Joan Masó

1.9k total citations · 1 hit paper
67 papers, 695 citations indexed

About

Joan Masó is a scholar working on Geography, Planning and Development, Artificial Intelligence and Ecological Modeling. According to data from OpenAlex, Joan Masó has authored 67 papers receiving a total of 695 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Geography, Planning and Development, 18 papers in Artificial Intelligence and 11 papers in Ecological Modeling. Recurrent topics in Joan Masó's work include Geographic Information Systems Studies (23 papers), Species Distribution and Climate Change (11 papers) and Atmospheric and Environmental Gas Dynamics (8 papers). Joan Masó is often cited by papers focused on Geographic Information Systems Studies (23 papers), Species Distribution and Climate Change (11 papers) and Atmospheric and Environmental Gas Dynamics (8 papers). Joan Masó collaborates with scholars based in Spain, United Kingdom and Switzerland. Joan Masó's co-authors include Alaitz Zabala, Xavier Pons, Steffen Fritz, Uta Wehn, Dilek Fraisl, Margaret M. Gold, Stefano Nativi, Inian Moorthy, Linda See and Grégory Giuliani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Thin Solid Films and Remote Sensing.

In The Last Decade

Joan Masó

63 papers receiving 660 citations

Hit Papers

Mapping citizen science contributions to the UN sustainab... 2020 2026 2022 2024 2020 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Mapping citizen science contributions to the UN sustainable development goals
    2020 246 citations Linda See, Uta Wehn et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Joan Masó Spain 12 169 159 123 109 98 67 695
Luigi Ceccaroni Spain 15 59 0.3× 169 1.1× 94 0.8× 24 0.2× 173 1.8× 55 861
Michael Goodchild United States 10 206 1.2× 99 0.6× 68 0.6× 435 4.0× 112 1.1× 13 1.2k
Stefan Steiniger Chile 14 228 1.3× 46 0.3× 130 1.1× 283 2.6× 67 0.7× 36 979
Frank Ostermann Netherlands 16 330 2.0× 70 0.4× 53 0.4× 370 3.4× 212 2.2× 63 1.3k
Vyron Antoniou Greece 12 186 1.1× 111 0.7× 87 0.7× 489 4.5× 58 0.6× 21 933
Nedjeljko Frančula Croatia 11 195 1.2× 40 0.3× 127 1.0× 288 2.6× 82 0.8× 86 1.1k
Martin Sudmanns Austria 15 176 1.0× 38 0.2× 187 1.5× 78 0.7× 147 1.5× 37 635
Grega Milčinski France 7 208 1.2× 55 0.3× 89 0.7× 154 1.4× 37 0.4× 21 611
Ana‐Maria Olteanu‐Raimond France 12 171 1.0× 66 0.4× 58 0.5× 304 2.8× 65 0.7× 33 724
Tobias Sturn Austria 12 196 1.2× 99 0.6× 223 1.8× 133 1.2× 41 0.4× 33 558

Countries citing papers authored by Joan Masó

Since Specialization
Citations

This map shows the geographic impact of Joan Masó's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Joan Masó with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan Masó more than expected).

Fields of papers citing papers by Joan Masó

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joan Masó. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Joan Masó. The network helps show where Joan Masó may publish in the future.

Co-authorship network of co-authors of Joan Masó

This figure shows the co-authorship network connecting the top 25 collaborators of Joan Masó. A scholar is included among the top collaborators of Joan Masó based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joan Masó. Joan Masó is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Palma, Raúl, et al.. (2025). Iliad Approach for Semantic Interoperability in Digital Twins of the Ocean. 1–10. 1 indexed citations
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4.
Masó, Joan, et al.. (2024). Digital Twins for Research and Innovation in Support of the European Green Deal Data Space: A Systematic Review. Remote Sensing. 16(19). 3672–3672. 1 indexed citations
5.
Domingo‐Marimon, Cristina, et al.. (2022). Aligning citizen science and remote sensing phenology observations to characterize climate change impact on vegetation. Environmental Research Letters. 17(8). 85007–85007. 8 indexed citations
6.
López, Francisco Javier Ariza, et al.. (2021). An Analysis of Existing Production Frameworks for Statistical and Geographic Information: Synergies, Gaps and Integration. ISPRS International Journal of Geo-Information. 10(6). 374–374. 2 indexed citations
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Masó, Joan, et al.. (2019). A provenance metadata model integrating ISO geospatial lineage and the OGC WPS: Conceptual model and implementation. Transactions in GIS. 23(5). 1102–1124. 11 indexed citations
9.
Masó, Joan, et al.. (2018). REMOTE SENSING ANALYTICAL GEOSPATIAL OPERATIONS DIRECTLY IN THE WEB BROWSER. SHILAP Revista de lepidopterología. XLII-4. 403–410. 6 indexed citations
10.
Wehn, Uta, Joan Masó, Rianne Giesen, et al.. (2018). The Ground Truth 2.0 generic methodology tested in six citizen observatories. EGU General Assembly Conference Abstracts. 5259. 1 indexed citations
11.
Moorthy, Inian, Steffen Fritz, Linda See, et al.. (2018). WeObserve: An Ecosystem of Citizen Observatories for Environmental Monitoring. IIASA PURE (International Institute of Applied Systems Analysis). 14026. 3 indexed citations
12.
Masó, Joan, et al.. (2017). W3C PROV to describe provenance at the dataset, feature and attribute levels in a distributed environment. Computers Environment and Urban Systems. 64. 103–117. 20 indexed citations
13.
Blonda, P., et al.. (2016). Current status of the Essential Variables as an instrument to assess the Earth Observation Networks in Europe. Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona). 1 indexed citations
14.
Bigagli, Lorenzo, et al.. (2014). Designing and implementing a Quality Broker: the GeoViQua experience. EGUGA. 16636. 1 indexed citations
15.
Ninyerola, Miquel, et al.. (2014). QualityML: a dictionary for quality metadata encoding. EGU General Assembly Conference Abstracts. 10452. 3 indexed citations
16.
Masó, Joan, et al.. (2013). A Provenance Visualization Tool for Global Earth Observation System of Systems. EGU General Assembly Conference Abstracts. 1 indexed citations
17.
Masó, Joan, et al.. (2012). Analysis of quality metadata in the GEOSS Clearinghouse. 7. 352–377. 11 indexed citations
18.
Masó, Joan, Xavier Pons, & Alaitz Zabala. (2011). Tuning the second-generation SDI: theoretical aspects and real use cases. International Journal of Geographical Information Systems. 26(6). 983–1014. 27 indexed citations
19.
Masó, Joan, et al.. (2005). CAMM, catálogo de metadatos de Miramon: implementación en una corporación, el DMAH. Mapping. 24–31. 2 indexed citations
20.
Zabala, Alaitz, Xavier Pons, Joan Masó, et al.. (2005). Effects of JPEG2000 lossy compression on remote sensing image classification for mapping natural areas. Annual Conference on Computers. 93. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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