Nicholas Hamm

55 papers receiving 3.1k citations

Nicholas Hamm's Hit Papers

A machine learning method to estimate PM2.5 concentrations across China with remote sensing, meteorological and land use information 2018 · 455 citations
4550+4+8Years since publication4008001.2k

Peers

Nicholas Hamm
Comparison fields: 5 of 153
  • Ecological Modeling 683
  • Environmental Engineering 703
  • Health, Toxicology and Mutagenesis 658
  • Nature and Landscape Conservation 483
  • Global and Planetary Change 782
Replace Nathaniel D. Herold with:
Nathaniel D. Herold United States
Patrick Danielson United States
Angela Lausch Germany
Martin Wegmann Germany
Birgit Kleinschmit Germany
J.A. Fry United States
Ross K. Meentemeyer United States
Jin Li China
Markus Neteler Italy
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Citations per year

Countries citing papers authored by Nicholas Hamm

Since Specialization
Citations

This map shows the geographic impact of Nicholas Hamm'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 Nicholas Hamm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Hamm more than expected).

Fields of papers citing papers by Nicholas Hamm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicholas Hamm. 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 Nicholas Hamm. The network helps show where Nicholas Hamm may publish in the future.

Co-authors

The 25 scholars most cited alongside Nicholas Hamm, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nicholas Hamm Line = papers co-authored together Nicholas Hamm links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Where is positional uncertainty a problem for species distribution modelling?
Hit paper breakdown →
20131269
2
A machine learning method to estimate PM2.5 concentrations across China with remote sensing, meteorological and land use information
Hit paper breakdown →
2018455
3 2017166
4 2021143
5 2012128
6 2010118
7 2011103
8 201679
9 201670
10 200547
11 201742
12 201537
13 201432
14 201832
15 201430
16 199929
17 200928
18 201827
19 201624
20 201424

About Nicholas Hamm

Nicholas Hamm is a scholar working on Environmental Engineering, Global and Planetary Change, Ecology, Health, Toxicology and Mutagenesis and Artificial Intelligence, having authored 57 papers that have together received 3.1k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (8 papers), Land Use and Ecosystem Services (7 papers), Remote Sensing in Agriculture (7 papers), Geochemistry and Geologic Mapping (7 papers), Soil Geostatistics and Mapping (5 papers), Urban Heat Island Mitigation (5 papers), Remote-Sensing Image Classification (5 papers) and Air Quality Monitoring and Forecasting (5 papers). The work is most often cited by research in Ecological Modeling (683 citations), Environmental Engineering (703 citations), Health, Toxicology and Mutagenesis (658 citations), Nature and Landscape Conservation (483 citations) and Global and Planetary Change (782 citations). Nicholas Hamm has collaborated with scholars based in Netherlands, China and United Kingdom. Frequent co-authors include Andrew K. Skidmore, Babak Naimi, T.A. Groen, Albertus G. Toxopeus, Alfred Stein, Jianping Guo, Yuming Guo, Wei Cao, Hongyan Ren and Gongbo Chen. Their work appears in journals such as Remote Sensing, The Science of The Total Environment, International Journal of Applied Earth Observation and Geoinformation, Atmospheric Environment and International Journal of Remote Sensing.

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.

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