###### Abstract
The problem of quantifying the uncertainty of modal characteristics that are estimated from a single batch of (operational) vibration data gained interest during the past few years, reflecting the complexity of accurately identifying the structural state. Since environmental variations also influence modal properties, a training period that covers the range of environmental changes is required to filter out their effects. In this context, the objective of this work is to assess the structural health of a reinforced concrete building located in Valparaiso, Chile, a coastal area characterized by the presence of soft soil and a near-surface water table. The focus of this study is a detailed comparative analysis of the building's dynamic response to three types of records: ambient vibrations, vibrations generated by adjacent construction, and seismic records. The results are examined over time, allowing for the identification of behavioral patterns and possible variations in the structural response to different sources of excitation. In the study, ambient vibrations, vibrations from adjacent construction, and seismic events were recorded, with data collected during the years 2022, 2023, and 2024. In this study, the Stochastic Subspace Identification with Covariances (SSI-COV) [7] method is employed using a MATLAB toolbox developed by the University of Leuven [13]. This methodological approach facilitates the precise identification of modal parameters, which are essential for a structural health evaluation based on the analysis of recorded vibrations. SSI-COV stands out for its efficiency and accuracy in extracting modal characteristics, even in the presence of noise and without the need for artificial excitations [14]. The implementation of this toolbox enables a robust interpretation of the data obtained, providing critical information for decision-making in infrastructure maintenance and management. This manuscript addresses the question about the quality of the results of using SSI-COV on the aforementioned building for different inputs. In our case, the inputs have different sources and natures: seismic activity, ambient vibrations, and vibrations from a neighboring construction site. When talking about quality of the results, we mean to compare the output and results of the analysis using all or only some of the available sensors, as well as looking to the characteristics of the modes computed. This paper is organized into six main chapters covering the methodology, case study, monitoring campaign, and results. Chapter 2 presents the methodology, focusing on the SSI-COV approach and its implementation in MATLAB to analyze the building's structural dynamics. Chapter 3 describes the building under study, including its structural characteristics, location in Valparaiso, Chile, and the environmental and seismic conditions of the area. Chapter 4 outlines the monitoring campaign, detailing the sensor specifications, characteristics, and arrangement, as well as the measurement dates, which encompass data from ambient vibrations, vibrations from adjacent construction, and seismic records. Chapter 5 presents the results of the analysis, while Chapter 6 provides the conclusions drawn from the study.