@article{MTMT:35625161,
	title = {Integration Failure or Integration risk? Revisiting the Modality of Return Migration in China},
	url = {https://m2.mtmt.hu/api/publication/35625161},
	author = {Li, Zhigang and Yu, Le and Gao, Feifan and Cheng, Hanbei and Liu, Yuqi},
	doi = {10.1007/s12061-024-09618-2},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	volume = {18},
	unique-id = {35625161},
	issn = {1874-463X},
	year = {2025},
	eissn = {1874-4621},
	pages = {Articlein press},
	orcid-numbers = {Yu, Le/0009-0002-6343-9961}
}

@article{MTMT:35614717,
	title = {Spatial Autocorrelation Methods in Identifying Migration Patterns: Case Study of Slovakia},
	url = {https://m2.mtmt.hu/api/publication/35614717},
	author = {Pregi, L. and Novotný, L.},
	doi = {10.1007/s12061-024-09615-5},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	volume = {18},
	unique-id = {35614717},
	issn = {1874-463X},
	year = {2025},
	eissn = {1874-4621}
}

@article{MTMT:35023944,
	title = {Convergence and Catch-Up of the Region Types in the Central and Eastern European Countries (NOV, 10.1007/s12061-023-09551-w, 2023)},
	url = {https://m2.mtmt.hu/api/publication/35023944},
	author = {Egri, Zoltan and Lengyel, Imre},
	doi = {10.1007/s12061-024-09579-6},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	unique-id = {35023944},
	issn = {1874-463X},
	year = {2024},
	eissn = {1874-4621},
	orcid-numbers = {Egri, Zoltan/0000-0002-7946-2296}
}

@article{MTMT:35020779,
	title = {Examining the Structural Inequities in the Quality of Nationwide Drinking Water Data in Aotearoa New Zealand: A Geospatial Cross-Sectional Study},
	url = {https://m2.mtmt.hu/api/publication/35020779},
	author = {Hobbs, M. and Puente-Sierra, M. and Marek, L. and Broadbent, J. M. and Chambers, T.},
	doi = {10.1007/s12061-024-09571-0},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	unique-id = {35020779},
	issn = {1874-463X},
	keywords = {WATER; GIS; Environment; inequity; data; spatial; geospatial; data equity},
	year = {2024},
	eissn = {1874-4621}
}

@article{MTMT:34342683,
	title = {The Changing Geography of Scientific Knowledge Production. Evidence from the Metropolitan area Level},
	url = {https://m2.mtmt.hu/api/publication/34342683},
	author = {Gui, Qinchang and Du, Debin and Liu, Chengliang},
	doi = {10.1007/s12061-023-09525-y},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	volume = {17},
	unique-id = {34342683},
	issn = {1874-463X},
	abstract = {The metropolitan areas act as incubators of new knowledge, and play a central role in the process of scientific knowledge production. On the basis of highly cited papers data, this paper adopts spatial scientometrics and social network analysis to investigate the geography, position and link of science cities between 2007 and 2017. The results are demonstrated below: (1) The two seemingly paradoxical trends, the regional concentration and global spread, coexist in the process of knowledge production, which are rapidly reshaping the global pattern of science. (2) The whole knowledge collaboration network has been dominated by the Global North cities, while the rise of the Global South cities has an increasing influence in the network, both driving the evolution of the world order. (3) The number of scientific collaborations between cities has increased dramatically, while domestic collaborations have higher strength than international collaborations. Finally, we discuss the limitations of this study and set out three directions in the future research agenda of knowledge production.},
	keywords = {metropolitan area; Highly-cited papers; Scientific knowledge production; Spatial bibliometric; Science cities},
	year = {2024},
	eissn = {1874-4621},
	pages = {157-174}
}

@article{MTMT:35351232,
	title = {Insights from the COVID-19 Pandemic: A Survey of Data Mining and Beyond},
	url = {https://m2.mtmt.hu/api/publication/35351232},
	author = {Afyouni, Imad and Hashim, Ibrahim and Aghbari, Zaher and Elsaka, Tarek and Almahmoud, Mothanna and Abualigah, Laith},
	doi = {10.1007/s12061-024-09588-5},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	volume = {17},
	unique-id = {35351232},
	issn = {1874-463X},
	keywords = {Forecasting; time series analysis; Medical imaging; Contact Tracing; COVID-19; Social data mining},
	year = {2024},
	eissn = {1874-4621},
	pages = {1359-1411}
}

