A global moderate resolution dataset of gross primary production of vegetation for 2000–2016

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This paper, published in 1950, received 416 indexed citations. Written by Yao Zhang, Xiangming Xiao, Xiaocui Wu, Sha Zhou, Geli Zhang, Yuanwei Qin and Jinwei Dong covering the research area of Ecology and Global and Planetary Change. It is primarily cited by scholars working on Global and Planetary Change (344 citations), Ecology (238 citations) and Atmospheric Science (59 citations). Published in Scientific Data.

Countries where authors are citing A global moderate resolution dataset of gross primary production of vegetation for 2000–2016

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This map shows the geographic impact of A global moderate resolution dataset of gross primary production of vegetation for 2000–2016. 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 A global moderate resolution dataset of gross primary production of vegetation for 2000–2016 with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A global moderate resolution dataset of gross primary production of vegetation for 2000–2016 more than expected).

Fields of papers citing A global moderate resolution dataset of gross primary production of vegetation for 2000–2016

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of A global moderate resolution dataset of gross primary production of vegetation for 2000–2016. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A global moderate resolution dataset of gross primary production of vegetation for 2000–2016.

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.

This paper is also available at doi.org/10.1038/sdata.2017.165.

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