Prince Chapman Agyeman

903 total citations
40 papers, 666 citations indexed

About

Prince Chapman Agyeman is a scholar working on Artificial Intelligence, Environmental Engineering and Pollution. According to data from OpenAlex, Prince Chapman Agyeman has authored 40 papers receiving a total of 666 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 27 papers in Environmental Engineering and 17 papers in Pollution. Recurrent topics in Prince Chapman Agyeman's work include Geochemistry and Geologic Mapping (30 papers), Soil Geostatistics and Mapping (26 papers) and Heavy metals in environment (16 papers). Prince Chapman Agyeman is often cited by papers focused on Geochemistry and Geologic Mapping (30 papers), Soil Geostatistics and Mapping (26 papers) and Heavy metals in environment (16 papers). Prince Chapman Agyeman collaborates with scholars based in Czechia, Germany and Nigeria. Prince Chapman Agyeman's co-authors include Ndiye Michael Kebonye, Kingsley John, Luboš Borůvka, Radim Vašát, James Kobina Mensah Biney, Karel Němeček, Ondřej Drábek, Martin Kočárek, Aleš Klement and Vahid Khosravi and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Scientific Reports.

In The Last Decade

Prince Chapman Agyeman

38 papers receiving 652 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Prince Chapman Agyeman Czechia 16 318 294 241 100 94 40 666
Ndiye Michael Kebonye Czechia 17 347 1.1× 325 1.1× 276 1.1× 120 1.2× 113 1.2× 47 778
Kingsley John Czechia 19 362 1.1× 329 1.1× 300 1.2× 148 1.5× 117 1.2× 61 847
Abdugheni Abliz China 13 150 0.5× 163 0.6× 268 1.1× 48 0.5× 75 0.8× 28 596
Seyed Roohollah Mousavi Iran 12 293 0.9× 136 0.5× 145 0.6× 152 1.5× 77 0.8× 31 584
Laura Paulette Romania 12 296 0.9× 334 1.1× 222 0.9× 107 1.1× 87 0.9× 25 678
Yuanda Zhu United States 14 412 1.3× 394 1.3× 174 0.7× 155 1.6× 85 0.9× 19 746
Bruno Teixeira Ribeiro Brazil 15 183 0.6× 168 0.6× 158 0.7× 161 1.6× 36 0.4× 50 604
Aakriti Sharma United States 9 441 1.4× 353 1.2× 141 0.6× 154 1.5× 33 0.4× 15 685
Mohammad Salehi Iran 16 196 0.6× 129 0.4× 105 0.4× 122 1.2× 31 0.3× 50 648
Oldřich Vacek Czechia 12 93 0.3× 148 0.5× 261 1.1× 95 0.9× 78 0.8× 25 587

Countries citing papers authored by Prince Chapman Agyeman

Since Specialization
Citations

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

Fields of papers citing papers by Prince Chapman Agyeman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Prince Chapman Agyeman. 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 Prince Chapman Agyeman. The network helps show where Prince Chapman Agyeman may publish in the future.