@article{MTMT:35315527,
	title = {Two Decades of Geospatial Evolution: Tracing the Analytical Journey towards Data-Driven Road Crash Prevention},
	url = {https://m2.mtmt.hu/api/publication/35315527},
	author = {Soltani, Ali and Mansourihanis, Omid and RoohaniQadikolaei, Mohsen and Zaroujtaghi, Ayda},
	doi = {10.1007/s12061-024-09587-6},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	volume = {17},
	unique-id = {35315527},
	issn = {1874-463X},
	keywords = {Geographic Information Systems; spatial analysis; Crash analysis; geospatial analysis; Data-driven approaches},
	year = {2024},
	eissn = {1874-4621},
	pages = {1301-1334},
	orcid-numbers = {Mansourihanis, Omid/0009-0007-3009-2902}
}

@article{MTMT:35073410,
	title = {Insights from the COVID-19 Pandemic: A Survey of Data Mining and Beyond},
	url = {https://m2.mtmt.hu/api/publication/35073410},
	author = {Afyouni, Imad and Hashim, Ibrahim and Aghbari, Zaher and Elsaka, Tarek and Almahmoud, Mothanna and Abualigah, Laith},
	doi = {10.1007/s12061-024-09588-5},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	volume = {17},
	unique-id = {35073410},
	issn = {1874-463X},
	year = {2024},
	eissn = {1874-4621},
	pages = {1-53}
}

@article{MTMT:34426590,
	title = {Convergence and Catch-Up of the Region Types in the Central and Eastern European Countries},
	url = {https://m2.mtmt.hu/api/publication/34426590},
	author = {Egri, Zoltán and Lengyel, Imre},
	doi = {10.1007/s12061-023-09551-w},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	volume = {17},
	unique-id = {34426590},
	issn = {1874-463X},
	abstract = {Our study investigates the economic growth and catch-up of the NUTS3 regions of 6 Central and Eastern European (CEE) member states of the European Union (EU), 4 countries acceding in 2004 (Czechia, Poland, Hungary, and Slovakia) and further two admitted in 2007 (Bulgaria and Romania), compared to the average of 14 older members of the EU between 2000 and 2019. We based our analysis on the urban–rural region types of the EU in the case of 185 regions, identifying predominantly urban, intermediate, and predominantly rural types. We apply Theil Index to examine the development of disparities and test the phenomena with unconditional β-convergence hypothesis. The analysis indicates that the growth of all CEE countries and their regions is faster than the EU14 average; the capitals considerably exceed it, the catch-up of other urban regions is also relatively fast, while it is very slow in the case of other regions. The convergence between the 185 regions is weak, based on the EU region typology it was initially strong between the capitals, moderate in the case of intermediate and rural types, while divergence can be observed in the urban types. The catch-up of less developed regions is very slow despite EU cohesion funding, even though 80% of the population live here. The stagnation of regional disparities and slow catch-up of less developed regions indicate the poor efficiency of the EU cohesion policy. © 2023, The Author(s).},
	keywords = {economic growth; Central and Eastern European countries; Catch-up; Theil index; Unconditional β-Convergence},
	year = {2024},
	eissn = {1874-4621},
	pages = {393-415}
}

@article{MTMT:35572630,
	title = {Spatial Autocorrelation Methods in Identifying Migration Patterns: Case Study of Slovakia},
	url = {https://m2.mtmt.hu/api/publication/35572630},
	author = {Pregi, Loránt and Novotný, Ladislav},
	doi = {10.1007/s12061-024-09615-5},
	journal-iso = {APPL SPAT ANAL POL},
	journal = {APPLIED SPATIAL ANALYSIS AND POLICY},
	volume = {18},
	unique-id = {35572630},
	issn = {1874-463X},
	abstract = {The collapse of the socialist regime led to significant changes in migration patterns, garnering considerable attention in geographical research. However, despite the increased interest, many studies on internal migration lack a detailed analysis of its spatial aspects. Spatial autocorrelation methods can reveal spatial patterns, but so far they have not been applied in the detailed research of internal migration in post-socialist countries. The aim of this study is to explore the spatial patterns of internal migration with regard to intra-regional and inter-regional migration processes using selected indicators of spatial autocorrelation (Global Moran’s I, Anselin local Moran’s I and Getis-Ord Gi* statistic) with Slovakia as a case study. A partial goal is to evaluate the benefits of applying these methods in the assessment of internal migration. Local indicators of spatial autocorrelation demonstrated significant differentiation of both intra-regional and inter-regional migration processes. The dominant intra-regional process is the decentralization of the population, which is very intensive in the regions of the largest towns and cities. Inter-regional migration displays spatial polarisation, emphasizing the importance of the location of key economic centres. The methodology employed in this study clearly displays the clusters of municipalities with above-average and below-average values. This approach enables the identification and cartographic interpretation of specific municipalities where migration contributes the most to the spatial redistribution of the population. The study serves as a valuable framework for similar analyses, emphasizing the broader applicability of spatial autocorrelation methods in studying migration patterns.},
	year = {2024},
	eissn = {1874-4621},
	orcid-numbers = {Pregi, Loránt/0000-0003-4921-4977; Novotný, Ladislav/0000-0003-2012-1347}
}