TY - CHAP AU - Einger, Gergő AU - Böröcz, Balázs AU - Katona, János AU - Pődör, Andrea ED - Szakál, Anikó TI - Testing the Detection of Road Surface Defects Using Machine Learning Methods T2 - IEEE 25th International Symposium on Computational Intelligence and Informatics (CINTI 2025) : Proceedings PB - IEEE Hungary Section CY - Piscataway (NJ) SN - 9798331552916 T3 - International Symposium on Computational Intelligence and Informatics, CINTI, ISSN 2380-8586 PY - 2025 SP - 173 EP - 177 PG - 5 DO - 10.1109/CINTI67731.2025.11311798 UR - https://m2.mtmt.hu/api/publication/36452711 ID - 36452711 LA - English DB - MTMT ER - TY - JOUR AU - Harmati, Barbara AU - Pődör, Andrea AU - Tick, Andrea TI - Time's Effect on Crime Prediction Precision and Accuracy JF - ACTA POLYTECHNICA HUNGARICA J2 - ACTA POLYTECH HUNG VL - 22 PY - 2025 IS - 8 SP - 157 EP - 177 PG - 21 SN - 1785-8860 DO - 10.12700/APH.22.8.2025.8.10 UR - https://m2.mtmt.hu/api/publication/36273236 ID - 36273236 AB - Crime detection with high prediction and accuracy has become a focused issue in the process of crime investigation and prevention. The higher the accuracy or precision of a crime detection model the more efficient crime investigation and prevention becomes. The present research aims to examine the possible precision and accuracy differences of using two different test datasets (TD) to calculate the predictive accuracy index (PAI), and the recapture rate index (RRI) for kernel density estimation (KDE), risk terrain modeling (RTM) and the combined RTM–KDE model. The present study focuses on theft and robbery cases of between 1 December 2015 and 30 November 2018 in Budapest, Hungary. The novelty of the research lies in its first-time usage in Budapest, in a Central European evolutionary urban structure. The results show that there are differences in prediction performance and in each model using a Test Dataset (TD) more distant in time from the initial dataset resulted in a more accurate prediction. The research proved that datasets with different time distances can have an impact on the predictive accuracy and precision of crime detection. LA - English DB - MTMT ER - TY - JOUR AU - Kounadi, Ourania AU - Vallejo-Velázquez, Mariana AU - Huang, Qilei AU - Pődör, Andrea TI - Are Places Where People Feel Safe or Unsafe Similar to Spatial Crime Patterns? Extracting the Collective Truth of the Spatial Crime Perception Gap Using Digital Sketch Maps JF - URBAN SCIENCE J2 - URBAN SCI VL - 9 PY - 2025 IS - 10 PG - 22 SN - 2413-8851 DO - 10.3390/urbansci9100397 UR - https://m2.mtmt.hu/api/publication/36384884 ID - 36384884 AB - This study examines the spatial crime perception gap (SCPG), the mismatch between perceived and actual crime, which can lead to unnecessary avoidance behaviors, anxiety, or lack of vigilance. While few studies have explored this phenomenon from a spatial perspective, this research analyses the collective spatial perception of safety and unsafety in Vienna and Budapest and compares them with recorded crime patterns. Using a digital sketch map survey tool, 656 participants identified safe and unsafe areas as well as their daily routes. The responses were analyzed using spatial analytical and statistical methods to delineate the perception gaps in space, which were also diversified by crime type aggregations, including all crimes, violent crimes, property crimes, and visible crimes. Distance-based analyses were also conducted to examine the “spatial diffusion” and “spatial endowment” effects. The results show that many areas that are perceived as unsafe are not statistical crime hotspots. Perception aligns more closely with violent crime patterns than with property or visible crimes. The spatial diffusion effect illustrates that crime hotspots may influence and expand the perception of unsafety in adjacent and nearby areas. The spatial endowment effect suggests that people are more likely to perceive an area as unsafe if it is further away from their activity spaces, while overlooking crime hotspots that may intersect with it. These patterns were consistent across both cities, although the perception gap was larger in Budapest, while the endowment effect was more pronounced in Vienna. By highlighting where and how perception diverges from reality, this study provides insights that can inform strategies to reduce unfounded fear and strengthen the perceived safety and