|
Meno a priezvisko:
|
doc. Mgr. Martin Šveda, PhD.
|
|
Typ dokumentu:
|
Vedecko/umelecko-pedagogická charakteristika osoby
|
|
Názov vysokej školy:
|
Univerzita Komenského v Bratislave
|
|
Sídlo vysokej školy:
|
Šafárikovo námestie 6, 818 06 Bratislava
|
| III.a - Zamestnanie-pracovné zaradenie | III.b - Inštitúcia | III.c - Časové vymedzenie |
|---|---|---|
| samostatný vedecký pracovník | Geografický ústav SAV | 2012- |
| odborný asistent | Univerzita Komenského v Bratislave, Prírodovedecká fakulta | 2017-2022 |
| V.1.a - Názov profilového predmetu | V.1.b - Študijný program | V.1.c - Stupeň | V.1.d - Študijný odbor |
|---|---|---|---|
| Geografia Slovenska (1) | Geografia, rozvoj regiónov a európska integrácia | I. | vedy o Zemi |
| Geografia Slovenska (2) | Geografia, rozvoj regiónov a európska integrácia | I. | vedy o Zemi |
| Analýza a vizualizácia priestorových údajov (1) | Geografia, rozvoj regiónov a európska integrácia | II. | vedy o Zemi |
| Analýza a vizualizácia priestorových údajov (2) | Geografia, rozvoj regiónov a európska integrácia | II. | vedy o Zemi |
| Analýza a vizualizácia priestorových údajov (3) | Geografia, rozvoj regiónov a európska integrácia | II. | vedy o Zemi |
| V.2.a - Názov študijného programu | V.2.b - Stupeň | V.2.c - Študijný odbor |
|---|---|---|
| Geografia, rozvoj regiónov a európska integrácia | I. | vedy o Zemi |
| Regionálna geografia, rozvoj regiónov a európska integrácia | II. | vedy o Zemi |
| Regionálna geografia | III. | vedy o Zemi |
| V.5.a - Názov predmetu | V.5.b - Študijný program | V.5.c - Stupeň | V.5.d - Študijný odbor |
|---|---|---|---|
| PC geoaplikácie (2) | Geografia, rozvoj regiónov a európska integrácia | I. | vedy o Zemi |
| Exkurzia po Slovensku | Geografia, rozvoj regiónov a európska integrácia | I. | vedy o Zemi |
| Urbánna geografia | Geografia, rozvoj regiónov a európska integrácia; Ekonomická a politická geografia a demografia | I. | vedy o Zemi |
| Rurálna geografia | Geografia, rozvoj regiónov a európska integrácia | I. | vedy o Zemi |
| Geografia Slovenska (1) | Geografia, kartografia a geoinformatika | I. | vedy o Zemi |
| Analýza a vizualizácie priestorových údajov (1-3) | Geografia, rozvoj regiónov a európska integrácia | II. | vedy o Zemi |
Šveda, M., & Madajová, M. S. (2023). Estimating distance decay of intra-urban trips using mobile phone data: The case of Bratislava, Slovakia. Journal of Transport Geography, 107, 103552. IF (JCR) 2021=5.9, Q1 [Geography] 2021
Šveda, M., Hurbánek, P., Madajová, M. S., Rosina, K., Förstl, F., Záboj, P., & Výbošťok, J. (2024). When spatial interpolation matters: Seeking an appropriate data transformation from the mobile network for population estimates. Computers, Environment and Urban Systems, 110, 102106. IF (JCR) 2023=7.1, Q1 [Geography] 2023
Šveda, M., Výbošťok, J., Gurňák, D. (2024): Cesta (z) mesta: Atlas suburbanizácie Bratislavy. N press: Bratislava.
Holec, J., Šveda, M., Szatmári, D., Feranec, J., Bobáľová, H., Kopecká, M., & Šťastný, P. (2021). Heat risk assessment based on mobile phone data: case study of Bratislava, Slovakia. Natural Hazards, 108(3), 3099-3120. (2020: 3.102 - IF, Q2 - JCR, 0.760 - SJR, Q1 - SJR).
