Romania, due to its historical background, has many vestigial belongings to the cultural heritage, out of which the most noticeable (by number, age, architecture, symbolism and representation) are the wooden churches. Under these circumstances the role of the current study is to emphasize certain practical aspects (focused on the need to assess, preserve, restore and valorize) regarding the use of modern technology based on photogrammetry and 3D scanning. The case study was represented by the “Saint Martyrs Constantin Brȃncoveanu and His Sons” wooden church from Oradea Municipality, Bihor County, Romania; the edifice being included on the list of historical monuments ever since 2010. The final goal being to create 3D models for both the exterior and interior of the monument for research, restoration in case of need, sharing for education, entertainment, tourism purposes etc.

This study evaluates the EUREF Permanent Network (EPN) station position time series of approximately 200 GNSS stations subject to the Repro 2 reprocessing campaign in order to characterize the dominant types of noise and amplitude and their impact on estimated velocity values and associated uncertainties. The visual inspection on how different noise model represents the analysed data was done using the power spectral density of the residuals and the estimated noise model and it is coherent with the calculated Allan deviation (ADEV)-white and flicker noise. The velocities resulted from the dominant noise model are compared to the velocity obtained by using the Median Interannual Difference Adjusted for Skewness (MIDAS). The results show that only 3 stations present a dominant random walk noise model compared to flicker and powerlaw noise model for the horizontal and vertical components. We concluded that the velocities for the horizontal and vertical component show similar values in the case of MIDAS and maximum likelihood estimation (MLE), but we also found that the associated uncertainties from MIDAS are higher compared to the uncertainties from MLE. Additionally, we concluded that there is a spatial correlation in noise amplitude, and also regarding the differences in velocity uncertainties for the Up component.

The seasonal signal determined by the Global Navigation Satellite System (GNSS), which is captured in the coordinate time series, exhibits annual and semi-annual periods. This signal is frequently modelled by two periodic signals with constant amplitude and phase-lag. The purpose of this study is to explore the implication of different types of geophysical events on the seasonal signal in three stages—in the time span that contains the geophysical events, before and after the geophysical event, but also the stationarity phenomena, which is analysed on approximately 200 reference stations from the EPN network since 1995. The novelty of the article is demonstrated by correlating three different types of geophysical events, such as earthquakes with a magnitude greater than 6° on the Richter scale, landslides, and volcanic activity, and analysing the variation in amplitude of the seasonal signal. The geophysical events situated within a radius of 30 km from the epicentre showed a higher seasonal value than when the timespan did not contain a geophysical event. The presence of flicker and random walk noise was computed using overlapping Hadamard variance (OHVAR) and the non-stationary behaviour of the time series of the CORS coordinates in the time frequency analysis was done using continuous wavelet transform (CWT).

Embracing the archaic methods used in supervision and/or management in the field of architecture, engineering, and construction (AEC) creates the imperative need to adopt and/or develop sustainable methods to reduce construction physical waste, as well as the non-physical waste. Thus, the articles present a method that convenes three different specializations, namely geodesy, civil engineering, and architecture, that make use of the 3D terrestrial laser scanner (TLS), 3D reconstruction, and the 3D analysis to make an accurate bill of quantity (BOQ) to be able to assess the quality of the construction in compliance with the idea of sustainable development in the AEC industry. This article describes the three major parts: obtaining the point cloud, the 3D modeling, and extracting the relevant data. The novelty of the research is threefold: (i) a viable methodology for obtaining an accurate BOQ by reducing the non-physical waste to avoid cost and time overruns; (ii) the significance and impact of a (a) strictly automated and (b) automatic with traditional survey to obtain the 3D model of the point cloud on the resulting area that requires rehabilitation or to be covered with intumescent paint; and (iii) a detailed analysis of the specific elements that can blunder the final 3D model, such as the shadowing effect that can appear in very complex construction structures. Moreover, the proposed methodology represents a significant advancement in optimizing 3D modeling to improve the comprehension of steel trusses in the field of AEC sector.

The present study deals with the estimation of the evolution tendency of the environmental stage of a protected habitat with predominant forest vegetation, during a short period of time, using techniques specific to remote sensing. Therefore, two important spectral indexes were tested while assessing the health of the forest ecosystems: i.e. the Normalized Difference Vegetation Index (NDVI) and the Structure Insensitive Pigment Index (SIPI) . The period of time taken into consideration for the study was, 2013 - 2019, having used medium resolution satellite photos, Landsat 8 OLI, having initially undergone standard pre-processing operations (resize data, radiometric calibration, atmospheric correction). The satellite images modified according to the Top of Atmosphere Reflectance and corrected topographically resulted into getting values for the two before mentioned indexes. The quantity-spatial results obtained, correlated to the monthly values of the precipitations processed in order to obtain the SPI (Standardized Precipitation Index), mostly reveal, in what SIPI and also NDVI are concerned, a slight decrease in the quality of the forest on the analysed area in the sense that the vegetation stress is increased under meteorological factors, expressed differently depending on the morphometric and pedological parameters of the habitat.

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