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:

1. 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.
2. 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.
3. 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

1. 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).
2. day
• Description: Date of the recorded data.
• Format: YYYY-MM-DD (e.g., 2023-03-28).
3. 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))).
4. flights
• Description: Number of aircraft flights that passed through the grid on that day.
• Format: Integer (e.g., 28).
5. GPS_jumps
• Description: Number of reported GNSS "jump" anomalies (possible spoofing incidents) in the grid on that day.
• Format: Integer (e.g., 1).
6. 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).
7. gaps_density
• Description: Density of GNSS gaps, calculated as the number of gaps divided by the number of flights.
• Format: Decimal (e.g., 0).
8. 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).
9. event_id_cnty
• Description: ACLED event ID corresponding to political violence events in the grid on that day.
• Format: String (e.g., BRA69267).
10. disorder_type
• Description: Type of disorder as classified by ACLED (e.g., "Political violence").
• Format: String.
11. event_type
• Description: General category of the event according to ACLED (e.g., "Violence against civilians").
• Format: String.
12. sub_event_type
• Description: Specific subtype of the event as per ACLED classification (e.g., "Attack").
• Format: String.
13. acled_count
• Description: Number of ACLED events in the grid on that day.
• Format: Integer (e.g., 1).
14. 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:

1. 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).
2. year_month
• Description: Month and year of the aggregated data.
• Format: String in Mon-YY format (e.g., Jan-23).
3. 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))).
4. flights
• Description: Total number of aircraft flights that passed through the grid cell during the month.
• Format: Integer (e.g., 1230).
5. GPS_jumps
• Description: Total number of GNSS "jump" anomalies (possible spoofing events) in the grid cell during the month.
• Format: Integer (e.g., 13).
6. GPS_gaps
• Description: Total number of GNSS "gap" anomalies, indicating interruptions in aircraft routes, during the month.
• Format: Integer (e.g., 0).
7. 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).
8. 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.
9. event_type
• Description: Semicolon-separated list of high-level ACLED event types (e.g., "Riots", "Protests").
• Format: String.
10. sub_event_type

• Description: Semicolon-separated list of detailed subtypes of ACLED events (e.g., "Mob violence", "Armed clash").
• Format: String.

1. acled_count

• Description: Total number of ACLED conflict events in the grid cell during the month.
• Format: Integer (e.g., 2).

1. 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).

1. gaps_density

• Description: Monthly density of GNSS gaps, calculated as GPS_gaps / flights.
• Format: Decimal (e.g., 0.0).

1. 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.