satellite measurement results) has led to increase in the number of researches in the field of studying modern crustal movements. Deformation analysis is a key component in exploring modern crustal and earth’s surface movements. Despite the large number of commercial and freely distributed software for the declared goal, the problem of integrating calculation results into the environment of freely distributed geoinformation systems is still relevant. The presented PyGeoStrain library includes some sets of corresponding subprograms, created QGIS 3 styles for visualizing deformation parameters, original test data, and a control GIS project for the example territory of the Caucasus. For deformation analysis, PyGeoStrain uses the classical geodetic approach to determining the components of the deformation tensor. The use of PyGeoStrain is an adequate replacement for analogue programs due to open access to the source
This work was funded by the Russian Science Foundation No. 23-17-00176 “System Seismic Hazard Assessment of the Central Part of the Greater Caucasus (Ossetian sector)”
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Citation:
Manevich A.I., 
Shevchuk R.V., 
Losev I.V., 
Kaftan V.I., 
Urmanov D.I., 
Shakirov A.I., 
(2023) Deformation analysis and visualization from GNSS observations in Python 3 and QGIS 3. Geodesy and cartography = Geodezia i Kartografia, 84(12), pp. 17-26. (In Russian). DOI: 10.22389/0016-7126-2023-1002-12-17-26
Publication History
Received: 31.05.2023
Accepted: 17.11.2023
Published: 25.01.2024

Content

2023 December DOI:
10.22389/0016-7126-2023-1002-12