Xiaojin Qian

416 total citations
20 papers, 294 citations indexed

About

Xiaojin Qian is a scholar working on Ecology, Global and Planetary Change and Plant Science. According to data from OpenAlex, Xiaojin Qian has authored 20 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Ecology, 14 papers in Global and Planetary Change and 8 papers in Plant Science. Recurrent topics in Xiaojin Qian's work include Remote Sensing in Agriculture (13 papers), Plant Water Relations and Carbon Dynamics (9 papers) and Land Use and Ecosystem Services (7 papers). Xiaojin Qian is often cited by papers focused on Remote Sensing in Agriculture (13 papers), Plant Water Relations and Carbon Dynamics (9 papers) and Land Use and Ecosystem Services (7 papers). Xiaojin Qian collaborates with scholars based in China, Australia and United Kingdom. Xiaojin Qian's co-authors include Liangyun Liu, Xinjie Liu, Holly Croft, Shanshan Du, Jing M. Chen, Quanjun Jiao, Siyuan Chen, Yongjiang Zhang, Qiu Shen and Zhihao Qin and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Hydrogen Energy and International Journal of Remote Sensing.

In The Last Decade

Xiaojin Qian

16 papers receiving 286 citations

Peers

Xiaojin Qian

ECOLO

GPC

Yunfei Wu China

Maria Tattaris Australia

Yongchang Ye United States

Cheryl Rogers Canada

Yorum Hwang South Korea

Guangman Song Japan

Cecilia Chavana‐Bryant United Kingdom

Sébastien Champagne France

Liangliang Jia China

Yunfei Wu China

Xiaojin Qian

254 ×1.3

ECOLO

256 ×1.5

GPC

117 ×1.1

57 ×1.1

40 ×1.3

Citations per year, relative to Xiaojin Qian Xiaojin Qian (= 1×) peers Yunfei Wu

Countries citing papers authored by Xiaojin Qian

Since Specialization

Citations

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

Fields of papers citing papers by Xiaojin Qian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaojin Qian

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

All Works

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20 of 20 papers shown

Zhang, Ke, Xiaojin Qian, Robert X. Gao, et al.. (2025). Potential of machine learning in leaf-based multi-source data driven tomato growth monitoring. Smart Agricultural Technology. 10. 100854–100854. 1 indexed citations

Qian, Xiaojin, Yongjiang Zhang, & Liangyun Liu. (2025). Growth-stage-dependent relationship between photosynthetic capacity and leaf biochemical traits in cotton. Industrial Crops and Products. 235. 121650–121650.

Qian, Xiaojin, et al.. (2025). Assessment of vegetation indices for estimating leaf chlorophyll content in sparse canopies. Ecological Informatics. 92. 103506–103506.

Wei, Wang, Haofei Wang, & Xiaojin Qian. (2024). Pattern evolution and spatial structure of ecological and construction security network of the Yangtze River Economic Belt in China. Environment Development and Sustainability. 1 indexed citations

Shikhovtsev, A. Yu., et al.. (2024). A review of astroclimate conditions at possible locations for the Eurasian Submillimeter Telescopes (ESMT). 901–904.

Sui, Lichun, Liangyun Liu, Xinjie Liu, et al.. (2023). NIRP as a remote sensing proxy for measuring gross primary production across different biomes and climate zones: Performance and limitations. International Journal of Applied Earth Observation and Geoinformation. 122. 103437–103437. 5 indexed citations

Qian, Xiaojin, et al.. (2023). Global Leaf Chlorophyll Content Dataset (GLCC) from 2003–2012 to 2018–2020 Derived from MERIS and OLCI Satellite Data: Algorithm and Validation. Remote Sensing. 15(3). 700–700. 10 indexed citations

Jiao, Quanjun, et al.. (2021). Improving the Retrieval of Crop Canopy Chlorophyll Content Using Vegetation Index Combinations. Remote Sensing. 13(3). 470–470. 37 indexed citations

Qian, Xiaojin, Xinjie Liu, Holly Croft, & Jing M. Chen. (2021). Relationship Between Leaf Maximum Carboxylation Rate and Chlorophyll Content Preserved Across 13 Species. Journal of Geophysical Research Biogeosciences. 126(2). 35 indexed citations

10.

Qian, Xiaojin, et al.. (2021). Assessment of Satellite Chlorophyll-Based Leaf Maximum Carboxylation Rate (Vcmax) Using Flux Observations at Crop and Grass Sites. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 5352–5360. 5 indexed citations

11.

Suárez, Lola, Xiaojin Qian, T. Poblete, et al.. (2021). Assessing the Contribution of Airborne-Retrieved Chlorophyll Fluorescence for Nitrogen Assessment in Almond Orchards. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 5853–5856. 3 indexed citations

12.

Jiao, Quanjun, et al.. (2021). Improving the Retrieval of Forest Canopy Chlorophyll Content From MERIS Dataset by Introducing the Vegetation Clumping Index. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 5515–5528. 7 indexed citations

13.

Liu, Liangyun, et al.. (2020). Estimating maize GPP using near-infrared radiance of vegetation. SHILAP Revista de lepidopterología. 2. 100009–100009. 42 indexed citations

14.

Qian, Xiaojin & Liangyun Liu. (2020). Retrieving Crop Leaf Chlorophyll Content Using an Improved Look-Up-Table Approach by Combining Multiple Canopy Structures and Soil Backgrounds. Remote Sensing. 12(13). 2139–2139. 25 indexed citations

15.

Qian, Xiaojin, Yongjiang Zhang, Liangyun Liu, & Shanshan Du. (2019). Exploring the potential of leaf reflectance spectra for retrieving the leaf maximum carboxylation rate. International Journal of Remote Sensing. 40(14). 5411–5428. 24 indexed citations

16.

Chen, Siyuan, Liangyun Liu, Xiao Zhang, et al.. (2019). Retrieval of the Fraction of Radiation Absorbed by Photosynthetic Components (FAPARgreen) for Forest Using a Triple-Source Leaf-Wood-Soil Layer Approach. Remote Sensing. 11(21). 2471–2471. 12 indexed citations

17.

Qian, Xiaojin, Liangyun Liu, Holly Croft, & Jingming Chen. (2019). C<sub>3</sub> plants converge on a universal relationship between leaf maximum carboxylation rate and chlorophyll content. 7 indexed citations

18.

Qian, Xiaojin, Liang Liang, Qiu Shen, et al.. (2016). Drought trends based on the VCI and its correlation with climate factors in the agricultural areas of China from 1982 to 2010. Environmental Monitoring and Assessment. 188(11). 639–639. 46 indexed citations

19.

Liang, Liang, Lianpeng Zhang, Shu Su, et al.. (2014). Estimating wheat leaves chlorophyll content using hyperspectral technology and integrated inversion approach. 28. 1–6. 4 indexed citations

20.

Luo, Deli, et al.. (2012). Hydrogen isotopes separation using frontal displacement chromatography with Pd–Al2O3 packed column. International Journal of Hydrogen Energy. 37(14). 10774–10778. 30 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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