World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
49
Citations
11692
World Ranking
5159
National Ranking
537

Jun Qin publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Jun Qin sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 119 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

Jun Qin D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Jun Qin sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 49 D-Index — 47th percentile

47% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

Overview

Jun Qin is affiliated with the Chinese Academy of Sciences in China and has a research focus primarily spanning environmental science and earth and planetary sciences. Their work includes numerous contributions to atmospheric science, global and planetary change, environmental engineering, artificial intelligence, and pollution.

Their research topics include solar radiation and photovoltaics, cryospheric studies and observations, climate variability and models, meteorological phenomena and simulations, energy and environment impacts, atmospheric aerosols and clouds, and soil moisture and remote sensing.

Jun Qin has published extensively in a variety of scientific venues. Frequent publication outlets include Earth System Science Data, Renewable Energy, Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, and the Journal of Hydrology.

They have collaborated regularly with several coauthors, including Ling Yao, Ning Lu, Hou Jiang, Kun Yang, and Chenghu Zhou.

Selected recent papers by Jun Qin include:

  • The first high-resolution meteorological forcing dataset for land process studies over China, 2020, Scientific Data
  • Direct and indirect impacts of urbanization on vegetation growth across the world's cities, 2022, Science Advances
  • Performance of air temperature from ERA5-Land reanalysis in coastal urban agglomeration of Southeast China, 2022, The Science of The Total Environment
  • Application of Improved Robot-assisted Laparoscopic Telesurgery with 5G Technology in Urology, 2022, European Urology
  • Multi-resolution dataset for photovoltaic panel segmentation from satellite and aerial imagery, 2021, Earth System Science Data

Best Publications

  • The first high-resolution meteorological forcing dataset for land process studies over China

    Jie He;Kun Yang;Kun Yang;Wenjun Tang;Hui Lu

  • Recent climate changes over the Tibetan Plateau and their impacts on energy and water cycle: A review

    Kun Yang;Hui Wu;Jun Qin;Changgui Lin

  • On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan Plateau

    Kun Yang;Jie He;Wenjun Tang;Jun Qin

  • Improving land surface temperature modeling for dry land of China

    Yingying Chen;Kun Yang;Jie He;Jun Qin

  • Response of hydrological cycle to recent climate changes in the Tibetan Plateau

    Kun Yang;Baisheng Ye;Degang Zhou;Bingyi Wu

  • The altitudinal dependence of recent rapid warming over the Tibetan Plateau

    Jun Qin;Kun Yang;Shunlin Liang;Xiaofeng Guo

  • A MULTISCALE SOIL MOISTURE AND FREEZE-THAW MONITORING NETWORK ON THE THIRD POLE

    Kun Yang;Jun Qin;Long Zhao;Yingying Chen

  • Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau

    Yingying Chen;Kun Yang;Jun Qin;Long Zhao

  • The dependence of precipitation types on surface elevation and meteorological conditions and its parameterization

    Baohong Ding;Kun Yang;Jun Qin;Lei Wang

  • Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia

    Jun Qin;Kun Yang;Ning Lu;Yingying Chen

  • Estimating surface temperature changes of lakes in the Tibetan Plateau using MODIS LST data

    Guoqing Zhang;Tandong Yao;Hongjie Xie;Jun Qin

  • Solar radiation trend across China in recent decades: a revisit with quality-controlled data

    W.-J. Tang;K. Yang;J. Qin;C. C. K. Cheng

  • Quality control and estimation of global solar radiation in China

    Wenjun Tang;Kun Yang;Jie He;Jun Qin

  • Observed Coherent Trends of Surface and Upper-Air Wind Speed over China since 1960

    Changgui Lin;Kun Yang;Jun Qin;Rong Fu

  • Improving the Noah Land Surface Model in Arid Regions with an Appropriate Parameterization of the Thermal Roughness Length

    Yingying Chen;Kun Yang;Degang Zhou;Jun Qin

  • Some practical notes on the land surface modeling in the Tibetan Plateau

    K. Yang;Y.-Y. Chen;J. Qin

  • Evaluation of SMAP, SMOS and AMSR2 soil moisture retrievals against observations from two networks on the Tibetan Plateau

    Yingying Chen;Kun Yang;Kun Yang;Jun Qin;Qian Cui

  • A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data

    Hou Jiang;Ning Lu;Ning Lu;Jun Qin;Wenjun Tang

  • Parameterizing soil organic carbon’s impacts on soil porosity and thermal parameters for Eastern Tibet grasslands

    YingYing Chen;Kun Yang;WenJun Tang;Jun Qin

  • Simultaneous estimation of both soil moisture and model parameters using particle filtering method through the assimilation of microwave signal

    Jun Qin;Shunlin Liang;Kun Yang;Ichiro Kaihotsu

  • A simple and efficient algorithm to estimate daily global solar radiation from geostationary satellite data

    Ning Lu;Jun Qin;Kun Yang;Jiulin Sun

Frequent Co-Authors

Kun Yang
Kun Yang Tsinghua University
Shunlin Liang
Shunlin Liang University of Hong Kong
Hui Lu
Hui Lu Tsinghua University
Toshio Koike
Toshio Koike University of Tokyo
Yaoming Ma
Yaoming Ma Chinese Academy of Sciences
Hongbin Ji
Hongbin Ji Chinese Academy of Sciences
Luonan Chen
Luonan Chen Chinese Academy of Sciences
Chenghu Zhou
Chenghu Zhou Chinese Academy of Sciences
Deliang Chen
Deliang Chen Tsinghua University
Fei Li
Fei Li Xi'an Jiaotong University

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