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.
Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information
2016302 citationsLinda See, Peter Mooney et al.ISPRS International Journal of Geo-Informationprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Grega Milčinski
Since
Specialization
Citations
This map shows the geographic impact of Grega Milčinski'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 Grega Milčinski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grega Milčinski more than expected).
This network shows the impact of papers produced by Grega Milčinski. 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 Grega Milčinski. The network helps show where Grega Milčinski may publish in the future.
Co-authorship network of co-authors of Grega Milčinski
This figure shows the co-authorship network connecting the top 25 collaborators of Grega Milčinski.
A scholar is included among the top collaborators of Grega Milčinski 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 Grega Milčinski. Grega Milčinski is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Moorthy, Inian, Tobias Sturn, Matej Batič, et al.. (2019). Improving Cloud Detection in Satellite Imagery using a Citizen Science Approach. IIASA PURE (International Institute of Applied Systems Analysis).3 indexed citations
Milčinski, Grega, et al.. (2017). SENTINEL-2 Services Library - efficient way for exploration and exploitation of EO data. EGUGA. 19502.4 indexed citations
11.
See, Linda, Peter Mooney, Giles M. Foody, et al.. (2016). Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information. ISPRS International Journal of Geo-Information. 5(5). 55–55.302 indexed citations breakdown →
See, Linda, J. Ching, Valéry Masson, et al.. (2015). Generating WUDAPT’s Specific Scale-dependent Urban Modeling and Activity Parameters: Collectionof Level 1 and Level 2 Data.6 indexed citations
15.
Ching, J., Grant Mills, Linda See, et al.. (2015). The Portal Component, Strategic Perspectives and Review of Tactical plans for Full Implementation of WUDAPT. MPG.PuRe (Max Planck Society).4 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.