psychological resilience of urban populations. LA - English DB - MTMT ER - TY - JOUR AU - Pődör, Andrea AU - Tick, Andrea TI - Surveillance and Subjectivity: A GIS-Based Study of Fear of Crime and CCTV Distribution JF - ACTA POLYTECHNICA HUNGARICA J2 - ACTA POLYTECH HUNG VL - 22 PY - 2025 IS - 12 SP - 197 EP - 214 PG - 18 SN - 1785-8860 DO - 10.12700/APH.22.12.2025.12.14 UR - https://m2.mtmt.hu/api/publication/36361181 ID - 36361181 LA - English DB - MTMT ER - TY - CHAP AU - Pődör, Andrea AU - Ourania, Kounadi AU - Mariana, Vallejo Velázquez ED - Abriha-Molnár, Vanda Éva TI - A városi bűncselekményi gócpontok felszámolásának hatása a bűnözéstől való félelem térbeli mintázatára T2 - Az elmélet és a gyakorlat találkozása a térinformatikában XVI. PB - Debreceni Egyetemi Kiadó CY - Debrecen SN - 9789634907114 PY - 2025 SP - & UR - https://m2.mtmt.hu/api/publication/36384889 ID - 36384889 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Pődör, Andrea AU - Ourania, Kounadi AU - Mariana, Vallejo Velázquez AU - Böröcz, Balázs AU - Molnár, Gábor ED - Szakál, Anikó TI - Integrating Human Perception and AI: A Random Forest Approach to Urban Safety T2 - IEEE 25th International Symposium on Computational Intelligence and Informatics (CINTI 2025) : Proceedings PB - IEEE Hungary Section CY - Piscataway (NJ) SN - 9798331552916 T3 - International Symposium on Computational Intelligence and Informatics, CINTI, ISSN 2380-8586 PY - 2025 SP - 259 EP - 263 PG - 5 UR - https://m2.mtmt.hu/api/publication/36452951 ID - 36452951 LA - English DB - MTMT ER - TY - JOUR AU - Vallejo-Velazquez, Mariana AU - Kounadi, Ourania AU - Pődör, Andrea TI - Assessing the Usability and Suitability of Area Mapping Tools for Capturing Spatial Perception and Knowledge JF - CARTOGRAPHIC JOURNAL J2 - CARTOGR J PY - 2025 PG - 22 SN - 0008-7041 DO - 10.1080/00087041.2025.2592376 UR - https://m2.mtmt.hu/api/publication/36849709 ID - 36849709 LA - English DB - MTMT ER - TY - CHAP AU - Bói, László AU - Pődör, Andrea AU - Mátyás, Szabolcs AU - Kis, Balint ED - Cecon, Franziska ED - Cojocaru, Igor ED - Müller-Török, Robert ED - Szádeczky, Tamás ED - Vrabie, Catalin TI - Communicating crimes with maps to citizens T2 - Proceedings of the Central and Eastern European eDem and eGov Days 2024 PB - Association for Computing Machinery (ACM) CY - New York, New York SN - 9798400717093 PY - 2024 SP - 187 EP - 194 PG - 8 DO - 10.1145/3670243.3673860 UR - https://m2.mtmt.hu/api/publication/35168238 ID - 35168238 AB - The scholarly investigation delves into a subject that has garnered limited attention: the dissemination of criminal activities through cartographic representations. Despite the ubiquitous presence of maps in various media outlets such as crime reports, newspapers, television, and online platforms, scholarly inquiry into this matter remains scant. Maps have long served as a conventional method of visual display within the field of criminal sciences, yet divergent viewpoints persist regarding their dissemination. While proponents advocate for the publication of crime maps, contending that they facilitate public awareness, others caution against their dissemination, citing potential misinterpretations. The primary objective of the study is to elucidate strategies for effectively presenting and communicating crime-related information to the general populace. Furthermore, the investigation endeavors to delineate the advantages and drawbacks associated with the publication of crime maps LA - English DB - MTMT ER - TY - CHAP AU - Katona, János AU - Pődör, Andrea ED - Petőné Csuka, Ildikó TI - AI-supported Visual Lisp Programming in Geoinformatics T2 - AIS 2024 - 19th International Symposium on Applied Informatics and Related Areas - Proceedings PB - Óbudai Egyetem CY - Székesfehérvár SN - 9789634493679 PY - 2024 SP - 71 EP - 74 PG - 4 UR - https://m2.mtmt.hu/api/publication/35577650 ID - 35577650 LA - English DB - MTMT ER - TY - CHAP AU - Kiszely, Márta AU - Pődör, Andrea ED - Szakál, Anikó TI - Advanced Visualization of Seismic Activity in the Vértes Mountain Region Post-M4.5 Mainshock T2 - IEEE 22nd International Symposium on Intelligent Systems and Informatics (SISY 2024) PB - IEEE Hungary Section CY - Pula SN - 9798350385595 PY - 2024 SP - 527 EP - 532 PG - 6 DO - 10.1109/SISY62279.2024.10737552 UR - https://m2.mtmt.hu/api/publication/35392064 ID - 35392064 LA - English DB - MTMT ER -