Co-authorship network of co-authors of Prince Chapman Agyeman

This figure shows the co-authorship network connecting the top 25 collaborators of Prince Chapman Agyeman. A scholar is included among the top collaborators of Prince Chapman Agyeman 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 Prince Chapman Agyeman. Prince Chapman Agyeman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Biney, James Kobina Mensah, et al.. (2025). Significance of Planet SuperDove and refined Sentinel-2 imagery fusion for enhanced soil organic carbon prediction in croplands. CATENA. 254. 108902–108902. 2 indexed citations
2.
Khosravi, Vahid, Asa Gholizadeh, Radka Kodešová, et al.. (2024). Visible, near-infrared, and shortwave-infrared spectra as an input variable for digital mapping of soil organic carbon. International Soil and Water Conservation Research. 13(1). 203–214.
3.
Kebonye, Ndiye Michael, et al.. (2024). Spatial scale drives pedodiversity-elevation relationship in Botswana. GEOMATICA. 76(2). 100037–100037.
4.
Kebonye, Ndiye Michael, Kingsley John, Manuel Delgado‐Baquerizo, et al.. (2024). Major overlap in plant and soil organic carbon hotspots across Africa. The Science of The Total Environment. 951. 175476–175476. 3 indexed citations
5.
Margenot, Andrew J., Leo M. Condron, Geneviève S. Metson, et al.. (2024). Missing phosphorus legacy of the Anthropocene: Quantifying residual phosphorus in the biosphere. Global Change Biology. 30(6). e17376–e17376. 9 indexed citations
6.
Addo, Samuel, et al.. (2024). Microplastics in the Volta Lake: Occurrence, distribution, and human health implications. Heliyon. 10(7). e29041–e29041. 11 indexed citations
7.
Agyeman, Prince Chapman, Luboš Borůvka, Ndiye Michael Kebonye, et al.. (2023). Prediction of the concentration of cadmium in agricultural soil in the Czech Republic using legacy data, preferential sampling, Sentinel-2, Landsat-8, and ensemble models. Journal of Environmental Management. 330. 117194–117194. 9 indexed citations
8.
Khosravi, Vahid, et al.. (2023). Further to quantification of content, can reflectance spectroscopy determine the speciation of cobalt and nickel on a mine waste dump surface?. The Science of The Total Environment. 872. 161996–161996. 5 indexed citations
9.
Agyeman, Prince Chapman, Kingsley John, Ndiye Michael Kebonye, et al.. (2022). Prediction of the concentration of antimony in agricultural soil using data fusion, terrain attributes combined with regression kriging. Environmental Pollution. 316(Pt 1). 120697–120697. 8 indexed citations
10.
Agyeman, Prince Chapman, Ndiye Michael Kebonye, Vahid Khosravi, et al.. (2022). Optimal zinc level and uncertainty quantification in agricultural soils via visible near-infrared reflectance and soil chemical properties. Journal of Environmental Management. 326(Pt A). 116701–116701. 3 indexed citations
11.
Ofori, Solomon, et al.. (2022). Assessing the influence of treated effluent on nutrient enrichment of surface waters using water quality indices and source apportionment. Water Practice & Technology. 17(7). 1523–1534. 3 indexed citations
12.
Agyeman, Prince Chapman, et al.. (2022). Prediction of nickel concentration in peri-urban and urban soils using hybridized empirical bayesian kriging and support vector machine regression. Scientific Reports. 12(1). 3004–3004. 20 indexed citations
13.
Agyeman, Prince Chapman, Kingsley John, Ndiye Michael Kebonye, Luboš Borůvka, & Radim Vašát. (2022). Combination of enrichment factor and positive matrix factorization in the estimation of potentially toxic element source distribution in agricultural soil. Environmental Geochemistry and Health. 45(5). 2359–2385. 18 indexed citations
14.
John, Kingsley, et al.. (2021). Comparison of Cubist models for soil organic carbon prediction via portable XRF measured data. Environmental Monitoring and Assessment. 193(4). 197–197. 24 indexed citations
15.
Kebonye, Ndiye Michael, Peter N. Eze, Kingsley John, et al.. (2021). An in-depth human health risk assessment of potentially toxic elements in highly polluted riverine soils, Příbram (Czech Republic). Environmental Geochemistry and Health. 44(2). 369–385. 11 indexed citations
16.
John, Kingsley, et al.. (2021). Hybridization of cokriging and gaussian process regression modelling techniques in mapping soil sulphur. CATENA. 206. 105534–105534. 16 indexed citations
17.
Agyeman, Prince Chapman, Kingsley John, Ndiye Michael Kebonye, et al.. (2021). Multi-geochemical background comparison and the identification of the best normalizer for the estimation of PTE contamination in agricultural soil. Environmental Geochemistry and Health. 44(10). 3597–3613. 6 indexed citations
18.
Agyeman, Prince Chapman, Kingsley John, Ndiye Michael Kebonye, et al.. (2020). Source apportionment, contamination levels, and spatial prediction of potentially toxic elements in selected soils of the Czech Republic. Environmental Geochemistry and Health. 43(1). 601–620. 35 indexed citations
19.
20.
Agyeman, Prince Chapman, et al.. (2020). Trend analysis of global usage of digital soil mapping models in the prediction of potentially toxic elements in soil/sediments: a bibliometric review. Environmental Geochemistry and Health. 43(5). 1715–1739. 26 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.

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