Šveda, M., & Hurbánek, P. (2025). Rural-urban rhythms: Hierarchy in commuting of mobile phone users in Slovakia. Journal of Transport Geography, 129, 104425. F (JCR) 2025=6.8, Q1 [Geography] 2025
Šveda, M., & Madajová, M. S. (2023). Estimating distance decay of intra-urban trips using mobile phone data: The case of Bratislava, Slovakia. Journal of Transport Geography, 107, 103552. IF (JCR) 2021=5.9, Q1 [Geography] 2021
Šveda, M., & Hurbánek, P. (2025). Rural-urban rhythms: Hierarchy in commuting of mobile phone users in Slovakia. Journal of Transport Geography, 129, 104425. F (JCR) 2025=6.8, Q1 [Geography] 2025
Šveda, M., Hurbánek, P., Madajová, M. S., Rosina, K., Förstl, F., Záboj, P., & Výbošťok, J. (2024). When spatial interpolation matters: Seeking an appropriate data transformation from the mobile network for population estimates. Computers, Environment and Urban Systems, 110, 102106. IF (JCR) 2023=7.1, Q1 [Geography] 2023
Holec, J., Šveda, M., Szatmári, D., Feranec, J., Bobáľová, H., Kopecká, M., & Šťastný, P. (2021). Heat risk assessment based on mobile phone data: case study of Bratislava, Slovakia. Natural Hazards, 108(3), 3099-3120. (2020: 3.102 - IF, Q2 - JCR, 0.760 - SJR, Q1 - SJR).
Šveda, M., Výbošťok, J., Gurňák, D. (2024): Cesta (z) mesta: Atlas suburbanizácie Bratislavy. N press: Bratislava.
Šveda, M., & Madajová, M. S. (2023). Estimating distance decay of intra-urban trips using mobile phone data: The case of Bratislava, Slovakia. Journal of Transport Geography, 107, 103552. IF (JCR) 2021=5.9, Q1 [Geography] 2021
Ohlasy:
[n1] 2024 zz ~ Nalin, A., Vignali, V., Lantieri, C., Cappellari, D., Zamengo, B., & Simone, A. (2024). Assessing veracity of big data: An in-depth evaluation process from the comparison of Mobile phone traces and groundtruth data in traffic monitoring. Journal of Transport Geography, 118, 103930.
[n1] 2024 zz ~ Yuan, L., Sho, K., Eom, S., Nishi, H., Hasegawa, D., Zhao, H., ... & Masumura, A. (2024). Changes in visitor behaviour across COVID-19 pandemic: Unveiling urban visitation dynamics and non-linear relationships with the built environment using mobile big data. Habitat International, 154, 103216.
[n1] 2024 zz ~ Pian, Q., Zhang, L., Zhou, D., & Xia, D. (2024). Structural characteristics of urban agglomeration transportation networks under sustainable development goals. International Journal of Sustainable Transportation, 18(7), 618-632.
[n1] 2025 zz ~ Verma, R., & Ukkusuri, S. V. (2025). What determines travel time and distance decay in spatial interaction and accessibility?. Journal of Transport Geography, 122, 104061.
[n1] 2024 zz ~ He, Z., Zhao, P., Xiao, Z., Huang, X., Li, Z., & Kang, T. (2024). Exploring the distance decay in port hinterlands under port regionalization using truck GPS data. Transportation Research Part E: Logistics and Transportation Review, 181, 103390.
[n1] 2025 zz ~ Zhang, G., Wang, D., Chen, M., Zeng, J., & Cai, Z. (2025). Assessing urban-scale spatiotemporal heterogeneous metro station coverage using multi-source mobility data. Journal of Transport Geography, 123, 104081.
[n1] 2024 zz ~ Wang, Y., Yao, X., Wang, J., Kang, C., Meng, X., Hu, G., ... & Li, X. (2024). Investigating the effect of industry-specific economic distance on the prediction of intercity population movement. Cities, 150, 105047.
[n1] 2024 zz ~ Zhao, Z., Jin, M., Jin, J., Liu, L., Gong, Y., & Liu, Y. (2024). Discovering the spatial heterogeneous constraints of distance on migration from counties to Shenzhen in China. Applied Geography, 171, 103384.
[n1] 2024 zz ~ Halás, M. (2025). Distance-decay function alternatives based on mobile phone location data. Journal of Transport Geography, 123, 104097.
[n1] 2024 zz ~ Deng, Y., Wu, J., Yu, C., Deng, J., Tu, M., & Wang, Y. (2024). Investigating influential factors on railway passenger flow utilizing multi-source data fusion and flow space theory: A case study of the Yangtze River Delta megalopolis, China. International Journal of Transportation Science and Technology.
