Haida Yu

454 total citations
11 papers, 400 citations indexed

About

Haida Yu is a scholar working on Ecology, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Haida Yu has authored 11 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Ecology, 7 papers in Global and Planetary Change and 5 papers in Atmospheric Science. Recurrent topics in Haida Yu's work include Remote Sensing in Agriculture (7 papers), Remote Sensing and Land Use (5 papers) and Rangeland Management and Livestock Ecology (3 papers). Haida Yu is often cited by papers focused on Remote Sensing in Agriculture (7 papers), Remote Sensing and Land Use (5 papers) and Rangeland Management and Livestock Ecology (3 papers). Haida Yu collaborates with scholars based in China and Japan. Haida Yu's co-authors include Yunxiang Jin, Jinya Li, Xiuchun Yang, Hailong Ma, Tian Gao, Bin Xu, Fen Zhao, Qiong Wu, Jianjun Qiu and Lina Zhao and has published in prestigious journals such as PLoS ONE, Remote Sensing of Environment and International Journal of Remote Sensing.

In The Last Decade

Haida Yu

11 papers receiving 393 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haida Yu China 7 312 206 140 85 67 11 400
Khaldoun Rishmawi United States 11 353 1.1× 331 1.6× 207 1.5× 68 0.8× 55 0.8× 13 525
Cécile Dardel France 5 205 0.7× 261 1.3× 40 0.3× 65 0.8× 50 0.7× 6 397
Laura M. Burkett United States 8 270 0.9× 209 1.0× 71 0.5× 66 0.8× 30 0.4× 13 438
Marcelle Grenier Canada 10 258 0.8× 190 0.9× 91 0.7× 32 0.4× 36 0.5× 12 419
Changming Yin China 9 244 0.8× 222 1.1× 188 1.3× 51 0.6× 50 0.7× 24 387
Julia C. Yang United States 6 206 0.7× 245 1.2× 89 0.6× 31 0.4× 61 0.9× 9 370
Magdalini Pleniou Greece 9 140 0.4× 303 1.5× 56 0.4× 56 0.7× 48 0.7× 16 344
Ralph Root United States 6 380 1.2× 428 2.1× 155 1.1× 51 0.6× 30 0.4× 10 492
V. Trichon France 11 224 0.7× 186 0.9× 135 1.0× 26 0.3× 32 0.5× 16 400
An T. N. Dang Australia 7 164 0.5× 154 0.7× 137 1.0× 22 0.3× 34 0.5× 8 306

Countries citing papers authored by Haida Yu

Since Specialization
Citations

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

Fields of papers citing papers by Haida Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haida Yu

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

All Works

11 of 11 papers shown
1.
Lü, Wenqing, et al.. (2020). Sophocarpine attenuates septic liver injury through suppression of the NLRP3 inflammasome via autophagy‑mediated degradation. Experimental and Therapeutic Medicine. 20(6). 1–1. 13 indexed citations
3.
Yang, Xiuchun, Bin Xu, Zhu Xiao-hua, et al.. (2015). A monitoring indicator system for remote sensing of grassland vegetation growth and suitability evaluation – a case study of the Xilingol Grassland in Inner Mongolia, China. International Journal of Remote Sensing. 36(19-20). 5105–5122. 5 indexed citations
4.
Li, Jinya, Lina Zhao, Bin Xu, et al.. (2014). Spatiotemporal Variations in Grassland Desertification Based on Landsat Images and Spectral Mixture Analysis in Yanchi County of Ningxia, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7(11). 4393–4402. 19 indexed citations
5.
Jin, Yunxiang, Xiuchun Yang, Jianjun Qiu, et al.. (2014). Remote Sensing-Based Biomass Estimation and Its Spatio-Temporal Variations in Temperate Grassland, Northern China. Remote Sensing. 6(2). 1496–1513. 139 indexed citations
6.
Yu, Haida. (2013). Estimation of Aboveground Biomass by Remote Sensing in the Western Inner Mongolia Grassland. Zhongguo shamo. 3 indexed citations
7.
Li, Jinya, Xiuchun Yang, Yunxiang Jin, et al.. (2013). Monitoring and analysis of grassland desertification dynamics using Landsat images in Ningxia, China. Remote Sensing of Environment. 138. 19–26. 99 indexed citations
8.
Gao, Tian, Xiuchun Yang, Yunxiang Jin, et al.. (2013). Spatio-Temporal Variation in Vegetation Biomass and Its Relationships with Climate Factors in the Xilingol Grasslands, Northern China. PLoS ONE. 8(12). e83824–e83824. 47 indexed citations
9.
Yu, Haida, et al.. (2013). Changes of Grassland Vegetation Growth in Xilin Gol League over 10 Years and Analysis on the Influence Factors. Geo-information Science. 15(2). 270–270. 4 indexed citations
10.
Gao, Tian, Bin Xu, Xiuchun Yang, et al.. (2013). Using MODIS time series data to estimate aboveground biomass and its spatio-temporal variation in Inner Mongolia’s grassland between 2001 and 2011. International Journal of Remote Sensing. 34(21). 7796–7810. 59 indexed citations
11.
Yu, Haida. (2012). The Progress of Remote Sensing Monitoring for Grassland Vegetation Growth. 2 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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