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.
Mapping citizen science contributions to the UN sustainable development goals
2020246 citationsDilek Fraisl, Jillian Campbell et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Inian Moorthy'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 Inian Moorthy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Inian Moorthy more than expected).
This network shows the impact of papers produced by Inian Moorthy. 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 Inian Moorthy. The network helps show where Inian Moorthy may publish in the future.
Co-authorship network of co-authors of Inian Moorthy
This figure shows the co-authorship network connecting the top 25 collaborators of Inian Moorthy.
A scholar is included among the top collaborators of Inian Moorthy 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 Inian Moorthy. Inian Moorthy is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Fritz, Steffen, Tobias Sturn, Mathias Karner, et al.. (2019). FotoQuest Go: A Citizen Science Approach to the Collection of In-Situ Land Cover and Land Use Data for Calibration and Validation. IIASA PURE (International Institute of Applied Systems Analysis).4 indexed citations
Dijk, M. van, Inian Moorthy, Binh T. Nguyen, Linda See, & Steffen Fritz. (2019). Tracking poverty using satellite imagery and big data. IIASA PURE (International Institute of Applied Systems Analysis).1 indexed citations
Lesiv, Myroslava, Sherilyn C. Fritz, Juan Carlos Laso Bayas, et al.. (2018). Global Field Sizes Dataset for Ecosystems Modeling. IIASA PURE (International Institute of Applied Systems Analysis). 17801.1 indexed citations
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
Moorthy, Inian, Tobias Sturn, Dilek Fraisl, et al.. (2018). FotoQuest Go: A citizen science tool for in-situ land use and land cover monitoring. IIASA PURE (International Institute of Applied Systems Analysis). 8124.1 indexed citations
See, Linda, Steffen Fritz, Tobias Sturn, et al.. (2016). Assessing the quality of crowdsourced in-situ land-use and land cover data from FotoQuest Austria application. IIASA PURE (International Institute of Applied Systems Analysis).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.