[n1] 2024 zz ~ Kita, P., Maciejewski, G., Žambochová, M., & Križan, F. (2024). Geomarketing as an important element of a food retailer’s business model: A managerial view. International Journal of Management and Economics.
[n1] 2024 zz ~ Leitch, S., & Wei, Z. (2024). Improving spatial access to healthcare facilities: an integrated approach with spatial analysis and optimization modeling. Annals of Operations Research, 1-18.
[n1] 2024 zz ~ Madanayake, A. R. S., Lee, K., & Lee, I. (2024). Mining contacts from spatio-temporal trajectories. AI Open, 5, 197-207.
[n1] 2024 zz ~ Zhang, J., Cai, J., Zhang, X., & Zhang, W. (2024). The Spatiotemporal Organizational Order of Living Circle Units Based on the Law of Walking Time-Distance Distributions. Land, 13(12), 2105.
[n1] 2024 zz ~ Verma, R., Debnath, M., Mittal, S., & Ukkusuri, S. V. (2024). Towards a generalized accessibility measure for transportation equity and efficiency. arXiv preprint arXiv:2404.04985.
[n1] 2024 zz ~ Wang, J., Luo, G., Huang, Y., Liu, M., & Wei, Y. (2023). Spatial characteristics and influencing factors of commuting in central urban areas using mobile phone data: A case study of nanning. Sustainability, 15(12), 9648.
[n1] 2024 zz ~ Zhang, B. (2024). Modelling Functional Spatial Structure in Mega-city Region Based on Human Mobility Pattern (Doctoral dissertation, King’s College London).
[n1] 2024 zz ~ Jaroš, V. (2023, May). Geolocation Data as a Research Tool for the Organization of the Settlement System and Mobility Mapping–Case Study of the Spatial Mobility Model in Czechia. In International Symposium on AI, Data and Digitalization (pp. 1-15). Cham: Springer Nature Switzerland.
[n1] 2024 zz ~ Ogbuju, E., Aliyu, A., Imoize, A. L., Rufai, M. A., Muhammad, A. S., & Oladipo, F. Government Policies and Economics of Computational Modelling in Wireless Networks. In Computational Modeling and Simulation of Advanced Wireless Communication Systems (pp. 260-296). CRC Press.
Šveda, M., Hurbánek, P., Madajová, M. S., Rosina, K., Förstl, F., Záboj, P., & Výbošťok, J. (2024). When spatial interpolation matters: Seeking an appropriate data transformation from the mobile network for population estimates. Computers, Environment and Urban Systems, 110, 102106. IF (JCR) 2023=7.1, Q1 [Geography] 2023
Ohlasy:
Park, C., No, W., & Kim, Y. (2025). A probabilistic AI-based pedestrian volume estimation model for street-level urban management. Journal of Transport Geography, 129, 104437.
Yang, Y., Tan, Z., & Schläpfer, M. (2025). Assessing the space-use efficiency of French cities by coupling city volumes with mobile data traffic. Sustainable Cities and Society, 124, 106292.
Stražovec, A., Erlebach, M., & Halás, M. (2025). Pulsating population: the rhythmicity of municipalities in the Czech Republic based on mobile phone location data. Journal of Maps, 21(1), 2528871.
Martínez-Bernabéu, L., Coombes, M., & Casado-Díaz, J. M. (2025). Assessing mobile phone data as proxy census commuting data for transport geography research: a critical review and case study. Journal of Transport Geography, 128, 104361.
Wang, J., Ma, S., Lv, Q., & Li, Q. (2025). Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data. Plos one, 20(6), e0320298.
Wei, Z., Ye, H., He, H., Low, K. H., Hao, L., Li, Z., ... & Liao, X. (2026). Interpretable machine learning for street-level population modeling in the built environment: Implications for urban low-altitude operations. Building and Environment, 114763.
Moghari, S., Fallah, M. K., Gorgin, S., & Shin, S. (2024). LEAF: A Lifestyle Approximation Framework Based on Analysis of Mobile Network Data in Smart Cities. Smart Cities, 7(6), 3315-3333.
Kachari, R. (2026). Integrating large language models into spatial analysis: experimental insights from GIS interpolation. Spatial Information Research, 34(3), 22.
