irlcode/cctv

This is the code and data to replicate the analysis in Serebrennikov, Skougarevskiy (2023).

Data and Code For A tale of four cities: Exploring environmental characteristics of CCTV equipment placement

This is the code and data to replicate the analysis in Serebrennikov, Skougarevskiy (2023).

Repository structure

/
├── code
    ├── 1._Parameter_searching_and_cross-validation.R   # Parameters search, block cross-validation, final estimation
    ├── 2._SHAP_Analysis.R                              # SHAP-analysis and Plots based on it.
    ├── Table_1_code.R                                  # Produce Table 1 
    ├── Figure_1_code.R                                 # Produce Figure 1
    ├── 1a._Robustness_check_Parameter_searching_and_cross-validation.R # Robustness check for city centers
    └── 2a._Robustness_check_SHAP_Analysis.R            # Robustness check for city centers
├── data
    ├── BE_100_catboost_best_params.rds                 # Best parameters for Brussels' model
    ├── BE_all_osm_objects_Freqtab.RDS                  # Frequency tab for Brussels
    ├── BE_buffer_long_100_RandSamp_GEOM.rds            # Brussels geodata for block cross-validation
    ├── BE_buffer_wide_100_RandSamp.csv                 # Brussels data for analysis
    ├── data_all_catboost_buffer_100.rdata              # Brussels prepared data
    ├── feature_importance_catboost_buffer_100.rdata    # Data for feature importance plot
    ├── FR_100_catboost_best_params.rds                 # Best parameters for Paris' model
    ├── FR_all_osm_objects_Freqtab.RDS                  # Frequency tab for Paris
    ├── FR_buffer_long_100_RandSamp_GEOM.rds            # Paris data for analysis
    ├── FR_buffer_wide_100_RandSamp.csv                 # Paris prepared data
    ├── RU_100_catboost_best_params.rds                 # Best parameters for Moscow's model
    ├── RU_all_osm_objects_Freqtab.RDS                  # Frequency tab for Moscow
    ├── RU_buffer_long_100_RandSamp_GEOM.rds            # Moscow data for analysis
    ├── RU_buffer_wide_100_RandSamp.csv                 # Moscow prepared data
    ├── SC_100_catboost_best_params.rds                 # Best parameters for Edinburgh's model
    ├── SC_all_osm_objects_Freqtab.RDS                  # Frequency tab for Edinburgh
    ├── SC_buffer_long_100_RandSamp_GEOM.rds            # Edinburgh data for analysis
    └── SC_buffer_wide_100_RandSamp.csv                 # Edinburgh prepared data

Data availability statement

The data that support the findings of this study were derived from the following resources available in the public domain:

• OpenStreetMap data under Open Data Commons Open Database License
• Moscow CCTV locations open data published by Moscow city administration under Russian Government Decree N 583 of 10.07.2013 allowing free use
• Paris CCTV locations open data published by French Ministry of the Interior under Open Licence
• Edinburgh CCTV locations open data published by the Scottish Government under Open Government License v3.0
• Kontur Population Dataset by Kontur under Creative Commons Attribution International (CC BY) licence

Licence

Creative Commons License Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Copyright © the respective contributors, as shown by the AUTHORS file.

Contacts

Dmitriy Serebrennikov, assoсiated researcher at the Institute for the Rule of Law at the European University at St. Petersburg

[email protected]