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.
Dynamic World, Near real-time global 10 m land use land cover mapping
2022547 citationsChristopher F. Brown, Steven P. Brumby et al.Scientific Dataprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Mikaela Weisse
Since
Specialization
Citations
This map shows the geographic impact of Mikaela Weisse'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 Mikaela Weisse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikaela Weisse more than expected).
This network shows the impact of papers produced by Mikaela Weisse. 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 Mikaela Weisse. The network helps show where Mikaela Weisse may publish in the future.
Co-authorship network of co-authors of Mikaela Weisse
This figure shows the co-authorship network connecting the top 25 collaborators of Mikaela Weisse.
A scholar is included among the top collaborators of Mikaela Weisse 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 Mikaela Weisse. Mikaela Weisse is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Brown, Christopher F., Steven P. Brumby, Brookie Guzder-Williams, et al.. (2022). Dynamic World, Near real-time global 10 m land use land cover mapping. Scientific Data. 9(1).547 indexed citations breakdown →
3.
Weisse, Mikaela & Elizabeth Dow Goldman. (2021). Just 7 Commodities Replaced an Area of Forest Twice the Size of Germany Between 2001 and 2015.6 indexed citations
Harris, Nancy L., et al.. (2018). When a Tree Falls, Is It Deforestation?.1 indexed citations
11.
Weisse, Mikaela & Elizabeth Dow Goldman. (2018). 2017 Was the Second-Worst Year on Record for Tropical Tree Cover Loss.13 indexed citations
12.
Broich, Mark, Mirela G. Tulbure, Arwan Putra Wijaya, Mikaela Weisse, & Fred Stolle. (2017). Quantifying South East Asia's forest degradation using latest generation optical and radar satellite remote sensing. AGU Fall Meeting Abstracts. 2017.1 indexed citations
13.
Weisse, Mikaela, et al.. (2017). Places to Watch: Identifying High-Priority Forest Disturbance from Near–Real Time Satellite Data.3 indexed citations
14.
Petersen, Rachael, et al.. (2017). Logging, Mining, And Agricultural Concessions Data Transparency: A Survey Of 14 Forested Countries.3 indexed citations
15.
Goldman, Elizabeth Dow & Mikaela Weisse. (2017). Technical Blog: Caveats to the 2016 Tree Cover Loss Data, Explained.1 indexed citations
16.
Weisse, Mikaela, et al.. (2017). Indigenous Communities Fend Off Invaders in the Peruvian Amazon.1 indexed citations
17.
Weisse, Mikaela & Elizabeth Dow Goldman. (2017). Global Tree Cover Loss Rose 51 Percent in 2016.10 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.