Jirásek, P., & Šomplák, R. (2025). Digital Revolution in Spatial Planning: The Potential of Geolocation Data in Czechia. Urban Science, 9(5), 158.
Šveda, M., Madajová, M. S., Barlík, P., Križan, F., & Šuška, P. (2020). Mobile phone data in studying urban rhythms: Towards an analytical framework. Moravian Geographical Reports, 28(4), 248-258.
Ohlasy:
Liu, Y., Hu, Y., Wang, D., Cheng, Y., Yan, L., Wei, D., & Jiao, J. (2026). Decomposing urban spatial rhythms: A big-small data fusion framework for activity pattern identification. Cities, 169, 106548.
Xia, J., Li, R., Yang, X., Wang, J., & Zou, N. (2026). High-resolution population distribution prediction considering the spatiotemporal heterogeneity of geolocated behavior. International Journal of Geographical Information Science, 40(6), 1618-1650.
Stražovec, A., Erlebach, M., & Halás, M. (2025). Pulsating population: the rhythmicity of municipalities in the Czech Republic based on mobile phone location data. Journal of Maps, 21(1), 2528871.
Halás, M. (2024). Temporality in the delimitation of functional regions: The use of mobile phone location data. Regional Studies, 58(11), 2175-2187.
Halás, M. (2025). Distance-decay function alternatives based on mobile phone location data. Journal of Transport Geography, 123, 104097.
Zhang, Y., Wang, X., Zhi, G., Zhou, H., & Cui, N. (2025). The rhythms of citizens’ leisure and recreation: A case study based on social media data. Frontiers in Ecology and Evolution, 13, 1615395.
Halas, M., & Klapka, P. (2023). The timescape of the city: Example of spatial interactions based on big data. Habitat International, 131, 102736.
Gökçe Kılıç, P., & Terzi, F. (2025). Big Data, Mobility and Rhythms in Istanbul: A Data-Driven Analysis of Urban Temporal Dynamics. Applied Spatial Analysis and Policy, 18(4), 144.
Kraft, S., Blažek, V. O. J. T. Ě. C. H., & Marada, M. (2022). Exploring the daily mobility rhythms in an urban environment: Using the data from intelligent transport systems. Geografie, 127(2), 127-144.
Lískovec, R., Lichter, M., & Mulíček, O. (2022). Chronotopes of urban centralities: Looking for prominent urban times and places. The Geographical Journal, 188(2), 166-176.
Makhrova, A. G., Babkin, R. A., Kirillov, P. L., Starikova, A. V., & Sheludkov, A. V. (2022). Temporary mobility and population pulsations in space of post-Soviet Russia. Regional Research of Russia, 12(1), 36-50.
Nemeškal, J. (2026). A 90-minute city: football fans dividing Prague. Journal of Maps, 22(1), 2671919.
Holec, J., Šveda, M., Szatmári, D., Feranec, J., Bobáľová, H., Kopecká, M., & Šťastný, P. (2021). Heat risk assessment based on mobile phone data: case study of Bratislava, Slovakia. Natural Hazards, 108(3), 3099-3120.
Ohlasy:
Li, F., Yigitcanlar, T., Nepal, M., Thanh, K. N., & Dur, F. (2022). Understanding urban heat vulnerability assessment methods: a PRISMA review. Energies, 15(19), 6998.
Brogno, L., Barbano, F., Leo, L. S., & Di Sabatino, S. (2025). Review on heatwaves: a risk perspective. Environmental Research Letters, 20(6), 063004.
Li, F., Yigitcanlar, T., Nepal, M., Thanh, K. N., & Dur, F. (2024). A novel urban heat vulnerability analysis: Integrating machine learning and remote sensing for enhanced insights. Remote Sensing, 16(16), 3032.
Ma, L., Huang, G., Johnson, B. A., Chen, Z., Li, M., Yan, Z., ... & Lian, D. (2023). Investigating urban heat-related health risks based on local climate zones: A case study of Changzhou in China. Sustainable Cities and Society, 91, 104402.
Yoo, C., Im, J., Weng, Q., Cho, D., Kang, E., & Shin, Y. (2023). Diurnal urban heat risk assessment using extreme air temperatures and real-time population data in Seoul. Iscience, 26(11).
