Seismic hazard assessment of the urban area of Ambato, Ecuador, in deterministic form

Seismic microzonation of the urban area of Ambato, Ecuador, was done in 2018 in a probabilistic and a deterministic manner. This type of calculation is presented in the first part of the article. For this purpose, three geologic faults and three strong-motion equations were considered. For each geologic fault, recurrence periods are determined using two methods. It is seen that a magnitude 6.3 earthquake associated with the blind faults traversing Ambato may occur in 80 to 100 years, and one of magnitude 6.5 in the next 300 years. Geophysical and geotechnical studies of the urban area of the city of Ambato are presented. These permitted the acquisition of curves with the same period of soil vibration and equal speed of the shear wave in the first 30 m, plus the classification of soils of the city. Later, six models of strong soil movements were considered and horizontal acceleration spectra of the soil were obtained in a mesh of points separated every 500 m, for each soil profile. Average spectra were found for soil profiles C, D and E when making comparisons with the spectra found in the 2018 study. Based on the results of the present study and those from 2018, new spectral forms are proposed for the urban area of the city of Ambato (called spectral envelopes) and compared to spectra reported by seismic regulations in force in Ecuador (NEC-15).

BS-LSTM: An Ensemble Recurrent Approach to Forecasting Soil Movements in the Real World

Machine learning (ML) proposes an extensive range of techniques, which could be applied to forecasting soil movements using historical soil movements and other variables. For example, researchers have proposed recurrent ML techniques like the long short-term memory (LSTM) models for forecasting time series variables. However, the application of novel LSTM models for forecasting time series involving soil movements is yet to be fully explored. The primary objective of this research is to develop and test a new ensemble LSTM technique (called “Bidirectional-Stacked-LSTM” or “BS-LSTM”). In the BS-LSTM model, forecasts of soil movements are derived from a bidirectional LSTM for a period. These forecasts are then fed into a stacked LSTM to derive the next period’s forecast. For developing the BS-LSTM model, datasets from two real-world landslide sites in India were used: Tangni (Chamoli district) and Kumarhatti (Solan district). The initial 80% of soil movements in both datasets were used for model training and the last 20% of soil movements in both datasets were used for model testing. The BS-LSTM model’s performance was compared to other LSTM variants, including a simple LSTM, a bidirectional LSTM, a stacked LSTM, a CNN-LSTM, and a Conv-LSTM, on both datasets. Results showed that the BS-LSTM model outperformed all other LSTM model variants during training and test in both the Tangni and Kumarhatti datasets. This research highlights the utility of developing recurrent ensemble models for forecasting soil movements ahead of time.

INTERACTION BETWEEN DIRECT GEOREFERENCING, CONTROL POINT CONFIGURATION AND CAMERA SELF-CALIBRATION FOR RTK-BASED UAV PHOTOGRAMMETRY

Unmanned Aerial Vehicles (UAV) are enjoying increasing popularity in the photogrammetric community. The Chinese supplier DJI is the market leader with about 70% of the global consumer UAV market. The Phantom model has been available for more than 10 years and its current version "RTK" is equipped with a 2-frequency GNSS receiver, as a basis for direct georeferencing of image flights, using RTK or PPK technologies.In the context of the paper, different case studies are investigated, which allow statements on the geometric accuracy of UAV image flights as well as on the self-calibration of the camera systems.In the first example, four DJI Phantom 4 RTK systems are examined, which were flown in a cross flight pattern configuration on the area of the UAV test field "Zeche Zollern" in Dortmund, Germany. The second example analyses the results of an open moorland area where the establishment of GCPs is extremely difficult and expensive, hence direct georeferencing offers a promising way to evaluate deformations, soil movements or mass calculations. In this example a DJI Matrice 210 v2 RTK drone has been used and the results of two different software packages (Agisoft Metashape and RealityCapture) are analysed. The third example presents a reference building that has been established by the Lower Saxony administration for geoinformation in order to evaluate UAV photogrammetry for cadastral purposes. Here again a DJI Phantom 4 RTK has been tested in a variety of flight configurations and a large number of high precision ground control and check points.The case studies show that the RTK option leads to sufficient results if at least 1 GCP is introduced. Flights without any GCPs lead to a significant height error in the order of up to 30 GSD.