Geospatial Dataset of GNSS Anomalies and Political Violence Events

Geospatial Dataset of GNSS Anomalies and Political Violence Events Overview The Geospatial Dataset of GNSS Anomalies and Political Violence Events is a collection of data that integrates aircraft flight information, GNSS (Global Navigation Satellite System) anomalies, and political violence events from the ACLED (Armed Conflict Location & Event Data Project) database. Dataset Files The dataset consists of three CSV files: Daily_GNSS_Anomalies_and_ACLED-2023-V1.csv Description: Contains all grids and dates that had aircraft traffic during 2023. Number of Records: 6,777,228 Purpose: Provides a complete view of aircraft movements and associated data, including grids without any GNSS anomalies. Daily_GNSS_Anomalies_and_ACLED-2023-V2.csv Description: A filtered version of V1, including only the grids and dates where GNSS anomalies (jumps or gaps) were reported. Number of Records: 718,237 Purpose: Focuses on areas and times with GNSS anomalies for targeted analysis. Monthly_GNSS_Anomalies_and_ACLED-2023-V9.csv Description: Contains aggregated monthly data for each grid cell, combining GNSS anomalies and ACLED political violence events. Summarizes aircraft traffic, anomaly counts, and conflict activity at a monthly resolution. Number of Records: 25,770 Purpose: Enables temporal trend analysis and spatial correlation studies between GNSS interference and political violence, using reduced data volume suitable for modeling and visualization. Data Fields: Daily_GNSS_Anomalies_and_ACLED-2023-V1.csv and Daily_GNSS_Anomalies_and_ACLED-2023-V2.csv grid_id Description: Unique identifier for a grid cell on Earth measuring 0.5 degrees latitude by 0.5 degrees longitude. Format: String combining latitude and longitude (e.g., -10.0_-36.0). day Description: Date of the recorded data. Format: YYYY-MM-DD (e.g., 2023-03-28). geometry Description: Polygon coordinates of the grid cell in Well-Known Text (WKT) format. Format: POLYGON((longitude latitude, ...)) (e.g., POLYGON((-36.0 -10.0, -35.5 -10.0, -35.5 -9.5, -36.0 -9.5, -36.0 -10.0))). flights Description: Number of aircraft flights that passed through the grid on that day. Format: Integer (e.g., 28). GPS_jumps Description: Number of reported GNSS "jump" anomalies (possible spoofing incidents) in the grid on that day. Format: Integer (e.g., 1). GPS_gaps Description: Number of reported GNSS "gap" anomalies, indicating gaps in aircraft routes, in the grid on that day. Format: Integer (e.g., 0). gaps_density Description: Density of GNSS gaps, calculated as the number of gaps divided by the number of flights. Format: Decimal (e.g., 0). jumps_density Description: Density of GNSS jumps, calculated as the number of jumps divided by the number of flights. Format: Decimal (e.g., 0.035714286). event_id_cnty Description: ACLED event ID corresponding to political violence events in the grid on that day. Format: String (e.g., BRA69267). disorder_type Description: Type of disorder as classified by ACLED (e.g., "Political violence"). Format: String. event_type Description: General category of the event according to ACLED (e.g., "Violence against civilians"). Format: String. sub_event_type Description: Specific subtype of the event as per ACLED classification (e.g., "Attack"). Format: String. acled_count Description: Number of ACLED events in the grid on that day. Format: Integer (e.g., 1). acled_flag Description: Indicator of ACLED event presence in the grid on that day (0 for no events, 1 for one or more events). Format: Integer (0 or 1). Data Fields: Monthly_GNSS_Anomalies_and_ACLED-2023-V9.csv The file contains monthly aggregated GNSS anomaly and ACLED event data per grid cell. The structure and meaning of each field are detailed below: grid_id Description: Unique identifier for a grid cell on Earth measuring 0.5° latitude by 0.5° longitude. Format: String combining latitude and longitude (e.g., -0.5_-79.0). year_month Description: Month and year of the aggregated data. Format: String in Mon-YY format (e.g., Jan-23). geometry Description: Polygon coordinates of the grid cell in Well-Known Text (WKT) format. Format: POLYGON((longitude latitude, ...))(e.g., POLYGON((-79.0 -0.5, -78.5 -0.5, -78.5 0.0, -79.0 0.0, -79.0 -0.5))). flights Description: Total number of aircraft flights that passed through the grid cell during the month. Format: Integer (e.g., 1230). GPS_jumps Description: Total number of GNSS "jump" anomalies (possible spoofing events) in the grid cell during the month. Format: Integer (e.g., 13). GPS_gaps Description: Total number of GNSS "gap" anomalies, indicating interruptions in aircraft routes, during the month. Format: Integer (e.g., 0). event_id_cnty Description: Semicolon-separated list of ACLED event IDs associated with the grid cell during the month. Format: String (e.g., ECU3151;ECU3158;ECU3150). disorder_type Description: Semicolon-separated list of disorder types (e.g., "Political violence", "Demonstrations") reported by ACLED in that grid cell during the month. Format: String. event_type Description: Semicolon-separated list of high-level ACLED event types (e.g., "Riots", "Protests"). Format: String. sub_event_type Description: Semicolon-separated list of detailed subtypes of ACLED events (e.g., "Mob violence", "Armed clash"). Format: String. acled_count Description: Total number of ACLED conflict events in the grid cell during the month. Format: Integer (e.g., 2). acled_flag Description: Conflict presence indicator: 1 if any ACLED event occurred in the grid cell during the month, otherwise 0. Format: Integer (0 or 1). gaps_density Description: Monthly density of GNSS gaps, calculated as GPS_gaps / flights. Format: Decimal (e.g., 0.0). jumps_density Description: Monthly density of GNSS jumps, calculated as GPS_jumps / flights. Format: Decimal (e.g., 0.0106). Data Sources GNSS Anomalies Data: Calculated from ADS-B (Automatic Dependent Surveillance-Broadcast) messages obtained via the OpenSky Network's Trino database. GNSS anomalies include "jumps" (potential spoofing incidents) and "gaps" (interruptions in aircraft route data). Political Violence Events Data: Sourced from the ACLED database, which provides detailed information on political violence and protest events worldwide. Temporal and Spatial Coverage Temporal Coverage: From January 1, 2023, to December 31, 2023. Daily records provide temporal granularity for time-series analysis. Spatial Coverage: Global coverage with grid cells measuring 0.5 degrees latitude by 0.5 degrees longitude. Each grid cell represents an area on Earth's surface, facilitating spatial analysis. Usage and Applications Security Analysis: Assess potential correlations between GNSS anomalies and political violence events. Identify regions with increased risk of GNSS spoofing or signal disruption. Research and Development: Develop models to predict socio-political events based on GNSS anomalies. Study the impact of political instability on aviation safety. Policy and Decision Making: Inform aviation authorities and policymakers about regions requiring enhanced navigation security measures. Support conflict analysis and monitoring efforts.