Derakhshan, S., Bautista, T. N., Bouwman, M., Huang, L., Lee, L., Tarczynski, J., ... & Longcore, T. (2023). Smartphone locations reveal patterns of cooling center use as a heat mitigation strategy. Applied Geography, 150, 102821.
Brogno, L., Barbano, F., Leo, L. S., & Di Sabatino, S. (2024). A novel framework for the assessment of hydro-meteorological risks taking into account nature-based solutions. Environmental Research Letters, 19(7), 074040.
ŠVEDA, Martin - BARLÍK, Peter. Daily commuting in the Bratislava metropolitan area: case study with mobile positioning data. In Papers in Applied Geography, 2018, vol. 4, no. 4, p. 409-423.
Ohlasy:
Hadachi, A., Pourmoradnasseri, M., & Khoshkhah, K. (2020). Unveiling large-scale commuting patterns based on mobile phone cellular network data. Journal of transport Geography, 89, 102871.
Halás, M. (2025). Distance-decay function alternatives based on mobile phone location data. Journal of Transport Geography, 123, 104097.
Halás, M., Blažek, V., Klapka, P., & Kraft, S. (2021). Population movements based on mobile phone location data: the Czech Republic. Journal of Maps, 17(1), 116-122.
Zévl, J. J., & Ouředníček, M. (2025). Suburban Autonomy? The Case of Inter‐Suburban Commuting Outside Prague. Tijdschrift voor economische en sociale geografie, 116(2), 176-193.
Kraft, S., Halás, M., Klapka, P., & Blažek, V. (2022). Functional regions as a platform to define integrated transport system zones: The use of population flows data. Applied geography, 144, 102732.
Pintér, G., & Felde, I. (2022). Commuting analysis of the budapest metropolitan area using mobile network data. ISPRS International Journal of Geo-Information, 11(9), 466.
Kopáčik, G., Vaishar, A., & Šimara, E. (2021). The dynamics of population distributions in cities based on daily mobile phone operations: A case study of some Moravian cities. Moravian Geographical Reports, 29(1), 71-86.
Rodríguez, M., Molina, J., & Camacho, J. A. (2022). Mapping functional areas in Spain using mobile positioning data. European Urban and Regional Studies, 29(2), 145-151.
VEGA 1/0082/15: Špecifiká časovo-priestorového správania človeka pod vplyvom spoločensko-ekonomických zmien. (riešiteľ)
APVV-20-0302: Alternatívne potravinové siete: od konzumnej k udržateľnej spotrebe (riešiteľ )
APVV-16-0462: Suburbanizácia - vývoj a dopady na sociálno-priestorovú štruktúru zázemia Bratislavy (hlavný riešiteľ)
APVV-19-0281: Mapovanie rozmiestnenia a mobility populácie na Slovensku s využitím lokalizačných údajov mobilnej siete (riešiteľ)
APVV 20-0432, Suburbanizácia: Komunita, identita a každodennosť, 2021 - 2023, riešiteľ
APVV-24-0360: Vidiecko-mestské rytmy: Analýza denných rutín obyvateľov Slovenska prostredníctvom geolokačných údajov mobilnej siete (hlavný riešiteľ)
| VII.a - Aktivita, funkcia | VII.b - Názov inštitúcie, grémia | VII.c - Časové vymedzenia pôsobenia |
|---|---|---|
| Člen redakčnej rady časopisu | Moravian Geographical reports (CC) | 2020- |
| Člen redakčnej rady časopisu | Geographia Slovaca (Geogafický ústav SAV | 2018- |
| Člen gremilánej rady Metropolitného inštitútu Bratislava | Metropolitný inštitút Bratislavy | 2021- |
| Člen rady pre reformu verejnej správy | Ministerstvo vnútra SR | 2022- |
| VIII.a - Názov inštitúcie | VIII.b - Sídlo inštitúcie | VIII.c - Obdobie trvania pôsobenia/pobytu (uviesť dátum odkedy dokedy trval pobyt) | VIII.d - Mobilitná schéma, pracovný kontrakt, iné (popísať) |
|---|---|---|---|
| Karlova univerzita v Prahe, Přírodovědecká fakulta, Katedra sociální geografie a regionálního rozvoje | Albertov 6, 128 00 Praha 2 (CZ) | 3-6.12.2019 | vyžiadané prednášky |