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.
The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes
20153.9k citationsChris Funk, Pete Peterson et al.profile →
A quasi-global precipitation time series for drought monitoring
2014594 citationsChris Funk, Pete Peterson et al.profile →
A five‐year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States
2007536 citationsJ. P. Verdin, Brian Wardlow et al.profile →
Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach
2013497 citationsG. B. Senay, S. Bohms et al.profile →
A land data assimilation system for sub-Saharan Africa food and water security applications
2017445 citationsAmy McNally, Shraddhanand Shukla et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of J. P. Verdin'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 J. P. Verdin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. P. Verdin more than expected).
This network shows the impact of papers produced by J. P. Verdin. 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 J. P. Verdin. The network helps show where J. P. Verdin may publish in the future.
Co-authorship network of co-authors of J. P. Verdin
This figure shows the co-authorship network connecting the top 25 collaborators of J. P. Verdin.
A scholar is included among the top collaborators of J. P. Verdin 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 J. P. Verdin. J. P. Verdin is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Budde, Michael, Chris Funk, G. J. Husak, et al.. (2016). Earth Observations for Early Detection of Agricultural Drought: Contributions of the Famine Early Warning Systems Network (FEWS NET). AGU Fall Meeting Abstracts. 2016.1 indexed citations
5.
Hobbins, Mike, Sandeep Kumar Shukla, G. J. Husak, et al.. (2016). What role does evaporative demand play in driving drought in Africa. AGUFM. 2016.1 indexed citations
6.
Justice, Christina, Inbal Becker‐Reshef, B. Barker, et al.. (2016). Strengthening Agricultural Decisions in Countries at Risk of Food Insecurity: The GEOGLAM Crop Monitor for Early Warning. AGU Fall Meeting Abstracts. 2016.2 indexed citations
7.
Peterson, Pete, Chris Funk, M. F. Landsfeld, et al.. (2015). The Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) v2.0 Dataset: 35 year Quasi-Global Precipitation Estimates for Drought Monitoring. 2015 AGU Fall Meeting. 2015.3 indexed citations
8.
Peterson, Pete, Chris Funk, M. F. Landsfeld, et al.. (2014). The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) Dataset: Quasi-Global Precipitation Estimates for Drought Monitoring and Trend Analysis. AGU Fall Meeting Abstracts. 2014.1 indexed citations
9.
Budde, Michael, Gideon Galu, Christopher Funk, J. P. Verdin, & James Rowland. (2014). Famine Early Warning Systems Network (FEWS NET) Contributions to Strengthening Resilience and Sustainability for the East African Community. 2014 AGU Fall Meeting. 2014.6 indexed citations
10.
Senay, G. B., et al.. (2014). Uncertainty Analysis on an Operational Simplified Surface Energy Balance algorithm for Estimation of Evapotranspiration at Multiple Flux Tower Sites. AGU Fall Meeting Abstracts. 2014.1 indexed citations
11.
Senay, G. B., et al.. (2014). Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products. AGUFM. 2014.1 indexed citations
12.
Peterson, Pete, Chris Funk, G. J. Husak, et al.. (2013). The Climate Hazards group InfraRed Precipitation (CHIRP) with Stations (CHIRPS): Development and Validation. AGU Fall Meeting Abstracts. 2013.14 indexed citations
13.
Senay, G. B., et al.. (2013). Large-scale Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: Modeling and Validation. AGUFM. 2013.1 indexed citations
14.
Hobbins, Mike, et al.. (2013). NOAA Introduces its First-Generation Reference Evapotranspiration Product. AGUFM. 2013.2 indexed citations
15.
Wardlow, Brian, Martha C. Anderson, & J. P. Verdin. (2012). Remote sensing of drought : innovative monitoring approaches. CRC Press eBooks.123 indexed citations
16.
Akbari, Abolghasem, Michael P. Chornack, Tyler B. Coplen, et al.. (2008). Water Resources Availability in Kabul, Afghanistan. AGUFM. 2008.1 indexed citations
Budde, Michael, James Rowland, & J. P. Verdin. (2008). Assessing Impacts of the 2008 Drought on Winter Wheat Production in Afghanistan Using MODIS 250m NDVI Time Series. AGU Fall Meeting Abstracts. 2008.1 indexed citations
19.
Artan, G. A., Hussein Gadain, Christina Bandaragoda, K. O. Asante, & J. P. Verdin. (2006). Utility of Satellite Derived Rainfall Data for Flood Risk Monitoring. AGU Spring Meeting Abstracts. 2007.1 indexed citations
20.
Verdin, J. P.. (1999). Geospatial climate monitoring products: Tools for food security assessment. PhDT.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.