Time series analysis and spatial data analysis allow us to analyze and understand how events and attributes of a place change over time. This per presents the design and development of an innovative mobile application aimed at capturing, organizing, and analyzing location-based spatial data for performing time series analysis. The proposed mobile application is developed using the Unity framework and seamlessly integrates image capture, note-taking, GPS tracking, and a robust SQLite database, offering users a comprehensive memory management system. This work focuses on performing time series analysis techniques for detecting anomalous behavior in urban parking lots. The mobile application includes two modules: 1) Data Collection Module, and 2) Data Visualization Module. The data collection module allows users to add pins in the parking lot and collect data in text, audio, and video format for time series analysis. The data visualization module incorporates the time series analysis for data captured in the data collection module to provide meaningful insights, into the identification of recurring patterns in the parking lot.