cctv

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

https://github.com/irlcode/cctv

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cctv explainable-ml r species-distribution-modelling surveillance-systems
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This is the code and data to replicate the analysis in Serebrennikov, Skougarevskiy (2023).

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cctv explainable-ml r species-distribution-modelling surveillance-systems
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README.md

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 (2024).

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
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

serebrennikov.dmtr@eu.spb.ru

Owner

  • Name: Institute for the Rule of Law at European University at St. Petersburg
  • Login: irlcode
  • Kind: organization
  • Email: ipp@eu.spb.ru
  • Location: Saint Petersburg, Russia

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