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.
A climatic stratification of the environment of Europe
2005614 citationsMarc J. Metzger, R.G.H. Bunce et al.profile →
Environmental science: Agree on biodiversity metrics to track from space
2015302 citationsAndrew K. Skidmore, Nathalie Pettorelli et al.Natureprofile →
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 C.A. Mücher'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 C.A. Mücher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C.A. Mücher more than expected).
This network shows the impact of papers produced by C.A. Mücher. 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 C.A. Mücher. The network helps show where C.A. Mücher may publish in the future.
Co-authorship network of co-authors of C.A. Mücher
This figure shows the co-authorship network connecting the top 25 collaborators of C.A. Mücher.
A scholar is included among the top collaborators of C.A. Mücher 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 C.A. Mücher. C.A. Mücher is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Skidmore, Andrew K., Nathalie Pettorelli, Nicholas C. Coops, et al.. (2015). Environmental science: Agree on biodiversity metrics to track from space. Nature. 523(7561). 403–405.302 indexed citations breakdown →
Suomalainen, Juha, C.A. Mücher, Lammert Kooistra, & Erik H. Meesters. (2014). Mapping Health of Bonaire Coral Reefs Using a Lightweight Hyperspectral Mapping System - First Results. Socio-Environmental Systems Modeling. 15619.1 indexed citations
Wascher, Dirk, M. van Eupen, C.A. Mücher, & Ilse R. Geijzendorffer. (2010). Biodiversity of European agricultural landscapes : enhancing a high nature value farmland indicator. Socio-Environmental Systems Modeling.5 indexed citations
Wit, Allard de & C.A. Mücher. (2009). Satellite-derived trends in phenology over Europe: real trends or algorithmic effects. Socio-Environmental Systems Modeling. 4837.2 indexed citations
Hazeu, G.W. & C.A. Mücher. (2005). Historic land use dynamics in and around Natura2000 sites as indicators for impact on biodiversity; Phase 1 of the BIOPRESS project for the Netherlands. Data Archiving and Networked Services (DANS).1 indexed citations
17.
Clevers, J.G.P.W., Harm Bartholomeus, C.A. Mücher, & Allard de Wit. (2004). Use of MERIS data for land cover mapping in the Netherlands. Socio-Environmental Systems Modeling. 549. 21.5 indexed citations
18.
Mücher, C.A., S.M. Hennekens, R.G.H. Bunce, & J.H.J. Schaminée. (2004). Mapping European habitats to support the design and implementation of a pan-European ecological network; the PEENHAB-project. Socio-Environmental Systems Modeling.9 indexed citations
19.
Mücher, C.A., et al.. (2001). Development of a consistent methodology to derive land cover information on a European scale from remote sensing for environmental monitoring; the PELCOM report. Socio-Environmental Systems Modeling.16 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.