DOI: 10.5281/zenodo.14199647
title: Geospatial Dataset of GNSS Anomalies and Political Violence Events

description: 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.