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.
25 years of the WOFOST cropping systems model
2018306 citationsAllard de Wit, Hendrik Boogaard et al.Agricultural Systemsprofile →
How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis
2015281 citationsHendrik Boogaard, M.K. van Ittersum et al.Field Crops Researchprofile →
Machine learning for large-scale crop yield forecasting
2020211 citationsDilli Paudel, Hendrik Boogaard et al.Agricultural Systemsprofile →
Interpretability of deep learning models for crop yield forecasting
202373 citationsDilli Paudel, Allard de Wit et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Hendrik Boogaard
Since
Specialization
Citations
This map shows the geographic impact of Hendrik Boogaard'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 Hendrik Boogaard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hendrik Boogaard more than expected).
Fields of papers citing papers by Hendrik Boogaard
This network shows the impact of papers produced by Hendrik Boogaard. 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 Hendrik Boogaard. The network helps show where Hendrik Boogaard may publish in the future.
Co-authorship network of co-authors of Hendrik Boogaard
This figure shows the co-authorship network connecting the top 25 collaborators of Hendrik Boogaard.
A scholar is included among the top collaborators of Hendrik Boogaard 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 Hendrik Boogaard. Hendrik Boogaard is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ittersum, M.K. van, et al.. (2019). Minimum emission pathways to triple Africa’s cereal production by 2050. Socio-Environmental Systems Modeling.1 indexed citations
9.
Wit, Allard de, Hendrik Boogaard, Davide Fumagalli, et al.. (2018). 25 years of the WOFOST cropping systems model. Agricultural Systems. 168. 154–167.306 indexed citations breakdown →
10.
Tesfaye, Kindie, M.K. van Ittersum, Keith Wiebe, et al.. (2018). Can Ethiopia feed itself by 2050? Estimating cereal self-sufficiency to 2050. Socio-Environmental Systems Modeling.3 indexed citations
Janssen, Sander, D.W.G. van Kraalingen, Hendrik Boogaard, et al.. (2012). A generic data schema for crop experiment data in food security research. Socio-Environmental Systems Modeling. 2447–2454.1 indexed citations
14.
Wit, Allard de, Hendrik Boogaard, & C.A. van Diepen. (2009). Regional crop yield forecasting: a probabilistic approach. EGUGA. 4820.1 indexed citations
15.
Boogaard, Hendrik, R. van der Wijngaart, & C.A. van Diepen. (2009). Overview CGMS and related tools. Socio-Environmental Systems Modeling. 22(2). 8–10.2 indexed citations
16.
Diepen, C.A. van & Hendrik Boogaard. (2009). History of CGMS in the MARS project. Socio-Environmental Systems Modeling. 22(2). 11–14.2 indexed citations
Su, Zhongbo, et al.. (2002). Assessing Relative Soil Moisture With Remote Sensing Data: Theory and Experimental Validation. EGS General Assembly Conference Abstracts. 3169.
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.