Predicting context-sensitive urban safety space quality

Short description: PPGIS data is increasingly collected understand location-specific human values, perceptions, behavior, and preferences for future land use and development. The motivation of this work is to study aspects affecting PPGIS data quality.

Keywords:  PPGIS, emotional cartography, data quality

Topic at: TU Vienna

Staff involved: Georg Gartner (georg.gartner@tuwien.ac.at) ; Jiri Panek

Description:

Inspired by Kajosaari et. al (2024) the proposed master’s thesis should use the available open-data for Prague Emotional map - containing 98,364 points complemented with 30,941 comments from 5,973 respondents across the city of Prague to map urban safety perceptions by combining subjective safety data (e.g., feelings of safety or instances of discomfort) with objective environmental variables that influence these perceptions. The proposed master thesis research should create, validate, test and explain the perception of urban safety model. The model would spatially extrapolate perception of urban safety data to predict perceived urban safety across the entire city, revealing (micro)local differences.  

Literature/references:

  1. Kajosaari, Anna, Kamyar Hasanzadeh, Nora Fagerholm, Pilvi Nummi, Paula Kuusisto-Hjort, and Marketta Kyttä. "Predicting context-sensitive urban green space quality to support urban green infrastructure planning." Landscape and Urban Planning242 (2024): 104952.
  2. Linhartová, Petra, Igor Ivan, and Jiří Pánek. "Visualising residents’ fear of crime with recorded crime data from four Czech cities." Journal of Maps 18, no. 1 (2022): 26-32.
  3. Pánek, Jiří, Radek Barvíř, Jakub Koníček, and Milan Brlík. "The emotional map of Prague–data on what locals think about the Czech capital?." Data in brief 39 (2021): 107649.