Geodynamics

Abstract

The study analyzes the coordinate time series of five permanent International GNSS Service (IGS) stations located in New Zealand. It also considers their annual movement from 2009 to 2018. The raw data in the form of Receiver Independence Exchange (RINEX) files were taken from IGS database and processes by means of online processing service AUSPOS. Using coordinate time series, horizontal and vertical displacement rates were calculated covering the ten-year study period. According to the results, stations located at the North Island of New Zealand revealed an uplift of 31-32 mm/yr. At the same time, stations placed on the South Island showed the 21-22 mm/yr of positive vertical displacement. Regarding the horizontal displacements, their rates increase in North-South direction over the study region. In particular, two stations of North Island, located at the North-Western part, appeared in 24-25 mm/yr displacement, and one station at the Southern part of North Island showed the 35 mm/yr displacement rate. Stations, established at South Island, showed the horizontal displacement rates of 41-56 mm/yr. This research confirms the main contribution made to the field of crustal deformation studies, including the updated values of displacements along with their directions over the recent years. The results of this study can be used for further geodynamics investigations as well as for finding the most likely earthquake locations of the current study area.

The Use of Artificial Intelligence and Satellite Remote Sensing in Land Cover Change Detection: Review and Perspectives

“…In the early stages, methods for LCCD relied on traditional machine learning techniques such as Maximum Likelihood [70][71][72][73][74][75][76][77][78][79], Support Vector Machine (SVM) [80], and Random Forest (RF) [81,82] for classifying land features, followed by vector change comparison to generate change maps. Fabian and Tikuye utilized satellite remote sensing data to train an RF model to classify land features into different types and subsequently analyzed the land cover change [81,82].…”

Analysis and classification of actual geodetic methods for studying the quantitative parameters of earth surface deformations

“…Since the 1970s, Earth remote sensing (ERS) data have been actively used to monitor and identify geomorphological changes [Cracknell, 2018]. ERS data depict the objective situation of processes and phenomena on the Earth's surface at a particular time, and regular repetition of images allows tracing their dynamics [Hlotov & Biala, 2022a]. Remote methods for studying deformation of Earth's surface changes are based on a non-contact method for obtaining information about the area under study, while using various ERS systems: digital, television, infrared, laser, radiothermal and radar.…”

“…The spatial resolution of the captured image refers to the dimension of the pixel representing certain area covered on the ground, so the data can be subdivided into low, medium, high and ultra-high resolution groups [Kokhan & Vostokov, 2009]. Data from multispectral imaging systems are widely used in classification methods, investigations with vegetation indices application, and in retrospective analysis of the spatial development of territories [Hlotov & Biala, 2022a;Casagli et al, 2017]. The ultra-highresolution data make it possible to apply the structure from motion (SfM) method to detect vertical and sub-vertical displacements of the Earth's surface.…”